Hippocampal Remapping as Hidden State Inference

Cells in the hippocampus tuned to spatial location (place cells) typically change their tuning when an animal changes context, a phenomenon known as remapping. A fundamental challenge to understanding remapping is the fact that what counts as a “context change” has never been precisely defined. Furt...

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Главные авторы: Sanders, Honi, Wilson, Matthew A., Gershman, Samueal J.
Формат: Technical Report
Опубликовано: Center for Brains, Minds and Machines (CBMM), bioRxiv 2019
Online-ссылка:https://hdl.handle.net/1721.1/122040
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author Sanders, Honi
Wilson, Matthew A.
Gershman, Samueal J.
author_facet Sanders, Honi
Wilson, Matthew A.
Gershman, Samueal J.
author_sort Sanders, Honi
collection MIT
description Cells in the hippocampus tuned to spatial location (place cells) typically change their tuning when an animal changes context, a phenomenon known as remapping. A fundamental challenge to understanding remapping is the fact that what counts as a “context change” has never been precisely defined. Furthermore, different remapping phenomena have been classified on the basis of how much the tuning changes after different types and degrees of context change, but the relationship between these variables is not clear. We address these ambiguities by formalizing remapping in terms of hidden state inference. According to this view, remapping does not directly reflect objective, observable properties of the environment, but rather subjective beliefs about the hidden state of the environment. We show how the hidden state framework can resolve a number of puzzles about the nature of remapping.
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spelling mit-1721.1/1220402019-09-06T03:00:51Z Hippocampal Remapping as Hidden State Inference Sanders, Honi Wilson, Matthew A. Gershman, Samueal J. Cells in the hippocampus tuned to spatial location (place cells) typically change their tuning when an animal changes context, a phenomenon known as remapping. A fundamental challenge to understanding remapping is the fact that what counts as a “context change” has never been precisely defined. Furthermore, different remapping phenomena have been classified on the basis of how much the tuning changes after different types and degrees of context change, but the relationship between these variables is not clear. We address these ambiguities by formalizing remapping in terms of hidden state inference. According to this view, remapping does not directly reflect objective, observable properties of the environment, but rather subjective beliefs about the hidden state of the environment. We show how the hidden state framework can resolve a number of puzzles about the nature of remapping. This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216. 2019-09-05T16:06:11Z 2019-09-05T16:06:11Z 2019-08-22 Technical Report Working Paper Other https://hdl.handle.net/1721.1/122040 CBMM Memo;101 application/pdf Center for Brains, Minds and Machines (CBMM), bioRxiv
spellingShingle Sanders, Honi
Wilson, Matthew A.
Gershman, Samueal J.
Hippocampal Remapping as Hidden State Inference
title Hippocampal Remapping as Hidden State Inference
title_full Hippocampal Remapping as Hidden State Inference
title_fullStr Hippocampal Remapping as Hidden State Inference
title_full_unstemmed Hippocampal Remapping as Hidden State Inference
title_short Hippocampal Remapping as Hidden State Inference
title_sort hippocampal remapping as hidden state inference
url https://hdl.handle.net/1721.1/122040
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AT wilsonmatthewa hippocampalremappingashiddenstateinference
AT gershmansamuealj hippocampalremappingashiddenstateinference