Literature DB >> 31115118

Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults.

Ruiyang Ge1, Paul Kot1, Xiang Liu1, Donna J Lang2, Jane Z Wang3, William G Honer4, Fidel Vila-Rodriguez1.   

Abstract

The hippocampus is a key brain region that participates in a range of cognitive and affective functions, and is involved in the etiopathogenesis of numerous neuropsychiatric disorders. The structural complexity and functional diversity of the hippocampus suggest the existence of structural and functional subdivisions within this structure. For the first time, we parcellated the human hippocampus with two independent data sets, each of which consisted of 198 T1-weighted structural magnetic resonance imaging (sMRI) images of healthy young subjects. The method was based on gray matter volume (GMV) covariance, which was quantified by a bivariate voxel-to-voxel linear correlation approach, as well as a multivariate masked independent component analysis approach. We subsequently interrogated the relationship between the GMV covariance patterns and the functional connectivity patterns of the hippocampal subregions using sMRI and resting-state functional MRI (fMRI) data from the same participants. Seven distinct GMV covariance-based subregions were identified for bilateral hippocampi, with robust reproducibility across the two data sets. We further demonstrated that the structural covariance patterns of the hippocampal subregions had a correspondence with the intrinsic functional connectivity patterns of these subregions. Together, our results provide a topographical configuration of the hippocampus with converging structural and functional support. The resulting subregions may improve our understanding of the hippocampal connectivity and functions at a subregional level, which provides useful parcellations and masks for future neuroscience and clinical research on the structural and/or functional connectivity of the hippocampus.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  MRI; gray matter volume; hippocampus; independent component analysis; parcellation; structural covariance

Mesh:

Year:  2019        PMID: 31115118      PMCID: PMC6865476          DOI: 10.1002/hbm.24628

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


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  5 in total

1.  Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults.

Authors:  Ruiyang Ge; Paul Kot; Xiang Liu; Donna J Lang; Jane Z Wang; William G Honer; Fidel Vila-Rodriguez
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