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Toward the biological model of the hippocampus as the successor representation agent

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Affiliated Author(s)
이현수
Alternative Author(s)
Lee, Hyun Su
Journal Title
Biosystems
ISSN
0303-2647
Issued Date
2022
Keyword
HippocampusPredictive mapSuccessor representationTemporal difference learningHeterosynaptic plasticity
Abstract
The hippocampus is an essential brain region for spatial memory and learning. Recently, a theoretical model of the hippocampus based on temporal difference (TD) learning has been published. Inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition, they argued that the rate of firing of CA1 place cells in the hippocampus represents the probability of state transition. This theory, called predictive map theory, claims that the hippocampus representing space learns the probability of transition from the current state to the future state. The neural correlates of expecting the future state are the firing rates of the CA1 place cells. This explanation is plausible for the results recorded in behavioral experiments, but it is lacking the neurobiological implications.

Modifying the SR learning algorithm added biological implications to the predictive map theory. Similar with the simultaneous needs of information of the current and future state in the SR learning algorithm, the CA1 place cells receive two inputs from CA3 and entorhinal cortex. Mathematical transformation showed that the SR learning algorithm is equivalent to the heterosynaptic plasticity rule. The heterosynaptic plasticity phenomena in CA1 were discussed and compared with the modified SR update rule. This study attempted to interpret the TD algorithm as the neurobiological mechanism occurring in place learning, and to integrate the neuroscience and artificial intelligence approaches in the field.
Department
Dept. of Anatomy (해부학)
Publisher
School of Medicine (의과대학)
Citation
[1]Hyunsu Lee, “Toward the biological model of the hippocampus as the successor representation agent,” Biosystems, vol. 213. School of Medicine (의과대학), p. 104612, 2022. doi: 10.1016/j.biosystems.2022.104612.
Type
Article
DOI
10.1016/j.biosystems.2022.104612
URI
http://kumel.medlib.dsmc.or.kr/handle/2015.oak/44170
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Anatomy (해부학)
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