HOME   DIRECTORY   ACTIVITIES   PROPOSE ACTIVITY   APPLY   FOR VISITORS   ONLINE TALKS   OUTREACH 
KITP Program: Statistical Learning in the Brain
(Jun 12 - Jul 21, 2023)
Coordinators: Livia de Hoz, József Fiser, and Máté Lengyel
 Overview
 This Week
 Next Week
 Online Talks >
 ...newest
 PodcastXML
 ...help?
 Conference
 Participants
 ...by date
 ...today
 
KITP
 Home
 This Week
 Next Week
 Directory
 All Talks
 RelFluids23
 Information

Speakers: Please contact us about file upload for your slides.

Time Speaker Title
6/13 What is statistical learning?
6/13, 9:00am Livia de Hoz
(Charite)
Jozsef Fiser
(Central European University)
Mate Lengyel
(University of Cambridge, Central European University)		 General introduction, information session, practicalities[Video][CC][Transcript]
6/13, 10:00am All Participants Participant's one slide-introductions: part 1[Video][CC][Transcript]
6/13, 11:00am All Participants Participant's one slide-introductions: part 2[Video][CC][Transcript]
6/13, 11:30am All Participants Speed dating
6/13, 1:30pm Aaron Seitz
University of California, Riverside		 What is statistical learning?[Video][CC][Transcript]
6/13, 2:00pm Athena Akrami
(Sainsbury Wellcome Centre, UCL)
Lauren Emberson
(University of British Columbia)
Jozsef Fiser
(Central European University)
Aaron Seitz
(University of California, Riverside)		 Round table discussion[Video]
6/13, 3:45pm All participants Group presentation and discussions[Video]
6/14 What is statistical learning? Theoretical approaches
6/14, 9:00am Elad Schneidman
Weizmann Institute of Science		 Statistical learning: frequencies, pair-wise interactions, and more[Video][CC][Transcript]
6/14, 9:45am Gasper Tkacik
Institute of Science and Technology, Austria		 Efficient coding for network interactions[Video][CC][Transcript]
6/14, 11:00am All Participants Participant's one slide-introductions: part 3[Video][CC][Transcript]
6/14, 11:15am Ilya Nemenman
Emory University		 Learning complex neural codes[Video][CC][Transcript]
6/14, 12:00pm Elad Schneidman
Weizmann Institute of Science		 Discussion: Challenges in building theories of statistical learning[Video][CC][Transcript]
6/15 Statistical learning vs reinforcement learning
6/15, 9:00am All Participants Participant's one slide-introductions: part 4[Video][CC][Transcript]
6/15, 9:05am Livia de Hoz
(Charite)
Athena Akrami
(Sainsbury Wellcome Centre, UCL)		 Introduction to the neurobiology and systems neuroscience view of statistical learning[Video][CC][Transcript]
6/15, 9:30am Athena Akrami
Sainsbury Wellcome Centre, UCL		 Math vs. Brains - Can/should all statistical learning problems be framed as reinforcement learning?[Slides][Video][CC][Transcript]
6/15, 11:00am Athena Akrami
Sainsbury Wellcome Centre, UCL		 Roundtable discussion[Video][CC][Transcript]
6/16 Theme TBA
6/16, 9:00am Nick Turk-Browne
Yale University		 Review: What is the relationship between statistical learning and episodic memory?[Video][CC][Transcript]
6/16, 11:00am Nick Turk-Browne
(Yale University)
Kishore Kuchibhotla
(Johns Hopkins University)
Bradley Love
(UCL)		 Roundtable discussion: Why are learning and memory studied separately? Are there different types of statistical learning by memory system? Why do we learn so much but remember so little early in life?[Video]
6/19 Implicit learning of Task Structure
6/20 Interplay between neural representations and learning
6/20, 9:00am All Participants Participant's one slide-introductions: part 5[Video][CC][Transcript]
6/20, 9:05am Sara Solla
Northwestern University		 Neural manifolds and learning[Video][CC][Transcript]
6/20, 11:00am Sara Solla
(Northwestern University)
Sebastian Goldt
(SISSA)
Marcelo Mattar
(New York University)
Elad Schneidman
(Weizmann Institute of Science)
Gasper Tkacik
(Institute of Science and Technology Austria)		 Roundtable discussion: From sensory modes to neural modes to behavioral modes: low-dimensional representations everywhere! The role of dimensionality and geometry of neural representations in statistical learning.[Video]
6/21 Statistical learning for control
6/21, 9:00am Marcelo Mattar
New York University		 Review talk[Slides][Video][CC][Transcript]
6/21, 11:00am Marcelo Mattar
(New York University)
Anna Schapiro
(University of Pennsylvania)
Ishita Dasgupta
(DeepMind)
James Whittington
(University of Oxford, Stanford University)
Mate Lengyel
(University of Cambridge, Central European University)		 Roundtable discussion[Video][CC][Transcript]
6/22 Bridging (statistical) learning in cognitive experiments, animal experiments and theory
6/22, 9:00am Tara Keck
University College London		 How can we think about links across cognitive experiments, animal experiments and theory[Video][CC][Transcript]
6/22, 9:30am All participants Group discussions part I: animal experimentalists, cognitive scientists and theorists[Video][CC][Transcript]
6/22, 11:00am All participants Group discussions part II: cross groups[Video]
6/23 From pairwise associations to higher-order correlations: what and how do neural networks learn from them?
6/23, 9:00am Sebastian Goldt
SISSA		 Beyond pairwise associations: what and how do artificial neural networks learn from them?[Slides][Video][CC][Transcript]
6/23, 11:00am Jonathan Victor
Weill Cornell Medical College		 Early visual processing of higher-order statistics[Slides][Video][CC][Transcript]
6/23, 11:30am Mate Lengyel
University of Cambridge, Central European University		 Bayesian chunk learning: beyond pairwise associations, beyond modalities[Video][CC][Transcript]
6/26 Perception and Statistical Learning in Development
6/26, 9:00am Lauren Emberson
University of British Columbia		 The puzzle of SL and perceptual development[Video][CC][Transcript]
6/26, 11:00am Lauren Emberson
University of British Columbia		 Panel Discussion and break-out groups: Joszef Fiser, Simon Rumpel, Andrew Saxe, Dezso Nemeth[Video][CC][Transcript]
6/26, 12:15pm Maneesh Sahani
UCL		 How the brain constructs a world?[Video]
KITP Blackboard Lunch
6/27 Active sensing: sensory-motor contingencies, perception, task context, and learning
6/27, 9:00am Ziad Hafed
Werner Reichardt Centre for Integrative Neuroscience		 On the sensory consequences of rapid eye movements, with links to predictive coding, state estimation, and perception[Video][CC][Transcript]
6/27, 9:40am Tim Brady
UC San Diego		 Consequences of statistical learning on perception & working memory[Slides][Video][CC][Transcript]
6/27, 10:50am Kishore Kuchibhotla
Johns Hopkins University		 Rapid emergence of latent knowledge in cortical networks drives learning[Video][CC][Transcript]
6/27, 11:30am Jonathan Victor
Weill Cornell Medical College		 Task-driven influences on fixational eye movements[Slides][Video][CC][Transcript]
6/28 How task statistics and biology shape neural response
6/28, 9:00am James Whittington
Stanford University & Oxford University		 What we know about how task and biology constraints neural representation?[Video][CC][Transcript]
6/28, 11:00am Ryan Low
UCL		 Structure and variability of hippocampal dynamics across tasks[Video][CC][Transcript]
6/28, 11:30am Andrew Saxe
UCL		 Dynamics of abstraction in deep networks[Video][CC][Transcript]
6/28, 12:00pm James Whittington
Stanford University and Oxford University		 Discussion: Can we categorise how different types of task statistics / biological constraints impact neural response?[Video][CC][Transcript]
6/29 The different role of recent and accumulative statistics
6/29, 9:00am Merav Ahissar
Hebrew University of Jerusalem		 Different contributions of recent and long-term statistics[Video][CC][Transcript]
6/29, 10:00am Athena Akrami
University College London		 WM versus short term memory across species[Video][CC][Transcript]
6/29, 11:00am Tim Brady
UC San Diego		 Visual memory for recent, earlier and accumulative events[Video][CC][Transcript]
6/29, 11:30am Mate Lengyel
University College London		 Modeling longer versus recent statistics - learning different contexts[Video][CC][Transcript]
6/30 The dynamics of neural representations in predictive learning
6/30, 9:00am Andrew Saxe
University College London		 Solvable models of deep learning dynamics, predictive coding and statistical learning[Video][CC][Transcript]
6/30, 11:00am Merav Ahissar
(Hebrew University of Jerusalem)
Sebastian Goldt
(Scuola Internazionale Superiore di Studi Avanzati)
Athena Akrami
(University College London)		 Discussion: making predictions concrete[Video][CC][Transcript]
7/03
7/03, 9:00am Livia de Hoz
(Charite Berlin)
Jozsef Fiser
(Central European University)		 General introduction, information session, practicalities[Video]
7/03, 10:00am All Participants Participant's one slide-introductions: part 6[Video][CC][Transcript]
7/03, 11:00am David Gross
KITP		 On ITP and KITP
7/05 The impact of intrinsic volatility in neuronal circuits on learning and memory
7/05, 9:00am Simon Rumpel
Univ. Mainz		 Experimental results on synaptic and representational drift[Slides][Video][CC][Transcript]
7/05, 10:00am Michael Goard
UCSB		 Stability and volatility in the mouse visual system[Slides][Video][CC][Transcript]
7/05, 11:00am Mitya Chklovskii
Flatiron Institute		 Volatility in neuronal circuits: bug or feature?[Video][CC][Transcript]
7/05, 12:00am All participants Dimensions of learning: Where does Statistical Learning map to?[Video]
7/06 Statistical Learning in the Auditory System
7/06, 9:00am Jennifer Linden
University College London		 Introduction to the session and Representation of Primitives for Statistical Learning in the Auditory System[Video][CC][Transcript]
7/06, 9:30am Eli Nelken
Hebrew Univ.		 Statistical learning in single neurons: data and models[Video][CC][Transcript]
7/06, 11:00am Livia de Hoz
Charite		 Sensitivity of subcortical activity to statistics acquired slow and fast[Video][CC][Transcript]
7/06, 11:30am Bernhard Englitz
Donders Inst.		 Hearing the needle in the haystack[Video][CC][Transcript]
7/07 On the ineluctable manifestation of uncertainty
7/07, 9:00am Maneesh Sahani
University College London		 Internal beliefs, uncertainty and learning[Video][CC][Transcript]
7/07, 11:00am Maneesh Sahani
(University College London)
Peter Latham
(University College London)
Mate Lengyel
(University of Cambridge, Central European University)		 Discussion: internal beliefs, uncertainty and learning[Video]
7/10-13 Conference: Timescales of Plasticity and Underlying Mechanisms
7/14 The role of prediction in statistical learning
7/14, 9:00am Miguel Maravall
U. Sussex		 Parsing statistical learning[Video][CC][Transcript]
7/14, 10:00am Jozsef Fiser
CEU		 Lamp-posts and hidden representations[Video][CC][Transcript]
7/14, 11:30am Floris de Lange
RU Nijmegen		 Successor representation in human primary visual cortex and hippocampus[Video][CC][Transcript]
7/14, 12:00pm Peter Dayan
MPI-BK		 Accounting for Every Choice[Video][CC][Transcript]
7/17 The role of prediction in statistical learning
7/17, 9:00am Floris de Lange
Radboud University, Donders Institute		 Prediction in statistical learning[Video][CC][Transcript]
7/17, 10:00am Andrew Saxe
University College London		 Prediction as a learning objective[Video][CC][Transcript]
7/17, 11:00am Israel Nelken
Hebrew University		 Prediction errors and predictions in the auditory system[Video][CC][Transcript]
7/18 What can we learn about the brain?
7/18, 9:00am Peter Latham
University College London		 Mathematical framework of learning as inference and control[Video][CC][Transcript]
7/18, 11:00am Mitya Chklovskii
Flatiron Institute		 Neurons as Direct Data-Driven Controllers (DD-DC) II[Video][CC][Transcript]
7/18, 11:45am Marta Zlatic
University of Cambridge, MRC Laboratory of Molecular Biology		 How can we use the architecture of learning circuits to provide clues about learning algorithms and constrain learning models?[Video][CC][Transcript]
7/19 Studying statistical learning in animals
7/19, 9:00am Aurore Avargues-Weber
Centre de Recherche sur la Cognition Animale		 Mastering learning about relations: a honeybee perspective[Video][CC][Transcript]
7/19, 11:00am Marta Zlatic
University of Cambridge, MRC Laboratory of Molecular Biology		 Combining brain-wide connectivity maps with brain-wide activity and behaviour maps to understand learning in Drosophila[Video][CC][Transcript]
7/19, 11:30am Yonatan Aljadeff
University of California San Diego		 How flies got their sensilla? Statistical learning on evolutionary timescales[Video][CC][Transcript]
7/19, 12:00pm Huizhong Tao
University of Southern California		 A bottom-up sensory pathway for reward associative learning[Video][CC][Transcript]
7/20 Statistical learning for interference and generalization
7/20, 9:00am Christine Constantinople
New York University		 Neural mechanisms of inference[Embargoed]
7/20, 9:45am Li Zhang
University of Southern California		 "Dormant" Cells and Sparse Coding in Awake Auditory Cortex[Video][CC][Transcript]
7/20, 11:00am Rob Froemke
New York University		 Love, death, and statistical learning[Video][CC][Transcript]
7/21 Keynote lecture
7/21, 9:00am All Participants Roasting the program organizers
7/21, 11:00am Daniel Wolpert
Columbia University		 Keynote: Statistical learning in sensorimotor control[Video]
email: contact | printer friendly