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CINQ seminar series - Mr Blake Richards, Ph.D. - Learning from unexpected events in the neocortical microcircuit

  • 22 Oct 2020
  • 1:30 PM - 2:30 PM
  • Virtual talk on Zoom

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Conférence en anglais   ||   The talk will be given in English


Pour cette conférence, le CINQ a le plaisir d'accueillir M. Blake Richards. M. Richards est professeur adjoint au département de neurologie et de neurochirurgie ainsi qu'à l'École d'informatique, à McGill University. Il est chercheur à l'Institut neurologique de Montréal (le Neuro) et à l'Institut d'intelligence artificielle du Québec (MILA).

For this talk, the CINQ is pleased to welcome Mr Blake Richards. Mr Richards is an an assistant professor in the department of neurology and neurosurgery  and the School of Computer Science at McGill University. He is also a member of the Montreal Neurological Institute and a Core Faculty Member at the Quebec Artificial Intelligence Institute.

Title :  Learning from unexpected events in the neocortical microcircuit

Abstract :  

A long-standing hypothesis in computational neuroscience is that the neocortex learns a hierarchical model of the world by predicting incoming sensory data, and learning from unexpected events. This hypothesis predicts that: (1) There should be distinct responses to expected and unexpected stimuli. (2) As a circuit learns about stimuli, the responses to both expected and unexpected stimuli should change. (3) There should be differences between the manner in which top-down and bottom-up driven responses change during learning. (4) The response changes should be long-lasting and predictable from the differences in the responses to expected and unexpected stimuli. Here, we use chronic two-photon imaging of supra- and sub-granular pyramidal neurons in mouse visual cortex to test these hypotheses. We habituated the mice to sequences of random Gabor frames with embedded patterns to help shape expectations. We then conducted imaging over three days during which time we exposed the mice to sequences that violated the previous patterns. We find that all four of the above predictions are borne out in the data: pyramidal neurons respond differently to unexpected stimuli, the responses to both expected and unexpected stimuli evolve over time, the evolution of these responses is different in the distal apical dendrites and the somata, and the differences in responses predicted this evolution over days. Altogether, this data supports the hierarchical predictive model hypothesis, and provides greater information about how this learning is implemented in the neocortical microcircuit.


Thursday October 22nd, 2020

Virtual talk on Zoom

Meeting ID 846 0058 4732 or direct link

1:30 PM to 2:30 PM : Talk

3:00 PM to 4:00 PM : Coffee talk with students and post doctoral fellows (registration required)




We look forward to seeing you there!




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