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Session: MRI Quantitative Imaging [Return to Session]

Comparison of Effective Connectivity and Functional Connectivity for Brain Health in Middle-Aged Adults

K Chuang1,2*, S Ramakrishnapillai2, K Madden2, J St Amant2, K Gwizdala 2, R Dhullipudi2, L Bazzano3, O Carmichael2, (1) Louisiana State University, Baton Rouge, LA, (2) Pennington Biomedical Research Center, Baton Rouge, LA, (3) Tulane School of Public Health and Tropical Medicine, New Orleans, LA

Presentations

MO-C930-IePD-F9-2 (Monday, 7/11/2022) 9:30 AM - 10:00 AM [Eastern Time (GMT-4)]

Exhibit Hall | Forum 9

Purpose: Effective connectivity, the causal influence that brain functional activity in a source brain location exerts over functional activity in a target brain location, has the potential to provide richer information about brain networks than functional connectivity, which only quantifies activity synchrony between locations. However, head-to-head comparisons between effective and functional connectivity from functional MRI data are rare, especially among diverse cognitively healthy middle aged and older adults.

Methods: One hundred participants aged 54.2±4.3 years performed a Stroop task during functional MRI scanning. Effective connectivity and functional connectivity among 24 regions of interest previously identified as activated by this task were calculated using a deep stacking networks method and Pearson correlation, respectively. Graph metrics were then calculated from directed graphs for effective connectivity and undirected graphs for functional connectivity. Linear regression models related graph metrics to demographic, cardiometabolic, and cognitive measures averaged over visits occurring at ages less than 20, 21-40, and over 40 years old.

Results: Systolic blood pressure (SBP) and diastolic blood pressure (DBP) over age 40 was associated with effective connectivity based graph metrics (degree, modularity and characteristic path length or CPL, maximum p-values=0.038). Associations between SBP or DBP and functional connectivity based graph metrics were not significant. BMIs at ages before 20 and 21-40 were associated with effective connectivity based metrics (strength, modularity, and flow coefficient, maximum p-value=0.049), and functional connectivity based modularity (p-value=0.012). Normal-appearing white matter volume and white matter hyperintensity volume over 40 were associated with an effective connectivity based strength (p-value=0.021), and functional connectivity based metrics (degree, modularity, CPL, maximum p-value=0.033).

Conclusion: In a diverse, cognitively healthy, middle-aged community sample, graph metrics derived from effective connectivity based directed graphs tracked more closely with recognized indicators of brain health than standard graph metrics derived from functional connectivity based undirected graphs.

Funding Support, Disclosures, and Conflict of Interest: Funding for this work was provided by NIH grants R01AG041200 and R01AG062309 as well as the Pennington Biomedical Research Foundation.

Keywords

MRI, Functional Imaging, Brain

Taxonomy

IM- MRI : Functional MRI (fMRI)

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