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Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults.
Ge, Ruiyang; Kot, Paul; Liu, Xiang; Lang, Donna J; Wang, Jane Z; Honer, William G; Vila-Rodriguez, Fidel.
Afiliação
  • Ge R; Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.
  • Kot P; Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.
  • Liu X; Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.
  • Lang DJ; Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.
  • Wang JZ; Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada.
  • Honer WG; Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.
  • Vila-Rodriguez F; Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.
Hum Brain Mapp ; 40(13): 3738-3752, 2019 09.
Article em En | MEDLINE | ID: mdl-31115118
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Imageamento por Ressonância Magnética / Conectoma / Substância Cinzenta / Hipocampo Limite: Adolescent / Adult / Female / Humans / Male Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Imageamento por Ressonância Magnética / Conectoma / Substância Cinzenta / Hipocampo Limite: Adolescent / Adult / Female / Humans / Male Idioma: En Ano de publicação: 2019 Tipo de documento: Article