Computational Neuroscience Journal Club

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• Laurence Aitchison (CBL)
• Tuesday 28 November 2017, 16:00-17:00
• Cambridge University Engineering Department, CBL, BE4-38 (http://learning.eng.cam.ac.uk/Public/Directions).

If you have a question about this talk, please contact Rodrigo Echeveste.

Laurence Aitchison will cover:

• The hippocampus as a predictive map

• Kimberly L Stachenfeld, Matthew M Botvinick & Samuel J Gershman

• Nature Neuroscience (October 2017)

• https://www.nature.com/articles/nn.4650

Abstract: A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity and policy dependence in place cells suggests that the representation is not purely spatial. We approach this puzzle from a reinforcement learning perspective: what kind of spatial representation is most useful for maximizing future reward? We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. Furthermore, we argue that entorhinal grid cells encode a low-dimensionality basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.

This talk is part of the Computational Neuroscience series.

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