Correspondence between structure and function in the human brain at rest

Segall, Judith M.; Allen, Elena A.; Jung, Rex E.; Erhardt, Erik B.; Arja, Sunil K.; Kiehl, Kent; Calhoun, Vince D.

doi:10.3389/fninf.2012.00010

Title: Correspondence between structure and function in the human brain at rest

Journal Article · Sun Jan 01 00:00:00 EST 2012 · Frontiers in Neuroinformatics

DOI:https://doi.org/10.3389/fninf.2012.00010· OSTI ID:1628199

Segall, Judith M. ^[1]; Allen, Elena A. ^[2]; Jung, Rex E. ^[3]; Erhardt, Erik B. ^[2]; Arja, Sunil K. ^[2]; Kiehl, Kent ^[2]; Calhoun, Vince D. ^[4]

Mind Research Network, Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Family and Community Medicine
Mind Research Network, Albuquerque, NM (United States)
Mind Research Network, Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Neurosurgery
Mind Research Network, Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering

To further understanding of basic and complex cognitive functions, previous connectome research has identified functional and structural connections of the human brain. Functional connectivity is often measured by using resting-state functional magnetic resonance imaging (rs-fMRI) and is generally interpreted as an indirect measure of neuronal activity. Gray matter (GM) primarily consists of neuronal and glia cell bodies; therefore, it is surprising that the majority of connectome research has excluded GM measures. Therefore, we propose that by exploring where GM corresponds to function would aid in the understanding of both structural and functional connectivity and in turn the human connectome. A cohort of 603 healthy participants underwent structural and functional scanning on the same 3 T scanner at the Mind Research Network. To investigate the spatial correspondence between structure and function, spatial independent component analysis (ICA) was applied separately to both GM density (GMD) maps and to rs-fMRI data. ICA of GM delineates structural components based on the covariation of GMD regions among subjects. For the rs-fMRI data, ICA identified spatial patterns with common temporal features. These decomposed structural and functional components were then compared by spatial correlation. Basal ganglia components exhibited the highest structural to resting-state functional spatial correlation (r = 0.59). Cortical components generally show correspondence between a single structural component and several resting-state functional components. We also studied relationships between the weights of different structural components and identified the precuneus as a hub in GMD structural network correlations. In addition, we analyzed relationships between component weights, age, and gender; concluding that age has a significant effect on structural components.

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Research Organization:: Mind Research Network, Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: FG02-08ER64581

OSTI ID:: 1628199

Journal Information:: Frontiers in Neuroinformatics, Vol. 6; ISSN 1662-5196

Publisher:: FrontiersCopyright Statement

Country of Publication:: United States

Language:: English

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Prediction of Mild Cognitive Impairment Conversion Using a Combination of Independent Component Analysis and the Cox Model Liu, Ke; Chen, Kewei; Yao, Li Frontiers in Human Neuroscience, Vol. 11 https://doi.org/10.3389/fnhum.2017.00033	journal	February 2017
Mapping the Connectome: Multi-Level Analysis of Brain Connectivity Leergaard, Trygve B.; Hilgetag, Claus C.; Sporns, Olaf Frontiers in Neuroinformatics, Vol. 6 https://doi.org/10.3389/fninf.2012.00014	journal	January 2012
A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets Panta, Sandeep R.; Wang, Runtang; Fries, Jill Frontiers in Neuroinformatics, Vol. 10 https://doi.org/10.3389/fninf.2016.00009	journal	March 2016
Schizophrenia Shows Disrupted Links between Brain Volume and Dynamic Functional Connectivity Abrol, Anees; Rashid, Barnaly; Rachakonda, Srinivas Frontiers in Neuroscience, Vol. 11 https://doi.org/10.3389/fnins.2017.00624	journal	November 2017
Quantity yields quality when it comes to creativity: a brain and behavioral test of the equal-odds rule Jung, Rex E.; Wertz, Christopher J.; Meadows, Christine A. Frontiers in Psychology, Vol. 6 https://doi.org/10.3389/fpsyg.2015.00864	journal	June 2015
Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia Gupta, Cota Navin; Castro, Eduardo; Rachkonda, Srinivas Frontiers in Psychiatry, Vol. 8 https://doi.org/10.3389/fpsyt.2017.00179	journal	September 2017

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