Post mTBI fatigue is associated with abnormal brain functional connectivity

Love Engström Nordin, Marika Christina Möller, Per Julin, Aniko Bartfai, Farouk Hashim, Tie-Qiang Li, Love Engström Nordin, Marika Christina Möller, Per Julin, Aniko Bartfai, Farouk Hashim, Tie-Qiang Li

Abstract

This study set out to investigate the behavioral correlates of changes in resting-state functional connectivity before and after performing a 20 minute continuous psychomotor vigilance task (PVT) for patients with chronic post-concussion syndrome. Ten patients in chronic phase after mild traumatic brain injury (mTBI) with persisting symptoms of fatigue and ten matched healthy controls participated in the study. We assessed the participants' fatigue levels and conducted resting-state fMRI before and after a sustained PVT. We evaluated the changes in brain functional connectivity indices in relation to the subject's fatigue behavior using a quantitative data-driven analysis approach. We found that the PVT invoked significant mental fatigue and specific functional connectivity changes in mTBI patients. Furthermore, we found a significant linear correlation between self-reported fatigue and functional connectivity in the thalamus and middle frontal cortex. Our findings indicate that resting-state fMRI measurements may be a useful indicator of performance potential and a marker of fatigue level in the neural attentional system.

Figures

Figure 1. Boxplots of the ROI averages…
Figure 1. Boxplots of the ROI averages of CCI and CSI for the brain regions with significant effects (p ≤ 0.05) of the 2 fixed factors (the PVT and subject group) and their interactions as assessed with 3-way ANOVA method.
(a) The effect of the PVT on CCI; (b) The effect of the PVT on CSI; (c) CCI difference between mTBI patients and healthy controls; (d) CSI difference between mTBI patients and healthy controls; (e) The interaction effect of CCI showing that mTBI patients and healthy controls are affected differently by the PVT performance; (f) The interaction effect of CSI showing that mTBI patients and healthy controls are affected differently by the PVT. (g) Average CCI for ROIs with significant correlation with VAS-f; (h) Average CSI for ROIs with significant correlation with VAS-f. The central marks of the boxplots are the median, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points considered to be not outliers, and the outliers are plotted individually as red crosses.
Figure 2. Summary of F-score results from…
Figure 2. Summary of F-score results from the 3-way ANOVA analysis of CCI and CSI data to depict the brain regions of statistically significant differences (p ≤ 0.05) in functional connectivity associated with the 2 fixed factors (the PVT and subject group) and their interaction.
(a) The brain regions with statistical significant change in CCI before and after PVT for all participants; (b) The brain regions with statistically significant change in CSI before and after PVT for all participants; (c) The brain regions with statistically significant CCI difference between mTBI patients and healthy controls; (d) The brain regions with statistically significant CSI difference between mTBI patients and healthy controls; (e) The brain regions with statistically significant interaction effect of two main factors on CCI. That is the brain areas where CCI of the mTBI patients and healthy controls are affected differently by the PVT performance; (f) The brain regions with statistically significant interaction effect of two main factors on CSI. That is the brain areas where CSI of the mTBI patients and controls are affected differently by the PVT performance.
Figure 3. Results obtained from the linear…
Figure 3. Results obtained from the linear regression analysis of functional connectivity as a function of the self-reported fatigue.
(a) Brain regions with significant (p ≤ 0.05) correlation between CCI and VAS-f. (b) Brain regions with significant (p ≤ 0.05) correlation between CSI and VAS-f.
Figure 4. Scattered plot of the ROI…
Figure 4. Scattered plot of the ROI averages of functional connectivity for the brain regions that have significant (p 
(a) ROI averages of CCI as a function of VAS-f for all participants. (b) ROI averages of CSI as a function of VAS-f for all participants. The error bars denote the standard deviation of the different voxels within the detected ROI. The filled and blank symbols represent the measurements before and after the PVTs, respectively.
Figure 5. Scattered plot of the ROI…
Figure 5. Scattered plot of the ROI averages of functional connectivity for the brain regions that have significant (FWER, p ≤ 0.05) linear correlation with self-reported fatigue.
(a) ROI averages of CSI as a function of VAS-f for the control subjects after PVT (control_t2). (b) ROI averages of CSI as a function of VAS-f for mTBI participants after PVT (mTBI_t2). The error bars denote the standard deviation of the different voxels within the detected ROI. The black and red lines represent the linear regression estimates for the controls and mTBI patients, respectively.
Figure 6. The effect of CC threshold…
Figure 6. The effect of CC threshold on results from the 3-way ANOVA modeling of the derived CCI and CSI maps is illustrated.
(a) The detected brain volume with statistically significant subject group difference in CCI (FWER, p ≤ 0.05) as function of CC threshold value; (b) The detected brain volume with statistically significant subject group difference in CSI (FWER, p ≤ 0.05) as function of CC threshold value; (c) The ROI average F-score for the detected brain volume with statistically significant subject group difference in CCI (FWER, p ≤ 0.05) as function of CC threshold value; (d) The ROI average F-score for the detected brain volume with statistically significant subject group difference in CSI (FWER, p ≤ 0.05) as function of CC threshold value; The curves in (a,b) denote a 2nd-order polynomial non-linear curve fittings to the detected brain volumes as function of CC threshold values. The error bars in (c,d) denote the standard deviation of the different voxels within the detected ROI.

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