KITP Program: Statistical Learning in the Brain
(Jun 12 - Jul 21, 2023)
Coordinators: Livia de Hoz, József Fiser, and Máté Lengyel

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Time Speaker Title
6/13 What is statistical learning?
6/13, 9:00am Livia de Hoz
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
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
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
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
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
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
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
Structure and variability of hippocampal dynamics across tasks[Video][CC][Transcript]
6/28, 11:30am Andrew Saxe
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, 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
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
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
Sensitivity of subcortical activity to statistics acquired slow and fast[Embargoed]
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
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
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]
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