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Patterns of Cerebellar-Cortical Structural Covariance Mirror Anatomical Connectivity of Sensorimotor and Cognitive Networks

Authors: Alasmar ZChakravarty MMPenhune VBSteele CJ


Affiliations

1 Department of Psychology, Concordia University, Montreal, Quebec, Canada.
2 School of Health, Concordia University, Montreal, Quebec, Canada.
3 Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada.
4 Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
5 Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
6 International Laboratory for Brain, Music, and Sound Research (BRAMS), Montreal, Quebec, Canada.
7 Center for Research in Brain, Language, and Music (CRBLM), Montreal, Quebec, Canada.
8 Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Description

The cortex and cerebellum are densely connected through reciprocal input/output projections that form segregated circuits. These circuits are shown to differentially connect anterior lobules of the cerebellum to sensorimotor regions, and lobules Crus I and II to prefrontal regions. This differential connectivity pattern leads to the hypothesis that individual differences in structure should be related, especially for connected regions. To test this hypothesis, we examined covariation between the volumes of anterior sensorimotor and lateral cognitive lobules of the cerebellum and measures of cortical thickness (CT) and surface area (SA) across the whole brain in a sample of 270 young adults drawn from the HCP dataset. We observed that patterns of cerebellar-cortical covariance differed between sensorimotor and cognitive networks. Anterior motor lobules of the cerebellum showed greater covariance with sensorimotor regions of the cortex, while lobules Crus I and Crus II showed greater covariance with frontal and temporal regions. Interestingly, cerebellar volume showed predominantly negative relationships with CT and predominantly positive relationships with SA. Individual differences in SA are thought to be largely under genetic control while CT is thought to be more malleable by experience. This suggests that cerebellar-cortical covariation for SA may be a more stable feature, whereas covariation for CT may be more affected by development. Additionally, similarity metrics revealed that the pattern of covariance showed a gradual transition between sensorimotor and cognitive lobules, consistent with evidence of functional gradients within the cerebellum. Taken together, these findings are consistent with known patterns of structural and functional connectivity between the cerebellum and cortex. They also shed new light on possibly differing relationships between cerebellar volume and cortical thickness and surface area. Finally, our findings are consistent with the interactive specialization framework which proposes that structurally and functionally connected brain regions develop in concert.


Keywords: cerebellumcortical decompositionnormative modelingsimilarity analysisstructural covariance


Links

PubMed: https://pubmed.ncbi.nlm.nih.gov/39791308/

DOI: 10.1002/hbm.70079