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Computational Neuroscience Journal Club

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  • UserYul Kang and Wayne Soo
  • ClockTuesday 26 October 2021, 14:00-15:30
  • HouseOnline on Zoom.

If you have a question about this talk, please contact Jake Stroud .

Please join us for our fortnightly journal club online via zoom where two presenters will jointly present a topic together. The next topic is ‘Flexible computation in the entorhinal-hippocampal system’ presented by Wayne Soo and Yul Kang.

Zoom information: https://us02web.zoom.us/j/84958321096?pwd=dFpsYnpJYWVNeHlJbEFKbW1OTzFiQT09 Meeting ID: 841 9788 6178 Passcode: 659046

Summary: In Part 1, we will cover the “linear reinforcement learning” model proposed by Piray & Daw (2021), which allows flexible replanning under changing goals with a computationally inexpensive, linear approximation of the Bellman equation, and explains the cost of cognitive control and grid and border cell activities. In Part 2, we will look at a proposed generative process of sequential internal state representations that can interpolate between qualitatively distinct regimes of sequential hippocampal reactivations. This is achieved by a systematic modulation along the medial entorhinal cortex dorsoventral axis of grid population input into the hippocampus.

Relevant reading:

McNamee, D. C., Stachenfeld, K. L., Botvinick, M. M. & Gershman, S. J. Flexible modulation of sequence generation in the entorhinal–hippocampal system. Nat Neurosci 1–12 (2021) doi:10.1038/s41593-021-00831-7. https://www.nature.com/articles/s41593-021-00831-7

P. Piray and N. Daw, Linear reinforcement learning: Flexible reuse of computation in planning, grid fields, and cognitive control, Nat Comm, 2021, https://www.nature.com/articles/s41467-021-25123-3

This talk is part of the Computational Neuroscience series.

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