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Mapping frontoinsular cortex from diffusion microstructure

Cabeen, Ryan P. and Toga, Arthur W. and Allman, John M. (2022) Mapping frontoinsular cortex from diffusion microstructure. Cerebral Cortex . Art. No. bhac237. ISSN 1047-3211. doi:10.1093/cercor/bhac237. (In Press) https://resolver.caltech.edu/CaltechAUTHORS:20220802-744668000

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Abstract

We developed a novel method for mapping the location, surface area, thickness, and volume of frontoinsular cortex (FI) using structural and diffusion magnetic resonance imaging. FI lies in the ventral part of anterior insular cortex and is characterized by its distinctive population von Economo neurons (VENs). Functional neuroimaging studies have revealed its involvement in affective processing, and histopathology has implicated VEN loss in behavioral-variant frontotemporal dementia and chronic alcoholism; however, structural neuroimaging of FI has been relatively limited. We delineated FI by jointly modeling cortical surface geometry and its coincident diffusion microstructure parameters. We found that neurite orientation dispersion in cortical gray matter can be used to map FI in specific individuals, and the derived measures reflect a range of behavioral factors in young adults from the Human Connectome Project (N=1052). FI volume was larger in the left hemisphere than the right (31%), and the percentage volume of FI was larger in women than men (15.3%). FI volume was associated with measures of decision-making (delay discounting, substance abuse), emotion (negative intrusive thinking and perception of hostility), and social behavior (theory of mind and working memory for faces). The common denominator is that larger FI size is related to greater self-control and social awareness.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/cercor/bhac237DOIArticle
https://www.humanconnectome.org/study/hcp-young-adult/data-releasesRelated ItemData
https://cabeen.io/qitwikiRelated ItemQuantitative Imaging Toolkit
https://resource.loni.usc.edu/resources/downloads/Related ItemLONI Neuroimaging Quality Control System (LONI QC)
ORCID:
AuthorORCID
Cabeen, Ryan P.0000-0002-1372-3588
Toga, Arthur W.0000-0001-7902-3755
Additional Information:© The Author(s) 2022. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Received: 04 January 2022. Revision received: 20 May 2022. Accepted: 21 May 2022. Published: 27 June 2022. Data were provided in part by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. This work was supported by National Institutes of Health (grant number P41EB015922) and made possible in part by grant number 2020-225670 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation. Availability of data and materials. Data used in our study is available with permission from the Human Connectome Project 1. Our data image analysis and visualization tools available online as part of the Quantitative Imaging Toolkit (QIT) 2,3. Conflicts of interest statement: None declared. Ethics approval. This project received approval from the Institutional Review Board of the University of Southern California and the California Institute of Technology, as well as approval from the Human Connectome Project for Restricted Access through ConnectomeDB. Consent to participate. Written informed consent was obtained from all individual participants as part of the conduct of the Human Connectome Project.
Group:Tianqiao and Chrissy Chen Institute for Neuroscience
Funders:
Funding AgencyGrant Number
NIHP41EB015922
Chan Zuckerberg Initiative2020-225670
Silicon Valley Community FoundationUNSPECIFIED
NIH1U54MH091657
Washington UniversityUNSPECIFIED
Subject Keywords:frontoinsular cortex, anterior agranular insular cortex, diffusion MRI, decision-making, social behavior
DOI:10.1093/cercor/bhac237
Record Number:CaltechAUTHORS:20220802-744668000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220802-744668000
Official Citation:Ryan P Cabeen, Arthur W Toga, John M Allman, Mapping frontoinsular cortex from diffusion microstructure, Cerebral Cortex, 2022;, bhac237, https://doi.org/10.1093/cercor/bhac237
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:116036
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:02 Aug 2022 17:35
Last Modified:02 Aug 2022 17:35

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