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Whole-Brain 3D Activation and Functional Connectivity Mapping in Mice using Transcranial Functional Ultrasound Imaging

Whole-Brain 3D Activation and Functional Connectivity Mapping in Mice using Transcranial Functional Ultrasound Imaging

Published on: February 24, 2021

Modeling awake hippocampal reactivations with model-based bidirectional search.

Mehdi Khamassi¹, Benoît Girard²

¹Institute of Intelligent Systems and Robotics (ISIR), Sorbonne Université and CNRS (Centre National de la Recherche Scientifique), 75005, Paris, France. Mehdi.Khamassi@sorbonne-universite.fr.

Biological Cybernetics

|February 18, 2020

Summary

This study introduces a novel bidirectional search model to explain hippocampal replay events during learning. The model integrates forward and backward replay, clarifying their roles in decision-making and memory consolidation.

Keywords:

Computational neuroscience Hippocampal replay Navigation Reinforcement learning

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Acute Mouse Brain Slicing to Investigate Spontaneous Hippocampal Network Activity

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Published on: August 28, 2020

Area of Science:

Neuroscience
Computational Neuroscience
Reinforcement Learning

Background:

Hippocampal offline reactivations (replay events) are crucial for learning and memory consolidation.
Replay events are linked to transforming reward information for decision-making.
The variety in replay order and location remains unexplained by current models.

Purpose of the Study:

To present a unified computational model explaining diverse hippocampal reactivations.
To investigate how replay contributes to reinforcement learning and memory consolidation.
To elucidate the role of the hippocampo-prefronto-striatal network in learning.

Main Methods:

Developed a model-based bidirectional search algorithm.
Combined forward trajectory sampling with backward prioritized sweeping.
Simulated agent behavior in a T-maze task to analyze replay events.

Main Results:

The model successfully accounts for forward and backward hippocampal reactivations.
Forward reactivations occurred at decision points; backward reactivations occurred at reward sites.
Model simulations showed replay events diminish as learning stabilizes and can generate novel trajectories.

Conclusions:

A bidirectional search mechanism can explain varied hippocampal replay patterns.
This model offers insights into how the brain learns and consolidates memories.
The findings highlight the importance of replay in decision-making and potential network roles.