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Cell type-specific connectome predicts distributed working memory activity in the mouse brain.

Xingyu Ding1, Sean Froudist-Walsh1,2, Jorge Jaramillo1,3

  • 1Center for Neural Science, New York University, New York, United States.

Elife
|January 4, 2024
PubMed
Summary
This summary is machine-generated.

A new large-scale mouse brain model reveals how working memory relies on distributed brain networks. Cell type-specific connections and interneuron density shape how the brain maintains information, highlighting the need for detailed connectomics.

Keywords:
attractorcell-typescomputational modelconnectomeinterneuronslarge-scalemouseneuroscienceworking memory

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Cognitive Science

Background:

  • Advances in connectomics and neurophysiology enable whole-brain mechanism studies.
  • Working memory is crucial for internally holding and processing information without sensory input.

Purpose of the Study:

  • To develop a large-scale model of the multiregional mouse brain to study working memory.
  • To investigate how connectome data and interneuron density influence working memory coding.

Main Methods:

  • Constructed a mesoscopic model of the mouse brain using interareal cortical connection data.
  • Incorporated a macroscopic gradient of parvalbumin-expressing interneuron density.
  • Analyzed cell type-specific graph measures to predict activity patterns and subnetworks.

Main Results:

  • Working memory coding is distributed but modular, influenced by long-range, cell type-specific targeting and interneuron density.
  • Identified a core subnetwork essential for memory maintenance.
  • The model exhibited multiple attractor states, representing self-sustained internal brain states.

Conclusions:

  • The developed model provides a framework for interpreting large-scale brain activity recordings during cognitive tasks.
  • Emphasizes the critical role of cell type-specific connectomics in understanding brain function.
  • Suggests that distributed yet modular coding, shaped by specific neuronal populations, underlies working memory.