Mapping frontoinsular cortex from diffusion microstructure
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.
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.Attached Files
Published - bhac237.pdf
Supplemental Material - fic-map-supplement_bhac237.pdf
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Additional details
- PMCID
- PMC10016069
- Eprint ID
- 116036
- Resolver ID
- CaltechAUTHORS:20220802-744668000
- P41EB015922
- NIH
- 2020-225670
- Chan Zuckerberg Initiative
- Silicon Valley Community Foundation
- 1U54MH091657
- NIH
- Washington University
- Created
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2022-08-02Created from EPrint's datestamp field
- Updated
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2023-07-06Created from EPrint's last_modified field
- Caltech groups
- Tianqiao and Chrissy Chen Institute for Neuroscience, Division of Biology and Biological Engineering