Effects of Tasks on Functional Connectivity Derived from Inter-Individual Correlations of ReHo
Poster No:
1167
Submission Type:
Abstract Submission
Authors:
Xin Di1, Pratik Jain1, Bharat Biswal1
Institutions:
1New Jersey Institute of Technology, Newark, NJ
First Author:
Co-Author(s):
Introduction:
Research on brain functional connectivity frequently examines intra-individual, moment-to-moment correlations of functional activity, primarily using functional MRI (fMRI). Inter-individual correlations have also been analyzed using data from both fMRI (Taylor et al., 2012) and positron emission tomography (PET)(Di et al., 2017; Di & Biswal, and Alzheimer's Disease Neu, 2012). Many studies utilize a "resting-state" condition, where participants are scanned without being assigned specific tasks. This approach raises questions about how task conditions might influence inter-individual correlation estimates. Specifically, it remains uncertain how various tasks affect functional covariance measures of connectivity. Drawing on earlier findings that within-individual functional connectivity patterns are largely consistent across tasks (Cole et al., 2014), we hypothesized that functional covariance connectivity would similarly exhibit stability across different task conditions.
Methods:
We analyzed fMRI data from the 100 unrelated participants in the Human Connectome Project (HCP) (Barch et al., 2013), focusing on resting-state and six task conditions. The tasks included emotion, gambling, language, motor, relational, social, and working memory. Regional homogeneity (ReHo), a regional functional measure (Taylor et al., 2012; Zang et al., 2004) , was calculated for each task and resting-state run. The analysis utilized 114 regions of interest (ROIs) spanning cortical areas (Schaefer et al., 2018) and subcortical regions (Tzourio-Mazoyer et al., 2002).
For each task/rest condition, average ReHo values were extracted for each ROI, and inter-individual correlation coefficients were computed across the 114 ROIs, yielding a 114 x 114 covariance matrix. To evaluate the similarity of inter-individual correlation matrices across conditions, we calculated correlation coefficients between ROI pairs under different task/rest conditions. Additionally, repeated-measures analysis of variance (ANOVA) was performed to assess differences in correlations among the task and resting-state conditions.
For each task/rest condition, average ReHo values were extracted for each ROI, and inter-individual correlation coefficients were computed across the 114 ROIs, yielding a 114 x 114 covariance matrix. To evaluate the similarity of inter-individual correlation matrices across conditions, we calculated correlation coefficients between ROI pairs under different task/rest conditions. Additionally, repeated-measures analysis of variance (ANOVA) was performed to assess differences in correlations among the task and resting-state conditions.
Results:
The inter-individual correlation matrices for different task and resting-state conditions are presented in Figure 1. Whole-brain inter-individual correlation patterns were strikingly similar across tasks, with correlations exceeding 0.78. However, the resting-state condition exhibited the lowest correlations with the task conditions.
A repeated-measures ANOVA identified ROI pairs with significantly different connectivity across task conditions. The task-modulated connections were primarily concentrated within the visual network, somatomotor network, control network, and interactions among these networks. Comparisons between task conditions and the resting-state condition revealed consistent patterns across tasks (Figure 2). Specifically, connectivity within visual and somatomotor regions was generally lower during tasks, while connectivity between visual/somatomotor regions and control or subcortical regions was higher in task conditions compared with the resting-state condition.
A repeated-measures ANOVA identified ROI pairs with significantly different connectivity across task conditions. The task-modulated connections were primarily concentrated within the visual network, somatomotor network, control network, and interactions among these networks. Comparisons between task conditions and the resting-state condition revealed consistent patterns across tasks (Figure 2). Specifically, connectivity within visual and somatomotor regions was generally lower during tasks, while connectivity between visual/somatomotor regions and control or subcortical regions was higher in task conditions compared with the resting-state condition.
·Figure 1
·Figure 2
Conclusions:
The connectivity matrices derived from inter-individual correlations of ReHo were highly consistent across different task conditions, aligning with previous findings on within-individual functional connectivity (Cole et al., 2014). However, subtle but significant differences in functional connectivity were observed, likely reflecting the involvement of specific brain regions associated with the tasks studied. Future research should account for task design when investigating inter-individual connectivity within specific brain systems.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 1
fMRI Connectivity and Network Modeling 2
Keywords:
FUNCTIONAL MRI
NORMAL HUMAN
Other - inter-individual correlation
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
Cole, M. W., Bassett, D. S., Power, J. D., Braver, T. S., & Petersen, S. E. (2014). Intrinsic and task-evoked network architectures of the human brain. Neuron, 83, 238–251. https://doi.org/10.1016/j.neuron.2014.05.014
Di, X., & Biswal, and Alzheimer’s Disease Neu, B. B. (2012). Metabolic Brain Covariant Networks as Revealed by FDG-PET with Reference to Resting-State fMRI Networks. Brain Connectivity, 2(5), 275–283. https://doi.org/10.1089/brain.2012.0086
Di, X., Gohel, S., Thielcke, A., Wehrl, H. F., Biswal, B. B., & Alzheimer’s Disease Neuroimaging Initiative. (2017). Do all roads lead to Rome? A comparison of brain networks derived from inter-subject volumetric and metabolic covariance and moment-to-moment hemodynamic correlations in old individuals. Brain Structure & Function, 222(8), 3833–3845. https://doi.org/10.1007/s00429-017-1438-7
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