Cell Type-specific Connectome Predicts Distributed Working Memory Activity in the Mouse Brain

Overview

Journal Elife

Specialty Biology

Date 2024 Jan 4

PMID 38174734

Authors

Xingyu Ding

Sean Froudist-Walsh

Jorge Jaramillo

Junjie Jiang

Xiao-Jing Wang

Affiliations

Soon will be listed here.

Abstract

Recent advances in connectomics and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the multiregional mouse brain for a cardinal cognitive function called working memory, the brain's ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for interareal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous attractor states, which are self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.

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