https://memory.psych.upenn.edu/mediawiki/api.php?action=feedcontributions&user=Ckeane1&feedformat=atom Computational Memory Lab - User contributions [en] 2024-03-28T12:50:51Z User contributions MediaWiki 1.26.4 https://memory.psych.upenn.edu/mediawiki/index.php?title=File:KahanaCV.pdf&diff=7085 File:KahanaCV.pdf 2020-12-08T15:43:33Z <p>Ckeane1: Ckeane1 uploaded a new version of File:KahanaCV.pdf</p> <hr /> <div></div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=People&diff=7084 People 2020-11-25T15:30:58Z <p>Ckeane1: /* Postdoctoral Fellows, Medical Residents, &amp; Graduate Students */</p> <hr /> <div><br /> &lt;big&gt;[https://memory.psych.upenn.edu/InternalWiki/Contact_List Full Contact List] (CML Internal Wiki)&lt;/big&gt;<br /> <br /> &lt;big&gt;[[More Lab Photos]]&lt;/big&gt;<br /> <br /> __FORCETOC__<br /> __TOC__<br /> <br /> == Lab Director ==<br /> &lt;gallery widths=500px heights=500px&gt;<br /> File:MikeKahana.jpg|&lt;big&gt;[[Michael J. Kahana|Michael J. Kahana, Ph.D.]]&lt;/big&gt;&lt;br /&gt;kahana@psych.upenn.edu&lt;br /&gt;CML Principal Investigator<br /> <br /> &lt;/gallery&gt;<br /> <br /> == Visiting Scholars ==<br /> &lt;gallery widths=225px heights=300px&gt; <br /> File: Healy.jpg|&lt;big&gt; [http://psych.colorado.edu/~ahealy/ Alice Healy, Ph.D.] &lt;/big&gt;&lt;br /&gt; alice.healy@colorado.edu &lt;br /&gt; University of Colorado Boulder<br /> &lt;/gallery&gt;<br /> <br /> == Postdoctoral Fellows, Medical Residents, &amp; Graduate Students ==<br /> &lt;gallery widths=225px heights=300px&gt; <br /> File:ND.jpg|&lt;big&gt;Nick Diamond&lt;/big&gt;&lt;br /&gt;diamondn@sas.upenn.edu&lt;br /&gt; Postdoctoral Fellow <br /> File:sakon.jpeg|&lt;big&gt;John Sakon&lt;/big&gt;&lt;br /&gt;sakon@sas.upenn.edu&lt;br /&gt; Postdoctoral Fellow<br /> File:noa.JPG| &lt;big&gt;Noa Herz &lt;/big&gt;&lt;br /&gt;herz.noa@gmail.com&lt;br /&gt; Postdoctoral Fellow<br /> File:halpern.png| &lt;big&gt;David Halpern &lt;/big&gt;&lt;br /&gt;djhalp@sas.upenn.edu&lt;br /&gt; Postdoctoral Fellow<br /> File:Daniel.jpg|&lt;big&gt;Daniel Schonhaut&lt;/big&gt;&lt;br /&gt;daniel.schonhaut@gmail.com&lt;br /&gt; Ph.D. Student<br /> File:Aka.jpg| &lt;big&gt;Ada Aka &lt;/big&gt;&lt;br /&gt;adaaka@wharton.upenn.edu&lt;br /&gt; Ph.D. Student <br /> &lt;/gallery&gt;<br /> <br /> == Research Staff ==<br /> &lt;gallery widths=225px heights=300px&gt;<br /> File:DebGaspari.jpg|&lt;big&gt;Deb Gaspari&lt;/big&gt;&lt;br /&gt;gaspari@sas.upenn.edu&lt;br /&gt;Grants Manager<br /> File:Colyer.jpg|&lt;big&gt;Ryan Colyer, Ph.D. &lt;/big&gt;&lt;br /&gt; rcolyer@sas.upenn.edu &lt;br /&gt;Scientific Programmer<br /> File:CKeane.jpg|&lt;big&gt;Connor Keane&lt;/big&gt;&lt;br /&gt; ckeane1@sas.upenn.edu &lt;br /&gt; Data and Programming Specialist<br /> File:jrudoler.jpg|&lt;big&gt;Joseph Rudoler &lt;/big&gt;&lt;br /&gt; jrudoler@sas.upenn.edu &lt;br /&gt; Clinical Research Specialist<br /> File:evansnyder.jpg|&lt;big&gt;Evan Snyder &lt;/big&gt;&lt;br /&gt; evsnyder@sas.upenn.edu &lt;br /&gt; Clinical Research Specialist<br /> File:madison.jpg|&lt;big&gt;Madison Paron &lt;/big&gt;&lt;br /&gt; mreasnor@sas.upenn.edu &lt;br /&gt; Research Specialist<br /> File:Dougherty.jpg|&lt;big&gt;Matthew Dougherty &lt;/big&gt;&lt;br /&gt; doughem@sas.upenn.edu &lt;br /&gt; Research Specialist<br /> &lt;/gallery&gt;<br /> <br /> &lt;!-- <br /> Add this back in if we hire more developers:<br /> == Software Developers ==<br /> &lt;gallery widths=225px heights=300px&gt;<br /> <br /> &lt;/gallery&gt;<br /> --&gt;<br /> <br /> == Undergraduate and High School Student Researchers ==<br /> &lt;gallery widths=150px heights=200px&gt;<br /> &lt;!--File:Jimmy.jpg|&lt;big&gt;James Germi&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Alyssa.jpg|&lt;big&gt;Alyssa Johncola&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Johanna.jpg|&lt;big&gt;Johanna Phillips&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Stamati.jpg|&lt;big&gt;Stamati Liapis&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Tanvi.jpg|&lt;big&gt;Tanvi Patel&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Omar.jpg|&lt;big&gt;Omar Lopez&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:QK.jpg|&lt;big&gt;Q Kalantary&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:SunnyLu.jpg|&lt;big&gt;Sunny Lu&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:TGianangelo.jpg|&lt;big&gt;Taylor Gianangelo&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Belo.jpeg|&lt;big&gt;Saidah Belo-Osagie&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Chien.jpg|&lt;big&gt;Terry Chien&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:DeCorso.png|&lt;big&gt;Kevin DeCorso&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Person-placeholder.png|&lt;big&gt;David Diwik&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Goldman.JPG|&lt;big&gt;Shai Goldman&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:ShivaliGovani.jpg|&lt;big&gt;Shivali Govani&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Megha.jpg|&lt;big&gt;Megha Keshav&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Person-placeholder.png|&lt;big&gt;Nicole Laczewski&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Mack.png|&lt;big&gt;Lance Mack&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Lim.JPG|&lt;big&gt;Jang Won Lim&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Mansour.jpg|&lt;big&gt;Mia Mansour&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Person-placeholder.png|&lt;big&gt;Anh Tran&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Jasmine2.jpg|&lt;big&gt;Jasmine Wang&lt;/big&gt;&lt;br /&gt;--&gt;<br /> &lt;!--File:Collin1.jpg|&lt;big&gt;Collin Loughead&lt;/big&gt;&lt;br /&gt;--&gt;<br /> &lt;!--File:JDong.jpg|&lt;big&gt;Jessie Dong&lt;br /&gt;&gt;--&gt;<br /> &lt;!--File:EGoldman.jpg| &lt;big&gt;Elan Goldman &lt;br /&gt;--&gt;<br /> &lt;!--File:MorrisonJ.jpg|&lt;big&gt;James Morrison&lt;br /&gt;&gt;--&gt;<br /> &lt;!--File:JoAnnS.jpg|&lt;big&gt;Jo Ann Sun&lt;br /&gt;&gt;--&gt;<br /> &lt;!--File:JWeiner.jpg|&lt;big&gt;Josh Weiner&lt;br /&gt;&gt;--&gt;<br /> &lt;!--File:Eash.jpg|&lt;big&gt;Eash Aggarwal &lt;br /&gt; &gt;&gt;--&gt;<br /> &lt;!--File:Dhayes.JPG|&lt;big&gt;Daniel Hayes &lt;br /&gt; --&gt;<br /> &lt;!--File:edie.jpg| &lt;big&gt;Edie Graber &lt;br /&gt;--&gt;<br /> &lt;!--File:Hannahyoon.jpg| &lt;big&gt;Hannah Yoon &lt;br /&gt;--&gt; <br /> File:Person-placeholder.png| &lt;big&gt;Hokua Tarnas &lt;br /&gt; <br /> File:Deepti.jpg| &lt;big&gt;Deepti Tantry &lt;br /&gt;<br /> File:ricardoa.jpg| &lt;big&gt;Ricardo Adrogue &lt;br /&gt;<br /> File:benepstein.jpg| &lt;big&gt;Ben Epstein &lt;br /&gt;<br /> <br /> <br /> &lt;/gallery&gt;<br /> <br /> == Lab Alumni ==<br /> &lt;gallery widths=100px perrow=7&gt;<br /> File:GeorgiaR.jpg|Georgia Reilly&lt;br /&gt; MPH Candidate<br /> File:Nora1.jpg|Nora Herweg, Ph.D.<br /> File: Wanda1.jpg‎|Paul A. Wanda, Ph.D.<br /> File:RichardAZ.jpg|Richard Adamovich-Zeitlin&lt;br /&gt; Medical Student &lt;br /&gt; Hofstra University<br /> File:Kelly.jpg| Kelly Addis, Ph.D.&lt;br /&gt;Safety and Health Consultant,&lt;br /&gt;Boise State University<br /> File:Kylie.jpg| Kylie Hower Alm, Ph.D.&lt;br/&gt; Postdoctoral Fellow, &lt;br/&gt; Johns Hopkins School of Medicine<br /> File:Franco.png|Franco Bautista &lt;br /&gt; <br /> File:Erin.jpg|Erin Beck&lt;br /&gt;Director of Site Recruitment and Management, Recruitment Partners LLC <br /> File: Broitman.jpg| Adam Broitman &lt;br /&gt;Ph.D. Student&lt;br /&gt;Cornell University<br /> File:Burke.jpg|[http://sites.google.com/site/johnfredburkememoryresearch/ John Burke, Ph.D.]&lt;br /&gt;Resident&lt;br /&gt;University of California, San Francisco<br /> File:Stas1.jpg|Stanislav Busygin, Ph.D.<br /> File:JeremyC.jpg| [https://www.ualberta.ca/science/about-us/contact-us/faculty-directory/jeremy-caplan Jeremy Caplan, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br/&gt;University of Alberta <br /> File:Chen.jpg| Steven Chen &lt;br /&gt; Lead Developer, &lt;br /&gt; Symcat<br /> File:Kylene Photo 2.jpg| Kylene Cochrane &lt;br/&gt; Ph.D. Student &lt;br/&gt; Drexel University<br /> File:Cohen.jpg| Etan Cohen &lt;br /&gt; Writer and producer&lt;br/&gt;Known for Madagascar: Escape 2 Africa, &lt;br/&gt; Men in Black 3<br /> File:Rivka.jpg| Rivka Cohen &lt;br /&gt; Ph.D. Student &lt;br /&gt; University of Pennsylvania<br /> File:Liz.jpg|Elizabeth Crutchley&lt;br /&gt;Lab Manager, &lt;br /&gt; Infant Language Center, University of Pennsylvania<br /> File:Patrick.jpg|Patrick Crutchley&lt;br /&gt;Data Scientist, &lt;br /&gt; [http://qntfy.com Qntfy]<br /> File:Danoff.jpg| Michelle Danoff&lt;br /&gt; Associate Product Manager, &lt;br /&gt; Google <br /> File:Leon1.jpg| Leon Davis &lt;br /&gt;<br /> File:Orin.jpg| Orin Davis, Ph.D. &lt;br /&gt; Principal Investigator, [http://www.qllab.org/ Quality of Life Laboratory]<br /> File:DeCorso.png|Kevin DeCorso &lt;br /&gt;<br /> File:Mike1.jpg|Michael DePalatis &lt;br /&gt; Research Scientist, Inscripta <br /> File:EmilyD.jpg| Emily Dolan, Ph.D. &lt;br /&gt;Director of Applied Research, ASPCA &lt;br/&gt;University of Washington<br /> File:Zach.jpg| Zachary Duey &lt;br /&gt; Software Engineer &lt;br /&gt; Blackfynn<br /> File:Arne.jpg| [https://psychology.arizona.edu/users/arne-ekstrom Arne Ekstrom, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; University of Arizona <br /> File:Ellner.jpg| Samantha Ellner &lt;br /&gt; senior manager strategy and business operations, Harry's, inc<br /> File:Gennady.png| [http://www.gennaerlikhman.com Gennady Erlikhman, Ph.D.] &lt;br /&gt; Postdoctoral Researcher, &lt;br /&gt; University California, LA<br /> File:JonathanEW.jpg|Jonathan Eskreis-Winkler&lt;br /&gt; Ph.D. Student in Statistics, University of Chicago<br /> File:Youssef.jpg | [http://ezzyat.wordpress.com Youssef Ezzyat, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt;Swarthmore College<br /> File:Logan1.jpg| Logan Fickling &lt;br /&gt; Ph.D. Student &lt;br /&gt; University of Pennsylvania<br /> File:LynneG.png| Lynne Gauthier &lt;br /&gt; Associate Professor, UMASS Lowell <br /> File:Travis.png| Travis Gebhardt &lt;br /&gt; staff engineer, Blink Health <br /> File:Aaron.jpg| Aaron Geller, M.D. &lt;br /&gt; MD Candidate, &lt;br /&gt; Northern regional epilepsy group <br /> File:Jimmy.jpg|James Germi&lt;br /&gt; Researcher, &lt;br /&gt; University of Texas, Southwestern<br /> File:TGianangelo.jpg|Taylor Gianangelo&lt;br /&gt; MD Candidate, University of Florida College of Medicine <br /> File:TomG.jpg|Tom Gradel&lt;br /&gt; Chief Technology Operator,&lt;br/&gt;Guiding Technologies Corp<br /> File:Jeff.jpg|Jeffrey Greenberg&lt;br /&gt;<br /> File:Goldman.JPG|Shai Goldman&lt;br /&gt;<br /> File:ShivaliGovani.jpg|Shivali Govani&lt;br /&gt; School of Dental Medicine, University of Pennsylvania<br /> File:Person-placeholder.png| Caroline Haimm &lt;br /&gt; Research Coordinator, Duckworth Lab, &lt;br/&gt;University of Pennsylvania<br /> File:Haque.jpg|Rafi Haque&lt;br /&gt;M.D./Ph.D. Student, Emory University<br /> File:Karl.jpg|[http://karlhealey.github.com/Site/Karl_Healey.html Karl Healey, Ph.D.]&lt;br /&gt;Assistant Professor,&lt;br /&gt; Michigan State University<br /> File:Zeinab.png| Zeinab Helili &lt;br /&gt; Research Specialist, &lt;br /&gt; Hospital of the University of Pennsylvania<br /> File:chittela.jpg| Hemanth Chittela &lt;br /&gt; Software Engineer, Bridgewater Associates <br /> File:Masaki.jpg| Masaki Horii &lt;br /&gt; Systems Engineer &lt;br /&gt; Photo-Sonics, Inc.<br /> File:Marc.jpg| [https://www.bu.edu/psych/profile/marc-howard-ph-d/ Marc Howard, Ph.D.] &lt;br /&gt; Professor, &lt;br /&gt; Boston University <br /> File:Katherine.jpg| Katherine Hurley &lt;br /&gt; Ph.D. Student, &lt;br /&gt; George Washington University<br /> File:Ghwang.jpg| Grace Hwang, Ph.D. &lt;br /&gt; Principal investigator, &lt;br /&gt; Johns Hopkins University<br /> File:JoshJ.jpg| [https://bme.columbia.edu/faculty/joshua-jacobs Joshua Jacobs, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; Columbia University<br /> File:Ilana.jpg| Ilana Jerud, M.D. &lt;br /&gt; Psychiatrist, &lt;br /&gt; New York-Presbyterian/Weill Cornell<br /> File:Alyssa.jpg|Alyssa Johncola&lt;br /&gt;Researcher,&lt;br/&gt;University of Pennsylvania <br /> File:Person-placeholder.png| Pauline T. Johnsen, Ph.D. &lt;br /&gt; <br /> File: ‎Johri.jpg|Ansh Johri &lt;br /&gt; Medical Student, Penn State<br /> File:Katerman.jpg|Brandon Katerman&lt;br /&gt; Temple Student<br /> File:Kadel.jpg|Ally Kadel &lt;br /&gt; software engineering technical coach, Flatiron School <br /> File:Person-placeholder.png| Ester Kahana &lt;br /&gt;<br /> File:Person-placeholder.png| Brian Kamins<br /> File:Person-placeholder.png| Jonathan Kay &lt;br /&gt;<br /> File:Megha.jpg| Megha Keshav&lt;br /&gt;technical problem solver&lt;br/&gt;Epic <br /> File:RogerKhazan.png| Roger Khazan, Ph.D. &lt;br /&gt;Cybersecurity Leader, &lt;br /&gt; MIT Lincoln Laboratory <br /> File:DanK.jpg| Dan Kimball, J.D., Ph.D. &lt;br /&gt; Associate Professor, &lt;br /&gt; University of Oklahoma <br /> File:MatthewK.png| Matthew P. Kirschen, M.D., Ph.D. &lt;br /&gt; Pediatric Critical Care, Attending Physician, &lt;br /&gt; Children's Hospital of Philadelphia <br /> File:KrystalK.png| Krystal Klein, Ph.D. &lt;br /&gt; Cognitive Psychologist, Research Analyst, &lt;br /&gt; Oregon Health &amp; Science University <br /> File:Person-placeholder.png| Dov Kogen &lt;br /&gt; Associate, &lt;br /&gt; Weil, Gotshal, and Manges<br /> File:Igor.jpg| Igor Korolev, D.O., Ph.D.&lt;br /&gt; Physician, Jackson Memorial Hospital <br /> File:Kragel.jpg|James Kragel, Ph.D.&lt;br /&gt; Postdoctoral Fellow, Northwestern University<br /> File:Josh.jpg|Josh Kriegel&lt;br /&gt;Postbac, &lt;br /&gt; Columbia University<br /> File:Penina.jpg|Penina Krieger&lt;br /&gt; Gates Cambridge Scholar, &lt;br /&gt; medical student &lt;br/&gt; NYU School of Medicine <br /> File:Joel.jpg|Joel Kuhn&lt;br /&gt;Ph.D. Student, &lt;br /&gt; UC San Diego<br /> File:Nikhita_Kunwar.jpeg| Nikhita Kunwar &lt;br /&gt; University of Pennsylvania<br /> File:Person-placeholder.png|Nicole Laczewski&lt;br /&gt;strategist &lt;br /&gt;Bloomberg LP <br /> File: Sandy3.jpg|Sandra LaMonaca&lt;br /&gt;Executive Assistant, &lt;br/&gt; Ryan Veterinary Hospital of the University of Pennsylvania<br /> File:Person-placeholder.png| Richard Lawrence &lt;br /&gt; Ph.D. Student, &lt;br /&gt; U.C. Berkley <br /> File:Person-placeholder.png| Eben Lazarus &lt;br /&gt; Ph.D. Student, &lt;br /&gt; Harvard University<br /> File:Kenton.jpg| Kenton Lee &lt;br /&gt; Ph.D. Student, &lt;br /&gt; University of Washington <br /> File:Brad.jpg| [https://profiles.utsouthwestern.edu/profile/153415/bradley-lega.html Brad Lega, M.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; UT Southwestern Medical Center<br /> File:Deb.jpg|Deborah Levy&lt;br /&gt;Ph.D. Student, &lt;br /&gt;Vanderbilt University<br /> File:Matt_Levy.jpg| Mathew Levy &lt;br/&gt; University of Pennsylvania<br /> File:TimLew.png| Tim Lew &lt;br /&gt; Data Scientist, &lt;br /&gt; Quora<br /> File:Effie.jpg| Effie Li &lt;br /&gt; Ph.D. Student, &lt;br /&gt; Stanford University<br /> File:Lim.JPG| Jang Won Lim &lt;br /&gt;<br /> File:Nicole.jpg|[http://sites.google.com/site/nmarielong Nicole Long, Ph.D.]&lt;br /&gt;Assistant Professor,&lt;br /&gt;University of Virginia<br /> File:Lubken.jpg|Jason Lubken&lt;br /&gt; Sr. Data Science Software Engineer, Penn Medicine Predictive Healthcare<br /> File:Ningcheng.jpg| Ningcheng (Peter) Li &lt;br /&gt; M.D. Student, &lt;br /&gt; Yale University<br /> File:Stamati.jpg| [http://sites.bu.edu/cnl/members/stamati-liapis/ Stamati Liapis] &lt;br /&gt; Ph.D. Student, &lt;br /&gt; Boston University<br /> File:Lynn.jpg|[http://sites.google.com/site/lynnlohnas/ Lynn Lohnas, Ph.D.]&lt;br /&gt; Assistant Professor, &lt;br /&gt; Syracuse University<br /> File:Omar.jpg|Omar Lopez&lt;br /&gt;<br /> File:Anastasia.jpg|[[Anastasia_Lyalenko_Memorial_Fund|Anastasia Lyalenko]] &lt;br /&gt; [[Anastasia_Lyalenko_Memorial_Fund| Memorial Page]]<br /> File:Mack.png|Lance Mack &lt;br /&gt; data scientist &lt;br /&gt; Uber<br /> File:Person-placeholder.png| Josh Magarick &lt;br /&gt; Member of the Voleon Group Research Staff<br /> File:JeremyM.jpg| [http://dartmouth.edu/faculty-directory/jeremy-rothman-manning Jeremy Manning, Ph.D.] &lt;br /&gt; Assistant Professor, Dartmouth College <br /> &lt;!--File:Mansour.jpg|Mia Mansour&lt;br /&gt;<br /> File:Yuvi.jpg| Yuvi Masory &lt;br /&gt; Independent consultant<br /> File:StevenMeisler.jpg| Steven Meisler &lt;br /&gt; Clinical Research Coordinator, &lt;br /&gt; Massachusetts General Hospital<br /> File: Max.jpg| Max Merkow, M.D. &lt;br /&gt;Neurosurgeon, &lt;br /&gt; East Bay Brain &amp; Spine Medical Group<br /> File:Jonathan.jpg| Jonathan Miller. Ph.D. &lt;br /&gt; Postdoctoral Research Scientist &lt;br /&gt; Columbia University <br /> File: NKratz1.jpg | Nicole Miller &lt;br /&gt; Ph.D. Student, &lt;br /&gt; University of Chicago<br /> File:Matt.jpg| Matt Mollison, Ph.D &lt;br /&gt; Chief Data Scientist, &lt;br /&gt; branch international<br /> File:BryanMoore.JPG| Bryan Moore, M.D. &lt;br /&gt; graduate research fellow, University of Southern California <br /> File:Neal.jpg| [https://nealwmorton.com Neal Morton, Ph.D.] &lt;br /&gt; Postdoctoral Fellow, &lt;br /&gt; University of Texas at Austin<br /> File:EhrenNewman.png|[https://psych.indiana.edu/directory/faculty/newman-ehren.html Ehren Newman, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; Indiana University, Bloomington<br /> File:Novich.jpg| Corey Novich &lt;br /&gt; Sortware Engineer, &lt;br /&gt; Harmonix Music Systems<br /> File:Logan.jpg| Logan O'Sullivan&lt;br /&gt; Career Services Organizer, &lt;br /&gt; University of Pennsylvania Law School <br /> File:Jesse1.jpg| Jesse Pazdera &lt;br /&gt; Ph.D. Student, &lt;br /&gt; McMaster University<br /> File:Person-placeholder.png| Peter Pantelis, Ph.D. &lt;br /&gt; Director of Analytics, &lt;br /&gt; patch.com<br /> File:Isaac.jpg|Isaac Pedisich&lt;br /&gt; Software Developer, &lt;br /&gt; University of Pennsylvania<br /> File:TungP.jpg|Tung Phan, Ph.D. &lt;br /&gt; Applied Machine Learning Scientist, &lt;br /&gt; Amazon<br /> File:Johanna.jpg|Johanna Phillips&lt;br /&gt;<br /> File:Sean.jpg| [http://www.polyn.com/ Sean Polyn, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; Vanderbilt University <br /> File:Person-placeholder.png| Eric Pressman &lt;br /&gt; User Experience Manager, &lt;br /&gt; Sr. User Experience Specialist, &lt;br /&gt; MathWorks <br /> File:Ashwin.jpg| Ashwin Ramayya, M.D./ Ph.D.&lt;br /&gt;Neurosurgery Resident, &lt;br /&gt; University of Pennsylvania<br /> File:Randazzo.jpg|Michael Randazzo &lt;br /&gt; Internal Medicine, &lt;br /&gt; University of Pennsylvania<br /> File:Dan.jpg| Daniel S. Rizzuto, Ph.D. &lt;br /&gt; CEO, Nia Therapeutics<br /> File:EmilyR.jpg| Emily Rosenberg &lt;br /&gt; Med Student, &lt;br /&gt; Penn State<br /> File:Rachel.jpg|Rachel Russell&lt;br /&gt; Research Coordinator, &lt;br /&gt; University of Pennsylvania<br /> File:Colin.jpg| Colin Sauder &lt;br /&gt; scientific director &lt;br /&gt; adams clinical<br /> File:Schleifer2.jpg| Ian Schleifer &lt;br /&gt; Avionics Software Development Engineer &lt;br /&gt; Blue Origin<br /> File:Person-placeholder.png| Abraham Schneider, Ph.D. &lt;br /&gt; <br /> File:GregSchwartz.png| Greg Schwartz, Ph.D. &lt;br /&gt; Assistant Professor, &lt;br /&gt; Northwestern University<br /> File:Per.jpg| [https://psychology.as.virginia.edu/people/profile/pbs5u Per B. Sederberg, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; University of Virginia<br /> File:Seelig.jpg| David Seelig &lt;br /&gt; Harry C. Coles, &lt;br /&gt; Jr. Post-doctoral Fellow at Annenberg Public Policy Center, &lt;br /&gt; University of Pennsylvania <br /> File:Misha.jpg| Misha Serruya, M.D., Ph.D. &lt;br /&gt; Neurologist neuroscientist, &lt;br /&gt; Jefferson Hospital <br /> File:Sileo.jpg| Joseph Sileo &lt;br /&gt; University of Pennsylvania<br /> File:Yevgeniy.jpg| Yevgeniy Sirotin, Ph.D. &lt;br /&gt; Senior Principal Scientist, &lt;br /&gt; Manager at SAIC<br /> File:Julia.jpg| Julia (Barnathan) Skolnik &lt;br /&gt; assistant director of professional development, Franklin Institute <br /> File:Henry.jpg| Henry Solberg &lt;br /&gt; Masters Student &lt;br /&gt; Mathematics &lt;br /&gt; University of Illinois Urbana-Champaign<br /> File:Solway.jpg| [https://psyc.umd.edu/facultyprofile/solway/alec Alec Solway, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; University of Maryland<br /> File:Solomon1.jpg|Ethan Solomon &lt;br /&gt; M.D./Ph.D. Student<br /> File:Jessica.jpg| Jessica Spencer, M.D. &lt;br /&gt; Assistant Professor, &lt;br /&gt; Reproductive Endocrinologist, &lt;br /&gt; Emory School of Medicine <br /> File:Maciek.jpg| Maciek Swat, Ph.D. &lt;br /&gt; Inscripta<br /> File:Vitaly.jpg| Vitaly Terushkin, M.D. &lt;br /&gt; Clinical Instructor in Dermatology, &lt;br /&gt; Joan &amp; Sanford Medical College of Cornell University<br /> File:Michele.jpg| Michele Tully Tine, Ph.D. &lt;br /&gt; Associate Professor, Dartmouth College <br /> File:DanUtin.png| Dan Utin &lt;br /&gt; Research Staff, &lt;br /&gt; MIT Lincoln Laboratory <br /> File:Marieke.jpg| [http://www.ai.rug.nl/~mkvanvugt/ Marieke van Vugt, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; University of Groningen <br /> File:Jasmine2.jpg|Jasmine Wang&lt;br /&gt; VCU Chemical and Life Science Engineering, &lt;br /&gt; Virginia Commonwealth University<br /> File:ChristophW.jpg| [http://cogsci.info/ Christoph Weidemann, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; Swansea University <br /> File:Ryan.jpg|Ryan Bailey Williams &lt;br /&gt;<br /> File:Wyble.jpg| [http://wyblelab.com/ Brad Wyble, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; Pennsylvania State University<br /> File:Alison.jpg|Alison Xu&lt;br /&gt; Medical Student, Albert Einstein College of Medicine<br /> File:Xu.jpg|Jenny Xu&lt;br /&gt;<br /> File:yaffe.png|Robert Yaffe, Ph.D. &lt;br /&gt; Software Engineer, &lt;br /&gt; Google<br /> File:Kareem.jpg| [https://irp.nih.gov/pi/kareem-zaghloul Kareem Zaghloul, M.D., Ph.D] &lt;br /&gt; Investigator, &lt;br /&gt; NINDS <br /> File:Franklin.jpg| [https://www.codecygnus.com/team/franklin-zaromb/ Franklin Zaromb, Ph.D.] &lt;br /&gt; Data Science Consultant, &lt;br /&gt; Code Cygnus<br /> &lt;/gallery&gt;<br /> <br /> [[Category:People]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7083 Behavioral toolbox 2020-11-25T15:21:36Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> Download Here: [https://github.com/vucml/EMBAM github]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible here: [https://github.com/pennmem/pybeh github]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''paradigms''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''utils''': tools to transform and clean data into input formats for analysis functions.<br /> * '''helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Paradigms ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> ==== Plot ====<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7082 Behavioral toolbox 2020-11-25T15:21:16Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> Download Here: [https://github.com/vucml/EMBAM github]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible at [https://github.com/pennmem/pybeh github]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''paradigms''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''utils''': tools to transform and clean data into input formats for analysis functions.<br /> * '''helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Paradigms ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> ==== Plot ====<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7081 Behavioral toolbox 2020-11-25T15:19:10Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> Download Here: [[https://github.com/vucml/EMBAM]]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible at [[https://github.com/pennmem/pybeh]]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''paradigms''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''utils''': tools to transform and clean data into input formats for analysis functions.<br /> * '''helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Paradigms ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> ==== Plot ====<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7080 Behavioral toolbox 2020-11-25T15:18:23Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> Download Here: [https://github.com/vucml/EMBAM]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible at [https://github.com/pennmem/pybeh]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''paradigms''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''utils''': tools to transform and clean data into input formats for analysis functions.<br /> * '''helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Paradigms ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> ==== Plot ====<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot/plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7079 Behavioral toolbox 2020-11-25T15:16:56Z <p>Ckeane1: /* Analyses */</p> <hr /> <div>__NOTOC__<br /> Download Here: [https://github.com/vucml/EMBAM]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible at [https://github.com/pennmem/pybeh]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''paradigms''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''utils''': tools to transform and clean data into input formats for analysis functions.<br /> * '''helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Paradigms ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> == Plot ==<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7078 Behavioral toolbox 2020-11-25T15:16:40Z <p>Ckeane1: /* Introduction */</p> <hr /> <div>__NOTOC__<br /> Download Here: [https://github.com/vucml/EMBAM]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible at [https://github.com/pennmem/pybeh]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''paradigms''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''utils''': tools to transform and clean data into input formats for analysis functions.<br /> * '''helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Analyses ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> == Plot ==<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Behavioral_toolbox&diff=7077 Behavioral toolbox 2020-11-25T15:14:36Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> Download Here: [https://github.com/vucml/EMBAM]<br /> <br /> == Introduction ==<br /> <br /> On this page, you can download the most current release of the behavioral toolbox, which is now maintained by the Vanderbilt Computational Memory Lab. The University of Pennsylvania Computational Memory Lab<br /> now maintains a Python version of these tools, accessible at [https://github.com/pennmem/pybeh]<br /> <br /> This release also comes with a detailed readme.txt file, and each function has detailed documentation. Nonetheless, there are some points about the toolbox that are worth reiterating here.<br /> <br /> This toolbox has three main directories:<br /> <br /> * '''Analyses''': core analysis functions, which calculate the following per participant:<br /> *# &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;: probability of recall.<br /> *# &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;: serial position curve.<br /> *# &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;: probability of first recall as a function of serial position.<br /> *# &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;: conditional response probability as a function of lag.<br /> *# &lt;code&gt;&lt;nowiki&gt;pli.m&lt;/nowiki&gt;&lt;/code&gt;: number of prior-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;xli.m&lt;/nowiki&gt;&lt;/code&gt;: number of extra-list intrusions recalled.<br /> *# &lt;code&gt;&lt;nowiki&gt;temp_fact.m&lt;/nowiki&gt;&lt;/code&gt;: temporal clustering score.<br /> *# &lt;code&gt;&lt;nowiki&gt;dist_fact.m&lt;/nowiki&gt;&lt;/code&gt;: distance clustering score, based on a distance matrix provided by the user (most commonly, the distance matrix is an LSA matrix so that this function can be used to determine semantic clustering).<br /> * '''Plots''': makes graphs from the outputs of select Analyses functions.<br /> * '''Helpers''': many of these functions are just used internally for the functions in the Analyses directory, but some particularly useful functions are described in more detail below.<br /> <br /> == Analyses ==<br /> <br /> Most of the Analyses functions expect the associated information from a free recall study to be in a particular format, and provide output in a particular format as well.<br /> <br /> ==== Inputs ====<br /> <br /> In a free recall study, each trial has certain information associated with it: the items presented, the items recalled, the corresponding subject.<br /> <br /> Combined across all such trials, one can generate matrices where each row represents a trial, each column represents a recalled item. Specifically, column i represents output position i, and if no item was recalled for that output position, it is simply left as 0. Two main ways of representing these recalls are to index recalled items by the serial position for that presented list: integers from 1 to the list-length (referred to as ''recalls_matrix'' in toolbox functions). Another way is to index items by their number in the word pool (''rec_itemnos''). The latter allows for more detailed information to be extracted, such as if any items recalled were prior-list intrusions.<br /> <br /> Corresponding to each trial row, one can also generate matrices with each of the items presented according to their number in the wordpool (''pres_itemnos'').<br /> <br /> Critical to most functions is a vector where each row corresponds to the number of the subject for that trial (''subjects'').<br /> <br /> To facilitate analyses of extra-list and prior-list intrusions, many functions expect as input a matrix with intrusion information (''intrusions''). Briefly, an item recalled as an extra-list intrusion is indexed as -1, and a prior-list intrusion is indexed by a positive integer indicating the number of lists back from which it occurred. For the specifics of how this matrix can be created and is designed, see &lt;code&gt;&lt;nowiki&gt;helpers/matrixops/make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt;.<br /> <br /> ==== Outputs ====<br /> <br /> All of the functions in this release output a number or a set of numbers for each participant, depending on the analysis. When the analysis outputs one number per participant (e.g. &lt;code&gt;&lt;nowiki&gt;p_rec.m&lt;/nowiki&gt;&lt;/code&gt;), the output is a vector, where each row corresponds to the number for one participant. The numbers are listed according to the ascending order of subject numbers. When the analysis outputs more than one number per subject, the rows still correspond to the ascending order of subject numbers, and the columns index the different values for the analysis for that one subject (e.g. the columns indicate probability of recall at ascending serial positions for the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt;).<br /> <br /> == Helpers ==<br /> <br /> Many of the functions in the Helpers subdirectories are internal functions meant to supplement the functions provided in the Analyses folder. For Release 1, only the functions in the Masks directory and the function &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; in the Matrixops folder are designed to be explicitly called upon by the user. &lt;code&gt;&lt;nowiki&gt;make_intrusions.m&lt;/nowiki&gt;&lt;/code&gt; was described above in the Inputs section of this file, and Masks are described in more detail below.<br /> <br /> ==== Masks ====<br /> <br /> Masks are matrices with logical elements used to 'mask' out particular recalled and/or presented items. For instance, suppose we are only interested in recall of the odd-numbered items. One could simply create a mask the same size as ''pres_itemnos'', where all even-numbered items are false, and all odd-numbered items are true. One could then create a similar mask for the recalled items, and then pass these two masks into the appropriate analysis function.<br /> <br /> NOTE: Many functions make default masks if they are not provided by the user.<br /> <br /> == Plot ==<br /> <br /> The plot functions have been designed especially to take the output of functions from the Analyses folder of the Behavioral Toolbox Release 1, and turn them into lovely plots. Simply pass in the numbers from those functions, and admire the figures.<br /> <br /> * &lt;code&gt;&lt;nowiki&gt;plot_crp.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;lag_crp.m&lt;/nowiki&gt;&lt;/code&gt;<br /> * &lt;code&gt;&lt;nowiki&gt;plot_spc.m&lt;/nowiki&gt;&lt;/code&gt; plots the output of &lt;code&gt;&lt;nowiki&gt;spc.m&lt;/nowiki&gt;&lt;/code&gt; OR &lt;code&gt;&lt;nowiki&gt;pfr.m&lt;/nowiki&gt;&lt;/code&gt;<br /> <br /> <br /> <br /> ''Click'' [[Data_Archive|here]] ''to visit the [[Data_Archive]].''<br /> [[Category:public]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Request_RAM_Public_Data_access&diff=7076 Request RAM Public Data access 2020-11-21T04:55:36Z <p>Ckeane1: Redirected page to Data Request</p> <hr /> <div>#REDIRECT [[Data Request]]<br /> <br /> Thank you for your interest in the RAM public data. To request access, please email our team at [mailto:cmlweb@psych.upenn.edu cmlweb@psych.upenn.edu] and include the following info:<br /> <br /> # Your name<br /> # Your affiliated institution (University or Company)<br /> # An indication that you would like access to the RAM data<br /> # A brief (1-2 sentence) message stating your intended use of the data<br /> <br /> [[RAM|Click here to return to the RAM project page.]]<br /> &lt;!--<br /> &lt;EmailForm&gt;<br /> {| <br /> | style=&quot;width: 200px&quot;| Name: || &lt;emailform name=40 /&gt; ||<br /> |-<br /> | Email: || &lt;emailform from=40 /&gt; || <br /> |-<br /> | Affiliated institution (university/company): || &lt;emailform institution=40 /&gt; ||<br /> |-<br /> | Please tell us a little bit about your planned use for this data: &lt;br&gt; &lt;small&gt;''(This is mostly spam prevention.)''&lt;/small&gt;<br /> | colspan=&quot;2&quot; | &lt;emailform comments=80x8 /&gt;<br /> |-<br /> | Solve the following math problem (spam prevention):<br /> | &lt;emailform math /&gt;<br /> |-<br /> | colspan=&quot;3&quot; align=&quot;center&quot; | &lt;emailform submit=&quot;Request Access&quot; /&gt;<br /> |}<br /> &lt;/EmailForm&gt;<br /> &lt;EmailForm result&gt;<br /> Thank you. A member of the CML will be in touch with you within two business days. If you have any questions, please e-mail [mailto:cmlweb@psych.upenn.edu cmlweb@psych.upenn.edu].<br /> {| width=&quot;300px&quot;<br /> | '''From:''' &lt;emailform name /&gt; &lt;emailform from/&gt;&lt;br /&gt;<br /> '''Institution:''' &lt;emailform institution /&gt; &lt;br /&gt;<br /> '''Comments:''' &lt;emailform comments /&gt;<br /> |}<br /> &lt;/EmailForm&gt;<br /> --&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Data_Request&diff=7075 Data Request 2020-11-21T04:55:07Z <p>Ckeane1: </p> <hr /> <div>Thank you for your interest in our electrophysiological data. To request access to the data from one or more of the studies listed on our [[Electrophysiological_Data | EEG data portal]], or to request access to the [[RAM | RAM project]] data, please fill out the form below. If you have<br /> any questions about the available data, please email kahana-requests@sas.upenn.edu.<br /> <br /> &lt;iframe k=&quot;qualtrics&quot; p=&quot;jfe/form/SV_ekB8v9H5rqufeT3&quot; width=&quot;700&quot; height=&quot;700&quot;/&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Request_EEG_access&diff=7074 Request EEG access 2020-11-21T04:54:01Z <p>Ckeane1: Redirected page to Data Request</p> <hr /> <div>#REDIRECT [[Data Request]]<br /> <br /> Thank you for your interest in our electrophysiological data. To request access to the data from one or more of the studies listed on our [[Electrophysiological_Data | EEG data portal]], or to request access to the [[RAM | RAM project]] data, please email our team at [mailto:cmlweb@psych.upenn.edu cmlweb@psych.upenn.edu] and include the following info:<br /> <br /> # Your name<br /> # Your affiliated institution (University or Company)<br /> # Which data you would like to access<br /> #* For papers listed on our [[Electrophysiological_Data | EEG data archive]], specify the paper(s) for which you would like data access<br /> #* For [[RAM]] data requests, specify that you would like to request RAM data access<br /> # A brief (1-2 sentence) message stating your intended use of the data<br /> <br /> For further information about the data sharing process, please be sure to read our [[Requesting_ Electrophysiological_Data| information page]] concerning data access requests.<br /> <br /> [[EEG data|Click here to return to the EEG Data Archive.]]<br /> <br /> &lt;!--<br /> &lt;EmailForm&gt;<br /> {| <br /> | style=&quot;width: 200px&quot;| Name: || &lt;emailform name=40 /&gt; ||<br /> |-<br /> | Email: || &lt;emailform from=40 /&gt; || <br /> |-<br /> | Affiliated institution (university/company): || &lt;emailform institution=40 /&gt; ||<br /> |-<br /> | Please tell us a little bit about your planned use for this data: &lt;br&gt; &lt;small&gt;''(This is mostly spam prevention.)''&lt;/small&gt;<br /> | colspan=&quot;2&quot; | &lt;emailform comments=80x8 /&gt;<br /> |-<br /> | Solve the following math problem (spam prevention):<br /> | &lt;emailform math /&gt;<br /> |-<br /> | colspan=&quot;3&quot; align=&quot;center&quot; | &lt;emailform submit=&quot;Request Access&quot; /&gt;<br /> |}<br /> &lt;/EmailForm&gt;<br /> &lt;EmailForm result&gt;<br /> Thank you. A member of the Kahana lab will be in touch with you within two business days. If you have any questions, please e-mail [mailto:cmlweb@psych.upenn.edu cmlweb@psych.upenn.edu].<br /> {| width=&quot;300px&quot;<br /> | '''From:''' &lt;emailform name /&gt; &lt;emailform from/&gt;&lt;br /&gt;<br /> '''Institution:''' &lt;emailform institution /&gt; &lt;br /&gt;<br /> '''Comments:''' &lt;emailform comments /&gt;<br /> |}<br /> &lt;/EmailForm&gt;<br /> --&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Data_Request&diff=7073 Data Request 2020-11-21T01:39:09Z <p>Ckeane1: </p> <hr /> <div>&lt;iframe k=&quot;qualtrics&quot; p=&quot;jfe/form/SV_ekB8v9H5rqufeT3&quot; width=&quot;700&quot; height=&quot;700&quot;/&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Data_Request&diff=7072 Data Request 2020-11-21T01:38:40Z <p>Ckeane1: Created page with &quot;&lt;iframe k=&quot;qualtrics&quot; p=&quot;jfe/form/SV_ekB8v9H5rqufeT3&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;&quot;</p> <hr /> <div>&lt;iframe k=&quot;qualtrics&quot; p=&quot;jfe/form/SV_ekB8v9H5rqufeT3&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Electrophysiology_Workshop_2020&diff=7069 Electrophysiology Workshop 2020 2020-10-23T19:01:29Z <p>Ckeane1: </p> <hr /> <div>Welcome to the home page for our Summer Workshop in Model-Based Cognitive Electrophysiology. Here, we will share all recorded lectures for those interested in our workshop materials.<br /> <br /> Link to interactive materials: https://github.com/pennmem/CMLWorkshop<br /> <br /> ===Lecture #1:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1YiuN7KEe2nlrluNrGVOoZCF5ext3Rswu/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #2:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/19bLA7F_yozE8YdU8I_2kCu-RjEjV3Tqr/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #3:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/18hNVmBzbdAcbx3zdatenPpg5tjFZlieN/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #4:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1qjTf0Jr60bD1STzJBil4EFQ1VjTa23Pn/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #5:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1o1AwNEb_4TFGjVaujV10TQNiYhJXx3ck/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #6:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1xysnLjmAOlH-XwqLx3mQBYkzWGIyWrA0/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #7:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1xgyu9rPUJXKhZ_BolsPTLzwRPBT4ZdkN/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;<br /> <br /> ===Lecture #8:===<br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1bl7WDxABvbljpXhVNm2-PM2z3N0YAClA/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Jobs&diff=7024 Jobs 2020-08-25T15:28:37Z <p>Ckeane1: </p> <hr /> <div>''' The Computational Memory Lab is currently seeking applications for the following positions: '''<br /> <br /> ==Application Developer B==<br /> <br /> This work will include the rapid and flexible development of new experiments in human memory, as well as critical improvements to existing programs and libraries. The candidate is expected to coordinate with a team of cognitive scientists, neuroscientists, and engineers on multiple projects involving brain stimulation to boost human cognitive abilities, online experiments of human memory, and computational cluster analyses of EEG data from human participants. Active coordination is expected with the systems development team to design systems, develop plans and testing procedures, and prepare releases. Other responsibilities may include resolving systems administration issues, file server and web system issues, and computer cluster issues. Additional projects may include analysis of collected data and simulations of human memory processes in computer models of memory.<br /> <br /> The position is planned as temporarily remote, with an expectation of on-site presence at the University of Pennsylvania upon resumption of on-site activities for this position category.<br /> <br /> Required qualifications:<br /> *Bachelor’s degree in Computer Science, Software Engineering, or related field, with 1 year of experience.<br /> *Experience in C++ and Python programming.<br /> *Demonstrated experience completing significant technical projects or working on large code bases.<br /> *Familiarity with Linux.<br /> *Familiarity with version control and deployment tools, such as git, conda, pip, travis, or similar.<br /> *Experience designing software architectures.<br /> *Ability to work on a software engineering team.<br /> *Responsive to software users and able to translate user needs into concrete software requirements.<br /> <br /> Preferred qualifications:<br /> *Expertise in Python programming.<br /> *Exceptional quantitative skills.<br /> *Experience with Unity or Qt.<br /> *Experience with data analysis.<br /> *Experience with hardware and electronics.<br /> <br /> To apply, click [https://wd1.myworkdaysite.com/recruiting/upenn/careers-at-penn/job/Leidy-Laboratories-of-Biology/Application-Developer-B_JR00022995| here]<br /> <br /> == Digital Media Design (Undergraduate Work-study Position) ==<br /> The Computational Memory Lab is looking to recruit a DMD student for the 2019 Fall semester to help design UNITY-based memory experiments to interface with closed-loop brain stimulation algorithms. Additionally, we are looking for a student who can assist with designing stunning graphical illustrations of scientific findings for inclusion in our lab's research publications. To apply for the position, please send a CV and transcript to Professor Kahana at kahana@psych.upenn.edu using the subject line: &quot;3-D Design”.<br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Undergraduate Research Assistant to assist with federally funded studies of human memory processes. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings and annotating vocal responses in memory tasks. This position requires an individual who possesses excellent interpersonal and organizational skills. This would be an ideal position for a student interested in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> To apply, please submit a resume to memorylab@psych.upenn.edu.--&gt;<br /> <br /> <br /> For more information on our research, please click [[Research| here]].<br /> [https://www.hr.upenn.edu/career/salary-offers For more information on Penn's salary structure, click here.]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Jobs&diff=7023 Jobs 2020-08-25T15:28:08Z <p>Ckeane1: </p> <hr /> <div>''' The Computational Memory Lab is currently seeking applications for the following positions: '''<br /> <br /> ==Application Developer B==<br /> <br /> This work will include the rapid and flexible development of new experiments in human memory, as well as critical improvements to existing programs and libraries. The candidate is expected to coordinate with a team of cognitive scientists, neuroscientists, and engineers on multiple projects involving brain stimulation to boost human cognitive abilities, online experiments of human memory, and computational cluster analyses of EEG data from human participants. Active coordination is expected with the systems development team to design systems, develop plans and testing procedures, and prepare releases. Other responsibilities may include resolving systems administration issues, file server and web system issues, and computer cluster issues. Additional projects may include analysis of collected data and simulations of human memory processes in computer models of memory.<br /> <br /> The position is planned as temporarily remote, with an expectation of on-site presence at the University of Pennsylvania upon resumption of on-site activities for this position category.<br /> <br /> Required qualifications:<br /> *Bachelor’s degree in Computer Science, Software Engineering, or related field, with 1 year of experience.<br /> *Experience in C++ and Python programming.<br /> *Demonstrated experience completing significant technical projects or working on large code bases.<br /> *Familiarity with Linux.<br /> *Familiarity with version control and deployment tools, such as git, conda, pip, travis, or similar.<br /> *Experience designing software architectures.<br /> *Ability to work on a software engineering team.<br /> *Responsive to software users and able to translate user needs into concrete software requirements.<br /> <br /> Preferred qualifications:<br /> *Expertise in Python programming.<br /> *Exceptional quantitative skills.<br /> *Experience with Unity or Qt.<br /> *Experience with data analysis.<br /> *Experience with hardware and electronics.<br /> <br /> Apply online here: https://wd1.myworkdaysite.com/recruiting/upenn/careers-at-penn/job/Leidy-Laboratories-of-Biology/Application-Developer-B_JR00022995<br /> <br /> == Digital Media Design (Undergraduate Work-study Position) ==<br /> The Computational Memory Lab is looking to recruit a DMD student for the 2019 Fall semester to help design UNITY-based memory experiments to interface with closed-loop brain stimulation algorithms. Additionally, we are looking for a student who can assist with designing stunning graphical illustrations of scientific findings for inclusion in our lab's research publications. To apply for the position, please send a CV and transcript to Professor Kahana at kahana@psych.upenn.edu using the subject line: &quot;3-D Design”.<br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Undergraduate Research Assistant to assist with federally funded studies of human memory processes. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings and annotating vocal responses in memory tasks. This position requires an individual who possesses excellent interpersonal and organizational skills. This would be an ideal position for a student interested in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> To apply, please submit a resume to memorylab@psych.upenn.edu.--&gt;<br /> <br /> <br /> For more information on our research, please click [[Research| here]].<br /> [https://www.hr.upenn.edu/career/salary-offers For more information on Penn's salary structure, click here.]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Jobs&diff=7022 Jobs 2020-08-25T15:23:53Z <p>Ckeane1: </p> <hr /> <div>''' The Computational Memory Lab is currently seeking applications for the following positions: '''<br /> <br /> == Digital Media Design (Undergraduate Work-study Position) ==<br /> The Computational Memory Lab is looking to recruit a DMD student for the 2019 Fall semester to help design UNITY-based memory experiments to interface with closed-loop brain stimulation algorithms. Additionally, we are looking for a student who can assist with designing stunning graphical illustrations of scientific findings for inclusion in our lab's research publications. To apply for the position, please send a CV and transcript to Professor Kahana at kahana@psych.upenn.edu using the subject line: &quot;3-D Design”.<br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Undergraduate Research Assistant to assist with federally funded studies of human memory processes. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings and annotating vocal responses in memory tasks. This position requires an individual who possesses excellent interpersonal and organizational skills. This would be an ideal position for a student interested in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> To apply, please submit a resume to memorylab@psych.upenn.edu.--&gt;<br /> <br /> <br /> For more information on our research, please click [[Research| here]].<br /> [https://www.hr.upenn.edu/career/salary-offers For more information on Penn's salary structure, click here.]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Jobs&diff=7021 Jobs 2020-08-25T15:17:53Z <p>Ckeane1: </p> <hr /> <div>''' The Computational Memory Lab is currently seeking applications for the following positions: '''<br /> <br /> &lt;!--<br /> &lt;!--== Research Specialist ==<br /> The Computational Memory Lab in the Department of Psychology at the University of Pennsylvania is seeking to recruit a full-time Research Specialist to assist with NIH-funded studies of human memory processes and their neural basis. The successful candidate will join a team of research scientists including PhD students and postdoctoral researchers, to assist with both conducting experimental studies and analyzing data. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> Major responsibilities include managing and expanding a pool of volunteers; carrying out experiments on human memory by means of high-density scalp EEG recordings; annotating vocal responses in memory tasks; assisting the research team in processing and analyzing these behavioral and electrophysiological data; supervising a team of undergraduate research assistants; and assisting in general lab administration (grants, progress reports, IRB protocols). <br /> <br /> Required Qualifications: <br /> • Bachelor's degree in psychology, cognitive science, neuroscience, or related field, and 0 to 1 year of experience.<br /> • Excellent organizational and interpersonal skills. <br /> <br /> Preferred Qualifications: <br /> • Relevant experience in human subjects research, especially with EEG, fMRI, eye tracking, behavioral measures, and related data analysis. <br /> • Familiarity with Python, MATLAB, R, or other languages, and familiarity with Linux environments. <br /> • A two-year commitment is desired.<br /> <br /> Apply online here: https://wd1.myworkdaysite.com/en-US/recruiting/upenn/careers-at-penn/job/Leidy-Laboratories-of-Biology/Research-Specialist-A--Computational-Memory-Lab_JR00017379<br /> <br /> == Clinical Research Specialist ==<br /> The Computational Memory Lab at the University of Pennsylvania seeks to recruit a research specialist who is eager to assist research studies contributing towards the development of novel therapies for patients with memory impairment. This position focuses on conducting neural recordings (intracranial EEG and single-neuron) and direct electrical brain stimulation in neurosurgical patient participants to probe and modulate the neural substrates of memory function. The successful candidate will join a multi-disciplinary team of researchers, clinicians, data scientists, and engineers to carry out research under National Institutes of Health grant funding. The ideal candidate possesses excellent interpersonal, organizational, and scientific skills and a passion for advanced cutting-edge medical research and technology development. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, or bioengineering, and provides an excellent opportunity to work with clinical researchers, neurologists, and neurosurgeons at top medical research centers across the country. The position requires familiarity with Python, MATLAB, or similar programming languages, and comfort working in a Unix environment, to facilitate data analysis using the lab’s tools. Exceptional candidates will have experience in data analysis and programming. A 2-year commitment is desired. Position is contingent on continued funding.<br /> <br /> Required Qualifications:<br /> • Bachelor's degree in psychology, cognitive science, neuroscience, bioengineering, or related field, and 0 to 1 year of experience.<br /> • Excellent organizational and interpersonal skills. <br /> • Ability to travel up to 20% of the time and work flexible hours as needed.<br /> <br /> Preferred Qualifications:<br /> • Relevant experience in human subjects research, especially in a clinical setting.<br /> • Familiarity with EEG, MRI, and other relevant technologies.<br /> • Familiarity with Python, MATLAB, R, or other languages, and familiarity with Linux environments. <br /> • A two-year commitment is desired.<br /> <br /> Apply online through https://wd1.myworkdaysite.com/en-US/recruiting/upenn/careers-at-penn/job/Leidy-Laboratories-of-Biology/Research-Specialist--Computational-Memory-Lab_JR00017387--&gt;<br /> <br /> ==Research Project Manager ==<br /> <br /> The Research Project Manager will work directly under the Principle Investigator to administer a large multi-site project aimed at using direct electrical stimulation of human brains as a manipulative tool to probe network physiology, especially memory-related networks, and as a potential therapy for cognitive restoration in patients suffering from the effects of traumatic brain injury or other neurological disorders. This a multi-functional role overseeing all aspects of these projects, with responsibilities ranging from hiring and managing a team of research and software development staff, coordinating data collection across multiple clinical research sites, managing regulatory affairs, developing training and workflows, in-person travel to clinical research centers to perform start-up activities and facilitate data collection, providing guidance and feedback to the systems development team responsible for developing the memory testing and stimulation platform, and other project management duties. Candidates must possess very strong technical skills, including experience with electrophysiology in either animal or human studies and in programming novel data analyses. This position is funded by federally-sponsored research grants and contingent on continued grant support<br /> <br /> Required Qualifications:<br /> <br /> A bachelor's degree in neuroscience, biomedical engineering, biophysics, psychology, or related field; 3-5 years of research experience, ideally in a setting of high-volume data collection and quantitative analysis; strong communication skills, excellent organizational skills; Basic neuroscience/neuroanatomy background knowledge; Familiarity with clinical and research electrophysiology systems (scalp EEG, intracranial EEG, human single unit recordings); Experience using UNIX/Linux systems; Experience with scientific/statistical computing techniques and languages; Human subjects research experience, especially in a clinical setting<br /> <br /> Preferred Qualifications:<br /> <br /> An advanced degree (MS, MEng, PhD, etc.) in neuroscience, biomedical engineering, biophysics, psychology, or related field; Experience with grant progress report preparation and proposal writing; Experience with regulatory affairs: IRB protocol submission and continuing reviews; Proficiency and stronger experience with those listed above in “Required”.<br /> <br /> == Digital Media Design (Undergraduate Work-study Position) ==<br /> The Computational Memory Lab is looking to recruit a DMD student for the 2019 Fall semester to help design UNITY-based memory experiments to interface with closed-loop brain stimulation algorithms. Additionally, we are looking for a student who can assist with designing stunning graphical illustrations of scientific findings for inclusion in our lab's research publications. To apply for the position, please send a CV and transcript to Professor Kahana at kahana@psych.upenn.edu using the subject line: &quot;3-D Design”.<br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Undergraduate Research Assistant to assist with federally funded studies of human memory processes. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings and annotating vocal responses in memory tasks. This position requires an individual who possesses excellent interpersonal and organizational skills. This would be an ideal position for a student interested in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> To apply, please submit a resume to memorylab@psych.upenn.edu.--&gt;<br /> <br /> &lt;!--== Research Coordinator ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania’s School of Arts and Sciences is seeking to recruit a full-time research coordinator/lab manager to assist the Principal Investigator with essential research operations in the laboratory, coordinating activities across three federally funded research grants.<br /> <br /> The research coordinator will have major responsibility for coordinating the administration and the day-to-day operations of multiple grants and related research and academic activities. The coordinator will work directly under the principal investigator, helping to enhance his effectiveness by providing management support for his numerous projects and by representing him and acting on his behalf in interactions with funding agencies, university administrators, lab personnel, and colleagues and collaborators at varied academic and medical organizations. The position will also assist Prof. Kahana with a large multicenter Department of Defense funded study (http://goo.gl/PclHCZ) as well as other federally funded projects.<br /> <br /> The position will also operate as the lab’s internal operations consultant, identifying areas for enhancing operational efficiency and working with technical team members to improve processes related to data collection, organization, and analysis as well as information management systems.<br /> <br /> This position will provide the opportunity to act as the ‘right hand’ to an academic leader who values focus, dedication, and hard work. This is an incredibly fast-moving role, requiring meticulous attention to detail and excellent time management skills. A positive, results-oriented professional with strong judgment, exceptional multitasking skills, and eagerness to take ownership of rewarding duties will thrive in this position.<br /> <br /> === Qualifications ===<br /> <br /> * Bachelor’s Degree in a technical area such as science, business, or engineering, and 1 to 2 years of experience or equivalent combination of education and experience is required.<br /> * Exceptional academic credentials and prior experience in positions requiring a high level of responsibility and attention to detail. <br /> * Ability to combine scientific, business, and computing skills, including familiarity with Mac OSX applications. <br /> <br /> [https://jobs.hr.upenn.edu/postings/27161 '''Apply online at https://jobs.hr.upenn.edu/postings/27161.''']<br /> <br /> <br /> == Research Specialist ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a full-time research specialist to assist with NIH-funded studies of human memory processes and how these processes change across the adult lifespan. The project is aimed at using computational models to interpret behavior and neural data both on healthy memory function in young adults and age-related impairments in memory performance. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories and how these processes are affected by aging. For more information about the lab and our projects, please visit http://memory.psych.upenn.edu. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering. <br /> <br /> Major responsibilities include managing and expanding a pool of both younger adults (18-30 years) and older adults (60+ years) volunteers; carrying out experiments on human memory by means of high-density scalp EEG recordings; annotating vocal responses in memory tasks; assisting the research team in processing and analyzing these behavioral and electrophysiological data; supervising a team of undergraduate research assistants; and assisting in general lab administration (grants, progress reports, IRB protocols). This position requires an individual who possesses excellent interpersonal, organizational, and scientific skills. This individual must be able to work independently with limited oversight to maximize the amount of high-quality data collected.<br /> <br /> === Qualifications ===<br /> <br /> * A Bachelor’s degree <br /> * 0 to 1 year of research experience relevant to the work being carried out in the computational memory lab, including experience working with research participants in the analysis of experimental data or equivalent combination of education and experience<br /> <br /> [https://jobs.hr.upenn.edu/postings/27162 '''Apply online at https://jobs.hr.upenn.edu/postings/27162.''']<br /> <br /> <br /> == Clinical Research Specialist ==<br /> <br /> The Computational Memory Laboratory at the University of Pennsylvania is hiring a Clinical Research Specialist to assist in the development of a novel brain stimulation therapy for patients with memory impairment. This full-time position is funded by DARPA as part of the Restoring Active Memory (RAM) project, a flagship neuro-engineering project within President Obama’s BRAIN Initiative. The successful candidate will join a multi-disciplinary team of researchers, clinicians, data scientists, and software developers to study the ways in which the brain stores and retrieves verbal and spatial memories. The selected candidate will administer memory tests and collect electrophysiological recordings from neurosurgical patients at medical centers in the Philadelphia area. He/she will also interface with research staff at leading neuroscience institutions around the country, coordinate regulatory submissions, process behavioral and electrophysiological data to produce experiment session reports, communicate results to physicians, and perform regular data quality audits. The ideal candidate possesses excellent interpersonal and organizational skills, a passion for advanced cutting-edge medical research and technology development, and some programming experience. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> === Qualifications ===<br /> <br /> *Bachelor’s degree strongly preferred and 3 to 5 year of experience or equivalent combination of education and experience, including: Excellent written and verbal communication skills. <br /> *Experience in working with research participants, especially in a clinical setting. <br /> *Ability to travel 10% of the time. <br /> *Experience with Python, MATLAB, or other programming languages preferred. <br /> *Experience with Windows, Mac, and Linux operating systems preferred. <br /> *Ability to work flexible hours is required.<br /> <br /> [http://jobs.hr.upenn.edu/postings/26250 '''Apply online at http://jobs.hr.upenn.edu/postings/26250.''']<br /> <br /> == Clinical Research Assistant ==<br /> <br /> The Computational Memory Lab at the University of Pennsylvania has an outstanding opportunity for a Clinical Research Assistant.<br /> <br /> For more information on the position and to apply, please visit: http://jobs.hr.upenn.edu/postings/21018 --&gt;<br /> <br /> <br /> &lt;!--== Scientific Programmer ==<br /> <br /> The Computational Memory Lab at the University of Pennsylvania has an outstanding opportunity for a Scientific Programmer.<br /> <br /> For more information on the position and to apply, please visit: http://jobs.hr.upenn.edu:80/postings/19734--&gt;<br /> <br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Research Assistant to assist with federally funded studies of human memory processes and how these processes change across the adult lifespan. The project is aimed at using computational models to interpret behavioral and neural data both on healthy memory function in young adults and age-related impairments in memory performance. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories and how these processes are affected by aging.<br /> <br /> This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings; annotating vocal responses in memory tasks; assisting the research team in processing and analyzing these behavioral and electrophysiological data; supervising a team of undergraduate research assistants; and assisting in general lab administration (grants, progress reports, IRB protocols). This position requires an individual who possesses excellent interpersonal, organizational, and scientific skills. This individual must be able to work independently with limited oversight to maximize the amount of high-quality data collected.<br /> <br /> To apply, submit a cover letter, unofficial transcripts, and a resume to memorylab@psych.upenn.edu<br /> <br /> == Senior Data Analyst ([http://www.darpa.mil/program/restoring-active-memory DARPA RAM Project]) ==<br /> <br /> The Computational Memory Lab is hiring a Senior Data Analyst. The selected applicant will lead the development of novel machine learning algorithms to decode cognitive states based upon multichannel intracranial time series data from human and nonhuman subjects. He/she will implement dimensionality reduction techniques and evaluate and implement large-scale data processing architectures (Hadoop, Hive, Spark, etc.) to manage the analysis of hundreds of terabytes of neural and behavioral data. He/she will interface with principal investigators and senior research staff at leading neuroscience institutions and medical device companies, and present results to project sponsors. The ideal candidate will possess exceptional statistical and programming skills, and the ability to communicate complex concepts through sophisticated data visualizations.<br /> <br /> '''Required Qualifications'''<br /> <br /> *PhD in computer science, statistics, engineering, neuroscience or directly related quantitative field, or MS with at least 4 years relevant post-graduate experience.<br /> *Background in machine learning, regression modeling, feature discovery/selection, optimization, exploratory data analysis, data mining, pattern recognition.<br /> *Experience with the development and implementation of novel machine learning techniques.<br /> *Experience with Python, C/C++ and object-oriented programming techniques.<br /> *Experience with scientific computing languages (Python, R, SAS, Matlab).<br /> <br /> '''Preferred Qualifications'''<br /> <br /> *Experience with neural time series analysis.<br /> *Experience with large-scale data storage processing architectures (Hadoop, Hive, Spark, etc.).<br /> *Experience with collaborative software development.<br /> *Experience with Windows, Mac and Linux development environments.<br /> *Good communication, interpersonal, and leadership skills.<br /> <br /> [https://jobs.hr.upenn.edu/postings/12092 '''Apply online at https://jobs.hr.upenn.edu/postings/12092''']<br /> <br /> == Senior Scientific Programmer ([http://www.darpa.mil/program/restoring-active-memory DARPA RAM Project]) ==<br /> <br /> The Computational Memory Lab is hiring a Senior Scientific Programmer to lead the development of software tools and computational resources needed to develop a novel brain stimulation therapy for patients with memory impairment. This groundbreaking neuro-engineering project is part of President Obama’s BRAIN Initiative. <br /> <br /> The selected applicant will lead the development of technical computing software, experimental programming libraries, cluster computing resources, and data transfer protocols. He/she will interface with senior research staff at multiple institutions and equipment vendors, and lead the development of a real-time system for closed-loop brain recording and stimulation, with high data acquisition and computational loads and low-latency requirements. He/she will manage the configuration of the closed-loop brain recording and stimulation system, including system updates and technical support to multiple clinical sites. Finally, he/she will lead the development and maintenance of systems to transfer experimental data from clinical sites to a centralized server. The ideal candidate will possess exceptional system development skills, past experience in mathematical programming, and the ability to develop and enhance a hybrid system implemented in multiple computer languages.<br /> <br /> '''Required Qualifications'''<br /> <br /> *Bachelor’s degree with at least 5 years relevant experience or Master’s degree with at least 3 years relevant experience<br /> *Proficiency with C/C++ and Python<br /> *Experience with scientific / statistical computing techniques and languages (MATLAB, SciPy, NumPy, etc.)<br /> *Experience with Windows, Mac or Linux or Unix development environments<br /> <br /> '''Preferred Qualifications'''<br /> <br /> *PhD in computer science, neuroscience, bioengineering, mathematics or physics <br /> *Experience with real-time computing and threading<br /> *Experience working in a fast-paced collaborative software development setting<br /> <br /> [http://jobs.hr.upenn.edu/postings/11057 '''Apply online at http://jobs.hr.upenn.edu/postings/11057.''']<br /> <br /> == Scientific Software Developer ([http://www.darpa.mil/program/restoring-active-memory DARPA RAM Project]) ==<br /> <br /> This position is responsible for developing and maintaining state-of-the-art tools to conduct human memory experiments and to develop new therapies to treat memory disorders. You will be responsible for the development and testing of experimental programming libraries, and data analysis of large neurophysiology data sets. You will integrate applications with other system components, create system and user-level documentation, and develop architectures to store and analyze large data sets. The position will be supervised by the project director and will interface extensively with project scientists, engineers and clinicians.<br /> <br /> '''Required Qualifications'''<br /> <br /> *Experience with Python, Matlab, or C/C++ required.<br /> *Ability to implement, understand, and maintain mathematical and scientific codes.<br /> <br /> '''Preferred Qualifications'''<br /> <br /> *Master’s or PhD in mathematics, computer science, engineering, or other scientific field preferred.<br /> *Experience with Big Data technologies, including Hadoop and Spark. SQL database programming. <br /> *Developing or maintaining public software libraries. <br /> *Identifying technical and algorithmic needs for research teams.<br /> *Software engineering, including algorithms, design, data structures, and object-oriented techniques.<br /> <br /> [http://jobs.hr.upenn.edu/postings/10538 '''Apply online at http://jobs.hr.upenn.edu/postings/10538.''']<br /> <br /> == Research Specialist A ==<br /> <br /> The Computational Memory Lab at the University of Pennsylvania is seeking to recruit a full-time research specialist for aresearch<br /> and development project. The project is aimed at producing cognitive enhancement through brain stimulation. The successful applicant will join a team of research<br /> scientists studying the ways in which the brain stores and retrieves verbal and spatial memories, and whether memory can be enhanced or attenuated by stimulation.<br /> <br /> This would be an ideal position for someone interested in ultimately pursuing graduate training in engineering (especially bio/biomedical), medicine, psychology,<br /> neuroscience, or cognitive science.<br /> <br /> Major responsibilities include carrying out experiments on human memory with neurosurgical patients who are undergoing long term monitoring with implanted<br /> electrodes; carrying out experiments on patients and healthy volunteers using scalp EEG; assisting the research team in processing and analyzing these behavioral and<br /> electrophysiological data; and assisting in general lab administration (grants, progress reports, IRB protocols). This position requires an individual who possesses<br /> excellent interpersonal, organizational, and scientific skills. This individual must be able to work independently (and alongside clinical personnel) with limited<br /> oversight to ensure that as much high-quality data is collected from each patient as possible.<br /> <br /> A 2-3 year minimum commitment is desired.<br /> <br /> === Required Qualifications ===<br /> <br /> *Bachelor's degree in Engineering, Psychology, Neuroscience, Pre-Med, or related field.<br /> *Excellent interpersonal, organizational, and scientific skills.<br /> *Ability to work independently (and alongside clinical professionals) with limited oversight to ensure that high-quality data is collected.<br /> <br /> === Preferred Qualifications ===<br /> *MATLAB, Unix, and/or Python experience.<br /> <br /> Job not yet posted to Penn jobs site.<br /> --&gt;<br /> <br /> &lt;!--For more information on our research, please click [[Research| here]].<br /> --&gt;<br /> [https://www.hr.upenn.edu/career/salary-offers For more information on Penn's salary structure, click here.]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Jobs&diff=7020 Jobs 2020-08-25T15:17:17Z <p>Ckeane1: </p> <hr /> <div>''' The Computational Memory Lab is currently seeking applications for the following positions: '''<br /> <br /> &lt;!--<br /> &lt;!--== Research Specialist ==<br /> The Computational Memory Lab in the Department of Psychology at the University of Pennsylvania is seeking to recruit a full-time Research Specialist to assist with NIH-funded studies of human memory processes and their neural basis. The successful candidate will join a team of research scientists including PhD students and postdoctoral researchers, to assist with both conducting experimental studies and analyzing data. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> Major responsibilities include managing and expanding a pool of volunteers; carrying out experiments on human memory by means of high-density scalp EEG recordings; annotating vocal responses in memory tasks; assisting the research team in processing and analyzing these behavioral and electrophysiological data; supervising a team of undergraduate research assistants; and assisting in general lab administration (grants, progress reports, IRB protocols). <br /> <br /> Required Qualifications: <br /> • Bachelor's degree in psychology, cognitive science, neuroscience, or related field, and 0 to 1 year of experience.<br /> • Excellent organizational and interpersonal skills. <br /> <br /> Preferred Qualifications: <br /> • Relevant experience in human subjects research, especially with EEG, fMRI, eye tracking, behavioral measures, and related data analysis. <br /> • Familiarity with Python, MATLAB, R, or other languages, and familiarity with Linux environments. <br /> • A two-year commitment is desired.<br /> <br /> Apply online here: https://wd1.myworkdaysite.com/en-US/recruiting/upenn/careers-at-penn/job/Leidy-Laboratories-of-Biology/Research-Specialist-A--Computational-Memory-Lab_JR00017379<br /> <br /> == Clinical Research Specialist ==<br /> The Computational Memory Lab at the University of Pennsylvania seeks to recruit a research specialist who is eager to assist research studies contributing towards the development of novel therapies for patients with memory impairment. This position focuses on conducting neural recordings (intracranial EEG and single-neuron) and direct electrical brain stimulation in neurosurgical patient participants to probe and modulate the neural substrates of memory function. The successful candidate will join a multi-disciplinary team of researchers, clinicians, data scientists, and engineers to carry out research under National Institutes of Health grant funding. The ideal candidate possesses excellent interpersonal, organizational, and scientific skills and a passion for advanced cutting-edge medical research and technology development. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, or bioengineering, and provides an excellent opportunity to work with clinical researchers, neurologists, and neurosurgeons at top medical research centers across the country. The position requires familiarity with Python, MATLAB, or similar programming languages, and comfort working in a Unix environment, to facilitate data analysis using the lab’s tools. Exceptional candidates will have experience in data analysis and programming. A 2-year commitment is desired. Position is contingent on continued funding.<br /> <br /> Required Qualifications:<br /> • Bachelor's degree in psychology, cognitive science, neuroscience, bioengineering, or related field, and 0 to 1 year of experience.<br /> • Excellent organizational and interpersonal skills. <br /> • Ability to travel up to 20% of the time and work flexible hours as needed.<br /> <br /> Preferred Qualifications:<br /> • Relevant experience in human subjects research, especially in a clinical setting.<br /> • Familiarity with EEG, MRI, and other relevant technologies.<br /> • Familiarity with Python, MATLAB, R, or other languages, and familiarity with Linux environments. <br /> • A two-year commitment is desired.<br /> <br /> Apply online through https://wd1.myworkdaysite.com/en-US/recruiting/upenn/careers-at-penn/job/Leidy-Laboratories-of-Biology/Research-Specialist--Computational-Memory-Lab_JR00017387--&gt;<br /> <br /> ==Research Project Manager ==<br /> <br /> The Research Project Manager will work directly under the Principle Investigator to administer a large multi-site project aimed at using direct electrical stimulation of human brains as a manipulative tool to probe network physiology, especially memory-related networks, and as a potential therapy for cognitive restoration in patients suffering from the effects of traumatic brain injury or other neurological disorders. This a multi-functional role overseeing all aspects of these projects, with responsibilities ranging from hiring and managing a team of research and software development staff, coordinating data collection across multiple clinical research sites, managing regulatory affairs, developing training and workflows, in-person travel to clinical research centers to perform start-up activities and facilitate data collection, providing guidance and feedback to the systems development team responsible for developing the memory testing and stimulation platform, and other project management duties. Candidates must possess very strong technical skills, including experience with electrophysiology in either animal or human studies and in programming novel data analyses. This position is funded by federally-sponsored research grants and contingent on continued grant support<br /> <br /> Required Qualifications:<br /> <br /> A bachelor's degree in neuroscience, biomedical engineering, biophysics, psychology, or related field; 3-5 years of research experience, ideally in a setting of high-volume data collection and quantitative analysis; strong communication skills, excellent organizational skills; Basic neuroscience/neuroanatomy background knowledge; Familiarity with clinical and research electrophysiology systems (scalp EEG, intracranial EEG, human single unit recordings); Experience using UNIX/Linux systems; Experience with scientific/statistical computing techniques and languages; Human subjects research experience, especially in a clinical setting<br /> <br /> Preferred Qualifications:<br /> <br /> An advanced degree (MS, MEng, PhD, etc.) in neuroscience, biomedical engineering, biophysics, psychology, or related field; Experience with grant progress report preparation and proposal writing; Experience with regulatory affairs: IRB protocol submission and continuing reviews; Proficiency and stronger experience with those listed above in “Required”.<br /> <br /> == Digital Media Design (Undergraduate Work-study Position) ==<br /> The Computational Memory Lab is looking to recruit a DMD student for the 2019 Fall semester to help design UNITY-based memory experiments to interface with closed-loop brain stimulation algorithms. Additionally, we are looking for a student who can assist with designing stunning graphical illustrations of scientific findings for inclusion in our lab's research publications. To apply for the position, please send a CV and transcript to Professor Kahana at kahana@psych.upenn.edu using the subject line: &quot;3-D Design”.<br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Undergraduate Research Assistant to assist with federally funded studies of human memory processes. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings and annotating vocal responses in memory tasks. This position requires an individual who possesses excellent interpersonal and organizational skills. This would be an ideal position for a student interested in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> To apply, please submit a resume to memorylab@psych.upenn.edu.--&gt;<br /> <br /> &lt;!--== Research Coordinator ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania’s School of Arts and Sciences is seeking to recruit a full-time research coordinator/lab manager to assist the Principal Investigator with essential research operations in the laboratory, coordinating activities across three federally funded research grants.<br /> <br /> The research coordinator will have major responsibility for coordinating the administration and the day-to-day operations of multiple grants and related research and academic activities. The coordinator will work directly under the principal investigator, helping to enhance his effectiveness by providing management support for his numerous projects and by representing him and acting on his behalf in interactions with funding agencies, university administrators, lab personnel, and colleagues and collaborators at varied academic and medical organizations. The position will also assist Prof. Kahana with a large multicenter Department of Defense funded study (http://goo.gl/PclHCZ) as well as other federally funded projects.<br /> <br /> The position will also operate as the lab’s internal operations consultant, identifying areas for enhancing operational efficiency and working with technical team members to improve processes related to data collection, organization, and analysis as well as information management systems.<br /> <br /> This position will provide the opportunity to act as the ‘right hand’ to an academic leader who values focus, dedication, and hard work. This is an incredibly fast-moving role, requiring meticulous attention to detail and excellent time management skills. A positive, results-oriented professional with strong judgment, exceptional multitasking skills, and eagerness to take ownership of rewarding duties will thrive in this position.<br /> <br /> === Qualifications ===<br /> <br /> * Bachelor’s Degree in a technical area such as science, business, or engineering, and 1 to 2 years of experience or equivalent combination of education and experience is required.<br /> * Exceptional academic credentials and prior experience in positions requiring a high level of responsibility and attention to detail. <br /> * Ability to combine scientific, business, and computing skills, including familiarity with Mac OSX applications. <br /> <br /> [https://jobs.hr.upenn.edu/postings/27161 '''Apply online at https://jobs.hr.upenn.edu/postings/27161.''']<br /> <br /> <br /> == Research Specialist ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a full-time research specialist to assist with NIH-funded studies of human memory processes and how these processes change across the adult lifespan. The project is aimed at using computational models to interpret behavior and neural data both on healthy memory function in young adults and age-related impairments in memory performance. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories and how these processes are affected by aging. For more information about the lab and our projects, please visit http://memory.psych.upenn.edu. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering. <br /> <br /> Major responsibilities include managing and expanding a pool of both younger adults (18-30 years) and older adults (60+ years) volunteers; carrying out experiments on human memory by means of high-density scalp EEG recordings; annotating vocal responses in memory tasks; assisting the research team in processing and analyzing these behavioral and electrophysiological data; supervising a team of undergraduate research assistants; and assisting in general lab administration (grants, progress reports, IRB protocols). This position requires an individual who possesses excellent interpersonal, organizational, and scientific skills. This individual must be able to work independently with limited oversight to maximize the amount of high-quality data collected.<br /> <br /> === Qualifications ===<br /> <br /> * A Bachelor’s degree <br /> * 0 to 1 year of research experience relevant to the work being carried out in the computational memory lab, including experience working with research participants in the analysis of experimental data or equivalent combination of education and experience<br /> <br /> [https://jobs.hr.upenn.edu/postings/27162 '''Apply online at https://jobs.hr.upenn.edu/postings/27162.''']<br /> <br /> <br /> == Clinical Research Specialist ==<br /> <br /> The Computational Memory Laboratory at the University of Pennsylvania is hiring a Clinical Research Specialist to assist in the development of a novel brain stimulation therapy for patients with memory impairment. This full-time position is funded by DARPA as part of the Restoring Active Memory (RAM) project, a flagship neuro-engineering project within President Obama’s BRAIN Initiative. The successful candidate will join a multi-disciplinary team of researchers, clinicians, data scientists, and software developers to study the ways in which the brain stores and retrieves verbal and spatial memories. The selected candidate will administer memory tests and collect electrophysiological recordings from neurosurgical patients at medical centers in the Philadelphia area. He/she will also interface with research staff at leading neuroscience institutions around the country, coordinate regulatory submissions, process behavioral and electrophysiological data to produce experiment session reports, communicate results to physicians, and perform regular data quality audits. The ideal candidate possesses excellent interpersonal and organizational skills, a passion for advanced cutting-edge medical research and technology development, and some programming experience. This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> === Qualifications ===<br /> <br /> *Bachelor’s degree strongly preferred and 3 to 5 year of experience or equivalent combination of education and experience, including: Excellent written and verbal communication skills. <br /> *Experience in working with research participants, especially in a clinical setting. <br /> *Ability to travel 10% of the time. <br /> *Experience with Python, MATLAB, or other programming languages preferred. <br /> *Experience with Windows, Mac, and Linux operating systems preferred. <br /> *Ability to work flexible hours is required.<br /> <br /> [http://jobs.hr.upenn.edu/postings/26250 '''Apply online at http://jobs.hr.upenn.edu/postings/26250.''']<br /> <br /> == Clinical Research Assistant ==<br /> <br /> The Computational Memory Lab at the University of Pennsylvania has an outstanding opportunity for a Clinical Research Assistant.<br /> <br /> For more information on the position and to apply, please visit: http://jobs.hr.upenn.edu/postings/21018 --&gt;<br /> <br /> <br /> &lt;!--== Scientific Programmer ==<br /> <br /> The Computational Memory Lab at the University of Pennsylvania has an outstanding opportunity for a Scientific Programmer.<br /> <br /> For more information on the position and to apply, please visit: http://jobs.hr.upenn.edu:80/postings/19734--&gt;<br /> <br /> <br /> &lt;!--== Research Assistant (Undergraduate Work-Study) ==<br /> <br /> The Computational Memory Laboratory in the Department of Psychology at the University of Pennsylvania is seeking to recruit a part-time Research Assistant to assist with federally funded studies of human memory processes and how these processes change across the adult lifespan. The project is aimed at using computational models to interpret behavioral and neural data both on healthy memory function in young adults and age-related impairments in memory performance. The successful candidate will join a team of research scientists studying the ways in which the brain stores and retrieves verbal and spatial memories and how these processes are affected by aging.<br /> <br /> This would be an ideal position for someone interested in ultimately pursuing graduate training in cognitive neuroscience, medicine, psychology, or bioengineering.<br /> <br /> Major responsibilities include carrying out experiments on human memory by means of high-density scalp EEG recordings; annotating vocal responses in memory tasks; assisting the research team in processing and analyzing these behavioral and electrophysiological data; supervising a team of undergraduate research assistants; and assisting in general lab administration (grants, progress reports, IRB protocols). This position requires an individual who possesses excellent interpersonal, organizational, and scientific skills. This individual must be able to work independently with limited oversight to maximize the amount of high-quality data collected.<br /> <br /> To apply, submit a cover letter, unofficial transcripts, and a resume to memorylab@psych.upenn.edu<br /> <br /> == Senior Data Analyst ([http://www.darpa.mil/program/restoring-active-memory DARPA RAM Project]) ==<br /> <br /> The Computational Memory Lab is hiring a Senior Data Analyst. The selected applicant will lead the development of novel machine learning algorithms to decode cognitive states based upon multichannel intracranial time series data from human and nonhuman subjects. He/she will implement dimensionality reduction techniques and evaluate and implement large-scale data processing architectures (Hadoop, Hive, Spark, etc.) to manage the analysis of hundreds of terabytes of neural and behavioral data. He/she will interface with principal investigators and senior research staff at leading neuroscience institutions and medical device companies, and present results to project sponsors. The ideal candidate will possess exceptional statistical and programming skills, and the ability to communicate complex concepts through sophisticated data visualizations.<br /> <br /> '''Required Qualifications'''<br /> <br /> *PhD in computer science, statistics, engineering, neuroscience or directly related quantitative field, or MS with at least 4 years relevant post-graduate experience.<br /> *Background in machine learning, regression modeling, feature discovery/selection, optimization, exploratory data analysis, data mining, pattern recognition.<br /> *Experience with the development and implementation of novel machine learning techniques.<br /> *Experience with Python, C/C++ and object-oriented programming techniques.<br /> *Experience with scientific computing languages (Python, R, SAS, Matlab).<br /> <br /> '''Preferred Qualifications'''<br /> <br /> *Experience with neural time series analysis.<br /> *Experience with large-scale data storage processing architectures (Hadoop, Hive, Spark, etc.).<br /> *Experience with collaborative software development.<br /> *Experience with Windows, Mac and Linux development environments.<br /> *Good communication, interpersonal, and leadership skills.<br /> <br /> [https://jobs.hr.upenn.edu/postings/12092 '''Apply online at https://jobs.hr.upenn.edu/postings/12092''']<br /> <br /> == Senior Scientific Programmer ([http://www.darpa.mil/program/restoring-active-memory DARPA RAM Project]) ==<br /> <br /> The Computational Memory Lab is hiring a Senior Scientific Programmer to lead the development of software tools and computational resources needed to develop a novel brain stimulation therapy for patients with memory impairment. This groundbreaking neuro-engineering project is part of President Obama’s BRAIN Initiative. <br /> <br /> The selected applicant will lead the development of technical computing software, experimental programming libraries, cluster computing resources, and data transfer protocols. He/she will interface with senior research staff at multiple institutions and equipment vendors, and lead the development of a real-time system for closed-loop brain recording and stimulation, with high data acquisition and computational loads and low-latency requirements. He/she will manage the configuration of the closed-loop brain recording and stimulation system, including system updates and technical support to multiple clinical sites. Finally, he/she will lead the development and maintenance of systems to transfer experimental data from clinical sites to a centralized server. The ideal candidate will possess exceptional system development skills, past experience in mathematical programming, and the ability to develop and enhance a hybrid system implemented in multiple computer languages.<br /> <br /> '''Required Qualifications'''<br /> <br /> *Bachelor’s degree with at least 5 years relevant experience or Master’s degree with at least 3 years relevant experience<br /> *Proficiency with C/C++ and Python<br /> *Experience with scientific / statistical computing techniques and languages (MATLAB, SciPy, NumPy, etc.)<br /> *Experience with Windows, Mac or Linux or Unix development environments<br /> <br /> '''Preferred Qualifications'''<br /> <br /> *PhD in computer science, neuroscience, bioengineering, mathematics or physics <br /> *Experience with real-time computing and threading<br /> *Experience working in a fast-paced collaborative software development setting<br /> <br /> [http://jobs.hr.upenn.edu/postings/11057 '''Apply online at http://jobs.hr.upenn.edu/postings/11057.''']<br /> <br /> == Scientific Software Developer ([http://www.darpa.mil/program/restoring-active-memory DARPA RAM Project]) ==<br /> <br /> This position is responsible for developing and maintaining state-of-the-art tools to conduct human memory experiments and to develop new therapies to treat memory disorders. You will be responsible for the development and testing of experimental programming libraries, and data analysis of large neurophysiology data sets. You will integrate applications with other system components, create system and user-level documentation, and develop architectures to store and analyze large data sets. The position will be supervised by the project director and will interface extensively with project scientists, engineers and clinicians.<br /> <br /> '''Required Qualifications'''<br /> <br /> *Experience with Python, Matlab, or C/C++ required.<br /> *Ability to implement, understand, and maintain mathematical and scientific codes.<br /> <br /> '''Preferred Qualifications'''<br /> <br /> *Master’s or PhD in mathematics, computer science, engineering, or other scientific field preferred.<br /> *Experience with Big Data technologies, including Hadoop and Spark. SQL database programming. <br /> *Developing or maintaining public software libraries. <br /> *Identifying technical and algorithmic needs for research teams.<br /> *Software engineering, including algorithms, design, data structures, and object-oriented techniques.<br /> <br /> [http://jobs.hr.upenn.edu/postings/10538 '''Apply online at http://jobs.hr.upenn.edu/postings/10538.''']<br /> <br /> == Research Specialist A ==<br /> <br /> The Computational Memory Lab at the University of Pennsylvania is seeking to recruit a full-time research specialist for aresearch<br /> and development project. The project is aimed at producing cognitive enhancement through brain stimulation. The successful applicant will join a team of research<br /> scientists studying the ways in which the brain stores and retrieves verbal and spatial memories, and whether memory can be enhanced or attenuated by stimulation.<br /> <br /> This would be an ideal position for someone interested in ultimately pursuing graduate training in engineering (especially bio/biomedical), medicine, psychology,<br /> neuroscience, or cognitive science.<br /> <br /> Major responsibilities include carrying out experiments on human memory with neurosurgical patients who are undergoing long term monitoring with implanted<br /> electrodes; carrying out experiments on patients and healthy volunteers using scalp EEG; assisting the research team in processing and analyzing these behavioral and<br /> electrophysiological data; and assisting in general lab administration (grants, progress reports, IRB protocols). This position requires an individual who possesses<br /> excellent interpersonal, organizational, and scientific skills. This individual must be able to work independently (and alongside clinical personnel) with limited<br /> oversight to ensure that as much high-quality data is collected from each patient as possible.<br /> <br /> A 2-3 year minimum commitment is desired.<br /> <br /> === Required Qualifications ===<br /> <br /> *Bachelor's degree in Engineering, Psychology, Neuroscience, Pre-Med, or related field.<br /> *Excellent interpersonal, organizational, and scientific skills.<br /> *Ability to work independently (and alongside clinical professionals) with limited oversight to ensure that high-quality data is collected.<br /> <br /> === Preferred Qualifications ===<br /> *MATLAB, Unix, and/or Python experience.<br /> <br /> Job not yet posted to Penn jobs site.<br /> --&gt;<br /> <br /> &lt;!--For more information on our research, please click [[Research| here]].--&gt;<br /> --&gt;<br /> [https://www.hr.upenn.edu/career/salary-offers For more information on Penn's salary structure, click here.]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Electrophysiology_Workshop_2020&diff=7001 Electrophysiology Workshop 2020 2020-08-04T21:53:57Z <p>Ckeane1: Ckeane1 moved page Electrophysiology Bootcamp 2020 to Electrophysiology Workshop 2020</p> <hr /> <div>Welcome to the home page for our Summer Workshop in Model-Based Cognitive Electrophysiology. Here, we will share all recorded lectures for those interested in our workshop materials.<br /> <br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1YiuN7KEe2nlrluNrGVOoZCF5ext3Rswu/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Electrophysiology_Bootcamp_2020&diff=7002 Electrophysiology Bootcamp 2020 2020-08-04T21:53:57Z <p>Ckeane1: Ckeane1 moved page Electrophysiology Bootcamp 2020 to Electrophysiology Workshop 2020</p> <hr /> <div>#REDIRECT [[Electrophysiology Workshop 2020]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Electrophysiology_Workshop_2020&diff=7000 Electrophysiology Workshop 2020 2020-08-04T21:03:25Z <p>Ckeane1: </p> <hr /> <div>Welcome to the home page for our Summer Workshop in Model-Based Cognitive Electrophysiology. Here, we will share all recorded lectures for those interested in our workshop materials.<br /> <br /> &lt;iframe k=cml_gdocs p=&quot;file/d/1YiuN7KEe2nlrluNrGVOoZCF5ext3Rswu/preview&quot; width=&quot;640&quot; height=&quot;480&quot;/&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=CEMS_2020&diff=6970 CEMS 2020 2020-07-23T17:22:09Z <p>Ckeane1: </p> <hr /> <div>[[File:CEMS2019.jpg|thumb|600px|''CEMS 2019'']]<br /> <br /> The 2020 Context and Episodic Memory Symposium (CEMS) will be held '''virtually from August 16th-19th'''. Health-related safety concerns and ongoing travel restrictions have led us to adopt an online format for CEMS 2020.<br /> <br /> <br /> In the past few weeks we have learned a great deal from the successes and challenges of other online conferences, and we are working to develop an online poster session format that will allow for meaningful and satisfying engagement for the CEMS community. This will include flexibility in the format and style of the poster presentations, as well as the creation of an intuitive system allowing attendees and poster presenters to interact with one another during the poster session itself. The symposium is designed to be a forum for the exchange of ideas among colleagues working on theoretical and empirical approaches to the study of context and episodic memory, broadly construed.<br /> <br /> <br /> We will be in touch soon with more details about our virtual poster sessions, registration, and about the broader structure of the conference. In the meantime, if you have any questions, do not hesitate to email context.symposium@gmail.com.<br /> <br /> &lt;!--== Conference Registration == <br /> <br /> Registration for CEMS 2020 is now open! Registration fees are:<br /> <br /> * $350 for faculty<br /> * $250 for non-faculty<br /> <br /> Conference registration includes breakfast and lunch on both days of the conference, as well as an opening night reception.<br /> <br /> [http://memory.psych.upenn.edu/files/CEMS/registration_form.html Click here to register for CEMS 2019.]<br /> <br /> ''Please note that registration prices will increase by $50 on April 29th, 2019.''<br /> <br /> == Location &amp; Hotel ==<br /> <br /> ===Venue===<br /> <br /> The venue for CEMS 2020 is the '''Inn at Penn''', located on the campus of the University of Pennsylvania.<br /> <br /> The Inn at Penn is a Four Diamond Hilton hotel, located at 3600 Sansom Street in historic Philadelphia, PA.<br /> <br /> More information on the Inn at Penn can be found on their [https://www.theinnatpenn.com/ website.] Click [http://maps.google.com/maps?q=inn+at+penn&amp;client=safari&amp;oe=UTF-8&amp;fb=1&amp;gl=us&amp;hq=inn+at+penn&amp;cid=0,0,3076482986473528171&amp;t=m&amp;z=16&amp;iwloc=A here] to view this location on Google Maps.<br /> <br /> === Hotel ===<br /> In addition to its role as the venue for CEMS 2020, the [https://www.theinnatpenn.com/ Inn at Penn] served as the preferred hotel for the event. --&gt;<br /> <br /> &lt;!-- In addition to its role as the venue for CEMS 2019, the [https://www.theinnatpenn.com/ Inn at Penn] will serve as the preferred hotel for the event. A limited number of rooms will be available at a special event rate of $235/night. <br /> <br /> To make use of this reduced rate, book your room(s) from our event page '''[https://book.passkey.com/e/49726546 here]'''.<br /> <br /> Please note that our room block includes the evenings of May 12 (Sunday into Monday) and May 13 (Monday into Tuesday). If you attempt to book outside of these dates, you may find the website lists rooms as &quot;not available.&quot; If this is the case, please limit the evenings you are attempting to book through the link above to May 12 and 13.<br /> --&gt;<br /> <br /> &lt;!--== Abstract Submission ==<br /> <br /> '''Abstract Submission for CEMS 2020 is now CLOSED. Thank you for your submissions.'''<br /> <br /> The symposium is designed to be a forum for the exchange of ideas among colleagues working on theoretical and empirical approaches to the study of context and episodic memory, broadly construed. <br /> <br /> The format of CEMS is to have a relatively small number of spoken presentations each followed by a commentary given by a scientist working on related problems. The program committee aims to identify submissions that highlight major new theoretical and/or empirical advances. Papers not selected for these spoken presentations can be given as poster presentations. In previous years, posters have been a major highlight of the meeting and have been very well attended.--&gt;<br /> <br /> &lt;!--'''Abstract submission is now OPEN for CEMS 2020!'''<br /> <br /> We welcome submissions of abstracts for one of three categories: spoken presentation, data blitz or poster presentation (please list all acceptable categories for your submission, in preferred order), and welcome submissions from all members of the scientific community. We are particularly interested in highlighting the work of women and under-represented groups in the field of memory research, and hope all members of the community will be encouraged to submit abstracts for consideration. <br /> <br /> Please email abstract submissions to Georgia Reilly (Research Coordinator) at context.symposium@gmail.com by '''Friday, February 7, 2020'''. We encourage submission of a written description of work (e.g., an extended, more detailed abstract or preprint) in addition to an abstract if such a description is available; this additional information is especially useful for the selection of spoken presentations.--&gt;<br /> <br /> <br /> == Schedule ==<br /> ''If you are presenting and have scheduling conflicts, please let us know as soon as possible by emailing [mailto:context.symposium@gmail.com context.symposium@gmail.com]''<br /> <br /> {| width=&quot;100%&quot;<br /> ! colspan=&quot;2&quot;| '''Monday''' <br /> ! colspan=&quot;2&quot;| '''Tuesday'''<br /> ! colspan=&quot;2&quot;| '''Wednesday'''<br /> |-<br /> | 11:00 || '''Michael Kahana''' ''(University of Pennsylvania)'': Welcome and introductory remarks. || 11:00 || '''Poster Session'''|| 11:00 || '''Michael Kahana''' ''(University of Pennsylvania)'': Welcome and introductory remarks.||<br /> |-<br /> | 11:05 || '''Signy Sheldon''' ''(McGill University)'': Retrieval orientation alters neural activity during autobiographical<br /> memory recollection. <br /> || 12:30 || '''Michael Kahana''' ''(University of Pennsylvania)'': Welcome and introductory remarks. || 11:05 || '''Geoff Ward''' ''(University of Essex)'': Positive effects of rehearsal in short-term, long-term and working memory tasks<br /> |-<br /> | || ** '''Discussant''': Sheldon's discussant'' <br /> |-<br /> | 11:40 || '''Josh Salet''' ''(University of Groningen)'': fMTP: A Unifying Computational Framework of Temporal Preparation Across Time Scales. || 12:35 || '''Jordan Suchow''' ''(Stevens Institute of Technology)'': Memory maintenance in a partially observable mind: rationally deciding what to maintain. || 11:40 || '''Oded Bein''' ''(New York University)'': Learning strengthens the structuring of events<br /> |-<br /> | || || || ** '''Discussant''': Suchow's discussant'' <br /> |-<br /> | 11:55 || '''Buddhika Bellana''' ''(John Hopkins University)'': A persistent influence of narrative transportation on subsequent thought. || 1:10 || '''Samantha Audrain''' ''(University of Toronto)'': Prior knowledge accelerates neocortical integration at the expense of episodic detail. <br /> || 11:55 || '''Christoph Weidemann''' ''(Swansea University; Columbia University)'': Neural measures of subsequent memory reflect endogenous variability in cognitive function.<br /> |-<br /> | 12:10 || '''Merika Sanders''' ''(University of Massachusetts Amherst)'': Manipulating representational demands of a memory discrimination task engages early brain regions || 12:25 || '''Neal Morton''' ''(University of Texas at Austin)'': Representations of common event structure in medial temporal lobe and frontoparietal cortex support efficient inference || 12:10 || '''Break'''<br /> |-<br /> | 12:25 || '''Break''' || 1:40 || '''Break''' || 12:25 || '''Pedro Bordalo''' ''(University of Oxford)'': Memory and Representativeness.<br /> |-<br /> | || || || || || ** '''Discussant''': Bordalo's Discussant''Affiliation''<br /> |-<br /> | 12:40 || '''Keynote Address: Daniel Schacter''' ''(Harvard University)'' || 1:55 || '''Lili Sahakyan''' ''(University of Illinois at Urbana-Champaign)'': Eye Movements Differentiate Intentional Forgetting from Strength-Based Memory Differences. || 1:00 || '''Wei Tang''' ''(Indiana University Bloomington)'': Reinstatement of temporal context observed with human scalp EEG during successful episodic memory retrieval.<br /> |-<br /> | || || || ** '''Discussant''': Sahakyan Discussant ''Affiliation'' <br /> |-<br /> | 1:40 || '''Break''' || 2:30 || '''Qihong Lu''' ''(Princeton University)'': Learning to use episodic memory for event prediction. || 1:15 || '''Sebastian Michelmann''' ''(Princeton University)'': One shot learning of a naturalistic story improves predictions on a fast time-scale in the auditory cortex. <br /> |-<br /> | 1:30 || '''Greg Cox''' ''(Vanderbilt University)'': Expanding the space: A dynamic model of encoding and recognition of episodic associations. || 2:45 || '''Kevin Himberger''' ''(John Hopkins University)'': Reconsidering the Automaticity of Visual Statistical Learning. || 1:30 || '''Alexandra Cohen''' ''(New York University)'': Influences of reward motivation on behavioral and neural memory processes across age.<br /> |-<br /> | || ** '''Discussant''': Ida Momennejad ''Columbia University''<br /> |-<br /> | 2:25 || '''Molly Hermiller''' ''(Northwestern University)'': Hippocampal-targeted theta-patterned stimulation immediately enhances hippocampal memory processing: A simultaneous TMS/fMRI experiment. || 3:00 || '''Robert Jacobs''' ''(University of Rochester)'': Efficient Data Compression in Perception and Perceptual Memory. || 1:45 || '''Break''' <br /> |-<br /> | 2:40 || '''Lukas Kunz''' ''(University of Freiburg)'': Anchor cells in human medial temporal lobe represent egocentric directions during spatial navigation. || 3:15 || '''Break'''|| 1:55 || '''Anna Schapiro''' ''(University of Pennsylvania)'': Interleaving facilitates the rapid formation of distributed representations. <br /> |-<br /> | || || || || || ** '''Discussant''': Anna's Discussant ''Affiliation''<br /> |-<br /> | 2:55 || '''Nora Herweg''' ''(University of Pennsylvania)'': Multi-unit activity in human MTL reflects retrieval of spatial and temporal context. || 3:25 || '''James Kragel''' ''(Northwestern University)'': Temporal context guides visual exploration during scene recognition. || 3:25 || '''Nick Diamond''' ''(University of Pennsylvania)'': Hippocampal contributions to remote real-world spatiotemporal context retrieval.<br /> |-<br /> | || || || ** '''Discussant''': Brad Wyble ''Penn State University''<br /> |-<br /> | 3:10 || '''Break''' || 4:00 || '''Cassandra Jacobs''' ''(University of Wisconsin, Madison)'': The Lexical Context Model of memory for words in lists. || 2:45 || '''Marc Coutanche'' '''(University of Pittsburgh)'': Recalling the when, where and what of naturalistic episodes.<br /> |-<br /> | 3:20 || '''Poster Session''' || 4:15 || '''Simon Dennis''' ''(University of Melbourne)'': ''(University of Wisconsin, Madison)'': The Lexical Context Model of memory for words in lists. || 3:00 || '''Break''' <br /> |-<br /> ||| || || || 3:10 || '''Poster Session'''<br /> |}<br /> <br /> == Past Symposia ==<br /> <br /> For information about past CEMS events, please [[CEMS|click here]].<br /> <br /> &lt;!--<br /> == Schedule for Poster Presentations ==<br /> ''Poster dimensions should be no larger than 40x60 inches. Poster boards, easels, and push pins will be provided. If you are presenting and have scheduling conflicts, please let us know as soon as possible by emailing [mailto:context.symposium@gmail.com context.symposium@gmail.com]''<br /> <br /> {| width=&quot;100%&quot;<br /> ! colspan=&quot;1&quot;| '''Monday Poster Session''' <br /> ! colspan=&quot;1&quot;| '''Tuesday Poster Session'''<br /> |-<br /> | '''Nicholas B. Diamond''' &amp; Brian Levine: ''Differential consolidation of detail and sequence structure in memory for a one-shot real-world event.'' || '''Vencislav Popov''', Matt So, Lynne Reder: ''Word frequency affects binding probability not memory precision.''<br /> |-<br /> |'''Ada Aka''', Sudeep Bhatia: ''Memory dynamics in free recall and memory-based choice behavior.'' || '''Ryan P. Kirkpatrick''' &amp; Per B. Sederberg: ''Fitting trial level effects in free recall experiments with inverse binomial sampling.''<br /> |-<br /> | '''Adam Broitman''', Hamid Turker, Khena Swallow: ''The P300 predicts subsequent biomarkers of recollection and familiarity.'' || '''Brandon G. Jacques''', Marc W. Howard, Per B. Sederberg: ''Improving statistical language models with information across multiple scales.''<br /> |-<br /> | '''Kevin P. Darby''' &amp; Per B. Sederberg: ''Contributions of temporal context and direct item-to-item binding in associative recognition memory.'' || '''Tyler A. Spears''', Marc W. Howard, Per B. Sederberg: ''Scale happens: Demonstrating the importance of timescale invariance in neural networks.''<br /> |-<br /> | '''Simon Dennis''', Paul Garrett, Hyungwook Yim, Jihun Hamm, Adam Osth, Vishnu Sreekumar, Ben Stone: ''Privacy versus open science.'' || '''Zoran Tiganj''', Nathanael Cruzado, Marc W. Howard: ''Towards a neural-level cognitive architecture: Modeling behavior in working memory tasks with neuron.''<br /> |-<br /> | '''Kevin D. Shabahang''', Hyungwook Yim, Simon Dennis: ''An associative theory of semantic composition.'' || ''' Blake L. Elliott''', Aikaterini Stefanidi, Gene A. Brewer: ''Memory and importance: Memory accessibility biases judgments of importance.''<br /> |-<br /> | '''Yue Liu''', Sam Levy, William Mau, Marc Howard: ''Population code for time on the scale of tens of minutes in mouse hippocampus.'' || '''Selda Eren-Kanat''', B. Hunter Ball, Gene A. Brewer: ''Towards a unified model of intention formation and retrieval.''<br /> |-<br /> | '''Zahra G. Esfahani''' &amp; Marc W. Howard: ''A physical model for pattern completion of highly overlapping patterns for human episodic memory.'' || '''Ghootae Kim''', Su Keun Jeong, Brice A. Kuhl: ''Context-based memory overlap enhances structural knowledge of similar experiences.''<br /> |-<br /> | '''Ian M. Bright''', Miriam L. R. Meister, Nathanael Cruzado, Zoran Tiganj, Elizabeth A. Buffalo, Marc W. Howard: ''A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex.'' || '''Elizabeth A. McDevitt''', Ghootae Kim, Nicholas B. Turk-Browne, Kenneth A. Norman: ''Reward value generalizes to memories linked via statistical learning.''<br /> |-<br /> | '''Min Kyung Hong''', Lisa K. Fazio, Sean M. Polyn: ''Examining the Episodic Context Account: Does retrieval practice enhance memory for context?'' || '''Qihong Lu''', Zi Ying Fan, Uri Hasson, Kenneth A. Norman: ''Patience is a virtue: A normative account of why waiting to encode and retrieve memories benefits event understanding.''<br /> |-<br /> | '''Andre Beukers''' &amp; Kenneth A. Norman: ''Curriculum effects in schema learning.'' || '''Silvy H.P. Collin''', Nicholas T. Franklin, Samuel J. Gershman, Andre Beukers, Uri Hasson, Kenneth A. Norman: ''Effect of schema inference on episodic memory.''<br /> |-<br /> | '''Nora A. Herweg''', Paul A. Wanda, Lukas Kunz, Armin Brandt, Michael R. Sperling, Ashwini D. Sharan, ... Michael J. Kahana: ''Decoding spatial information from local field potentials in the human MTL.'' || Yeon Soon Shin, '''Rolando Masis-Obando''', Riya Dave, Neggin Keshavarzian, Kenneth. A. Norman: ''Context-dependent memory effects in two immersive virtual reality environments: on Mars and underwater.'' <br /> |-<br /> | '''Effie Li''' &amp; Michael J. Kahana: ''EEG decoders unveil the hidden dynamics of human memory.'' || '''Yeon Soon Shin''', Yael Niv, Sarah DuBrow: ''A latent-cause inference account of event segmentation under perceptual ambiguity.'' <br /> |-<br /> | '''Kevin D. Himberger''', Amy S. Finn, Christopher J. Honey: ''Statistical learning: Measures and pitfalls.'' || Ryan Tan, '''Srinivas Kota''', Bradley Lega: ''Hippocampal-parietal interactions during retrieval of true versus false memories.''<br /> |-<br /> | '''Sagana Vijayarajah''' &amp; Margaret L. Schlichting: ''Selective attention to semantic versus perceptual features mediates memory for complex illustrations.'' || '''Linh Lazarus''', Abigail Dester, Mitchell G. Uitvlugt, M. Karl Healey: ''The Temporal Contiguity Effect is modulated, but not eliminated, by orthographic distinctiveness.''<br /> |-<br /> | '''Hongmi Lee''', &amp; Janice Chen: ''Narratives as networks: predicting memory from the structure of naturalistic events.'' || '''Abigail Dester''', Linh Lazarus, M. Karl Healey: ''Incidentally encoded memories show approximately scale invariant temporal contiguity.''<br /> |-<br /> | '''Alexandra Decker''', Katherine Duncan, Amy S. Finn: ''Children’s episodic memory formation depends more on attention than adults'.'' || '''Helen Schmidt''', Rosalie Samide, Rose A. Cooper, Maureen Ritchey: ''News Flash! Investigating the dynamics of emotional memory using real-life event videos.''<br /> |-<br /> | '''William J. Hopper''' &amp; David E. Huber: ''Testing the Primary and Convergent Retrieval model of recall: Recall practice produces faster recall success but also faster recall failure.'' || '''Joseph A. Sileo''', Rivka Cohen, Michael J. Kahana: ''Effects of pre-familiarization on recall dynamics.''<br /> |-<br /> | '''Taylor Curley''', Nichol Castro, Christopher Hertzog, John Dunlosky: ''Exploring the effects of encoding and semantic network properties on memory for related items.'' || '''Alexa Tompary''' &amp; Sharon L. Thompson-Schill: ''Quantifying semantic influences on distortions in episodic memory.''<br /> |-<br /> | '''Neal W. Morton''', Margaret L. Schlichting, Alison R. Preston: ''Events with common structure become organized within a hierarchical cognitive map in hippocampus and frontoparietal cortex.'' || '''Anuya Patil''' &amp; Katherine Duncan: ''Measuring the neural underpinnings of lingering mnemonic states.''<br /> |-<br /> | '''Paul F. Hill''', Danielle R. King, Bradley Lega, Michael D. Rugg: ''Comparison of fMRI correlates of successful episodic memory encoding in temporal lobe epilepsy patients and heathy controls.'' || '''Kyle Nealy''', Sheena Josselyn, Paul Frankland, Meg Schlichting, Katherine Duncan. ''Does the temporal proximity of related events modulate their integration in memory?''<br /> |-<br /> | '''Jack H. Wilson''' &amp; Amy H. Criss: ''Evidence for global matching during memory recovery.'' || '''Olga Lositsky''' &amp; David Badre: ''Gradual changes promote the generalization of behavioral rules across temporal contexts.''<br /> |-<br /> | '''Marc N. Coutanche''', Griffin E. Koch, John P. Paulus: ''Using neural representations during encoding to predict subsequent retrieval of dynamic events.'' || '''Rebecca A. Cutler''', Sarah Brown-Schmidt, Sean M. Polyn: ''Semantic structure in memory for narratives: A benefit for semantically congruent ideas.''<br /> |-<br /> | S. Brodt, S. Gais, J. Beck, M. Erb, K. Scheffler, '''Monika Schönauer''': ''Fast track to the neocortex: A memory engram in the posterior parietal cortex.'' || '''Chi T. Ngo''', Aidan J. Horner, Nora S. Newcombe, Ingrid R. Olson: ''The development of holistic episodic recollection.''<br /> |-<br /> | '''Adam F. Osth''', Douglas J. K. Mewhort, Andrew Heathcote: ''Global semantic similarity effects in recognition memory: Insights from BEAGLE representations and the diffusion decision model.'' || '''Matt Siegelman''' &amp; Chris Baldassano: ''Modeling brain representations of structured schematic poetry with recurrent neural networks.''<br /> |-<br /> | '''Cheng Qiu''', Long Luu, Alan A. Stocker: ''Benefits of conditioned inference in working memory recall.'' || '''Caroline S. Lee''', Mariam Aly, Chris Baldassano: ''Anticipation of temporally structured events in the brain.''<br /> |-<br /> | '''Srinivas Kota''', Michael D. Rugg, Linley Robinson, Bradley C. Lega: ''Hippocampal theta oscillations distinguish recollected from recognized memory items in associative recognition memory.'' || '''Brian Silston''', Kevin Ochsner, Mariam Aly: ''Threat impairs flexible use of a cognitive map.''<br /> |-<br /> | '''Sebastian Michelmann''', Howard Bowman, Uri Hasson, Kenneth A. Norman, Simon Hanslmayr: ''The structure of continuous memory replay across event boundaries in humans.'' || '''Eren Gunseli''' &amp; Mariam Aly: ''Establishing memory-driven attentional goals via hippocampus and medial prefrontal cortex.''<br /> |-<br /> | Simon Henin, Anita Shankar, Nicholas Hasulak, Daniel Friedman, Patricia Dugan, Lucia Melloni, ... '''Anli Liu''': ''Hippocampal gamma predicts associative memory performance as measured by acute and chronic intracranial EEG.'' || '''Nicholas Ruiz''' &amp; Mariam Aly: ''Cholinergic modulation enhances hippocampally-dependent spatial relational attention.''<br /> |-<br /> | '''Simon Henin''', Nicholas Turk-Browne, Daniel Friedman, Anli Liu, Patricia Dugan, Adeen Flinker, ... Lucia Melloni: ''Online tracking of neural changes during statistical learning.'' || '''Vishnu Sreekumar''', Baltazar Zavala, Kareem Zaghloul. ''Prefrontal-subthalamic contri<br /> --&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Software&diff=6919 Software 2020-05-04T20:12:24Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> == Experiments ==<br /> <br /> === Foundational Libraries ===<br /> * [http://pyepl.sourceforge.net PyEPL] (the Python Experiment-Programming Library) is a library for coding psychology experiments in Python. It supports presentation of both visual and auditory stimuli, and supports both manual (keyboard/joystick) and sound (microphone) input as responses. Visit the [http://pyepl.sourceforge.net PyEPL SourceForge page] for more information and downloads, or click [http://memory.psych.upenn.edu/files/pyepl_installer.zip here] for an updated installer, capable of working on El Capitan. ([[Publications#GellEtal07|Methods paper can be found here.]])<br /> * [[PandaEPL]] is a cross-platform Python library for programming 3D spatial navigation experiments. ([[Publications#SolwEtal13|Methods paper can be found here.]])<br /> * [[UnityEPL]] is a library of C# scripts that facilitates precise timing, logging, and communication with external hardware. Code is available [https://github.com/pennmem/UnityEPL here].<br /> <br /> === Experiment Paradigms ===<br /> PyEPL-based experiments used in the Kahana Lab.<br /> <br /> * pyFGS: Face/Grating Sternberg task ([http://memory.psych.upenn.edu/files/software/experiments/pyFGS.tgz tgz])<br /> * pyFR: Free Recall task ([http://memory.psych.upenn.edu/files/software/experiments/pyFR.tgz tgz])<br /> * YellowCab II: Virtual Driving task ([http://memory.psych.upenn.edu/files/software/experiments/yellowcab2.tgz tgz (58.3 MB)])<br /> * ycCross: YellowCab Variant ([http://memory.psych.upenn.edu/files/software/experiments/ycCross.tgz tgz (30.5 MB)])<br /> * ycMagellan: [[PandaEPL]]-based YellowCab variant, as used in [[Publications#MannEtal13|Manning et al., submitted]] ([http://memory.psych.upenn.edu/files/software/experiments/ycMagellan.tgz experiment tgz (50.8 MB)], [http://memory.psych.upenn.edu/files/software/experiments/ycMagellan_buildings.tgz buildings tgz (3.1 GB)])<br /> * Trackball: Blinking and eye-movement task ([http://memory.psych.upenn.edu/files/software/experiments/trackball.tgz tgz])<br /> * Testsync: Simple program to send sync pulses ([http://memory.psych.upenn.edu/files/software/experiments/testsync.tgz tgz])<br /> <br /> == Data Analysis ==<br /> * [[TotalRecall|Penn TotalRecall]]: score and annotate behavioral audio files (replaces PyParse)<br /> * [[behavioral_toolbox|Behavioral Toolbox]]: a suite of MATLAB functions to aid in analyzing behavioral Free Recall data<br /> * [https://github.com/pennmem/pybeh Python Behavioral Toolbox]: our MATLAB Behavioral Toolbox has been ported into Python<br /> * Our EEG Toolbox is a set of Matlab functions to help in analyzing EEG data.<br /> ** The latest public release can be downloaded [http://memory.psych.upenn.edu/files/software/eeg_toolbox/eeg_toolbox.zip here (zip)]. Current version is 1.3.2, last update June 25, 2008.<br /> ** '''Lab members and collaborators (e.g., members of the RAM team) should checkout the the most recent version from the lab’s SVN server''' (for instructions, see the internal wiki [https://memory-int.psych.upenn.edu/index.php/InternalWiki/Electrophysiology_analysis#Introduction| EEG Toolbox page]) <br /> **For documentation, please see the newest (January 14, 2015)[[Media:Analyzing_EEG_Data.pdf | tutorial for EEG analyses. ]] Additionally, use the &lt;code&gt;&lt;nowiki&gt; help &lt;/nowiki&gt;&lt;/code&gt; function in MATLAB for assistance with individual functions.<br /> <br /> == Simulation Packages ==<br /> * The Context Maintenance and Retrieval model ([[CMR]]).<br /> [[Category:public]]<br /> <br /> == CRP ==<br /> Please see [[CRP_Tutorial| our CRP tutorial page.]]<br /> <br /> == Wavmark ==<br /> Please see [[Wavmark| our Wavmark page.]]<br /> &lt;!--<br /> [[Psyc121]]--&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=File:KahanaCV.pdf&diff=6893 File:KahanaCV.pdf 2019-12-19T19:49:18Z <p>Ckeane1: Ckeane1 uploaded a new version of File:KahanaCV.pdf</p> <hr /> <div></div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=File:KahanaCV.pdf&diff=6872 File:KahanaCV.pdf 2019-11-05T16:39:21Z <p>Ckeane1: Ckeane1 uploaded a new version of File:KahanaCV.pdf</p> <hr /> <div></div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=CEMS_2009&diff=6860 CEMS 2009 2019-10-15T17:21:52Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> = Context and Episodic Memory Symposium 2009 =<br /> == January 2 - January 3, 2009, Palm Beach, Florida ==<br /> <br /> Here you will find information relating to the upcoming Context and Episodic Memory Symposium (CEMS), being held on the days of January 2nd and 3rd, 2009, in Palm Beach, Florida. The symposium is designed to be a forum for the exchange of ideas among colleagues working on theoretical and empirical approaches to the study of context and episodic memory, broadly construed.<br /> <br /> === Travel and Hotel ===<br /> The symposium is being held at the Ritz-Carlton Hotel in Palm Beach. As an attendee at the meeting, you can reserve a room at the hotel at a discount rate. In order to so, you can click [http://www.ritzcarlton.com/en/Properties/PalmBeach/Default.htm here] and enter &quot;UNPUNPA&quot; as the Group Code when you make your reservation. The nights for which the reduced rate apply are the 1st, 2nd, and 3rd of January. The discount rate for rooms is $319 per night. (Palm Beach is very expensive at that time of year, and the regular rates are over $600 per night). If you want to make reservations by phone, make sure to mention the name of the conference in order to receive the discount room rate. When traveling to the area, the most convenient airports are either Palm Beach International Airport (PBI) or Fort Lauderdale-Hollywood International Airport (FLL). There are still some decent fares (around $500 roundtrip for direct flights, as of early November). '''Note''': in order to receive the discount rate, you must reserve your room by December 2nd.<br /> <br /> === Registration ===<br /> The registration fee for the symposium is $280, which will include breakfast, refreshments, and lunches. You can find the registration website [http://www.seattletech.com/registrations/index.php?968-10013-i-t here].<br /> <br /> === Program ===<br /> Downloadable versions of the following program are available: [[attachment:CEMS2009_Program.pdf|PDF]], [[attachment:CEMS2009_Program.doc|Word]]<br /> -------<br /> '''Context and Episodic Memory Symposium &lt;&lt;BR&gt;&gt;Palm Beach, Florida&lt;&lt;BR&gt;&gt;January 2 – January 3, 2009'''<br /> -----<br /> '''''Friday'''''<br /> -----<br /> '''8:00''' BREAKFAST<br /> <br /> '''8:30''' Michael Kahana welcome and introductory remarks<br /> <br /> '''8:45''' Caren Rotello, University of Massachusetts&lt;&lt;BR&gt;&gt;<br /> ''Modeling Source Memory''<br /> <br /> '''9:15''' William Hockley, Wilfrid Laurier University &lt;&lt;BR&gt;&gt;<br /> ''The Effects of Environmental Context on Recognition Memory and Claims of Remembering''<br /> <br /> '''9:45''' Jason Ardnt, Middleberry College&lt;&lt;BR&gt;&gt;<br /> ''MINERVA-DP: A dual-process model of recognition memory''<br /> ----<br /> '''10:15''' BREAK<br /> ----<br /> '''10:30''' Amy Criss, Syracuse University&lt;&lt;BR&gt;&gt;<br /> ''An application of the diffusion model to the strength based mirror effect in recognition memory''<br /> <br /> '''11:00''' Jeff Starns, The Ohio State University&lt;&lt;BR&gt;&gt;<br /> ''Enhancing lure rejection by strengthening studied items: Contrasting encoding- and retrieval-based mechanisms from REM and BCDMEM''<br /> <br /> '''11:30''' Ken Malmberg, University of South Florida&lt;&lt;BR&gt;&gt;<br /> ''The Implications of Recognition Priming for Models of Recognition Memory''<br /> ----<br /> '''12:00''' LUNCH<br /> ----<br /> '''1:00''' Geoff Ward, University of Essex&lt;&lt;BR&gt;&gt;<br /> ''Free recall and Episodic memory: comparisons across tasks and timescales''<br /> <br /> '''1:30''' Lynn Lohnas, University of Pennsylvania&lt;&lt;BR&gt;&gt;<br /> ''Expanding the scope of memory search: Intra-list and inter-list effects in free recall''<br /> <br /> '''2:00''' Marc Howard, Syracuse University&lt;&lt;BR&gt;&gt;<br /> ''Temporal context, past, present, and future''<br /> <br /> '''2:30''' Jeremy Caplan, University of Alberta&lt;&lt;BR&gt;&gt;<br /> ''Is there a context-coding basis for paired associate learning?''<br /> ----<br /> '''3:00''' BREAK<br /> ----<br /> '''3:15''' David Huber, University of California, San Diego<br /> ''Testing signal-detection models of yes/no and two-alternative forced-choice recognition memory''<br /> <br /> '''3:45''' Ken Norman, Princeton University<br /> ''Can memories be weakened?''<br /> <br /> '''4:15''' Per Sederberg, Princeton University<br /> ''Tracking the dynamics of semantic and temporal cuing during free recall''<br /> -----<br /> '''''Saturday'''''<br /> -----<br /> <br /> '''8:30''' BREAKFAST<br /> <br /> '''9:00''' Roger Ratcliff, The Ohio State University<br /> ''Priming and associative recognition''<br /> <br /> '''9:35''' Simon Dennis, The Ohio State University<br /> ''The Inverse List Length Effect and the Return of the Global Matching Models''<br /> <br /> '''10:10''' Ben Murdock, University of Toronto&lt;&lt;BR&gt;&gt;<br /> ''The spacing and mirror and word-frequency effect''<br /> ----<br /> '''10:45''' BREAK<br /> ----<br /> '''11:15''' Rich Shiffrin, Indiana University<br /> ''The co-evolution of knowledge and event memory''<br /> ----<br /> '''12:00''' LUNCH<br /> ----<br /> '''1:15''' Mark Steyvers, University of California, Irvine&lt;&lt;BR&gt;&gt;<br /> ''A Bayesian theory of reconstructive memory''<br /> <br /> '''1:45''' Dan Kimball, University of Oklahoma&lt;&lt;BR&gt;&gt;<br /> ''Conjunctive and summative processes in human memory''<br /> <br /> '''2:15''' General discussion and wrap up<br /> <br /> '''2:45''' Group photo at the ocean<br /> [[Category:CEMS]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=CEMS_2009&diff=6859 CEMS 2009 2019-10-15T17:21:36Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> = Context and Episodic Memory Symposium 2009 =<br /> == January 2 - January 3, 2009, Palm Beach, Florida ==<br /> <br /> Here you will find information relating to the upcoming Context and Episodic Memory Symposium (CEMS), being held on the days of January 2nd and 3rd, 2009, in Palm Beach, Florida. The symposium is designed to be a forum for the exchange of ideas among colleagues working on theoretical and empirical approaches to the study of context and episodic memory, broadly construed.<br /> <br /> === Travel and Hotel ===<br /> The symposium is being held at the Ritz-Carlton Hotel in Palm Beach. As an attendee at the meeting, you can reserve a room at the hotel at a discount rate. In order to so, you can click [http://www.ritzcarlton.com/en/Properties/PalmBeach/Default.htm here] and enter &quot;UNPUNPA&quot; as the Group Code when you make your reservation. The nights for which the reduced rate apply are the 1st, 2nd, and 3rd of January. The discount rate for rooms is $319 per night. (Palm Beach is very expensive at that time of year, and the regular rates are over $600 per night). If you want to make reservations by phone, make sure to mention the name of the conference in order to receive the discount room rate. When traveling to the area, the most convenient airports are either Palm Beach International Airport (PBI) or Fort Lauderdale-Hollywood International Airport (FLL). There are still some decent fares (around $500 roundtrip for direct flights, as of early November). '''Note''': in order to receive the discount rate, you must reserve your room by December 2nd.<br /> <br /> === Registration ===<br /> The registration fee for the symposium is $280, which will include breakfast, refreshments, and lunches. You can find the registration website [http://www.seattletech.com/registrations/index.php?968-10013-i-t here].<br /> <br /> === Program ===<br /> Downloadable versions of the following program are available: [[attachment:CEMS2009_Program.pdf|PDF]], [[attachment:CEMS2009_Program.doc|Word]]<br /> -------<br /> '''Context and Episodic Memory Symposium &lt;&lt;BR&gt;&gt;Palm Beach, Florida&lt;&lt;BR&gt;&gt;January 2 – January 3, 2009'''<br /> -----<br /> '''''Friday'''''<br /> -----<br /> '''8:00''' BREAKFAST<br /> <br /> '''8:30''' Michael Kahana welcome and introductory remarks<br /> <br /> '''8:45''' Caren Rotello, University of Massachusetts&lt;&lt;BR&gt;&gt;<br /> ''Modeling Source Memory''<br /> <br /> '''9:15''' William Hockley, Wilfrid Laurier University &lt;&lt;BR&gt;&gt;<br /> ''The Effects of Environmental Context on Recognition Memory and Claims of Remembering''<br /> <br /> '''9:45''' Jason Ardnt, Middleberry College&lt;&lt;BR&gt;&gt;<br /> ''MINERVA-DP: A dual-process model of recognition memory''<br /> ----<br /> '''10:15''' BREAK<br /> ----<br /> '''10:30''' Amy Criss, Syracuse University&lt;&lt;BR&gt;&gt;<br /> ''An application of the diffusion model to the strength based mirror effect in recognition memory''<br /> <br /> '''11:00''' Jeff Starns, The Ohio State University&lt;&lt;BR&gt;&gt;<br /> ''Enhancing lure rejection by strengthening studied items: Contrasting encoding- and retrieval-based mechanisms from REM and BCDMEM''<br /> <br /> '''11:30''' Ken Malmberg, University of South Florida&lt;&lt;BR&gt;&gt;<br /> ''The Implications of Recognition Priming for Models of Recognition Memory''<br /> ----<br /> '''12:00''' LUNCH<br /> ----<br /> '''1:00''' Geoff Ward, University of Essex&lt;&lt;BR&gt;&gt;<br /> ''Free recall and Episodic memory: comparisons across tasks and timescales''<br /> <br /> '''1:30''' Lynn Lohnas, University of Pennsylvania&lt;&lt;BR&gt;&gt;<br /> ''Expanding the scope of memory search: Intra-list and inter-list effects in free recall''<br /> <br /> '''2:00''' Marc Howard, Syracuse University&lt;&lt;BR&gt;&gt;<br /> ''Temporal context, past, present, and future''<br /> <br /> '''2:30''' Jeremy Caplan, University of Alberta&lt;&lt;BR&gt;&gt;<br /> ''Is there a context-coding basis for paired associate learning?''<br /> ----<br /> '''3:00''' BREAK<br /> ----<br /> '''3:15''' David Huber, University of California, San Diego<br /> ''Testing signal-detection models of yes/no and two-alternative forced-choice recognition memory''<br /> <br /> '''3:45''' Ken Norman, Princeton University<br /> ''Can memories be weakened?''<br /> <br /> '''4:15''' Per Sederberg, Princeton University<br /> ''Tracking the dynamics of semantic and temporal cuing during free recall''<br /> -----<br /> '''''Saturday'''''<br /> -----<br /> <br /> '''8:30''' BREAKFAST<br /> <br /> '''9:00''' Roger Ratcliff, The Ohio State University<br /> ''Priming and associative recognition''<br /> <br /> '''9:35''' Simon Dennis, The Ohio State University<br /> ''The Inverse List Length Effect and the Return of the Global Matching Models''<br /> <br /> '''10:10''' Ben Murdock, University of Toronto&lt;&lt;BR&gt;&gt;<br /> ''The spacing and mirror and word-frequency effect''<br /> ----<br /> '''10:45''' BREAK<br /> ----<br /> '''11:15''' Rich Shiffrin, Indiana University<br /> ''The co-evolution of knowledge and event memory''<br /> ----<br /> '''12:00''' LUNCH<br /> ----<br /> '''1:15''' Mark Steyvers, University of California, Irvine&lt;&lt;BR&gt;&gt;<br /> ''A Bayesian theory of reconstructive memory''<br /> <br /> '''1:45''' Dan Kimball, University of Oklahoma&lt;&lt;BR&gt;&gt;<br /> ''Conjunctive and summative processes in human memory''<br /> <br /> '''2:15''' General discussion and wrap up<br /> <br /> '''2:45''' Group photo at the ocean.<br /> [[Category:CEMS]]</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Software&diff=6858 Software 2019-10-15T17:18:55Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> == Experiments ==<br /> <br /> === Foundational Libraries ===<br /> * [http://pyepl.sourceforge.net PyEPL] (the Python Experiment-Programming Library) is a library for coding psychology experiments in Python. It supports presentation of both visual and auditory stimuli, and supports both manual (keyboard/joystick) and sound (microphone) input as responses. Visit the [http://pyepl.sourceforge.net PyEPL SourceForge page] for more information and downloads, or click [http://memory.psych.upenn.edu/files/pyepl_installer.zip here] for an updated installer, capable of working on El Capitan. ([[Publications#GellEtal07|Methods paper can be found here.]])<br /> * [[PandaEPL]] is a cross-platform Python library for programming 3D spatial navigation experiments. ([[Publications#SolwEtal13|Methods paper can be found here.]])<br /> * [[UnityEPL]] is a library that interacts with the Unity VR software to facilitate creation of memory experiments. The code and documentation are posted to the following GitHub site.<br /> <br /> === Experiment Paradigms ===<br /> PyEPL-based experiments used in the Kahana Lab.<br /> <br /> * pyFGS: Face/Grating Sternberg task ([http://memory.psych.upenn.edu/files/software/experiments/pyFGS.tgz tgz])<br /> * pyFR: Free Recall task ([http://memory.psych.upenn.edu/files/software/experiments/pyFR.tgz tgz])<br /> * YellowCab II: Virtual Driving task ([http://memory.psych.upenn.edu/files/software/experiments/yellowcab2.tgz tgz (58.3 MB)])<br /> * ycCross: YellowCab Variant ([http://memory.psych.upenn.edu/files/software/experiments/ycCross.tgz tgz (30.5 MB)])<br /> * ycMagellan: [[PandaEPL]]-based YellowCab variant, as used in [[Publications#MannEtal13|Manning et al., submitted]] ([http://memory.psych.upenn.edu/files/software/experiments/ycMagellan.tgz experiment tgz (50.8 MB)], [http://memory.psych.upenn.edu/files/software/experiments/ycMagellan_buildings.tgz buildings tgz (3.1 GB)])<br /> * Trackball: Blinking and eye-movement task ([http://memory.psych.upenn.edu/files/software/experiments/trackball.tgz tgz])<br /> * Testsync: Simple program to send sync pulses ([http://memory.psych.upenn.edu/files/software/experiments/testsync.tgz tgz])<br /> <br /> == Data Analysis ==<br /> * [[TotalRecall|Penn TotalRecall]]: score and annotate behavioral audio files (replaces PyParse)<br /> * [[behavioral_toolbox|Behavioral Toolbox]]: a suite of MATLAB functions to aid in analyzing behavioral Free Recall data<br /> * [https://github.com/pennmem/pybeh Python Behavioral Toolbox]: our MATLAB Behavioral Toolbox has been ported into Python<br /> * Our EEG Toolbox is a set of Matlab functions to help in analyzing EEG data.<br /> ** The latest public release can be downloaded [http://memory.psych.upenn.edu/files/software/eeg_toolbox/eeg_toolbox.zip here (zip)]. Current version is 1.3.2, last update June 25, 2008.<br /> ** '''Lab members and collaborators (e.g., members of the RAM team) should checkout the the most recent version from the lab’s SVN server''' (for instructions, see the internal wiki [https://memory-int.psych.upenn.edu/index.php/InternalWiki/Electrophysiology_analysis#Introduction| EEG Toolbox page]) <br /> **For documentation, please see the newest (January 14, 2015)[[Media:Analyzing_EEG_Data.pdf | tutorial for EEG analyses. ]] Additionally, use the &lt;code&gt;&lt;nowiki&gt; help &lt;/nowiki&gt;&lt;/code&gt; function in MATLAB for assistance with individual functions.<br /> <br /> == Simulation Packages ==<br /> * The Context Maintenance and Retrieval model ([[CMR]]).<br /> [[Category:public]]<br /> <br /> == CRP ==<br /> Please see [[CRP_Tutorial| our CRP tutorial page.]]<br /> <br /> == Wavmark ==<br /> Please see [[Wavmark| our Wavmark page.]]<br /> &lt;!--<br /> [[Psyc121]]--&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=Software&diff=6857 Software 2019-10-15T17:14:14Z <p>Ckeane1: </p> <hr /> <div>__NOTOC__<br /> == Experiments ==<br /> <br /> === Foundational Libraries ===<br /> * [http://pyepl.sourceforge.net PyEPL] (the Python Experiment-Programming Library) is a library for coding psychology experiments in Python. It supports presentation of both visual and auditory stimuli, and supports both manual (keyboard/joystick) and sound (microphone) input as responses. Visit the [http://pyepl.sourceforge.net PyEPL SourceForge page] for more information and downloads, or click [http://memory.psych.upenn.edu/files/pyepl_installer.zip here] for an updated installer, capable of working on El Capitan. ([[Publications#GellEtal07|Methods paper can be found here.]])<br /> * [[PandaEPL]] is a cross-platform Python library for programming 3D spatial navigation experiments. ([[Publications#SolwEtal13|Methods paper can be found here.]])<br /> * [[UnityEPL]] is a library that interacts with the Unity VR software to facilitate creation of memory experiments. The code and documentation are posted to the following GitHub site.<br /> <br /> === Experiment Paradigms ===<br /> PyEPL-based experiments used in the Kahana Lab.<br /> <br /> * pyFGS: Face/Grating Sternberg task ([http://memory.psych.upenn.edu/files/software/experiments/pyFGS.tgz tgz])<br /> * pyFR: Free Recall task ([http://memory.psych.upenn.edu/files/software/experiments/pyFR.tgz tgz])<br /> * YellowCab II: Virtual Driving task ([http://memory.psych.upenn.edu/files/software/experiments/yellowcab2.tgz tgz (58.3 MB)])<br /> * ycCross: YellowCab Variant ([http://memory.psych.upenn.edu/files/software/experiments/ycCross.tgz tgz (30.5 MB)])<br /> * ycMagellan: [[PandaEPL]]-based YellowCab variant, as used in [[Publications#MannEtal13|Manning et al., submitted]] ([http://memory.psych.upenn.edu/files/software/experiments/ycMagellan.tgz experiment tgz (50.8 MB)], [http://memory.psych.upenn.edu/files/software/experiments/ycMagellan_buildings.tgz buildings tgz (3.1 GB)])<br /> * Trackball: Blinking and eye-movement task ([http://memory.psych.upenn.edu/files/software/experiments/trackball.tgz tgz])<br /> * Testsync: Simple program to send sync pulses ([http://memory.psych.upenn.edu/files/software/experiments/testsync.tgz tgz])<br /> <br /> == Data Analysis ==<br /> * [[TotalRecall|Penn TotalRecall]]: score and annotate behavioral audio files (replaces PyParse)<br /> * [[behavioral_toolbox|Behavioral Toolbox]]: a suite of MATLAB functions to aid in analyzing behavioral Free Recall data<br /> * [https://github.com/pennmem/pybeh Python Behavioral Toolbox]: our MATLAB Behavioral Toolbox has been ported into Python<br /> * Our EEG Toolbox is a set of Matlab functions to help in analyzing EEG data.<br /> ** The latest public release can be downloaded [http://memory.psych.upenn.edu/files/software/eeg_toolbox/eeg_toolbox.zip here (zip)]. Current version is 1.3.2, last update June 25, 2008.<br /> ** '''Lab members and collaborators (e.g., members of the RAM team) should checkout the the most recent version from the lab’s SVN server''' (for instructions, see the internal wiki [https://memory-int.psych.upenn.edu/InternalWiki/Electrophysiology_analysis#Introduction| EEG Toolbox page]) <br /> **For documentation, please see the newest (January 14, 2015)[[Media:Analyzing_EEG_Data.pdf | tutorial for EEG analyses. ]] Additionally, use the &lt;code&gt;&lt;nowiki&gt; help &lt;/nowiki&gt;&lt;/code&gt; function in MATLAB for assistance with individual functions.<br /> <br /> == Simulation Packages ==<br /> * The Context Maintenance and Retrieval model ([[CMR]]).<br /> [[Category:public]]<br /> <br /> == CRP ==<br /> Please see [[CRP_Tutorial| our CRP tutorial page.]]<br /> <br /> == Wavmark ==<br /> Please see [[Wavmark| our Wavmark page.]]<br /> &lt;!--<br /> [[Psyc121]]--&gt;</div> Ckeane1 https://memory.psych.upenn.edu/mediawiki/index.php?title=People&diff=6854 People 2019-09-16T14:25:57Z <p>Ckeane1: </p> <hr /> <div><br /> &lt;big&gt;[https://memory.psych.upenn.edu/InternalWiki/Contact_List Full Contact List] (CML Internal Wiki)&lt;/big&gt;<br /> <br /> &lt;big&gt;[[More Lab Photos]]&lt;/big&gt;<br /> <br /> __FORCETOC__<br /> __TOC__<br /> <br /> == Lab Director ==<br /> &lt;gallery widths=360px heights=480px&gt;<br /> File:Mike.jpg|&lt;big&gt;[[Michael J. Kahana|Michael J. Kahana, Ph.D.]]&lt;/big&gt;&lt;br /&gt;kahana@psych.upenn.edu&lt;br /&gt;CML Principal Investigator<br /> <br /> &lt;/gallery&gt;<br /> <br /> == Postdoctoral Fellows, Medical Residents, &amp; Graduate Students ==<br /> &lt;gallery widths=225px heights=300px&gt; <br /> File:Nora1.jpg|&lt;big&gt;Nora Herweg&lt;/big&gt;&lt;br /&gt;nherweg@sas.upenn.edu&lt;br /&gt; Postdoctoral Fellow <br /> File:Daniel.jpg|&lt;big&gt;Daniel Schonhaut&lt;/big&gt;&lt;br /&gt;Daniel.Schonhaut@pennmedicine.upenn.edu&lt;br /&gt; Ph.D. Student<br /> File:Aka.jpg| &lt;big&gt;Ada Aka &lt;/big&gt;&lt;br /&gt;adaaka@wharton.upenn.edu&lt;br /&gt; Ph.D. Student <br /> File:ND.jpg|&lt;big&gt;Nick Diamond&lt;/big&gt;&lt;br /&gt;diamondn@sas.upenn.edu&lt;br /&gt; Postdoctoral Fellow <br /> &lt;/gallery&gt;<br /> <br /> == Research Staff ==<br /> &lt;gallery widths=225px heights=300px&gt;<br /> File:DebGaspari.jpg|&lt;big&gt;Deb Gaspari&lt;/big&gt;&lt;br /&gt;gaspari@sas.upenn.edu&lt;br /&gt;Grants Manager<br /> File: Wanda1.jpg‎|&lt;big&gt;Paul A. Wanda, Ph.D. &lt;/big&gt;&lt;br /&gt;pwanda@sas.upenn.edu&lt;br /&gt;Project Manager, [[RAM]]<br /> File:TungP.jpg|&lt;big&gt;Tung Phan, Ph.D. &lt;/big&gt;&lt;br /&gt; tungphan@sas.upenn.edu &lt;br /&gt;Sr. Data Scientist<br /> File:Colyer.jpg|&lt;big&gt;Ryan Colyer, Ph.D. &lt;/big&gt;&lt;br /&gt; rcolyer@sas.upenn.edu &lt;br /&gt;Scientific Programmer<br /> File:GeorgiaR.jpg|&lt;big&gt;Georgia Reilly&lt;/big&gt;&lt;br /&gt; reillyg@sas.upenn.edu &lt;br /&gt; Research Coordinator<br /> File:CKeane.jpg|&lt;big&gt;Connor Keane&lt;/big&gt;&lt;br /&gt; ckeane1@sas.upenn.edu &lt;br /&gt; Data and Programming Specialist<br /> File:RichardAZ.jpg|&lt;big&gt;Richard Adamovich-Zeitlin&lt;/big&gt;&lt;br /&gt; richad@sas.upenn.edu &lt;br /&gt; Clinical Research Specialist<br /> File: Healy.jpg|&lt;big&gt; [http://psych.colorado.edu/~ahealy/ Alice Healy, Ph.D.] &lt;/big&gt;&lt;br /&gt; alice.healy@colorado.edu &lt;br /&gt; Visiting Scholar<br /> &lt;/gallery&gt;<br /> <br /> &lt;!-- <br /> Add this back in if we hire more developers:<br /> == Software Developers ==<br /> &lt;gallery widths=225px heights=300px&gt;<br /> <br /> &lt;/gallery&gt;<br /> --&gt;<br /> <br /> == Undergraduate and High School Student Researchers ==<br /> &lt;gallery widths=150px heights=200px&gt;<br /> &lt;!--File:Jimmy.jpg|&lt;big&gt;James Germi&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Alyssa.jpg|&lt;big&gt;Alyssa Johncola&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Johanna.jpg|&lt;big&gt;Johanna Phillips&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Stamati.jpg|&lt;big&gt;Stamati Liapis&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Tanvi.jpg|&lt;big&gt;Tanvi Patel&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Omar.jpg|&lt;big&gt;Omar Lopez&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:QK.jpg|&lt;big&gt;Q Kalantary&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:SunnyLu.jpg|&lt;big&gt;Sunny Lu&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:TGianangelo.jpg|&lt;big&gt;Taylor Gianangelo&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Belo.jpeg|&lt;big&gt;Saidah Belo-Osagie&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Chien.jpg|&lt;big&gt;Terry Chien&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:DeCorso.png|&lt;big&gt;Kevin DeCorso&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Person-placeholder.png|&lt;big&gt;David Diwik&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Goldman.JPG|&lt;big&gt;Shai Goldman&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:ShivaliGovani.jpg|&lt;big&gt;Shivali Govani&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Megha.jpg|&lt;big&gt;Megha Keshav&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Person-placeholder.png|&lt;big&gt;Nicole Laczewski&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Mack.png|&lt;big&gt;Lance Mack&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Lim.JPG|&lt;big&gt;Jang Won Lim&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Mansour.jpg|&lt;big&gt;Mia Mansour&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Person-placeholder.png|&lt;big&gt;Anh Tran&lt;/big&gt;&lt;br /&gt;<br /> &lt;!--File:Jasmine2.jpg|&lt;big&gt;Jasmine Wang&lt;/big&gt;&lt;br /&gt;--&gt;<br /> &lt;!--File:Collin1.jpg|&lt;big&gt;Collin Loughead&lt;/big&gt;&lt;br /&gt;--&gt;<br /> &lt;!--File:JDong.jpg|&lt;big&gt;Jessie Dong&lt;br /&gt;&gt;--&gt;<br /> File:EGoldman.jpg| &lt;big&gt;Elan Goldman &lt;br /&gt;<br /> File:Katerman.jpg|&lt;big&gt;Brandon Katerman&lt;br /&gt;<br /> &lt;!--File:MorrisonJ.jpg|&lt;big&gt;James Morrison&lt;br /&gt;&gt;--&gt;<br /> &lt;!--File:JoAnnS.jpg|&lt;big&gt;Jo Ann Sun&lt;br /&gt;&gt;--&gt;<br /> &lt;!--File:JWeiner.jpg|&lt;big&gt;Josh Weiner&lt;br /&gt;&gt;--&gt;<br /> File:Eash.jpg|&lt;big&gt;Eash Aggarwal &lt;br /&gt; <br /> File:Dhayes.JPG|&lt;big&gt;Daniel Hayes &lt;br /&gt; <br /> File:rudoler.jpg| &lt;big&gt;Joseph Rudoler &lt;br /&gt; <br /> <br /> <br /> &lt;/gallery&gt;<br /> <br /> == Lab Alumni ==<br /> &lt;gallery widths=100px perrow=7&gt;<br /> File:Kelly.jpg| Kelly Addis, Ph.D.&lt;br /&gt;Safety and Health Consultant,&lt;br /&gt;Boise State University<br /> File:Kylie.jpg| Kylie Hower Alm, Ph.D.&lt;br/&gt; Postdoctoral Fellow, &lt;br/&gt; Johns Hopkins School of Medicine<br /> File:Franco.png|Franco Bautista &lt;br /&gt; <br /> File:Erin.jpg|Erin Beck&lt;br /&gt;Director of Site Recruitment and Management, Recruitment Partners LLC <br /> File: Broitman.jpg| Adam Broitman &lt;br /&gt;Ph.D. Student&lt;br /&gt;Cornell University<br /> File:Burke.jpg|[http://sites.google.com/site/johnfredburkememoryresearch/ John Burke, Ph.D.]&lt;br /&gt;Resident&lt;br /&gt;University of California, San Francisco<br /> File:Stas1.jpg|Stanislav Busygin, Ph.D.<br /> File:JeremyC.jpg| [https://www.ualberta.ca/science/about-us/contact-us/faculty-directory/jeremy-caplan Jeremy Caplan, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br/&gt;University of Alberta <br /> File:Chen.jpg| Steven Chen &lt;br /&gt; Lead Developer, &lt;br /&gt; Symcat<br /> File:Kylene Photo 2.jpg| Kylene Cochrane &lt;br/&gt; Ph.D. Student &lt;br/&gt; Drexel University<br /> File:Cohen.jpg| Etan Cohen &lt;br /&gt; Writer and producer&lt;br/&gt;Known for Madagascar: Escape 2 Africa, &lt;br/&gt; Men in Black 3<br /> File:Rivka.jpg| Rivka Cohen &lt;br /&gt; Ph.D. Student &lt;br /&gt; University of Pennsylvania<br /> File:Liz.jpg|Elizabeth Crutchley&lt;br /&gt;Lab Manager, &lt;br /&gt; Infant Language Center, University of Pennsylvania<br /> File:Patrick.jpg|Patrick Crutchley&lt;br /&gt;Data Scientist, &lt;br /&gt; [http://qntfy.com Qntfy]<br /> File:Danoff.jpg| Michelle Danoff&lt;br /&gt; Associate Product Manager, &lt;br /&gt; Google <br /> File:Leon1.jpg| Leon Davis &lt;br /&gt;<br /> File:Orin.jpg| Orin Davis, Ph.D. &lt;br /&gt; Principal Investigator, [http://www.qllab.org/ Quality of Life Laboratory]<br /> File:DeCorso.png|Kevin DeCorso &lt;br /&gt;<br /> File:Mike1.jpg|Michael DePalatis &lt;br /&gt; Research Scientist, Inscripta <br /> File:EmilyD.jpg| Emily Dolan, Ph.D. &lt;br /&gt;Director of Applied Research, ASPCA &lt;br/&gt;University of Washington<br /> File:Zach.jpg| Zachary Duey &lt;br /&gt; Software Engineer &lt;br /&gt; Blackfynn<br /> File:Arne.jpg| [https://psychology.arizona.edu/users/arne-ekstrom Arne Ekstrom, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; University of Arizona <br /> File:Ellner.jpg| Samantha Ellner &lt;br /&gt; senior manager strategy and business operations, Harry's, inc<br /> File:Gennady.png| [http://www.gennaerlikhman.com Gennady Erlikhman, Ph.D.] &lt;br /&gt; Postdoctoral Researcher, &lt;br /&gt; University California, LA<br /> File:JonathanEW.jpg|Jonathan Eskreis-Winkler&lt;br /&gt; Ph.D. Student in Statistics, University of Chicago<br /> File:Youssef.jpg | [http://ezzyat.wordpress.com Youssef Ezzyat, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt;Swarthmore College<br /> File:Logan1.jpg| Logan Fickling &lt;br /&gt; Ph.D. Student &lt;br /&gt; University of Pennsylvania<br /> File:LynneG.png| Lynne Gauthier &lt;br /&gt; Associate Professor, UMASS Lowell <br /> File:Travis.png| Travis Gebhardt &lt;br /&gt; staff engineer, Blink Health <br /> File:Aaron.jpg| Aaron Geller, M.D. &lt;br /&gt; MD Candidate, &lt;br /&gt; Northern regional epilepsy group <br /> File:Jimmy.jpg|James Germi&lt;br /&gt; Researcher, &lt;br /&gt; University of Texas, Southwestern<br /> File:TGianangelo.jpg|Taylor Gianangelo&lt;br /&gt; MD Candidate, University of Florida College of Medicine <br /> File:TomG.jpg|Tom Gradel&lt;br /&gt; Chief Technology Operator,&lt;br/&gt;Guiding Technologies Corp<br /> File:Jeff.jpg|Jeffrey Greenberg&lt;br /&gt;<br /> File:Goldman.JPG|Shai Goldman&lt;br /&gt;<br /> File:ShivaliGovani.jpg|Shivali Govani&lt;br /&gt; School of Dental Medicine, University of Pennsylvania<br /> File:Person-placeholder.png| Caroline Haimm &lt;br /&gt; Research Coordinator, Duckworth Lab, &lt;br/&gt;University of Pennsylvania<br /> File:Haque.jpg|Rafi Haque&lt;br /&gt;M.D./Ph.D. Student, Emory University<br /> File:Karl.jpg|[http://karlhealey.github.com/Site/Karl_Healey.html Karl Healey, Ph.D.]&lt;br /&gt;Assistant Professor,&lt;br /&gt; Michigan State University<br /> File:Zeinab.png| Zeinab Helili &lt;br /&gt; Research Specialist, &lt;br /&gt; Hospital of the University of Pennsylvania<br /> File:chittela.jpg| Hemanth Chittela &lt;br /&gt; Software Engineer, Bridgewater Associates <br /> File:Masaki.jpg| Masaki Horii &lt;br /&gt; Systems Engineer &lt;br /&gt; Photo-Sonics, Inc.<br /> File:Marc.jpg| [https://www.bu.edu/psych/profile/marc-howard-ph-d/ Marc Howard, Ph.D.] &lt;br /&gt; Professor, &lt;br /&gt; Boston University <br /> File:Katherine.jpg| Katherine Hurley &lt;br /&gt; Ph.D. Student, &lt;br /&gt; George Washington University<br /> File:Grace.jpg| Grace Hwang, Ph.D. &lt;br /&gt; Senior research technician, &lt;br /&gt; CHOP<br /> File:JoshJ.jpg| [https://bme.columbia.edu/faculty/joshua-jacobs Joshua Jacobs, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; Columbia University<br /> File:Ilana.jpg| Ilana Jerud, M.D. &lt;br /&gt; Psychiatrist, &lt;br /&gt; New York-Presbyterian/Weill Cornell<br /> File:Alyssa.jpg|Alyssa Johncola&lt;br /&gt;Researcher,&lt;br/&gt;University of Pennsylvania <br /> File:Person-placeholder.png| Pauline T. Johnsen, Ph.D. &lt;br /&gt; <br /> File: ‎Johri.jpg|Ansh Johri &lt;br /&gt; Medical Student, Penn State<br /> File:Kadel.jpg|Ally Kadel &lt;br /&gt; software engineering technical coach, Flatiron School <br /> File:Person-placeholder.png| Ester Kahana &lt;br /&gt;<br /> File:Person-placeholder.png| Brian Kamins<br /> File:Person-placeholder.png| Jonathan Kay &lt;br /&gt;<br /> File:Megha.jpg| Megha Keshav&lt;br /&gt;technical problem solver&lt;br/&gt;Epic <br /> File:RogerKhazan.png| Roger Khazan, Ph.D. &lt;br /&gt;Cybersecurity Leader, &lt;br /&gt; MIT Lincoln Laboratory <br /> File:DanK.jpg| Dan Kimball, J.D., Ph.D. &lt;br /&gt; Associate Professor, &lt;br /&gt; University of Oklahoma <br /> File:MatthewK.png| Matthew P. Kirschen, M.D., Ph.D. &lt;br /&gt; Pediatric Critical Care, Attending Physician, &lt;br /&gt; Children's Hospital of Philadelphia <br /> File:KrystalK.png| Krystal Klein, Ph.D. &lt;br /&gt; Cognitive Psychologist, Research Analyst, &lt;br /&gt; Oregon Health &amp; Science University <br /> File:Person-placeholder.png| Dov Kogen &lt;br /&gt; Associate, &lt;br /&gt; Weil, Gotshal, and Manges<br /> File:Igor.jpg| Igor Korolev, D.O., Ph.D.&lt;br /&gt; Physician, Jackson Memorial Hospital <br /> File:Kragel.jpg|James Kragel, Ph.D.&lt;br /&gt; Postdoctoral Fellow, Northwestern University<br /> File:Josh.jpg|Josh Kriegel&lt;br /&gt;Postbac, &lt;br /&gt; Columbia University<br /> File:Penina.jpg|Penina Krieger&lt;br /&gt; Gates Cambridge Scholar, &lt;br /&gt; medical student &lt;br/&gt; NYU School of Medicine <br /> File:Joel.jpg|Joel Kuhn&lt;br /&gt;Ph.D. Student, &lt;br /&gt; UC San Diego<br /> File:Nikhita_Kunwar.jpeg| Nikhita Kunwar &lt;br /&gt; University of Pennsylvania<br /> File:Person-placeholder.png|Nicole Laczewski&lt;br /&gt;strategist &lt;br /&gt;Bloomberg LP <br /> File: Sandy3.jpg|Sandra LaMonaca&lt;br /&gt;Executive Assistant, &lt;br/&gt; Ryan Veterinary Hospital of the University of Pennsylvania<br /> File:Person-placeholder.png| Richard Lawrence &lt;br /&gt; Ph.D. Student, &lt;br /&gt; U.C. Berkley <br /> File:Person-placeholder.png| Eben Lazarus &lt;br /&gt; Ph.D. Student, &lt;br /&gt; Harvard University<br /> File:Kenton.jpg| Kenton Lee &lt;br /&gt; Ph.D. Student, &lt;br /&gt; University of Washington <br /> File:Brad.jpg| [https://profiles.utsouthwestern.edu/profile/153415/bradley-lega.html Brad Lega, M.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; UT Southwestern Medical Center<br /> File:Deb.jpg|Deborah Levy&lt;br /&gt;Ph.D. Student, &lt;br /&gt;Vanderbilt University<br /> File:Matt_Levy.jpg| Mathew Levy &lt;br/&gt; University of Pennsylvania<br /> File:TimLew.png| Tim Lew &lt;br /&gt; Data Scientist, &lt;br /&gt; Quora<br /> File:Effie.jpg| Effie Li &lt;br /&gt; Ph.D. Student, &lt;br /&gt; Stanford University<br /> File:Lim.JPG| Jang Won Lim &lt;br /&gt;<br /> File:Nicole.jpg|[http://sites.google.com/site/nmarielong Nicole Long, Ph.D.]&lt;br /&gt;Assistant Professor,&lt;br /&gt;University of Virginia<br /> File:Lubken.jpg|Jason Lubken&lt;br /&gt; Sr. Data Science Software Engineer, Penn Medicine Predictive Healthcare<br /> File:Ningcheng.jpg| Ningcheng (Peter) Li &lt;br /&gt; M.D. Student, &lt;br /&gt; Yale University<br /> File:Stamati.jpg| [http://sites.bu.edu/cnl/members/stamati-liapis/ Stamati Liapis] &lt;br /&gt; Ph.D. Student, &lt;br /&gt; Boston University<br /> File:Lynn.jpg|[http://sites.google.com/site/lynnlohnas/ Lynn Lohnas, Ph.D.]&lt;br /&gt; Assistant Professor, &lt;br /&gt; Syracuse University<br /> File:Omar.jpg|Omar Lopez&lt;br /&gt;<br /> File:Anastasia.jpg|[[Anastasia_Lyalenko_Memorial_Fund|Anastasia Lyalenko]] &lt;br /&gt; [[Anastasia_Lyalenko_Memorial_Fund| Memorial Page]]<br /> File:Mack.png|Lance Mack &lt;br /&gt; data scientist &lt;br /&gt; Uber<br /> File:Person-placeholder.png| Josh Magarick &lt;br /&gt; Member of the Voleon Group Research Staff<br /> File:JeremyM.jpg| [http://dartmouth.edu/faculty-directory/jeremy-rothman-manning Jeremy Manning, Ph.D.] &lt;br /&gt; Assistant Professor, Dartmouth College <br /> &lt;!--File:Mansour.jpg|Mia Mansour&lt;br /&gt;<br /> File:Yuvi.jpg| Yuvi Masory &lt;br /&gt; Independent consultant<br /> File:StevenMeisler.jpg| Steven Meisler &lt;br /&gt; Clinical Research Coordinator, &lt;br /&gt; Massachusetts General Hospital<br /> File: Max.jpg| Max Merkow, M.D. &lt;br /&gt;Neurosurgeon, &lt;br /&gt; East Bay Brain &amp; Spine Medical Group<br /> File:Jonathan.jpg| Jonathan Miller. Ph.D. &lt;br /&gt; Postdoctoral Research Scientist &lt;br /&gt; Columbia University <br /> File:Matt.jpg| Matt Mollison, Ph.D &lt;br /&gt; Chief Data Scientist, &lt;br /&gt; branch international<br /> File:BryanMoore.JPG| Bryan Moore, M.D. &lt;br /&gt; graduate research fellow, University of Southern California <br /> File:Neal.jpg| [https://nealwmorton.com Neal Morton, Ph.D.] &lt;br /&gt; Postdoctoral Fellow, &lt;br /&gt; University of Texas at Austin<br /> File:EhrenNewman.png|[https://psych.indiana.edu/directory/faculty/newman-ehren.html Ehren Newman, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; Indiana University, Bloomington<br /> File:Novich.jpg| Corey Novich &lt;br /&gt; Sortware Engineer, &lt;br /&gt; Harmonix Music Systems<br /> File:Logan.jpg| Logan O'Sullivan&lt;br /&gt; Career Services Organizer, &lt;br /&gt; University of Pennsylvania Law School <br /> File:Jesse1.jpg| Jesse Pazdera &lt;br /&gt; Ph.D. Student, &lt;br /&gt; McMaster University<br /> File:Person-placeholder.png| Peter Pantelis, Ph.D. &lt;br /&gt; Director of Analytics, &lt;br /&gt; patch.com<br /> File:Isaac.jpg|Isaac Pedisich&lt;br /&gt; Software Developer, &lt;br /&gt; University of Pennsylvania<br /> File:Johanna.jpg|Johanna Phillips&lt;br /&gt;<br /> File:Sean.jpg| [http://www.polyn.com/ Sean Polyn, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; Vanderbilt University <br /> File:Person-placeholder.png| Eric Pressman &lt;br /&gt; User Experience Manager, &lt;br /&gt; Sr. User Experience Specialist, &lt;br /&gt; MathWorks <br /> File:Ashwin.jpg| Ashwin Ramayya, M.D./ Ph.D.&lt;br /&gt;Neurosurgery Resident, &lt;br /&gt; University of Pennsylvania<br /> File:Randazzo.jpg|Michael Randazzo &lt;br /&gt; Internal Medicine, &lt;br /&gt; University of Pennsylvania<br /> File:Dan.jpg| Daniel S. Rizzuto, Ph.D. &lt;br /&gt; CEO, Nia Therapeutics<br /> File:EmilyR.jpg| Emily Rosenberg &lt;br /&gt; Med Student, &lt;br /&gt; Penn State<br /> File:Rachel.jpg|Rachel Russell&lt;br /&gt; Research Coordinator, &lt;br /&gt; University of Pennsylvania<br /> File:Colin.jpg| Colin Sauder &lt;br /&gt; scientific director &lt;br /&gt; adams clinical<br /> File:Schleifer2.jpg| Ian Schleifer &lt;br /&gt; Avionics Software Development Engineer &lt;br /&gt; Blue Origin<br /> File:Person-placeholder.png| Abraham Schneider, Ph.D. &lt;br /&gt; <br /> File:GregSchwartz.png| Greg Schwartz, Ph.D. &lt;br /&gt; Assistant Professor, &lt;br /&gt; Northwestern University<br /> File:Per.jpg| [https://psychology.as.virginia.edu/people/profile/pbs5u Per B. Sederberg, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; University of Virginia<br /> File:Seelig.jpg| David Seelig &lt;br /&gt; Harry C. Coles, &lt;br /&gt; Jr. Post-doctoral Fellow at Annenberg Public Policy Center, &lt;br /&gt; University of Pennsylvania <br /> File:Misha.jpg| Misha Serruya, M.D., Ph.D. &lt;br /&gt; Neurologist neuroscientist, &lt;br /&gt; Jefferson Hospital <br /> File:Sileo.jpg| Joseph Sileo &lt;br /&gt; University of Pennsylvania<br /> File:Yevgeniy.jpg| Yevgeniy Sirotin, Ph.D. &lt;br /&gt; Senior Principal Scientist, &lt;br /&gt; Manager at SAIC<br /> File:Julia.jpg| Julia (Barnathan) Skolnik &lt;br /&gt; assistant director of professional development, Franklin Institute <br /> File:Henry.jpg| Henry Solberg &lt;br /&gt; Masters Student &lt;br /&gt; Mathematics &lt;br /&gt; University of Illinois Urbana-Champaign<br /> File:Solway.jpg| [https://psyc.umd.edu/facultyprofile/solway/alec Alec Solway, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; University of Maryland<br /> File:Solomon1.jpg|Ethan Solomon &lt;br /&gt; M.D./Ph.D. Student<br /> File:Jessica.jpg| Jessica Spencer, M.D. &lt;br /&gt; Assistant Professor, &lt;br /&gt; Reproductive Endocrinologist, &lt;br /&gt; Emory School of Medicine <br /> File:Maciek.jpg| Maciek Swat, Ph.D. &lt;br /&gt; Inscripta<br /> File:Vitaly.jpg| Vitaly Terushkin, M.D. &lt;br /&gt; Clinical Instructor in Dermatology, &lt;br /&gt; Joan &amp; Sanford Medical College of Cornell University<br /> File:Michele.jpg| Michele Tully Tine, Ph.D. &lt;br /&gt; Associate Professor, Dartmouth College <br /> File:DanUtin.png| Dan Utin &lt;br /&gt; Research Staff, &lt;br /&gt; MIT Lincoln Laboratory <br /> File:Marieke.jpg| [http://www.ai.rug.nl/~mkvanvugt/ Marieke van Vugt, Ph.D.] &lt;br /&gt; Assistant Professor, &lt;br /&gt; University of Groningen <br /> File:Jasmine2.jpg|Jasmine Wang&lt;br /&gt; VCU Chemical and Life Science Engineering, &lt;br /&gt; Virginia Commonwealth University<br /> File:ChristophW.jpg| [http://cogsci.info/ Christoph Weidemann, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; Swansea University <br /> File:Ryan.jpg|Ryan Bailey Williams &lt;br /&gt;<br /> File:Wyble.jpg| [http://wyblelab.com/ Brad Wyble, Ph.D.] &lt;br /&gt; Associate Professor, &lt;br /&gt; Pennsylvania State University<br /> File:Alison.jpg|Alison Xu&lt;br /&gt; Medical Student, Albert Einstein College of Medicine<br /> File:Xu.jpg|Jenny Xu&lt;br /&gt;<br /> File:yaffe.png|Robert Yaffe, Ph.D. &lt;br /&gt; Software Engineer, &lt;br /&gt; Google<br /> File:Kareem.jpg| [https://irp.nih.gov/pi/kareem-zaghloul Kareem Zaghloul, M.D., Ph.D] &lt;br /&gt; Investigator, &lt;br /&gt; NINDS <br /> File:Franklin.jpg| [https://www.codecygnus.com/team/franklin-zaromb/ Franklin Zaromb, Ph.D.] &lt;br /&gt; Data Science Consultant, &lt;br /&gt; Code Cygnus<br /> &lt;/gallery&gt;<br /> <br /> [[Category:People]]</div> Ckeane1