Spatial cell-type enrichment predicts mouse brain connectivity
Summary: 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 understu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Cell Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211124723012706 |
| _version_ | 1797655118395473920 |
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| author | Shenghuan Sun Justin Torok Christopher Mezias Daren Ma Ashish Raj |
| author_facet | Shenghuan Sun Justin Torok Christopher Mezias Daren Ma Ashish Raj |
| author_sort | Shenghuan Sun |
| collection | DOAJ |
| description | Summary: 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. |
| first_indexed | 2024-03-11T17:09:31Z |
| format | Article |
| id | doaj.art-92a923f8230c47e69c84f4fad0dc6085 |
| institution | Directory Open Access Journal |
| issn | 2211-1247 |
| language | English |
| last_indexed | 2024-03-11T17:09:31Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cell Reports |
| spelling | doaj.art-92a923f8230c47e69c84f4fad0dc60852023-10-20T06:39:29ZengElsevierCell Reports2211-12472023-10-014210113258Spatial cell-type enrichment predicts mouse brain connectivityShenghuan Sun0Justin Torok1Christopher Mezias2Daren Ma3Ashish Raj4Department of Radiology, University of California, San Francisco, San Francisco, CA, USADepartment of Radiology, University of California, San Francisco, San Francisco, CA, USACold Spring Harbor Laboratory, Cold Spring Harbor, NY, USADepartment of Radiology, University of California, San Francisco, San Francisco, CA, USADepartment of Radiology, University of California, San Francisco, San Francisco, CA, USA; Corresponding authorSummary: 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.http://www.sciencedirect.com/science/article/pii/S2211124723012706CP: NeuroscienceCP: Cell biology |
| spellingShingle | Shenghuan Sun Justin Torok Christopher Mezias Daren Ma Ashish Raj Spatial cell-type enrichment predicts mouse brain connectivity Cell Reports CP: Neuroscience CP: Cell biology |
| title | Spatial cell-type enrichment predicts mouse brain connectivity |
| title_full | Spatial cell-type enrichment predicts mouse brain connectivity |
| title_fullStr | Spatial cell-type enrichment predicts mouse brain connectivity |
| title_full_unstemmed | Spatial cell-type enrichment predicts mouse brain connectivity |
| title_short | Spatial cell-type enrichment predicts mouse brain connectivity |
| title_sort | spatial cell type enrichment predicts mouse brain connectivity |
| topic | CP: Neuroscience CP: Cell biology |
| url | http://www.sciencedirect.com/science/article/pii/S2211124723012706 |
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