Low-frequency connectivity is associated with mild traumatic brain injury

Abstract

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

Keywords: Anxiety; Attention; Depression; Functional connectivity; Magnetoencephalography (MEG); Mild traumatic brain injury (mTBI); Neural oscillations; Resting-state.

Fig. 1

Analysis pipeline for resting-state functional connectivity. We employed an atlas-guided beamforming approach using all 90 cortical and subcortical regions in the AAL atlas to define seed regions. ‘Virtual-sensor’ time-series were reconstructed and filtered into canonical frequency bands, and a Hilbert transform is applied to derive estimates of instantaneous amplitude and phase. Each pairwise combination of time-series amplitude envelopes was then cross-correlated to define the degree of connectivity between seeds (‘amplitude envelope intrinsic coupling’). Adjacency matrices for each group were then compiled and submitted to a network based statistic analysis, and significant network differences are visualised using the BrainNet viewer toolbox.

Fig. 2

Mean and SD scores for the cognitive-behavioural assessments for the mTBI (green) and control (blue) groups. Conners: attention deficit and hyperactivity disorder; GAD7: Generalised Anxiety Disorder 7-item scale; PHQ9: Personalised Health Questionnaire 9-scale item for depression; severity: severity of concussion symptomology; symptoms: number of symptoms; WASI: Wechsler's Abbreviated Scale of Intelligence. *p < 0.05.

Fig. 3

Spectral power content for the mTBI and control groups. Top: mean, whole-brain spectral power content with ±1 standard error bars, showing a minor increase in 4–10 Hz power (arbitrary units) in the mTBI. Bottom: mean spectral power content for the low-frequency 3–15 Hz range, divided by hemisphere and lobe for the mTBI versus control group. Minor alterations in spectral power were found in left and right temporal, subcortical, and parietal regions in the mTBI group.

Fig. 4

Functional connectivity maps of frequency-specific increases in amplitude envelope correlations in mTBI compared to controls, for the delta (1–4 Hz; top), theta (4–7 Hz; middle) and alpha (8–14 Hz; bottom) frequency bands. All images derived from the NBS-Extent method (p < 0.05, corrected). Additionally, adjacency matrices of p values for contrasts of intra- and inter-hemispheric lobe-by-lobe connectivity measures for mTBI versus control are shown to the right in each panel; grey-to- white indicates significant interactions for mTBI > Controls (Bonferroni-corrected at p < 0.05), black indicates no significant difference (p > 0.05, corrected).

Fig. 5

Correlations of amplitude envelope coupling (edge weights) and node network strength versus Conners ADHD attentional outcome measures in mTBI for the delta, theta and alpha bands. Left panels show correlations for the Conners ADHD and connectivity correlations, and right panels show the inattentive subscale correlations. Note the high degree of overlap between the correlational networks, suggesting inattention problems in the mTBI are driving the correlational networks shown in the Conners ADHD outcome measure. Node radius is scaled by correlation coefficient. Edge weights show correlation coefficients with uncorrected p < 0.01; grey edges correlation coefficients > 0.6, green edges correlation coefficients > 0.65.

Fig. 6

Correlations of amplitude envelope coupling (edge weights) and node network strength versus GAD7 (anxiety; left panels) and PHQ9 (depression; right panels) cognitive-behavioural outcome measures in the alpha band in the mTBI group. These correlational networks appear similar, and are comparable to the Conners ADHD network in the alpha band. Node radius is scaled by correlation coefficient. Edge weights show correlation coefficients with uncorrected p < 0.01; grey edges correlation coefficients > 0.6, green edges correlation coefficients > 0.65.