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46 Resting State FC in the Default Mode Networks: A Prediction Model for Elevated Aggression from Connectivity Metrics and Neurocognitive Performance Across Multiple Stages of Recovery in mild TBI

Published online by Cambridge University Press:  21 December 2023

Deva Reign*
Affiliation:
University of Arizona, Tucson, Arizona, USA
Samantha Jankowski
Affiliation:
University of Arizona, Tucson, Arizona, USA
Natalie S. Dailey
Affiliation:
University of Arizona, Tucson, Arizona, USA
William D.S. Killgore
Affiliation:
University of Arizona, Tucson, Arizona, USA
*
Correspondence: Deva Reign, University of Arizona, dreign@arizona.edu
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Abstract

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Objective:

Mild traumatic brain injury (mTBI) remains one of the most prevalent brain injuries, affecting approximately one-in-sixty Americans. Previous studies have shown an association between white matter integrity and aggression at chronic stages (either 6-months or 12 months post-mTBI) however, the association between white matter axonal damage, neuropsychological outcomes, and elevated aggression in multiple stages since time-since-injury (TSI) is unclear. We hypothesized that functional connectivity between the default mode network (DMN), a key brain network involved in cognitive, self-reflective, and emotional processes, and other cortical regions would predict elevated aggression and emotional disturbances across multiples stages of recovery in mild TBI.

Participants and Methods:

Participants healthy controls (HC: n=35 total [15 male, 20 female], age M=24.40, SD=5.95; mTBI: n=121 total [43 male; 78 female], age M = 24.76, SD=7.48). Participants completed a cross-sectional study design at specific post-injury time points ranging from (2W, 1M,3M,6M,12M). Participants completed a comprehensive neuropsychological battery and a neuroimaging session, including resting state functional connectivity (FC). Here, we focus on the FC outcomes for the DMN. During the neuropsychological assessment, participants completed tests that measured learning and memory, speed of information processing, executive function, and attention. To predict neuropsychological performance from brain connectivity, we conducted a series of stepwise linear regression analyses with the 11 functional brain connections (extracted as Fisher’s z-transformed correlations between regions) as predictors and each of the 13 neurocognitive factor scores separately.

Results:

Consistent with our hypothesis, one predictor materialized as significant (R = .187, R2 = .035, F = 5.55, p = .020) for the Total Sample. Largely, positive connectivity between Right Inferior Frontal Gyrus and the PCC (seed) was associated with increased aggression in the Total Sample of all participants = .187, t = 2.36, p = .020). One predictor materialized as significant in Individuals the 2W group, (R = .719, R2 = .518, F = 8.58, p = .019). In general, greater negative (anticorrelated) connectivity between the Left Lateral Occipital Cortex = -.719, t = -2.93, p = .019) and the PCC (seed) and was associated with greater aggression at 2W, but no predictors emerged at 1M or 3M. Individuals in the 6M group showed one significant predictor (R = .675, R2 = .455, F = 16.71, p = .001). Specifically, greater positive connectivity between the Right Lateral Occipital Cortex (/? = .675, t = 4.09, p = .001) and PCC (seed) was associated with greater aggression at 6M. No associations were evident at 12M.

Conclusions:

Overall, these findings suggest functional connectivity between the posterior hub of the DMN and cortical regions within the occipital cortex was predictive of higher aggression in individuals with mTBI. However, the direction of this connectivity differed at 2W versus 6M, suggesting a complex process of recovery that may contribute differentially to aggression in patients with mTBI. As these regions are involved in self-consciousness and visual perception, this may point toward future avenues for aiding in functional recovery of emotional dysregulation in patients with persistent post-concussion syndrome.

Type
Poster Session 02: Acute & Acquired Brain Injury
Copyright
Copyright © INS. Published by Cambridge University Press, 2023