The rich get richer: brain injury elicits hyperconnectivity in core subnetworks

Local functional connectivity abnormalities in mild cognitive impairment and Alzheimer's disease: A meta-analytic investigation using minimum Bayes factor activation likelihood estimation

Functional magnetic resonance imaging research employing regional homogeneity (ReHo) analysis has uncovered aberrant local brain connectivity in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) in comparison with healthy controls. However, the precise localization, extent, and possible overlap of these aberrations are still not fully understood. To bridge this gap, we applied a novel meta-analytic and Bayesian method (minimum Bayes Factor Activation Likelihood Estimation, mBF-ALE) for a systematic exploration of local functional connectivity alterations in MCI and AD brains. We extracted ReHo data via a standardized MEDLINE database search, which included 35 peer-reviewed experiments, 1,256 individuals with AD or MCI, 1,118 healthy controls, and 205 x-y-z coordinates of ReHo variation. We then separated the data into two distinct datasets: one for MCI and the other for AD. Two mBF-ALE analyses were conducted, thresholded at "very strong evidence" (mBF ≥ 150), with a minimum cluster size of 200 mm³. We also assessed the spatial consistency and sensitivity of our Bayesian results using the canonical version of the ALE algorithm. For MCI, we observed two clusters of ReHo decrease and one of ReHo increase. Decreased local connectivity was notable in the left precuneus (Brodmann area - BA 7) and left inferior temporal gyrus (BA 20), while increased connectivity was evident in the right parahippocampal gyrus (BA 36). The canonical ALE confirmed these locations, except for the inferior temporal gyrus. In AD, one cluster each of ReHo decrease and increase were found, with decreased connectivity in the right posterior cingulate cortex (BA 30 extending to BA 23) and increased connectivity in the left posterior cingulate cortex (BA 31). These locations were confirmed by the canonical ALE. The identification of these distinct functional connectivity patterns sheds new light on the complex pathophysiology of MCI and AD, offering promising directions for future neuroimaging-based interventions. Additionally, the use of a Bayesian framework for statistical thresholding enhances the robustness of neuroimaging meta-analyses, broadening its applicability to small datasets.

Divergent functional connectivity changes associated with white matter hyperintensities

Age-related white matter hyperintensities are a common feature and are known to be negatively associated with structural integrity, functional connectivity, and cognitive performance. However, this has yet to be fully understood mechanistically. We analyzed multiple MRI modalities acquired in 465 non-demented individuals from the Swedish BioFINDER study including 334 cognitively normal and 131 participants with mild cognitive impairment. White matter hyperintensities were automatically quantified using fluid-attenuated inversion recovery MRI and parameters from diffusion tensor imaging were estimated in major white matter fibre tracts. We calculated fMRI resting state-derived functional connectivity within and between predefined cortical regions structurally linked by the white matter tracts. How change in functional connectivity is affected by white matter lesions and related to cognition (in the form of executive function and processing speed) was explored. We examined the functional changes using a measure of sample entropy. As expected hyperintensities were associated with disrupted structural white matter integrity and were linked to reduced functional interregional lobar connectivity, which was related to decreased processing speed and executive function. Simultaneously, hyperintensities were also associated with increased intraregional functional connectivity, but only within the frontal lobe. This phenomenon was also associated with reduced cognitive performance. The increased connectivity was linked to increased entropy (reduced predictability and increased complexity) of the involved voxels' blood oxygenation level-dependent signal. Our findings expand our previous understanding of the impact of white matter hyperintensities on cognition by indicating novel mechanisms that may be important beyond this particular type of brain lesions.

Changes of brain functional network in Alzheimer's disease and frontotemporal dementia: a graph-theoretic analysis

BACKGROUND

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the two most common neurodegenerative dementias, presenting with similar clinical features that challenge accurate diagnosis. Despite extensive research, the underlying pathophysiological mechanisms remain unclear, and effective treatments are limited. This study aims to investigate the alterations in brain network connectivity associated with AD and FTD to enhance our understanding of their pathophysiology and establish a scientific foundation for their diagnosis and treatment.

METHODS

We analyzed preprocessed electroencephalogram (EEG) data from the OpenNeuro public dataset, comprising 36 patients with AD, 23 patients with FTD, and 29 healthy controls (HC). Participants were in a resting state with eyes closed. We estimated the average functional connectivity using the Phase Lag Index (PLI) for lower frequencies (delta and theta) and the Amplitude Envelope Correlation with leakage correction (AEC-c) for higher frequencies (alpha, beta, and gamma). Graph theory was applied to calculate topological parameters, including mean node degree, clustering coefficient, characteristic path length, global and local efficiency. A permutation test was then utilized to assess changes in brain network connectivity in AD and FTD based on these parameters.

RESULTS

Both AD and FTD patients showed increased mean PLI values in the theta frequency band, along with increases in average node degree, clustering coefficient, global efficiency, and local efficiency. Conversely, mean AEC-c values in the alpha frequency band were notably diminished, which was accompanied by decreases average node degree, clustering coefficient, global efficiency, and local efficiency. Furthermore, AD patients in the occipital region showed an increase in theta band node degree and decreased alpha band clustering coefficient and local efficiency, a pattern not observed in FTD.

CONCLUSIONS

Our findings reveal distinct abnormalities in the functional network topology and connectivity in AD and FTD, which may contribute to a better understanding of the pathophysiological mechanisms of these diseases. Specifically, patients with AD demonstrated a more widespread change in functional connectivity, while those with FTD retained connectivity in the occipital lobe. These observations could provide valuable insights for developing electrophysiological markers to differentiate between the two diseases.

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

Different Trajectories of Functional Connectivity Captured with Gamma-Event Coupling and Broadband Measures of EEG in the Rat Fluid Percussion Injury Model

Functional connectivity (FC) after TBI is affected by an altered excitatory-inhibitory balance due to neuronal dysfunction, and the mechanistic changes observed could be reflected differently by contrasting methods. Local gamma event coupling FC (GEC-FC) is believed to represent multiunit fluctuations due to inhibitory dysfunction, and we hypothesized that FC derived from widespread, broadband amplitude signal (BBA-FC) would be different, reflecting broader mechanisms of functional disconnection. We tested this during sleep and active periods defined by high delta and theta EEG activity, respectively, at 1,7 and 28d after rat fluid-percussion-injury (FPI) or sham injury (n=6/group) using 10 indwelling, bilateral cortical and hippocampal electrodes. We also measured seizure and high-frequency oscillatory activity (HFOs) as markers of electrophysiological burden. BBA-FC analysis showed early hyperconnectivity constrained to ipsilateral sensory-cortex-to-CA1-hippocampus that transformed to mainly ipsilateral FC deficits by 28d compared to shams. These changes were conserved over active epochs, except at 28d when there were no differences to shams. In comparison, GEC-FC analysis showed large regions of hyperconnectivity early after injury within similar ipsilateral and intrahemispheric networks. GEC-FC weakened with time, but hyperconnectivity persisted at 28d compared to sham. Edge- and global connectivity measures revealed injury-related differences across time in GEC-FC as compared to BBA-FC, demonstrating greater sensitivity to FC changes post-injury. There was no significant association between sleep fragmentation, HFOs, or seizures with FC changes. The within-animal, spatial-temporal differences in BBA-FC and GEC-FC after injury may represent different mechanisms driving FC changes as a result of primary disconnection and interneuron loss.

Significance statement

The present study adds to the understanding of functional connectivity changes in preclinical models of traumatic brain injury. In previously reported literature, there is heterogeneity in the directionality of connectivity changes after injury, resulting from factors such as severity of injury, frequency band studied, and methodology used to calculate FC. This study aims to further clarify differential mechanisms that result in altered network topography after injury, by using Broadband Amplitude-Derived FC and Gamma Event Coupling-Derived FC in EEG. We found post-injury changes that differ in complexity and directionality between measures at and across timepoints. In conjunction with known results and future studies identifying different neural drivers underlying these changes, measures derived from this study could provide useful means from which to minimally-invasively study temporally-evolving pathology after TBI.

Effects of Low-Level Light Therapy on Resting-State Connectivity Following Moderate Traumatic Brain Injury: Secondary Analyses of a Double-blinded Placebo-controlled Study

Background Low-level light therapy (LLLT) has been shown to modulate recovery in patients with traumatic brain injury (TBI). However, the impact of LLLT on the functional connectivity of the brain when at rest has not been well studied. Purpose To use functional MRI to assess the effect of LLLT on whole-brain resting-state functional connectivity (RSFC) in patients with moderate TBI at acute (within 1 week), subacute (2-3 weeks), and late-subacute (3 months) recovery phases. Materials and Methods This is a secondary analysis of a prospective single-site double-blinded sham-controlled study conducted in patients presenting to the emergency department with moderate TBI from November 2015 to July 2019. Participants were randomized for LLLT and sham treatment. The primary outcome of the study was to assess structural connectivity, and RSFC was collected as the secondary outcome. MRI was used to measure RSFC in 82 brain regions in participants during the three recovery phases. Healthy individuals who did not receive treatment were imaged at a single time point to provide control values. The Pearson correlation coefficient was estimated to assess the connectivity strength for each brain region pair, and estimates of the differences in Fisher z-transformed correlation coefficients (hereafter, z differences) were compared between recovery phases and treatment groups using a linear mixed-effects regression model. These analyses were repeated for all brain region pairs. False discovery rate (FDR)-adjusted P values were computed to account for multiple comparisons. Quantile mixed-effects models were constructed to quantify the association between the Rivermead Postconcussion Symptoms Questionnaire (RPQ) score, recovery phase, and treatment group. Results RSFC was evaluated in 17 LLLT-treated participants (median age, 50 years [IQR, 25-67 years]; nine female), 21 sham-treated participants (median age, 50 years [IQR, 43-59 years]; 11 female), and 23 healthy control participants (median age, 42 years [IQR, 32-54 years]; 13 male). Seven brain region pairs exhibited a greater change in connectivity in LLLT-treated participants than in sham-treated participants between the acute and subacute phases (range of z differences, 0.37 [95% CI: 0.20, 0.53] to 0.45 [95% CI: 0.24, 0.67]; FDR-adjusted P value range, .010-.047). Thirteen different brain region pairs showed an increase in connectivity in sham-treated participants between the subacute and late-subacute phases (range of z differences, 0.17 [95% CI: 0.09, 0.25] to 0.26 [95% CI: 0.14, 0.39]; FDR-adjusted P value range, .020-.047). There was no evidence of a difference in clinical outcomes between LLLT-treated and sham-treated participants (range of differences in medians, -3.54 [95% CI: -12.65, 5.57] to -0.59 [95% CI: -7.31, 8.49]; P value range, .44-.99), as measured according to RPQ scores. Conclusion Despite the small sample size, the change in RSFC from the acute to subacute phases of recovery was greater in LLLT-treated than sham-treated participants, suggesting that acute-phase LLLT may have an impact on resting-state neuronal circuits in the early recovery phase of moderate TBI. ClinicalTrials.gov Identifier: NCT02233413 © RSNA, 2024 Supplemental material is available for this article.

Disrupted topological organization of functional brain networks in traumatic axonal injury

Traumatic axonal injury (TAI) may result in the disruption of brain functional networks and is strongly associated with cognitive impairment. However, the neural mechanisms affecting the neurocognitive function after TAI remain to be elucidated. We collected the resting-state functional magnetic resonance imaging data from 28 patients with TAI and 28 matched healthy controls. An automated anatomical labeling atlas was used to construct a functional brain connectome. We utilized a graph theoretical approach to investigate the alterations in global and regional network topologies, and network-based statistics analysis was utilized to localize the connected networks more precisely. The current study revealed that patients with TAI and healthy controls both showed a typical small-world topology of the functional brain networks. However, patients with TAI exhibited a significantly lower local efficiency compared to healthy controls, whereas no significant difference emerged in other small-world properties (Cp, Lp, γ, λ, and σ) and global efficiency. Moreover, patients with TAI exhibited aberrant nodal centralities in some regions, including the frontal lobes, parietal lobes, caudate nucleus, and cerebellum bilaterally, and right olfactory cortex. The network-based statistics results showed alterations in the long-distance functional connections in the subnetwork in patients with TAI, involving these brain regions with significantly altered nodal centralities. These alterations suggest that brain networks of individuals with TAI present aberrant topological attributes that are associated with cognitive impairment, which could be potential biomarkers for predicting cognitive dysfunction and help understanding the neuropathological mechanisms in patients with TAI.

Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict. Functional integrity of the brain and brain network topology have been suggested as biomarkers of language recovery. This study sought to investigate functional connectivity in four predefined brain networks (i.e., language, default mode, dorsal attention, and salience networks), in relation to aphasia severity and response to language therapy. Thirty patients with chronic post-stroke aphasia were recruited and received a treatment targeting word finding. Structural and functional brain scans were acquired at baseline and resting state functional connectivity for each network was calculated. Additionally, graph measures quantifying network properties were calculated for each network. These included global efficiency for all networks and average strength and clustering coefficient for the language network. Linear mixed effects models showed that mean functional connectivity in the default mode, dorsal attention, and salience networks as well as graph measures of all four networks are independent predictors of response to therapy. While greater mean functional connectivity and global efficiency of the dorsal attention and salience networks predicted greater treatment response, greater mean functional connectivity and global efficiency in the default mode network predicted poorer treatment response. Results for the language network were more nuanced with more efficient network configurations (as reflected in graph measures), but not mean functional connectivity, predicting greater treatment response. These findings highlight the prognostic value of resting-state functional connectivity in chronic treatment-induced aphasia recovery.

ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

Concussion-Related Disruptions to Hub Connectivity in the Default Mode Network Are Related to Symptoms and Cognition

Concussions present with a myriad of symptomatic and cognitive concerns; however, the relationship between these functional disruptions and the underlying changes in the brain are not yet well understood. Hubs, or brain regions that are connected to many different functional networks, may be specifically disrupted after concussion. Given the implications in concussion research, we quantified hub disruption within the default mode network (DMN) and between the DMN and other brain networks. We collected resting-state functional magnetic resonance imaging data from collegiate student-athletes (n = 44) at three time points: baseline (before beginning their athletic season), acute post-injury (approximately 48h after a diagnosed concussion), and recovery (after starting return-to-play progression, but before returning to contact). We used self-reported symptoms and computerized cognitive assessments collected across similar time points to link these functional connectivity changes to clinical outcomes. Concussion resulted in increased connectivity between regions within the DMN compared with baseline and recovery, and this post-injury connectivity was more positively related to symptoms and more negatively related to visual memory performance compared with baseline and recovery. Further, concussion led to decreased connectivity between DMN hubs and visual network non-hubs relative to baseline and recovery, and this post-injury connectivity was more negatively related to somatic symptoms and more positively related to visual memory performance compared with baseline and recovery. Relationships between functional connectivity, symptoms, and cognition were not significantly different at baseline versus recovery. These results highlight a unique relationship between self-reported symptoms, visual memory performance, and acute functional connectivity changes involving DMN hubs after concussion in athletes. This may provide evidence for a disrupted balance of within- and between-network communication highlighting possible network inefficiencies after concussion. These results aid in our understanding of the pathophysiological disruptions after concussion and inform our understanding of the associations between disruptions in brain connectivity and specific clinical presentations acutely post-injury.

Resting-state fMRI functional connectome of C9orf72 mutation status

OBJECTIVE

The resting-state functional connectome has not been extensively investigated in amyotrophic lateral sclerosis (ALS) spectrum disease, in particular in relationship with patients' genetic status.

METHODS

Here we studied the network-to-network connectivity of 19 ALS patients carrying the C9orf72 hexanucleotide repeat expansion (C9orf72+), 19 ALS patients not affected by C9orf72 mutation (C9orf72-), and 19 ALS-mimic patients (ALSm) well-matched for demographic and clinical variables.

RESULTS

When compared with ALSm, we observed greater connectivity of the default mode and frontoparietal networks with the visual network for C9orf72+ patients (P = 0.001). Moreover, the whole-connectome showed greater node degree (P < 0.001), while sensorimotor cortices resulted isolated in C9orf72+.

INTERPRETATION

Our results suggest a crucial involvement of extra-motor functions in ALS spectrum disease. In particular, alterations of the visual cortex may have a pathogenic role in C9orf72-related ALS. The prominent feature of these patients would be increased visual system connectivity with the networks responsible of the functional balance between internal and external attention.

Directed functional connectivity of the default-mode-network of young and older healthy subjects

Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging.

Deep brain stimulation of the central thalamus restores arousal and motivation in a zolpidem-responsive patient with akinetic mutism after severe brain injury

After severe brain injury, zolpidem is known to cause spectacular, often short-lived, restorations of brain functions in a small subgroup of patients. Previously, we showed that these zolpidem-induced neurological recoveries can be paralleled by significant changes in functional connectivity throughout the brain. Deep brain stimulation (DBS) is a neurosurgical intervention known to modulate functional connectivity in a wide variety of neurological disorders. In this study, we used DBS to restore arousal and motivation in a zolpidem-responsive patient with severe brain injury and a concomitant disorder of diminished motivation, more than 10 years after surviving hypoxic ischemia. We found that DBS of the central thalamus, targeted at the centromedian-parafascicular complex, immediately restored arousal and was able to transition the patient from a state of deep sleep to full wakefulness. Moreover, DBS was associated with temporary restoration of communication and ability to walk and eat in an otherwise wheelchair-bound and mute patient. With the use of magnetoencephalography (MEG), we revealed that DBS was generally associated with a marked decrease in aberrantly high levels of functional connectivity throughout the brain, mimicking the effects of zolpidem. These results imply that 'pathological hyperconnectivity' after severe brain injury can be associated with reduced arousal and behavioral performance and that DBS is able to modulate connectivity towards a 'healthier baseline' with lower synchronization, and, can restore functional brain networks long after severe brain injury. The presence of hyperconnectivity after brain injury may be a possible future marker for a patient's responsiveness for restorative interventions, such as DBS, and suggests that lower degrees of overall brain synchronization may be conducive to cognition and behavioral responsiveness.

Altered grey matter structural covariance in chronic moderate-severe traumatic brain injury

Traumatic brain injury (TBI) alters brain network connectivity. Structural covariance networks (SCNs) reflect morphological covariation between brain regions. SCNs may elucidate how altered brain network topology in TBI influences long-term outcomes. Here, we assessed whether SCN organisation is altered in individuals with chronic moderate-severe TBI (≥ 10 years post-injury) and associations with cognitive performance. This case-control study included fifty individuals with chronic moderate-severe TBI compared to 75 healthy controls recruited from an ongoing longitudinal head injury outcome study. SCNs were constructed using grey matter volume measurements from T1-weighted MRI images. Global and regional SCN organisation in relation to group membership and cognitive ability was examined using regression analyses. Globally, TBI participants had reduced small-worldness, longer characteristic path length, higher clustering, and higher modularity globally (p < 0.05). Regionally, TBI participants had greater betweenness centrality (p < 0.05) in frontal and central areas of the cortex. No significant associations were observed between global network measures and cognitive ability in participants with TBI (p > 0.05). Chronic moderate-severe TBI was associated with a shift towards a more segregated global network topology and altered organisation in frontal and central brain regions. There was no evidence that SCNs are associated with cognition.

Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network

In healthy subjects, activity in the default mode network (DMN) and the frontoparietal network (FPN) has consistently been associated with working memory (WM). In particular, the dorsolateral prefrontal cortex (DLPFC) is important for WM. The functional-anatomical basis of WM impairment in glioma patients is, however, still poorly understood. We investigated whether WM performance of glioma patients is reflected in resting-state functional connectivity (FC) between the DMN and FPN, additionally focusing on the DLPFC. Resting-state functional MRI data were acquired from 45 glioma patients prior to surgery. WM performance was derived from a pre-operative N-back task. Scans were parcellated into ROIs using both the Gordon and Yeo atlas. FC was calculated as the average Pearson correlation between functional time series. The FC between right DLPFC and DMN was inversely related to WM performance for both the Gordon and Yeo atlas (p = .010). No association was found for FC between left DLPFC and DMN, nor between the whole FPN and DMN. The results are robust and not dependent on atlas choice or tumor location, as they hold for both the Gordon and Yeo atlases, and independently of location variables. Our findings show that WM performance of glioma patients can be quantified in terms of interactions between regions and large-scale networks that can be measured with resting-state fMRI. These group-based results are a necessary step toward development of biomarkers for clinical management of glioma patients, and provide additional evidence that global disruption of the DMN relates to cognitive impairment in glioma patients.

Mild traumatic brain injury history is associated with lower brain network resilience in soldiers

Special Operations Forces combat soldiers sustain frequent blast and blunt neurotrauma, most often classified as mild traumatic brain injuries. Exposure to repetitive mild traumatic brain injuries is associated with persistent behavioural, cognitive, emotional and neurological symptoms later in life. Identifying neurophysiological changes associated with mild traumatic brain injury exposure, in the absence of present-day symptoms, is necessary for detecting future neurological risk. Advancements in graph theory and functional MRI have offered novel ways to analyse complex whole-brain network connectivity. Our purpose was to determine how mild traumatic brain injury history, lifetime incidence and recency affected whole-brain graph theoretical outcome measures. Healthy male Special Operations Forces combat soldiers (age = 33.2 ± 4.3 years) underwent multimodal neuroimaging at a biomedical research imaging centre using 3T Siemens Prisma or Biograph MRI scanners in this cross-sectional study. Anatomical and functional scans were preprocessed. The blood-oxygen-level-dependent signal was extracted from each functional MRI time series using the Big Brain 300 atlas. Correlations between atlas regions were calculated and Fisher z-transformed to generate subject-level correlation matrices. The Brain Connectivity Toolbox was used to obtain functional network measures for global efficiency (the average inverse shortest path length), local efficiency (the average global efficiency of each node and its neighbours), and assortativity coefficient (the correlation coefficient between the degrees of all nodes on two opposite ends of a link). General linear models were fit to compare mild traumatic brain injury lifetime incidence and recency. Nonparametric ANOVAs were used for tests on non-normally distributed data. Soldiers with a history of mild traumatic brain injury had significantly lower assortativity than those who did not self-report mild traumatic brain injury (t148 = 2.44, P = 0.016). The assortativity coefficient was significantly predicted by continuous mild traumatic brain injury lifetime incidence [F1,144 = 6.51, P = 0.012]. No differences were observed between recency groups, and no global or local efficiency differences were observed between mild traumatic brain injury history and lifetime incidence groups. Brain networks with greater assortativity have more resilient, interconnected hubs, while those with lower assortativity indicate widely distributed, vulnerable hubs. Greater lifetime mild traumatic brain injury incidence predicted lower assortativity in our study sample. Less resilient brain networks may represent a lack of physiological recovery in mild traumatic brain injury patients, who otherwise demonstrate clinical recovery, more vulnerability to future brain injury and increased risk for accelerated age-related neurodegenerative changes. Future longitudinal studies should investigate whether decreased brain network resilience may be a predictor for long-term neurological dysfunction.

The Current State of Functional MR Imaging for Trauma Prognostication

In this review, we discuss the basics of functional MRI (fMRI) techniques including task-based and resting state fMRI, and overview the major findings in patients with traumatic brain injury. We summarize the studies that have longitudinally evaluated the changes in brain connectivity and task-related activation in trauma patients during different phases of trauma. We discuss how these data may potentially be used for prognostication, treatment planning, or monitoring and management of trauma patients.

Longitudinal Patterns of Functional Connectivity in Moderate-to-Severe Traumatic Brain Injury

Longitudinal neuroimaging studies aid our understanding of recovery mechanisms in moderate-to-severe traumatic brain injury (TBI); however, there is a dearth of longitudinal functional connectivity research. Our aim was to characterize longitudinal functional connectivity patterns in two clinically important brain networks, the frontoparietal network (FPN) and the default mode network (DMN), in moderate-to-severe TBI. This inception cohort study of prospectively collected longitudinal data used resting-state functional magnetic resonance imaging (fMRI) to characterize functional connectivity patterns in the FPN and DMN. Forty adults with moderate-to-severe TBI (mean ± standard deviation [SD]; age = 39.53 ± 16.49 years, education = 13.92 ± 3.20 years, lowest Glasgow Coma Scale score = 6.63 ± 3.24, sex = 70% male) were scanned at approximately 0.5, 1-1.5, and 3+ years post-injury. Seventeen healthy, uninjured participants (mean ± SD; age = 38.91 ± 15.57 years, education = 15.11 ± 2.71 years, sex = 29% male) were scanned at baseline and approximately 11 months afterwards. Group independent component analyses and linear mixed-effects modeling with linear splines that contained a knot at 1.5 years post-injury were employed to investigate longitudinal network changes, and associations with covariates, including age, sex, and injury severity. In patients with TBI, functional connectivity in the right FPN increased from approximately 0.5 to 1.5 years post-injury (unstandardized estimate = 0.19, standard error [SE] = 0.07, p = 0.009), contained a slope change in the opposite direction, from positive to negative at 1.5 years post-injury (estimate = -0.21, SE = 0.11, p = 0.009), and marginally declined afterwards (estimate = -0.10, SE = 0.06, p = 0.079). Functional connectivity in the DMN increased from approximately 0.5 to 1.5 years (estimate = 0.15, SE = 0.05, p = 0.006), contained a slope change in the opposite direction, from positive to negative at 1.5 years post-injury (estimate = -0.19, SE = 0.08, p = 0.021), and was estimated to decline from 1.5 to 3+ years (estimate = -0.04, SE = 0.04, p = 0.303). Similarly, the left FPN increased in functional connectivity from approximately 0.5 to 1.5 years post-injury (estimate = 0.15, SE = 0.05, p = 0.002), contained a slope change in the opposite direction, from positive to negative at 1.5 years post-injury (estimate = -0.18, SE = 0.07, p = 0.008), and was estimated to decline thereafter (estimate = -0.04, SE = 0.03, p = 0.254). At approximately 0.5 years post-injury, patients showed hypoconnectivity compared with healthy, uninjured participants at baseline. Covariates were not significantly associated in any of the models. Findings of early improvement but a tapering and possible decline in connectivity thereafter suggest that compensatory effects are time-limited. These later reductions in connectivity mirror growing evidence of behavioral and structural decline in chronic moderate-to-severe TBI. Targeting such declines represents a novel avenue of research and offers potential for improving clinical outcomes.

Differential Patterns of Change in Brain Connectivity Resulting from Severe Traumatic Brain Injury

Background: Traumatic brain injury (TBI) damages white matter tracts, disrupting brain network structure and communication. There exists a wide heterogeneity in the pattern of structural damage associated with injury, as well as a large heterogeneity in behavioral outcomes. However, little is known about the relationship between changes in network connectivity and clinical outcomes. Materials and Methods: We utilize the rat lateral fluid-percussion injury model of severe TBI to study differences in brain connectivity in 8 animals that received the insult and 11 animals that received only a craniectomy. Diffusion tensor imaging is performed 5 weeks after the injury and network theory is used to investigate changes in white matter connectivity. Results: We find that (1) global network measures are not able to distinguish between healthy and injured animals; (2) injury induced alterations predominantly exist in a subset of connections (subnetworks) distributed throughout the brain; and (3) injured animals can be divided into subgroups based on changes in network motifs-measures of local structural connectivity. In addition, alterations in predicted functional connectivity indicate that the subgroups have different propensities to synchronize brain activity, which could relate to the heterogeneity of clinical outcomes. Discussion: These results suggest that network measures can be used to quantify progressive changes in brain connectivity due to injury and differentiate among subpopulations with similar injuries, but different pathological trajectories.

The Analysis of the Power Law Feature in Complex Networks

Consensus about the universality of the power law feature in complex networks is experiencing widespread challenges. In this paper, we propose a generic theoretical framework in order to examine the power law property. First, we study a class of birth-and-death networks that are more common than BA networks in the real world, and then we calculate their degree distributions; the results show that the tails of their degree distributions exhibit a distinct power law feature. Second, we suggest that in the real world two important factors-network size and node disappearance probability-will affect the analysis of power law characteristics in observation networks. Finally, we suggest that an effective way of detecting the power law property is to observe the asymptotic (limiting) behavior of the degree distribution within its effective intervals.

Targeting disrupted rich-club network organization with neuroplasticity-based computerized cognitive remediation in major depressive disorder patients

Disrupted rich-club organization has been extensively studied in major depressive disorder (MDD) patients. Although data indicate that neuroplasticity-based computerized cognitive remediation (nCCR) can accelerate clinical responses in MDD patients, the mechanisms underlying its antidepressant efficacy are unknown. In this study, all MDD patients underwent two (baseline and week 4) neuropsychological assessments and DTI imaging. Additionally, 17 MDD patients did nCCR for 30 hours spread across 4 weeks. Rich-club organization was calculated with a graph-theoretical approach, and SC-FC coupling was explored. After 4 weeks of treatment, the number of rich-club connections, global efficiency, and SC-FC coupling strength increased significantly and were negatively associated with TMT-B scores. The effects of nCCR on disrupted rich-club organization may partly underlie its efficacy in improving the executive function of patients with MDD. Effects of nCCR on disrupted rich-club organization may partly underlie its efficacy in improving the executive function of patients with MDD.

Adolescents with a concussion have altered brain network functional connectivity one month following injury when compared to adolescents with orthopedic injuries

Concussion is a mild traumatic brain injury (mTBI) with increasing prevalence among children and adolescents. Functional connectivity (FC) within and between the default mode network (DMN), central executive network (CEN) and salience network (SN) has been shown to be altered post-concussion. Few studies have investigated connectivity within and between these 3 networks following a pediatric concussion. The present study explored whether within and between-network FC differs between a pediatric concussion and orthopedic injury (OI) group aged 10-18. Participants underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan at 4 weeks post-injury. One-way ANCOVA analyses were conducted between groups with the seed-based FC of the 3 networks. A total of 55 concussion and 27 OI participants were included in the analyses. Increased within-network FC of the CEN and decreased between-network FC of the DMN-CEN was found in the concussion group when compared to the OI group. Secondary analyses using spherical SN regions of interest revealed increased within-network FC of the SN and increased between-network FC of the DMN-SN and CEN-SN in the concussion group when compared to the OI group. This study identified differential connectivity patterns following a pediatric concussion as compared to an OI 4 weeks post-injury. These differences indicate potential adaptive brain mechanisms that may provide insight into recovery trajectories and appropriate timing of treatment within the first month following a concussion.

Connectomic assessment of injury burden and longitudinal structural network alterations in moderate-to-severe traumatic brain injury

Traumatic brain injury (TBI) is a major public health problem. Caused by external mechanical forces, a major characteristic of TBI is the shearing of axons across the white matter, which causes structural connectivity disruptions between brain regions. This diffuse injury leads to cognitive deficits, frequently requiring rehabilitation. Heterogeneity is another characteristic of TBI as severity and cognitive sequelae of the disease have a wide variation across patients, posing a big challenge for treatment. Thus, measures assessing network-wide structural connectivity disruptions in TBI are necessary to quantify injury burden of individuals, which would help in achieving personalized treatment, patient monitoring, and rehabilitation planning. Despite TBI being a disconnectivity syndrome, connectomic assessment of structural disconnectivity has been relatively limited. In this study, we propose a novel connectomic measure that we call network normality score (NNS) to capture the integrity of structural connectivity in TBI patients by leveraging two major characteristics of the disease: diffuseness of axonal injury and heterogeneity of the disease. Over a longitudinal cohort of moderate-to-severe TBI patients, we demonstrate that structural network topology of patients is more heterogeneous and significantly different than that of healthy controls at 3 months postinjury, where dissimilarity further increases up to 12 months. We also show that NNS captures injury burden as quantified by posttraumatic amnesia and that alterations in the structural brain network is not related to cognitive recovery. Finally, we compare NNS to major graph theory measures used in TBI literature and demonstrate the superiority of NNS in characterizing the disease.

Contextual Effects of Traumatic Brain Injury on the Connectome: Differential Effects of Deployment- and Non-Deployment-Acquired Injuries

OBJECTIVE

To identify differential effects of mild traumatic brain injury (TBI) occurring in a deployment or nondeployment setting on the functional brain connectome.

SETTING

Veterans Affairs Medical Center.

PARTICIPANTS

In total, 181 combat-exposed veterans of the wars in Iraq and Afghanistan (n = 74 with deployment-related mild TBI, average time since injury = 11.0 years, SD = 4.1).

DESIGN

Cross-sectional observational study.

MAIN MEASURES

Mid-Atlantic MIRECC (Mid-Atlantic Mental Illness Research, Education, and Clinical Center) Assessment of TBI, Clinician-Administered PTSD Scale, connectome metrics.

RESULTS

Linear regression adjusting for relevant covariates demonstrates a significant (P < .05 corrected) association between deployment mild TBI with reduced global efficiency (nonstandardized β = -.011) and degree of the K-core (nonstandardized β = -.79). Nondeployment mild TBI was significantly associated with a reduced number of modules within the connectome (nonstandardized β = -2.32). Finally, the interaction between deployment and nondeployment mild TBIs was significantly (P < .05 corrected) associated with increased mean (nonstandardized β = 9.92) and mode (nonstandardized β = 14.02) frequency at which connections occur.

CONCLUSIONS

These results demonstrate distinct effects of mild TBI on the functional brain connectome when sustained in a deployment versus nondeployment context. This is consistent with findings demonstrating differential effects in other areas such as psychiatric diagnoses and severity, pain, sleep, and cognitive function. Furthermore, participants were an average of 11 years postinjury, suggesting these represent chronic effects of the injury. Overall, these findings add to the growing body of evidence, suggesting the effects of mild TBI acquired during deployment are different and potentially longer lasting than those of mild TBI acquired in a nondeployment context.

Rich-club reorganization of functional brain networks in acute mild traumatic brain injury with cognitive impairment

BACKGROUND

Mild traumatic brain injury (mTBI) is typically characterized by temporally limited cognitive impairment and regarded as a brain connectome disorder. Recent findings have suggested that a higher level of organization named the "rich-club" may play a central role in enabling the integration of information and efficient communication across different systems of the brain. However, the alterations in rich-club organization and hub topology in mTBI and its relationship with cognitive impairment after mTBI have been scarcely elucidated.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 88 patients with mTBI and 85 matched healthy controls (HCs). Large-scale functional brain networks were established for each participant. Rich-club organizations and network properties were assessed and analyzed between groups. Finally, we analyzed the correlations between the cognitive performance and changes in rich-club organization and network properties.

RESULTS

Both mTBI and HCs groups showed significant rich-club organization. Meanwhile, the rich-club organization was aberrant, with enhanced functional connectivity (FC) among rich-club nodes and peripheral regions in acute mTBI. In addition, significant differences in partial global and local network topological property measures were found between mTBI patients and HCs (P<0.01). In patients with mTBI, changes in rich-club organization and network properties were found to be related to early cognitive impairment after mTBI (P<0.05).

CONCLUSIONS

Our findings suggest that such patterns of disruption and reorganization will provide the basic functional architecture for cognitive function, which may subsequently be used as an earlier biomarker for cognitive impairment after mTBI.

Posterior-prefrontal and medial orbitofrontal regions play crucial roles in happiness and sadness recognition

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Brain areas underlying trade-off relations between emotions were identified.

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Damage to the PPF area reduces accuracy of happiness recognition.

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Damage to the PPF increases accuracy of sadness recognition.

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A similar tendency was observed in orbitofrontal regions for sadness recognition.

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Only a deficit in sadness, but not happiness, persisted in the chronic phase.

The core brain regions responsible for basic human emotions are not yet fully understood. We investigated the key areas responsible for emotion recognition of facial expressions of happiness and sadness using data obtained from patients who underwent local brain resection. A total of 44 patients with right cerebral hemispheric brain tumors and 33 healthy volunteers were enrolled and subjected to a facial expression recognition test. Voxel-based lesion-symptom mapping was performed to investigate the relationship between the accuracy of emotion recognition and the resected regions. Consequently, trade-off relationships were discovered: the posterior-prefrontal region was related to a low score of happiness recognition and a high score of sadness recognition (disorder-of-happiness group), whereas the medial orbitofrontal region was related to a low score of sadness recognition and a high score of happiness recognition (disorder-of-sadness group). The emotion recognition score in both the happiness and sadness disorder groups was significantly lower than that in the control group (p = 0.0009 and p = 0.021, respectively). Interestingly, the deficit in happiness recognition was temporary, whereas the deficit in sadness recognition persisted during the chronic phase. Using graph theoretical analysis, we identified structural connectivity between the posterior-prefrontal and medial orbitofrontal regions. When either of these regions was damaged, the tract volume connecting them was significantly reduced (p = 0.013). These results indicate that the posterior-prefrontal and medial orbitofrontal regions may be crucial for maintaining a balance between happiness and sadness recognition in humans. Investigating the clinical impact of certain area resections using lesion studies combined with connectivity analysis is a useful neuroimaging method for understanding neural networks.

Ghani ARIG, Wan Mohamad WNA, Mohamed Mustafar MF, Hanafi MH, Reza MF, Umar H, Mohd Zulkifly MF, Ang SY, Zakaria Z, Musa KI, Othman A, Embong Z, Sapiai NA, Kandasamy R, Ibrahim H, Abdullah MZ, Amaruchkul K, Valdes-Sosa P, Luisa-Bringas M, Biswal B, Songsiri J, Yaacob HS, Sumari P, Jamir Singh PS, Azman A, Abdullah JM. Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury

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.

A Decentralized ComBat Algorithm and Applications to Functional Network Connectivity

Recent studies showed that working with neuroimage data collected from different research facilities or locations may incur additional source dependency, affecting the overall statistical power. This problem can be mitigated with data harmonization approaches. Recently, the ComBat method has become commonly adopted for various neuroimage modalities. While open neuroimaging datasets are becoming more common, a substantial amount of data is still unable to be shared for various reasons. In addition, current approaches require moving all the data to a central location, which requires additional resources and creates redundant copies of the same datasets. To address these issues, we propose a decentralized harmonization approach that does not create redundant copies of the original datasets and performs remote operations on the datasets separately without sharing any individual subject data, ensuring a certain level of privacy and reducing regulatory hurdles. We proposed a novel approach called "Decentralized ComBat" which can harmonize datasets separately without combining the datasets. We tested our model by harmonizing functional network connectivity datasets from two traumatic brain injury studies in a decentralized way. Also, we used simulations to analyze the performance and scalability of our model when the number of data collection sites increases. We compare the output with centralized ComBat and show that the proposed approach produces similar results, increasing the sensitivity of the functional network connectivity analysis and validating our approach. Simulations show that our model can be easily scaled to many more datasets based on the requirement. In sum, we believe this provides a powerful tool, further complementing open data and allowing for integrating public and private datasets.

Altered canonical and striatal-frontal resting state functional connectivity in children with pathogenic variants in the Ras/mitogen-activated protein kinase pathway

Mounting evidence supports the role of the Ras/mitogen-activated protein kinase (Ras/MAPK) pathway in neurodevelopmental disorders. Here, the authors used a genetics-first approach to examine how Ras/MAPK pathogenic variants affect the functional organization of the brain and cognitive phenotypes including weaknesses in attention and inhibition. Functional MRI was used to examine resting state functional connectivity (RSFC) in association with Ras/MAPK pathogenic variants in children with Noonan syndrome (NS). Participants (age 4-12 years) included 39 children with NS (mean age 8.44, SD = 2.20, 25 females) and 49 typically developing (TD) children (mean age 9.02, SD = 9.02, 33 females). Twenty-eight children in the NS group and 46 in the TD group had usable MRI data and were included in final analyses. The results indicated significant hyperconnectivity for the NS group within canonical visual, ventral attention, left frontoparietal and limbic networks (p < 0.05 FWE). Higher connectivity within canonical left frontoparietal and limbic networks positively correlated with cognitive function within the NS but not the TD group. Further, the NS group demonstrated significant group differences in seed-based striatal-frontal connectivity (Z > 2.6, p < 0.05 FWE). Hyperconnectivity within canonical brain networks may represent an intermediary phenotype between Ras/MAPK pathogenic variants and cognitive phenotypes, including weaknesses in attention and inhibition. Altered striatal-frontal connectivity corresponds with smaller striatal volume and altered white matter connectivity previously documented in children with NS. These results may indicate delayed maturation and compensatory mechanisms and they are important for understanding the pathophysiology underlying cognitive phenotypes in NS and in the broader population of children with neurodevelopmental disorders.

Neural alterations in working memory of mild-moderate TBI: An fMRI study in Malaysia

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.

Alterations in the Topology of Functional Connectomes Are Associated with Post-Traumatic Stress Disorder and Blast-Related Mild Traumatic Brain Injury in Combat Veterans

Post-traumatic stress disorder (PTSD) is a common condition in post-deployment service members (SM). SMs of the conflicts in Iraq and Afghanistan also frequently experience traumatic brain injury (TBI) and exposure to blasts during deployments. This study evaluated the effect of these conditions and experiences on functional brain connectomes in post-deployment, combat-exposed veterans. Functional brain connectomes were created using 5-min resting-state magnetoencephalography data. Well-established clinical interviews determined current PTSD diagnosis, as well as deployment-acquired mild TBI and history of exposure to blast. Linear regression examined the effect of these conditions on functional brain connectomes beyond covariates. There were significant interactions between blast-related mild TBI and PTSD after correction for multiple comparisons including number of nodes (non-standardized parameter estimate [PE] = -12.47), average degree (PE = 0.05), and connection strength (PE = 0.05). A main effect of blast-related mild TBI was observed on the threshold level. These results demonstrate a distinct functional connectome presentation associated with the presence of both blast-related mild TBI and PTSD. These findings suggest the possibility that blast-related mild TBI alterations in functional brain connectomes affect the presentation or progression of recovery from PTSD. The current results offer mixed support for hyper-connectivity in the chronic phase of deployment TBI.

Cortical network modularity changes along the course of frontotemporal and Alzheimer's dementing diseases

Cortical network modularity underpins cognitive functions, so we hypothesized its progressive derangement along the course of frontotemporal (FTD) and Alzheimer's (AD) dementing diseases. EEG was recorded in 18 FTD, 18 AD, and 20 healthy controls (HC). In the FTD and AD patients, the EEG recordings were performed at the prodromal stage of dementia, at the onset of dementia, and three years after the onset of dementia. HC underwent three EEG recordings at 2-3-year time interval. Information flows underlying EEG activity recorded at electrode pairs were estimated by means of Mutual Information (MI) analysis. The functional organization of the cortical network was modelled by means of the Graph theory analysis on MI adjacency matrices. Graph theory analysis showed that the main hub of HC (Parietal area) was lost in FTD patients at onset of dementia, substituted by provincial hubs in frontal leads. No changes in global network organization were found in AD. Despite a progressive cognitive impairment during the FTD and AD progression, only the FTD patients showed a derangement in the cortical network modularity, possibly due to dysfunctions in frontal functional connectivity.

Global hippocampal and selective thalamic nuclei atrophy differentiate chronic TBI from Non-TBI

Traumatic brain injury (TBI) may increase susceptibility to neurodegenerative diseases later in life. One neurobiological parallel between chronic TBI and neurodegeneration may be accelerated aging and the nature of atrophy across subcortical gray matter structures. The main aim of the present investigation is to evaluate and rank the degree that subcortical gray matter atrophy differentiates chronic moderate-severe TBI from non-TBI participants by evaluating morphometric differences between groups. Forty individuals with moderate-severe chronic TBI (9.23 yrs from injury) and 33 healthy controls (HC) underwent high resolution 3D T1-weighted structural magnetic resonance imaging. Whole brain volume was classified into white matter, cortical and subcortical gray matter structures with hippocampi and thalami further segmented into subfields and nuclei, respectively. Extensive atrophy was observed across nearly all brain regions for chronic TBI participants. A series of multivariate logistic regression models identified subcortical gray matter structures of the hippocampus and thalamus as the most sensitive to differentiating chronic TBI from non-TBI participants (McFadden R² = .36, p < .001). Further analyses revealed the pattern of hippocampal atrophy to be global, occurring across nearly all subfields. The pattern of thalamic atrophy appeared to be much more selective and non-uniform, with largest between-group differences evident for nuclei bordering the ventricles. Subcortical gray matter was negatively correlated with time since injury (r = -.31, p = .054), while white matter and cortical gray matter were not. Cognitive ability was lower in the chronic TBI group (Cohen's d = .97, p = .003) and correlated with subcortical structures including the pallidum (r² = .23, p = .038), thalamus (r² = .36, p = .007) and ventral diencephalon (r² = .23, p = .036). These data may support an accelerated aging hypothesis in chronic moderate-severe TBI that coincides with a similar neuropathological profile found in neurodegenerative diseases.

Alterations in the Magnetoencephalography Default Mode Effective Connectivity following Concussion

BACKGROUND AND PURPOSE

Magnetoencephalography is sensitive to functional connectivity changes associated with concussion. However, the directional influences between functionally related regions remain unexplored. In this study, we therefore evaluated concussion-related magnetoencephalography-based effective connectivity changes within resting-state default mode network regions.

MATERIALS AND METHODS

Resting-state magnetoencephalography was acquired for 8 high school football players with concussion at 3 time points (preseason, postconcussion, postseason), as well as 8 high school football players without concussion and 8 age-matched controls at 2 time points (preseason, postseason). Time-series from the default mode network regions were extracted, and effective connectivity between them was computed for 5 different frequency bands. The default mode network regions were grouped into anterior and posterior default mode networks. The combined posterior-to-anterior and anterior-to-posterior effective connectivity values were averaged to generate 2 sets of values for each subject. The effective connectivity values were compared using a repeated measures ANOVA across time points for the concussed, nonconcussed, and control groups, separately.

RESULTS

A significant increase in posterior-to-anterior effective connectivity from preseason to postconcussion (corrected P value = .013) and a significant decrease in posterior-to-anterior effective connectivity from postconcussion to postseason (corrected P value = .028) were observed in the concussed group. Changes in effective connectivity were only significant within the delta band. Anterior-to-posterior connectivity demonstrated no significant change. Effective connectivity in the nonconcussed group and controls did not show significant differences.

CONCLUSIONS

The unidirectional increase in effective connectivity postconcussion may elucidate compensatory processes, invoking use of posterior regions to aid the function of susceptible anterior regions following brain injury. These findings support the potential value of magnetoencephalography in exploring directional changes of the brain network following concussion.

A Pilot Trial Examining the Merits of Combining Amantadine and Repetitive Transcranial Magnetic Stimulation as an Intervention for Persons With Disordered Consciousness After TBI

OBJECTIVE

Report pilot findings of neurobehavioral gains and network changes observed in persons with disordered consciousness (DoC) who received repetitive transcranial magnetic stimulation (rTMS) or amantadine (AMA), and then rTMS+AMA.

PARTICIPANTS

Four persons with DoC 1 to 15 years after traumatic brain injury (TBI).

DESIGN

Alternate treatment-order, within-subject, baseline-controlled trial.

MAIN MEASURES

For group and individual neurobehavioral analyses, predetermined thresholds, based on mixed linear-effects models and conditional minimally detectable change, were used to define meaningful neurobehavioral change for the Disorders of Consciousness Scale-25 (DOCS) total and Auditory-Language measures. Resting-state functional connectivity (rsFC) of the default mode and 6 other networks was examined.

RESULTS

Meaningful gains in DOCS total measures were observed for 75% of treatment segments and auditory-language gains were observed after rTMS, which doubled when rTMS preceded rTMS+AMA. Neurobehavioral changes were reflected in rsFC for language, salience, and sensorimotor networks. Between networks interactions were modulated, globally, after all treatments.

CONCLUSIONS

For persons with DoC 1 to 15 years after TBI, meaningful neurobehavioral gains were observed after provision of rTMS, AMA, and rTMS+AMA. Sequencing and combining of treatments to modulate broad-scale neural activity, via differing mechanisms, merits investigation in a future study powered to determine efficacy of this approach to enabling neurobehavioral recovery.

Resting state functional connectivity responses post-mild traumatic brain injury: a systematic review

Mild traumatic brain injuries (mTBI) are associated with functional network connectivity alterations throughout recovery. Yet, little is known about the adaptive or maladaptive nature of post-mTBI connectivity and which networks are predisposed to altered function and adaptation. The objective of this review was to determine functional connectivity changes post-mTBI and to determine the adaptive or maladaptive nature of connectivity through direct comparisons of connectivity and behavioral data. Literature was systematically searched and appraised for methodological quality. A total of 16 articles were included for review. There was conflicting evidence of post-mTBI connectivity responses as decreased connectivity was noted in 4 articles, 6 articles reported increased connectivity, 5 reported a mixture of increased and decreased connectivity, while 1 found no differences in connectivity. Supporting evidence for adaptive post-mTBI increases in connectivity were found, particularly in the frontoparietal, cerebellar, and default mode networks. Although initial results are promising, continued longitudinal research that systematically controls for confounding variables and that standardizes methodologies is warranted to adequately understand the neurophysiological recovery trajectory of mTBI.

Neural correlates of extrinsic and intrinsic outcome processing during learning in individuals with TBI: a pilot investigation

Outcome processing, the ability to learn from feedback, is an important component of adaptive behavior and rehabilitation. Evidence from healthy adults implicates the striatum and dopamine in outcome processing. Animal research shows that damage to dopaminergic pathways in the brain can lead to a disruption of dopamine tone and transmission. Such evidence thus suggests that persons with TBI experience deficits in outcome processing. However, no research has directly investigated outcome processing and associated neural mechanisms in TBI. Here, we examine outcome processing in individuals with TBI during learning. Given that TBI negatively impacts striatal and dopaminergic systems, we hypothesize that individuals with TBI exhibit deficits in learning from outcomes. To test this hypothesis, individuals with moderate-to-severe TBI and healthy adults were presented with a declarative paired-associate word learning task. Outcomes indicating performance accuracy were presented immediately during task performance and in the form of either monetary or performance-based feedback. Two types of feedback provided the opportunity to test whether extrinsic and intrinsic motivational aspects of outcome presentation play a role during learning and outcome processing. Our results show that individuals with TBI exhibited impaired learning from feedback compared to healthy participants. Additionally, individuals with TBI exhibited increased activation in the striatum during outcome processing. The results of this study suggest that outcome processing and learning from immediate outcomes is impaired in individuals with TBI and might be related to inefficient use of neural resources during task performance as reflected by increased activation of the striatum.

Ventromedial Prefrontal-Anterior Cingulate Hyperconnectivity and Resilience to Apathy in Traumatic Brain Injury

Apathy is a common and impairing sequela of traumatic brain injury (TBI). Yet, little is known about the neural mechanisms determining in which patients apathy does or does not develop post-TBI. We aimed to elucidate the impact of TBI on motivational neural circuits and how this shapes apathy over the course of TBI recovery. Resting-state functional magnetic resonance imaging data were collected in patients with subacute mild TBI (n = 44), chronic mild-to-moderate TBI (n = 26), and nonbrain-injured control participants (CTRL; n = 28). We measured ventromedial prefrontal cortex (vmPFC) functional connectivity (FC) as a function of apathy, using an a priori vmPFC seed adopted from a motivated decision-making study in an independent TBI study cohort. Patients reported apathy using a well-validated tool for assaying apathy in TBI. The vmPFC-to-wholebrain FC was contrasted between groups, and we fit regression models with apathy predicting vmPFC FC. Subacute and chronic TBI caused increased apathy relative to CTRL, replicating previous work suggesting that apathy has an enduring impact in TBI. The vmPFC was functionally connected to the canonical default network, and this architecture did not differ between subacute TBI, chronic TBI, and CTRL groups. Critically, in TBI, increased apathy scores predicted decreased vmPFC-dorsal anterior cingulate cortex (dACC) FC. Last, we subdivided the TBI group based on patients above versus below the threshold for "clinically significant apathy," finding that TBI patients with clinically significant apathy demonstrated comparable vmPFC-dACC FC to CTRLs, whereas TBI patients with subthreshold apathy scores demonstrated vmPFC-dACC hyperconnectivity relative to both CTRLs and patients with clinically significant apathy. Post-TBI vmPFC-dACC hyperconnectivity may represent an adaptive compensatory response, helping to maintain motivation and enabling resilience to the development of apathy after neurotrauma. Given the role of vmPFC-dACC circuits in value-based decision making, rehabilitation strategies designed to improve this ability may help to reduce apathy and improve functional outcomes in TBI.

Acquired olfactory loss alters functional connectivity and morphology

Removing function from a developed and functional sensory system is known to alter both cerebral morphology and functional connections. To date, a majority of studies assessing sensory-dependent plasticity have focused on effects from either early onset or long-term sensory loss and little is known how the recent sensory loss affects the human brain. With the aim of determining how recent sensory loss affects cerebral morphology and functional connectivity, we assessed differences between individuals with acquired olfactory loss (duration 7-36 months) and matched healthy controls in their grey matter volume, using multivariate pattern analyses, and functional connectivity, using dynamic connectivity analyses, within and from the olfactory cortex. Our results demonstrate that acquired olfactory loss is associated with altered grey matter volume in, among others, posterior piriform cortex, a core olfactory processing area, as well as the inferior frontal gyrus and angular gyrus. In addition, compared to controls, individuals with acquired anosmia displayed significantly stronger dynamic functional connectivity from the posterior piriform cortex to, among others, the angular gyrus, a known multisensory integration area. When assessing differences in dynamic functional connectivity from the angular gyrus, individuals with acquired anosmia had stronger connectivity from the angular gyrus to areas primary responsible for basic visual processing. These results demonstrate that recently acquired sensory loss is associated with both changed cerebral morphology within core olfactory areas and increase dynamic functional connectivity from olfactory cortex to cerebral areas processing multisensory integration.

Translating Functional Connectivity After Stroke: Functional Magnetic Resonance Imaging Detects Comparable Network Changes in Mice and Humans

[Figure: see text].

Graph Theoretical Analysis of Brain Network Characteristics in Brain Tumor Patients: A Systematic Review

Graph theory is a branch of mathematics that allows for the characterization of complex networks, and has rapidly grown in popularity in network neuroscience in recent years. Researchers have begun to use graph theory to describe the brain networks of individuals with brain tumors to shed light on disrupted networks. This systematic review summarizes the current literature on graph theoretical analysis of magnetic resonance imaging data in the brain tumor population with particular attention paid to treatment effects and other clinical factors. Included papers were published through June 24^th, 2020. Searches were conducted on Pubmed, PsycInfo, and Web of Science using the search terms (graph theory OR graph analysis) AND (brain tumor OR brain tumour OR brain neoplasm) AND (MRI OR EEG OR MEG). Studies were eligible for inclusion if they: evaluated participants with a primary brain tumor, used graph theoretical analyses on structural or functional MRI data, MEG, or EEG, were in English, and were an empirical research study. Seventeen papers met criteria for inclusion. Results suggest alterations in network properties are often found in people with brain tumors, although the directions of differences are inconsistent and few studies reported effect sizes. The most consistent finding suggests increased network segregation. Changes are most prominent with more intense treatment, in hub regions, and with factors such as faster tumor growth. The use of graph theory to study brain tumor patients is in its infancy, though some conclusions can be drawn. Future studies should focus on treatment factors, changes over time, and correlations with functional outcomes to better identify those in need of early intervention.

Quantitative multimodal imaging in traumatic brain injuries producing impaired cognition

PURPOSE OF REVIEW

Cognitive impairments are a devastating long-term consequence following traumatic brain injury (TBI). This review provides an update on the quantitative mutimodal neuroimaging studies that attempt to elucidate the mechanism(s) underlying cognitive impairments and their recovery following TBI.

RECENT FINDINGS

Recent studies have linked individual specific behavioural impairments and their changes over time to physiological activity and structural changes using EEG, PET and MRI. Multimodal studies that combine measures of physiological activity with knowledge of neuroanatomical and connectivity damage have also illuminated the multifactorial function-structure relationships that underlie impairment and recovery following TBI.

SUMMARY

The combined use of multiple neuroimaging modalities, with focus on individual longitudinal studies, has the potential to accurately classify impairments, enhance sensitivity of prognoses, inform targets for interventions and precisely track spontaneous and intervention-driven recovery.

Network topology changes in chronic mild traumatic brain injury (mTBI)

BACKGROUND

In mild traumatic brain injury (mTBI), diffuse axonal injury results in disruption of functional networks in the brain and is thought to be a major contributor to cognitive dysfunction even years after trauma.

OBJECTIVE

Few studies have assessed longitudinal changes in network topology in chronic mTBI. We utilized a graph theoretical approach to investigate alterations in global network topology based on resting-state functional connectivity in veterans with chronic mTBI.

METHODS

50 veterans with chronic mTBI (mean of 20.7 yrs. from trauma) and 40 age-matched controls underwent two functional magnetic resonance imaging scans 18 months apart. Graph theory analysis was used to quantify network topology measures (density, clustering coefficient, global efficiency, and modularity). Hierarchical linear mixed models were used to examine longitudinal change in network topology.

RESULTS

With all network measures, we found a significant group × time interaction. At baseline, brain networks of individuals with mTBI were less clustered (p = 0.03) and more modular (p = 0.02) than those of HC. Over time, the mTBI networks became more densely connected (p = 0.002), with increased clustering (p = 0.001) and reduced modularity (p < 0.001). Network topology did not change across time in HC.

CONCLUSION

These findings demonstrate that brain networks of individuals with mTBI remain plastic decades after injury and undergo significant changes in network topology even at the later phase of the disease.

Brain bases of recovery following cognitive rehabilitation for traumatic brain injury: a preliminary study

Many patients with traumatic brain injury (TBI) have persistent cognitive deficits, including decreased attention and working memory. This preliminary study examined fMRI data from a clinical trial implementing a 4-week virtual reality driving intervention to assess how sustained training can improve deficits related to traumatic brain injury. Previously-reported behavioral findings showed improvements in working memory and processing speed in those who received the intervention; this report explores the brain bases of these effects by comparing neural activity related to working memory (n-back task) and resting state connectivity before and after the intervention. In the baseline visit (n = 24), working memory activity was prominent in bilateral DLPFC and prefrontal cortex, anterior insula, medial superior frontal gyrus, left thalamus, bilateral supramarginal / angular gyrus, precuneus, and left posterior middle temporal gyrus. Following intervention, participants showed less global activation on the n-back task, with regions of activity only in the bilateral middle frontal cortex, posterior middle frontal gyrus, and supramarginal gyrus. Activity related to working memory load was reduced for the group that went through the intervention (n = 7) compared to the waitlist control group (n = 4). These results suggest that successful cognitive rehabilitation of working memory in TBI may be associated with increased efficiency of brain networks, evidenced by reduced activation of brain activity during cognitive processing. These results highlight the importance of examining brain activity related to cognitive rehabilitation of attention and working memory after brain injury.

Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group's short-term, intermediate, and long-term goals.

Long-term changes in the small-world organization of brain networks after concussion

There is a growing body of literature using functional MRI to study the acute and long-term effects of concussion on functional brain networks. To date, studies have largely focused on changes in pairwise connectivity strength between brain regions. Less is known about how concussion affects whole-brain network topology, particularly the “small-world” organization which facilitates efficient communication at both local and global scales. The present study addressed this knowledge gap by measuring local and global efficiency of 26 concussed athletes at acute injury, return to play (RTP) and one year post-RTP, along with a cohort of 167 athletic controls. On average, concussed athletes showed no alterations in local efficiency but had elevated global efficiency at acute injury, which had resolved by RTP. Athletes with atypically long recovery, however, had reduced global efficiency at 1 year post-RTP, suggesting long-term functional abnormalities for this subgroup. Analyses of nodal efficiency further indicated that global network changes were driven by high-efficiency visual and sensorimotor regions and low-efficiency frontal and subcortical regions. This study provides evidence that concussion causes subtle acute and long-term changes in the small-world organization of the brain, with effects that are related to the clinical profile of recovery.

Mapping default mode connectivity alterations following a single season of subconcussive impact exposure in youth football

Repetitive head impact (RHI) exposure in collision sports may contribute to adverse neurological outcomes in former players. In contrast to a concussion, or mild traumatic brain injury, “subconcussive” RHIs represent a more frequent and asymptomatic form of exposure. The neural network‐level signatures characterizing subconcussive RHIs in youth collision‐sport cohorts such as American Football are not known. Here, we used resting‐state functional MRI to examine default mode network (DMN) functional connectivity (FC) following a single football season in youth players (n = 50, ages 8–14) without concussion. Football players demonstrated reduced FC across widespread DMN regions compared with non‐collision sport controls at postseason but not preseason. In a subsample from the original cohort (n = 17), players revealed a negative change in FC between preseason and postseason and a positive and compensatory change in FC during the offseason across the majority of DMN regions. Lastly, significant FC changes, including between preseason and postseason and between in‐ and off‐season, were specific to players at the upper end of the head impact frequency distribution. These findings represent initial evidence of network‐level FC abnormalities following repetitive, non‐concussive RHIs in youth football. Furthermore, the number of subconcussive RHIs proved to be a key factor influencing DMN FC.

Resting-State Network Plasticity Induced by Music Therapy after Traumatic Brain Injury

Traumatic brain injury (TBI) is characterized by a complex pattern of abnormalities in resting-state functional connectivity (rsFC) and network dysfunction, which can potentially be ameliorated by rehabilitation. In our previous randomized controlled trial, we found that a 3-month neurological music therapy intervention enhanced executive function (EF) and increased grey matter volume in the right inferior frontal gyrus (IFG) in patients with moderate-to-severe TBI (N = 40). Extending this study, we performed longitudinal rsFC analyses of resting-state fMRI data using a ROI-to-ROI approach assessing within-network and between-network rsFC in the frontoparietal (FPN), dorsal attention (DAN), default mode (DMN), and salience (SAL) networks, which all have been associated with cognitive impairment after TBI. We also performed a seed-based connectivity analysis between the right IFG and whole-brain rsFC. The results showed that neurological music therapy increased the coupling between the FPN and DAN as well as between these networks and primary sensory networks. By contrast, the DMN was less connected with sensory networks after the intervention. Similarly, there was a shift towards a less connected state within the FPN and SAL networks, which are typically hyperconnected following TBI. Improvements in EF were correlated with rsFC within the FPN and between the DMN and sensorimotor networks. Finally, in the seed-based connectivity analysis, the right IFG showed increased rsFC with the right inferior parietal and left frontoparietal (Rolandic operculum) regions. Together, these results indicate that the rehabilitative effects of neurological music therapy after TBI are underpinned by a pattern of within- and between-network connectivity changes in cognitive networks as well as increased connectivity between frontal and parietal regions associated with music processing.

Sex-specific differences in resting-state functional connectivity of large-scale networks in postconcussion syndrome

Concussions are associated with a range of cognitive, neuropsychological and behavioral sequelae that, at times, persist beyond typical recovery times and are referred to as postconcussion syndrome (PCS). There is growing support that concussion can disrupt network-based connectivity post-injury. To date, a significant knowledge gap remains regarding the sex-specific impact of concussion on resting state functional connectivity (rs-FC). The aims of this study were to (1) investigate the injury-based rs-FC differences across three large-scale neural networks and (2) explore the sex-specific impact of injury on network-based connectivity. MRI data was collected from a sample of 80 concussed participants who fulfilled the criteria for postconcussion syndrome and 31 control participants who did not have any history of concussion. Connectivity maps between network nodes and brain regions were used to assess connectivity using the Functional Connectivity (CONN) toolbox. Network based statistics showed that concussed participants were significantly different from healthy controls across both salience and fronto-parietal network nodes. More specifically, distinct subnetwork components were identified in the concussed sample, with hyperconnected frontal nodes and hypoconnected posterior nodes across both the salience and fronto-parietal networks, when compared to the healthy controls. Node-to-region analyses showed sex-specific differences across association cortices, however, driven by distinct networks. Sex-specific network-based alterations in rs-FC post concussion need to be examined to better understand the underlying mechanisms and associations to clinical outcomes.

Neural Connectivity Changes Facilitated by Familiar Auditory Sensory Training in Disordered Consciousness: A TBI Pilot Study

For people with disordered consciousness (DoC) after traumatic brain injury (TBI), relationships between treatment-induced changes in neural connectivity and neurobehavioral recovery have not been explored. To begin building a body of evidence regarding the unique contributions of treatments to changes in neural network connectivity relative to neurobehavioral recovery, we conducted a pilot study to identify relationships meriting additional examination in future research. To address this objective, we examined previously unpublished neural connectivity data derived from a randomized clinical trial (RCT). We leveraged these data because treatment efficacy, in the RCT, was based on a comparison of a placebo control with a specific intervention, the familiar auditory sensory training (FAST) intervention, consisting of autobiographical auditory-linguistic stimuli. We selected a subgroup of RCT participants with high-quality imaging data (FAST n = 4 and placebo n = 4) to examine treatment-related changes in brain network connectivity and how and if these changes relate to neurobehavioral recovery. To discover promising relationships among the FAST intervention, changes in neural connectivity, and neurobehavioral recovery, we examined 26 brain regions and 19 white matter tracts associated with default mode, salience, attention, and language networks, as well as three neurobehavioral measures. Of the relationships discovered, the systematic filtering process yielded evidence supporting further investigation of the relationship among the FAST intervention, connectivity of the left inferior longitudinal fasciculus, and auditory-language skills. Evidence also suggests that future mechanistic research should focus on examining the possibility that the FAST supports connectivity changes by facilitating redistribution of brain resources. For a patient population with limited treatment options, the reported findings suggest that a simple, yet targeted, passive sensory stimulation treatment may have altered functional and structural connectivity. If replicated in future research, then these findings provide the foundation for characterizing the unique contributions of the FAST intervention and could inform development of new treatment strategies. For persons with severely damaged brain networks, this report represents a first step toward advancing understanding of the unique contributions of treatments to changing brain network connectivity and how these changes relate to neurobehavioral recovery for persons with DoC after TBI.

Clinical Trial Registry: NCT00557076, The Efficacy of Familiar Voice Stimulation During Coma Recovery (http://www.clinicaltrials.gov).