The Rich Get Richer: Brain Injury Elicits Hyperconnectivity in Core Subnetworks

<div><p>There remains much unknown about how large-scale neural networks accommodate neurological disruption, such as moderate and severe traumatic brain injury (TBI). A primary goal in this study was to examine the alterations in network topology occurring during the first year of recovery following TBI. To do so we examined 21 individuals with moderate and severe TBI at 3 and 6 months after resolution of posttraumatic amnesia and 15 age- and education-matched healthy adults using functional MRI and graph theoretical analyses. There were two central hypotheses in this study: 1) physical disruption results in increased functional connectivity, or hyperconnectivity, and 2) hyperconnectivity occurs in regions typically observed to be the most highly connected cortical hubs, or the “rich club”. The current findings generally support the hyperconnectivity hypothesis showing that during the first year of recovery after TBI, neural networks show increased connectivity, and this change is disproportionately represented in brain regions belonging to the brain's core subnetworks. The selective increases in connectivity observed here are consistent with the preferential attachment model underlying scale-free network development. This study is the largest of its kind and provides the unique opportunity to examine how neural systems adapt to significant neurological disruption during the first year after injury.</p></div

Data processing stream for fMRI pre-processing, ICA, and graph theory.

<p>Data processing stream for fMRI pre-processing, ICA, and graph theory.</p

Probability distribution for TBI and HC groups at separate time points.

<p>Degree distributions for healthy control and TBI samples. Node degree (k), calculated as the sum of the weights on edges incident to a given node, is plotted against the fraction of nodes having given degree P(k), for each group at each time point. Values binned at increments of 2. <b>Inset</b>: the frequency of component members appearing in the heavy tail of p(k), or the most highly connected nodes. A-insula-ACC = anterior insula-anterior cingulate cortex (anterior salience network); dDMN = posterior cingulate to medial frontal (dorsal default mode network); LECN = Left dorsolateral prefrontal cortex and parietal (executive control network; P-insula = posterior insula (Salience Network); Par-FEF: Intraparietal Sulcus/Frontal Eye Fields (Visuospatial Network); RECN = right dorsolateral prefrontal cortex and parietal (executive control network); vDMN = Retrosplenial Cortex/Medial Temporal Lobe (Ventral Default Mode Network); B.Ganglia = basal ganglia. <b><i>Note</i></b>: inset is collapsed to include all possible components assigned to each specific subnetwork and organized from highest to lowest node incidence in the TBI sample.</p

Illustrates the two of the most common nodes occurring for both samples at both time points for the right ECN network.

<p>Illustrates the two of the most common nodes occurring for both samples at both time points for the right ECN network.</p

General graph properties in TBI and HC groups.

<p>Global graph metrics. Significant between-group differences at Time 1(** p<0.05; *p<0.10). Note: <b>no</b> significant results survive corrections for multiple comparisons for an alpha of 0.05.</p

Illustrates two examples of functional components of the dorsal DMN in the “tail” of the degree distribution for the TBI sample.

<p>Note: DMN = default mode network, Med = Medial, PCC = posterior cingulate cortex.</p

Most highly connected nodes (hubs) for TBI and HCs at Time 1 and Time 2 (mean degree values).

<p>The most highly connected nodes determined by cutoff of 9.9 (2 standard deviations above the mean degree for HC data at Time 1). <b><i>Note</i></b>: values for components listed at Time 1, not listed for Time 2 (41 = 9.72; 51 = 8.8; 31 =  9.54; 49 = 8.96; 48 = 9.70; 50 = 8.91; 9 = 9.3; 42 = 9.31; 3 = 9.83) and for Time 2 but not Time 1 (52 = 9.83; 4 = 9.42; 39 = 8.79; 47 = 8.69; 16 = 8.69) were also at least 1 sd above the HC Time 1 mean, but below 2 sd cutoff. Components in <b>bold</b> are identical components between time points.</p

Demographic descriptors, injury information.

<p>GCS when available 15/22 cases; when not available, inclusion based upon positive CT finding. No between-group differences observed for age, education, gender, ethnicity, or Time between scans.</p

Illustrates two examples of functional components of the anterior insula (SN) in the “tail” of the degree distribution for the TBI sample.

<p>Note: SN = salience network.</p

Component separation based upon dynamic range and low to high frequency power ratio.

<p>Dynamic range and power ratio for 100 components during inclusive ICA (all subjects). Rejected components (red) were determined by inspection of low to high frequency ratio and spatial extent consistent with Allen et al., (2011). In the primary analysis, “equivocal” components were discarded and the time series for the 52 remaining components composed the final graph. Supplementary materials include an additional analysis that included “equivocal” components in order to determine their influence on the graph and the results are nearly identical (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104021#pone.0104021.s001" target="_blank">Table S1</a>).</p