Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothing

Fuente: arXiv
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Main Authors: Chung, Moo K., Dalton, Kim M., Kelley, Daniel J., Davidson, Richard J.
Format: Preprint
Published: 2025
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author Chung, Moo K.
Dalton, Kim M.
Kelley, Daniel J.
Davidson, Richard J.
author_facet Chung, Moo K.
Dalton, Kim M.
Kelley, Daniel J.
Davidson, Richard J.
contents This paper presents a streamlined image analysis framework for correlating behavioral measures to anatomical measures on the cortex and detecting the regions of abnormal brain-behavior correlates. We correlated a facial emotion discrimination task score and its response time to cortical thickness measurements in a group of high functioning autistic subjects. Many previous correlation studies in brain imaging neglect to account for unwanted age effect and other variables and the subsequent statistical parametric maps may report spurious results. We demonstrate that the partial correlation mapping strategy proposed here can remove the effect of age and global cortical area difference effectively while localizing the regions of high correlation difference. The advantage of the proposed correlation mapping strategy over the general linear model framework is that we can directly visualize more intuitive correlation measures across the cortex in each group.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00473
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothing
Chung, Moo K.
Dalton, Kim M.
Kelley, Daniel J.
Davidson, Richard J.
Neurons and Cognition
This paper presents a streamlined image analysis framework for correlating behavioral measures to anatomical measures on the cortex and detecting the regions of abnormal brain-behavior correlates. We correlated a facial emotion discrimination task score and its response time to cortical thickness measurements in a group of high functioning autistic subjects. Many previous correlation studies in brain imaging neglect to account for unwanted age effect and other variables and the subsequent statistical parametric maps may report spurious results. We demonstrate that the partial correlation mapping strategy proposed here can remove the effect of age and global cortical area difference effectively while localizing the regions of high correlation difference. The advantage of the proposed correlation mapping strategy over the general linear model framework is that we can directly visualize more intuitive correlation measures across the cortex in each group.
title Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothing
topic Neurons and Cognition
url https://arxiv.org/abs/2507.00473