Longitudinal increases in structural connectome segregation and functional connectome integration are associated with better recovery after mild TBI

Abstract

Traumatic brain injury damages white matter pathways that connect brain regions, disrupting transmission of electrochemical signals and causing cognitive and emotional dysfunction. Connectome‐level mechanisms for how the brain compensates for injury have not been fully characterized. Here, we collected serial MRI‐based structural and functional connectome metrics and neuropsychological scores in 26 mild traumatic brain injury subjects (29.4 ± 8.0 years, 20 males) at 1 and 6 months postinjury. We quantified the relationship between functional and structural connectomes using network diffusion (ND) model propagation time, a measure that can be interpreted as how much of the structural connectome is being utilized for the spread of functional activation, as captured via the functional connectome. Overall cognition showed significant improvement from 1 to 6 months (t25 = −2.15, p = .04). None of the structural or functional global connectome metrics was significantly different between 1 and 6 months, or when compared to 34 age‐ and gender‐matched controls (28.6 ± 8.8 years, 25 males). We predicted longitudinal changes in overall cognition from changes in global connectome measures using a partial least squares regression model (cross‐validated R2 = .27). We observe that increased ND model propagation time, increased structural connectome segregation, and increased functional connectome integration were related to better cognitive recovery. We interpret these findings as suggesting two connectome‐based postinjury recovery mechanisms: one of neuroplasticity that increases functional connectome integration and one of remote white matter degeneration that increases structural connectome segregation. We hypothesize that our inherently multimodal measure of ND model propagation time captures the interplay between these two mechanisms.

Network communication models improve the behavioral and functional predictive utility of the human structural connectome

“…Importantly, brain structure-function relationships encompass a rich and diverse field of research, with several alternative classes of higher order models showing promise in modeling function from structure. Examples include biophysical models of neural activity (Breakspear, 2017;Deco, Kringelbach, Jirsa, & Ritter, 2017;Sokolov et al, 2018), statistical methods (Messé, Rudrauf, Benali, & Marrelec, 2014;, and other approaches centered around network communication that we did not explore in the present work (Kuceyeski, Jamison, Owen, Raj, & Mukherjee, 2019;Mišić et al, 2015;Osmanloglu et al, 2019;Raj, Kuceyeski, & Weiner, 2012;Vázquez-Rodríguez, Liu, Hagmann, & Mišić, 2020). Likewise, relating neuroimaging data to behavior is a central goal of neuroscience (Medaglia, Lynall, & Bassett, 2015;.…”

Network communication models improve the behavioral and functional predictive utility of the human structural connectome

“…Importantly, brain structure-function relationships encompass a rich and diverse field of research, with several alternative classes of higher-order models showing promise in modeling function from structure. Examples include biophysical models of neural activity [38][39][40], statistical methods [41,42], and other approaches centered around network communication that we did not explore in the present work [26,[43][44][45]. Likewise, relating neuroimaging data to behavior is a central goal of neuroscience [46,47].…”

Functional connectome reorganization relates to post-stroke motor recovery and structural disruption

“…Interestingly, we showed correlations between amount of functional remapping and amount of motor improvement but only in the period of time in which most post-stroke recovery occurs (within 3 months after stroke) (Lee et al, 2015). However, resting-state functional connectivity, though related to task-based responses, may not be fully representative of brain activation patterns underlying specific behaviors, and has shown to be constrained by the structural connectome (Kuceyeski et al, 2019;Honey et al, 2009). Thus, it is possible that the remapping observed is not a functional remapping per se (in the sense of remapping a region's role in a specific task), but a shift in balance of a brain area's functional connectivity profile at rest, which could reflect task-based functional compensations, changes in network topology, and/or underlying structural remodelling.…”