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The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those affected with non-severe TBI. Traumatic brain injury (TBI) is a wide-spectrum disease that has heterogeneous effects on its victims and impacts everyday functioning. The functional disruption of the default mode network (DMN) after TBI has been established, but its link to causal effective connectivity remains to be explored. This study investigated the differences in the DMN between healthy participants and mild and moderate TBI, in terms of functional and effective connectivity using resting-state functional magnetic resonance imaging (fMRI). Nineteen non-severe TBI (mean age 30.84 ± 14.56) and twenty-two healthy (HC; mean age 27.23 ± 6.32) participants were recruited for this study. Resting-state fMRI data were obtained at the subacute phase (mean days 40.63 ± 10.14) and analyzed for functional activation and connectivity, independent component analysis, and effective connectivity within and between the DMN. Neuropsychological tests were also performed to assess the cognitive and memory domains. Compared to the HC, the TBI group exhibited lower activation in the thalamus, as well as significant functional hypoconnectivity between DMN and LN. Within the DMN nodes, decreased activations were detected in the left inferior parietal lobule, precuneus, and right superior frontal gyrus. Altered effective connectivities were also observed in the TBI group and were linked to the diminished activation in the left parietal region and precuneus. With regard to intra-DMN connectivity within the TBI group, positive correlations were found in verbal and visual memory with the language network, while a negative correlation was found in the cognitive domain with the visual network. Our results suggested that aberrant activities and functional connectivities within the DMN and with other RSNs were accompanied by the altered effective connectivities in the TBI group. These alterations were associated with impaired cognitive and memory domains in the TBI group, in particular within the language domain. These findings may provide insight for future TBI observational and interventional research.

BackgroundImpairment in cognitive function is a recognized outcome of traumatic brain injury (TBI). However, the degree of impairment has variable relationship with TBI severity and time post injury. The underlying pathology is often due to diffuse axonal injury that has been found even in mild TBI. In this study, we examine the state of white matter putative connectivity in patients with non-severe TBI in the subacute phase, i.e., within 10 weeks of injury and determine its relationship with neuropsychological scores.MethodsWe conducted a case-control prospective study involving 11 male adult patients with non-severe TBI and an age-matched control group of 11 adult male volunteers. Diffusion MRI scanning and neuropsychological tests were administered within 10 weeks post injury. The difference in fractional anisotropy (FA) values between the patient and control groups was examined using tract-based spatial statistics. The FA values that were significantly different between patients and controls were then correlated with neuropsychological tests in the patient group.ResultsSeveral clusters with peak voxels of significant FA reductions (p < 0.05) in the white matter skeleton were seen in patients compared to the control group. These clusters were located in the superior fronto-occipital fasciculus, superior longitudinal fasciculus, uncinate fasciculus, and cingulum, as well as white matter fibers in the area of genu of corpus callosum, anterior corona radiata, superior corona radiata, anterior thalamic radiation and part of inferior frontal gyrus. Mean global FA magnitude correlated significantly with MAVLT immediate recall scores while matrix reasoning scores correlated positively with FA values in the area of right superior fronto-occipital fasciculus and left anterior corona radiata.ConclusionThe non-severe TBI patients had abnormally reduced FA values in multiple regions compared to controls that correlated with several measures of executive function during the sub-acute phase of TBI.

The effective connectivity can reveal the causal relationships between nodes of the Default Mode Network (DMN), which may reveal any impairment to the network following moderate traumatic brain injury (MTBI). Eight sub-acute MTBI patients and eight controls were recruited for this study. The results indicated that effective connectivity (EC) within MTBI group was higher in number and strength compared to the controls. Moreover, the network hubs within DMN are associated with increased connection strength in MTBI group. The ECs in MTBI are also largely influenced by top-down backward connections. In conclusion, the network reorganization within the DMN reflects the effect of MTBI and may subsequently impair other brain functions. This knowledge can be used to correctly identify the patient for appropriate trauma management.

Working memory (WM) encompasses crucial cognitive processes or abilities to retain and manipulate temporary information for immediate execution of complex cognitive tasks in daily functioning such as reasoning and decision‐making. The WM of individuals sustaining traumatic brain injury (TBI) was commonly compromised, especially in the domain of WM. The current study investigated the brain responses of WM in a group of participants with mild–moderate TBI compared to their healthy counterparts employing functional magnetic resonance imaging. All consented participants (healthy: n = 26 and TBI: n = 15) performed two variations of the n‐back WM task with four load conditions (0‐, 1‐, 2‐, and 3‐back). The respective within‐group effects showed a right hemisphere‐dominance activation and slower reaction in performance for the TBI group. Random‐effects analysis revealed activation difference between the two groups in the right occipital lobe in the guided n‐back with cues, and in the bilateral occipital lobe, superior parietal region, and cingulate cortices in the n‐back without cues. The left middle frontal gyrus was implicated in the load‐dependent processing of WM in both groups. Further group analysis identified that the notable activation changes in the frontal gyri and anterior cingulate cortex are according to low and high loads. Though relatively smaller in scale, this study was eminent as it clarified the neural alterations in WM in the mild–moderate TBI group compared to healthy controls. It confirmed the robustness of the phenomenon in TBI with the reproducibility of the results in a heterogeneous non‐Western sample.

This study investigated the functional connectivity of the neural networks when vibrotactile stimulation is applied to the fingertips of young adults. Twenty healthy, right-handed subjects were stimulated with vibrotactile stimulation whilst being scanned with a 3.0 T magnetic resonance imaging scanner. The subjects were stimulated at 30 Hz – 240 Hz using a piezoelectric vibrator attached to the subjects' bilateral index fingers. The scanned data were processed with independent component analysis (ICA), while the temporal configuration and spatial localisation of the component were investigated. The activation locations were tabulated and compared with regions of somatosensory in the brain. Using ICA, somatosensory regions and their neighbouring areas identified one or more of these components mapped to the common significant regions in the medial frontal gyrus (MFG), paracentral lobule (PaCL), precentral gyrus (PrG), postcentral gyrus (PoG), inferior parietal lobule (IPL), and cingulate gyrus (CgG). Using Neuromark as a reference, six significant networks with the highest correlation values, r>0.5, were identified: the visual network (VIN), sensorimotor network (SMN), cognitive-control network (CCN), subcortical network (SCN), default-mode network (DMN), and auditory network (AUN). It showed that VIN and SMN were the most activated during the vibrotactile stimulation. A comparison of the network volumes and peak activations during the conditions demonstrated changes in volume and corresponding peak activation during vibrotactile stimulation. This study contributes to a better understanding of the underlying mechanisms of the somatosensory areas. Other than that, not only this study highlighted the underlying effect of vibrotactile stimulation towards the functional brain connectivity at network levels, but it also highlighted the impact of frequencies in somatosensory studies. In the future, we suggest that exploring the change in the range of frequencies and examining its differences will allow us to comprehend aspects of somatosensory networks and their connectivity.

This paper extends our frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. i) Create lifespan Hermitian Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control developmental equations for the mean and standard deviation of qEEG traditional and Hermitian Riemannian descriptive parameters were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. ii) We also show that the multinational harmonized Hermitian Riemannian norms produce z-scores with increased diagnostic accuracy to predict brain dysfunction at school-age produced by malnutrition only in the first year of life. We provide data and software for constructing norms. iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.