Spatial cell-type enrichment predicts mouse brain connectivity

Sun, Shenghuan, Torok, Justin, Mezias, Christopher, Ma, Daren, Raj, Ashish (October 2023) Spatial cell-type enrichment predicts mouse brain connectivity. Cell Reports, 42 (10). p. 113258. ISSN 2211-1247

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DOI: 10.1016/j.celrep.2023.113258


A fundamental neuroscience topic is the link between the brain's molecular, cellular, and cytoarchitectonic properties and structural connectivity. Recent studies relate inter-regional connectivity to gene expression, but the relationship to regional cell-type distributions remains understudied. Here, we utilize whole-brain mapping of neuronal and non-neuronal subtypes via the matrix inversion and subset selection algorithm to model inter-regional connectivity as a function of regional cell-type composition with machine learning. We deployed random forest algorithms for predicting connectivity from cell-type densities, demonstrating surprisingly strong prediction accuracy of cell types in general, and particular non-neuronal cells such as oligodendrocytes. We found evidence of a strong distance dependency in the cell connectivity relationship, with layer-specific excitatory neurons contributing the most for long-range connectivity, while vascular and astroglia were salient for short-range connections. Our results demonstrate a link between cell types and connectivity, providing a roadmap for examining this relationship in other species, including humans.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > computational biology > algorithms
organism description > animal
organs, tissues, organelles, cell types and functions > organs types and functions > brain
bioinformatics > computational biology
organism description > animal > mammal
organism description > animal > mammal > rodent > mouse
organs, tissues, organelles, cell types and functions > organs types and functions
organism description > animal > mammal > rodent
CSHL Authors:
Communities: CSHL labs > Mitra lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 18 October 2023
Date Deposited: 01 Nov 2023 16:05
Last Modified: 11 Jan 2024 14:24
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