Dynamic Functional Network Analysis in Mild Traumatic Brain Injury

Abstract

Mild traumatic brain injury (mTBI) is one of the most common neurological disorders for which a subset of patients develops persistent postconcussive symptoms. Previous studies discovered abnormalities and disruptions in the brain functional networks of mTBI patients principally using static functional connectivity measures which assume that neural communication across the brain is static during resting state conditions. In this study, we examine the differences in dynamic neural communication between mTBI and control participants through the application of a combination of dynamic functional analysis and graph theoretic algorithms. Resting state functional magnetic resonance imaging data was obtained on 47 mTBI patients at the acute stage of injury and 30 demographically matched healthy control participants. Results show unique alterations in both the static and dynamic functional connectivity at the acute stage in mTBI patients who suffer persistent symptoms (‡6 months after injury). In addition, mTBI patients with postconcussion syndrome demonstrated a unique allocation of time in various brain states compared to both control participants and mTBI patients with favorable outcomes. These findings suggest that global damage to the overall communication across the brain in the acute stage may contribute to chronic mTBI symptoms. Dynamic functional analysis is a powerful tool that provides insights into the brain states and the innovative analysis methodology utilized may hold the potential to delineate patients predisposed to poor outcomes upon early presentation following injury.

Functional outcome is tied to dynamic brain states after mild to moderate traumatic brain injury

“…Previous studies have reported increased connectivity (Hillary et al, ; Kaushal et al, ; Mayer et al, ), and less efficient organization of brain networks in patients with TBI relative to healthy subjects (Pandit et al, ). Our findings are also supported by a recent study showing that patients with persistent symptoms at 6 months after mTBI spend less time in efficient brain states (Hou et al, ). Although patients with incomplete recovery in the present study had significantly more symptoms than those with complete recovery, it is important to note that having persistent symptoms is not equal to incomplete recovery as measured with the Glasgow Outcome Scale Extended.…”

“…In addition to static functional connectivity analyses, the current study examined specific time‐related patterns of functional connectivity, defined as dynamic brain states, in patients with mainly mild TBI. Previous studies have already shown the potential of dynamic connectivity analyses in the investigation of posttraumatic symptoms, and classification of patients with mild TBI (Hou et al, ; van der Horn, Liemburg, et al, ; Vergara et al, ). In the present study, k‐means clustering was used to partition the time‐varying functional connections into patterns of connectivity, defined as dynamic brain states.…”

“…In the current study, patients were first scanned at approximately 4–5 weeks postinjury, which impedes drawing inferences about connectivity changes earlier after injury. However, there are various studies that have shown changes in static and dynamic functional connectivity within the first weeks after injury (Hou et al, ; Kaushal et al, ; Mayer et al, ). Our results showed that patients with complete recovery had few disruptions of connectivity as compared to patients incomplete recovery.…”

“…This approach also obligates researchers to apply multiple comparison corrections, which may give rise to type II errors, especially in such a heterogeneous condition as mTBI (Mayer et al, ). Additionally, up until now, most studies have focused on static functional connectivity (connectivity between regions) or static functional network connectivity (FNC, connectivity between temporally coherent networks) measures, while there is preliminary evidence showing that time‐related patterns of FNC (i.e., dynamic FNC) may provide more detailed information about injury effects and recovery after TBI (Hou et al, ; van der Horn et al, ; Vergara, Mayer, Kiehl, & Calhoun, ). The brain's neural landscape is a dynamic system, which changes its configuration in response to ongoing cognitive and emotional demands (Du, Fu, & Calhoun, ).…”

Tools of the trade: Estimating time-varying connectivity patterns from fMRI data

“…Alterations in dFC states were also observed in mild traumatic brain injury (mTBI) patients (Vergara et al, 2018;Hou et al, 2019;van der Horn et al, 2019) and had better discriminatory power than sFC (Vergara et al, 2018). In relapsing-remitting multiple sclerosis (RRMS), dorsal and ventral attention networks displayed lower within-network dFC and higher between-network dFC, and the dFC alterations were linked to white matter lesion damage (Huang et al, 2019).…”