Decreased Regional Homogeneity in Patients With Acute Mild Traumatic Brain Injury: A Resting-State fMRI Study

Functional Connectivity Changes on Resting-State fMRI after Mild Traumatic Brain Injury: A Systematic Review

BACKGROUND

Mild traumatic brain injury is theorized to cause widespread functional changes to the brain. Resting-state fMRI may be able to measure functional connectivity changes after traumatic brain injury, but resting-state fMRI studies are heterogeneous, using numerous techniques to study ROIs across various resting-state networks.

PURPOSE

We systematically reviewed the literature to ascertain whether adult patients who have experienced mild traumatic brain injury show consistent functional connectivity changes on resting-state -fMRI, compared with healthy patients.

DATA SOURCES

We used 5 databases (PubMed, EMBASE, Cochrane Central, Scopus, Web of Science).

STUDY SELECTION

Five databases (PubMed, EMBASE, Cochrane Central, Scopus, and Web of Science) were searched for research published since 2010. Search strategies used keywords of "functional MR imaging" and "mild traumatic brain injury" as well as related terms. All results were screened at the abstract and title levels by 4 reviewers according to predefined inclusion and exclusion criteria. For full-text inclusion, each study was evaluated independently by 2 reviewers, with discordant screening settled by consensus.

DATA ANALYSIS

Data regarding article characteristics, cohort demographics, fMRI scan parameters, data analysis processing software, atlas used, data characteristics, and statistical analysis information were extracted.

DATA SYNTHESIS

Across 66 studies, 80 areas were analyzed 239 times for at least 1 time point, most commonly using independent component analysis. The most analyzed areas and networks were the whole brain, the default mode network, and the salience network. Reported functional connectivity changes varied, though there may be a slight trend toward decreased whole-brain functional connectivity within 1 month of traumatic brain injury and there may be differences based on the time since injury.

LIMITATIONS

Studies of military, sports-related traumatic brain injury, and pediatric patients were excluded. Due to the high number of relevant studies and data heterogeneity, we could not be as granular in the analysis as we would have liked.

CONCLUSIONS

Reported functional connectivity changes varied, even within the same region and network, at least partially reflecting differences in technical parameters, preprocessing software, and analysis methods as well as probable differences in individual injury. There is a need for novel rs-fMRI techniques that better capture subject-specific functional connectivity changes.

Functional connectivity-hemodynamic (un)coupling changes in chronic mild brain injury are associated with mental health and neurocognitive indices: a resting state fMRI study

PURPOSE

To examine hemodynamic and functional connectivity alterations and their association with neurocognitive and mental health indices in patients with chronic mild traumatic brain injury (mTBI).

METHODS

Resting-state functional MRI (rs-fMRI) and neuropsychological assessment of 37 patients with chronic mTBI were performed. Intrinsic connectivity contrast (ICC) and time-shift analysis (TSA) of the rs-fMRI data allowed the assessment of regional hemodynamic and functional connectivity disturbances and their coupling (or uncoupling). Thirty-nine healthy age- and gender-matched participants were also examined.

RESULTS

Patients with chronic mTBI displayed hypoconnectivity in bilateral hippocampi and parahippocampal gyri and increased connectivity in parietal areas (right angular gyrus and left superior parietal lobule (SPL)). Slower perfusion (hemodynamic lag) in the left anterior hippocampus was associated with higher self-reported symptoms of depression (r =  - 0.53, p = .0006) and anxiety (r =  - 0.484, p = .002), while faster perfusion (hemodynamic lead) in the left SPL was associated with lower semantic fluency (r =  - 0.474, p = .002). Finally, functional coupling (high connectivity and hemodynamic lead) in the right anterior cingulate cortex (ACC)) was associated with lower performance on attention and visuomotor coordination (r =  - 0.50, p = .001), while dysfunctional coupling (low connectivity and hemodynamic lag) in the left ventral posterior cingulate cortex (PCC) and right SPL was associated with lower scores on immediate passage memory (r =  - 0.52, p = .001; r =  - 0.53, p = .0006, respectively). Uncoupling in the right extrastriate visual cortex and posterior middle temporal gyrus was negatively associated with cognitive flexibility (r =  - 0.50, p = .001).

CONCLUSION

Hemodynamic and functional connectivity differences, indicating neurovascular (un)coupling, may be linked to mental health and neurocognitive indices in patients with chronic mTBI.

Repetitive mild closed-head injury induced synapse loss and increased local BOLD-fMRI signal homogeneity

Repeated mild head injuries due to sports, or domestic violence and military service are increasingly linked to debilitating symptoms in the long term. Although symptoms may take decades to manifest, potentially treatable neurobiological alterations must begin shortly after injury. Better means to diagnose and treat traumatic brain injuries, requires an improved understanding of the mechanisms underlying progression and means through which they can be measured. Here, we employ a repetitive mild closed-head injury (rmTBI) and chronic variable stress (CVS) mouse model to investigate emergent structural and functional brain abnormalities. Brain imaging is achieved with [ 18 F]SynVesT-1 positron emission tomography, with the synaptic vesicle glycoprotein 2A ligand marking synapse density and BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI). Animals were scanned six weeks after concluding rmTBI/Stress procedures. Injured mice showed widespread decreases in synaptic density coupled with an i ncrease in local BOLD-fMRI synchrony detected as regional homogeneity. Injury-affected regions with higher synapse density showed a greater increase in fMRI regional homogeneity. Taken together, these observations may reflect compensatory mechanisms following injury. Multimodal studies are needed to provide deeper insights into these observations.

A Comprehensive and Broad Approach to Resting-State Functional Connectivity in Adult Patients with Mild Traumatic Brain Injury

BACKGROUND AND PURPOSE

Several recent works using resting-state fMRI suggest possible alterations of resting-state functional connectivity after mild traumatic brain injury. However, the literature is plagued by various analysis approaches and small study cohorts, resulting in an inconsistent array of reported findings. In this study, we aimed to investigate differences in whole-brain resting-state functional connectivity between adult patients with mild traumatic brain injury within 1 month of injury and healthy control subjects using several comprehensive resting-state functional connectivity measurement methods and analyses.

MATERIALS AND METHODS

A total of 123 subjects (72 patients with mild traumatic brain injury and 51 healthy controls) were included. A standard fMRI preprocessing pipeline was used. ROI/seed-based analyses were conducted using 4 standard brain parcellation methods, and the independent component analysis method was applied to measure resting-state functional connectivity. The fractional amplitude of low-frequency fluctuations was also measured. Group comparisons were performed on all measurements with appropriate whole-brain multilevel statistical analysis and correction.

RESULTS

There were no significant differences in age, sex, education, and hand preference between groups as well as no significant correlation between all measurements and these potential confounders. We found that each resting-state functional connectivity measurement revealed various regions or connections that were different between groups. However, after we corrected for multiple comparisons, the results showed no statistically significant differences between groups in terms of resting-state functional connectivity across methods and analyses.

CONCLUSIONS

Although previous studies point to multiple regions and networks as possible mild traumatic brain injury biomarkers, this study shows that the effect of mild injury on brain resting-state functional connectivity has not survived after rigorous statistical correction. A further study using subject-level connectivity analyses may be necessary due to both subtle and variable effects of mild traumatic brain injury on brain functional connectivity across individuals.

Deep learning-based multimodality classification of chronic mild traumatic brain injury using resting-state functional MRI and PET imaging

Mild traumatic brain injury (mTBI) is a public health concern. The present study aimed to develop an automatic classifier to distinguish between patients with chronic mTBI (n = 83) and healthy controls (HCs) (n = 40). Resting-state functional MRI (rs-fMRI) and positron emission tomography (PET) imaging were acquired from the subjects. We proposed a novel deep-learning-based framework, including an autoencoder (AE), to extract high-level latent and rectified linear unit (ReLU) and sigmoid activation functions. Single and multimodality algorithms integrating multiple rs-fMRI metrics and PET data were developed. We hypothesized that combining different imaging modalities provides complementary information and improves classification performance. Additionally, a novel data interpretation approach was utilized to identify top-performing features learned by the AEs. Our method delivered a classification accuracy within the range of 79-91.67% for single neuroimaging modalities. However, the performance of classification improved to 95.83%, thereby employing the multimodality model. The models have identified several brain regions located in the default mode network, sensorimotor network, visual cortex, cerebellum, and limbic system as the most discriminative features. We suggest that this approach could be extended to the objective biomarkers predicting mTBI in clinical settings.

Identification of chronic mild traumatic brain injury using resting state functional MRI and machine learning techniques

Mild traumatic brain injury (mTBI) is a major public health concern that can result in a broad spectrum of short-term and long-term symptoms. Recently, machine learning (ML) algorithms have been used in neuroscience research for diagnostics and prognostic assessment of brain disorders. The present study aimed to develop an automatic classifier to distinguish patients suffering from chronic mTBI from healthy controls (HCs) utilizing multilevel metrics of resting-state functional magnetic resonance imaging (rs-fMRI). Sixty mTBI patients and forty HCs were enrolled and allocated to training and testing datasets with a ratio of 80:20. Several rs-fMRI metrics including fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), degree centrality (DC), voxel-mirrored homotopic connectivity (VMHC), functional connectivity strength (FCS), and seed-based FC were generated from two main analytical categories: local measures and network measures. Statistical two-sample t-test was employed comparing between mTBI and HCs groups. Then, for each rs-fMRI metric the features were selected extracting the mean values from the clusters showing significant differences. Finally, the support vector machine (SVM) models based on separate and multilevel metrics were built and the performance of the classifiers were assessed using five-fold cross-validation and via the area under the receiver operating characteristic curve (AUC). Feature importance was estimated using Shapley additive explanation (SHAP) values. Among local measures, the range of AUC was 86.67-100% and the optimal SVM model was obtained based on combined multilevel rs-fMRI metrics and DC as a separate model with AUC of 100%. Among network measures, the range of AUC was 80.42-93.33% and the optimal SVM model was obtained based on the combined multilevel seed-based FC metrics. The SHAP analysis revealed the DC value in the left postcentral and seed-based FC value between the motor ventral network and right superior temporal as the most important local and network features with the greatest contribution to the classification models. Our findings demonstrated that different rs-fMRI metrics can provide complementary information for classifying patients suffering from chronic mTBI. Moreover, we showed that ML approach is a promising tool for detecting patients with mTBI and might serve as potential imaging biomarker to identify patients at individual level.

Clinical trial registration

[clinicaltrials.gov], identifier [NCT03241732].

Combining MRI and cognitive evaluation to classify concussion in university athletes

Current methods of concussion assessment lack the objectivity and reliability to detect neurological injury. This multi-site study uses combinations of neuroimaging (diffusion tensor imaging and resting state functional MRI) and cognitive measures to train algorithms to detect the presence of concussion in university athletes. Athletes (29 concussed, 48 controls) completed symptom reports, brief cognitive evaluation, and MRI within 72 h of injury. Hierarchical linear regression compared groups on cognitive and neuroimaging measures while controlling for sex and data collection site. Logistic regression and support vector machine models were trained using cognitive and neuroimaging measures and evaluated for overall accuracy, sensitivity, and specificity. Concussed athletes reported greater symptoms than controls (∆R² = 0.32, p < .001), and performed worse on tests of concentration (∆R² = 0.07, p < .05) and delayed memory (∆R² = 0.17, p < .001). Concussed athletes showed lower functional connectivity within the frontoparietal and primary visual networks (p < .05), but did not differ on mean diffusivity and fractional anisotropy. Of the cognitive measures, classifiers trained using delayed memory yielded the best performance with overall accuracy of 71%, though sensitivity was poor at 46%. Of the neuroimaging measures, classifiers trained using mean diffusivity yielded similar accuracy. Combining cognitive measures with mean diffusivity increased overall accuracy to 74% and sensitivity to 64%, comparable to the sensitivity of symptom report. Trained algorithms incorporating both MRI and cognitive performance variables can reliably detect common neurobiological sequelae of acute concussion. The integration of multi-modal data can serve as an objective, reliable tool in the assessment and diagnosis of concussion.

Resting-State Functional MRI Metrics in Patients With Chronic Mild Traumatic Brain Injury and Their Association With Clinical Cognitive Performance

Mild traumatic brain injury (mTBI) accounts for more than 80% of people experiencing brain injuries. Symptoms of mTBI include short-term and long-term adverse clinical outcomes. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was conducted to measure voxel-based indices including fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) in patients suffering from chronic mTBI; 64 patients with chronic mTBI at least 3 months post injury and 40 healthy controls underwent rs-fMRI scanning. Partial correlation analysis controlling for age and gender was performed within mTBI cohort to explore the association between rs-fMRI metrics and neuropsychological scores. Compared with controls, chronic mTBI patients showed increased fALFF in the left middle occipital cortex (MOC), right middle temporal cortex (MTC), and right angular gyrus (AG), and increased ReHo in the left MOC and left posterior cingulate cortex (PCC). Enhanced FC was observed from left MOC to right precuneus; from right MTC to right superior temporal cortex (STC), right supramarginal, and left inferior parietal cortex (IPC); and from the seed located at right AG to left precuneus, left superior medial frontal cortex (SMFC), left MTC, left superior temporal cortex (STC), and left MOC. Furthermore, the correlation analysis revealed a significant correlation between neuropsychological scores and fALFF, ReHo, and seed-based FC measured from the regions with significant group differences. Our results demonstrated that alterations of low-frequency oscillations in chronic mTBI could be representative of disruption in emotional circuits, cognitive performance, and recovery in this cohort.

Machine Learning Classification of Mild Traumatic Brain Injury Using Whole-Brain Functional Activity: A Radiomics Analysis

Objectives

To investigate the classification performance of support vector machine in mild traumatic brain injury (mTBI) from normal controls.

Methods

Twenty-four mTBI patients (15 males and 9 females; mean age, 38.88 ± 13.33 years) and 24 age and sex-matched normal controls (13 males and 11 females; mean age, 40.46 ± 11.4 years) underwent resting-state functional MRI examination. Seven imaging parameters, including amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), degree centrality (DC), voxel-mirrored homotopic connectivity (VMHC), long-range functional connectivity density (FCD), and short-range FCD, were entered into the classification model to distinguish the mTBI from normal controls.

Results

The ability for any single imaging parameters to distinguish the two groups is lower than multiparameter combinations. The combination of ALFF, fALFF, DC, VMHC, and short-range FCD showed the best classification performance for distinguishing the two groups with optimal AUC value of 0.778, accuracy rate of 81.11%, sensitivity of 88%, and specificity of 75%. The brain regions with the highest contributions to this classification mainly include bilateral cerebellum, left orbitofrontal cortex, left cuneus, left temporal pole, right inferior occipital cortex, bilateral parietal lobe, and left supplementary motor area.

Conclusions

Multiparameter combinations could improve the classification performance of mTBI from normal controls by using the brain regions associated with emotion and cognition.

Neuroimaging Correlates of Syndromal Anxiety Following Traumatic Brain Injury: A Systematic Review of the Literature

BACKGROUND

Traumatic brain injury (TBI) can precipitate new-onset psychiatric symptoms or worsen existing psychiatric conditions. To elucidate specific mechanisms for this interaction, neuroimaging is often used to study both psychiatric conditions and TBI. This systematic review aims to synthesize the existing literature of neuroimaging findings among patients with anxiety after TBI.

METHODS

We conducted a Preferred Reporting Items for Systematic Review and Meta-Analyses-compliant literature search via PubMed (MEDLINE), PsychINFO, EMBASE, and Scopus databases before May, 2019. We included studies that clearly defined TBI, measured syndromic anxiety as a primary outcome, and statistically analyzed the relationship between neuroimaging findings and anxiety symptoms.

RESULTS

A total of 5982 articles were retrieved from the systematic search, of which 65 studied anxiety and 13 met eligibility criteria. These studies were published between 2004 and 2017, collectively analyzing 764 participants comprised of 470 patients with TBI and 294 non-TBI controls. Imaging modalities used included magnetic resonance imaging, functional magnetic resonance imaging, diffusion tensor imaging, electroencephalogram, magnetic resonance spectrometry, and magnetoencephalography. Eight of 13 studies presented at least one significant finding and together reflect a complex set of changes that lead to anxiety in the setting of TBI. The left cingulate gyrus in particular was found to be significant in 2 studies using different imaging modalities. Two studies also revealed perturbances in functional connectivity within the default mode network.

CONCLUSIONS

This is the first systemic review of neuroimaging changes associated with anxiety after TBI, which implicated multiple brain structures and circuits, such as the default mode network. Future research with consistent, rigorous measurements of TBI and syndromic anxiety, as well as attention to control groups, previous TBIs, and time interval between TBI and neuroimaging, are warranted. By understanding neuroimaging correlates of psychiatric symptoms, this work could inform future post-TBI screening and surveillance, preventative efforts, and early interventions to improve neuropsychiatric outcomes.

Multi-Modal Analysis of Resting-State fMRI Data in mTBI Patients and Association With Neuropsychological Outcomes

Various cognitive disorders have been reported for mild traumatic brain injury (mTBI) patients during the acute stage. This acute stage provides an opportunity for clinicians to optimize treatment protocols, which are based on the evaluation of brain structural connectivity. So far, most brain functional magnetic resonance imaging studies are focused on moderate to severe traumatic brain injuries (TBIs). In this study, we prospectively collected resting state data on 50 mTBI within 3 days of injury and 50 healthy volunteers and analyzed them using Amplitude of low-frequency fluctuation (ALFF), Regional Homogeneity (ReHo), graph theory methods and behavior measure, to explore the dysfunctional brain regions in acute mTBI. In our study, a total of 50 patients suffering <3 days mTBI and 50 healthy subjects were tested in rs-fMRI, as well as under neuropsychological examinations including the Wechsler Intelligence Scale and Stroop Color and Word Test. The correlation analysis was conducted between graph theoretic parameters and neuropsychological results. For the mTBI group, the ReHo of the inferior temporal gyrus and the cerebellum superior are significantly lower than in the control group, and the ALFF of the left insula, the cerebellum inferior, and the middle occipital gyrus were significantly higher than in the control group, which implies the dysfunctionality usually observed in Parkinson's disease. Executive function disorder was significantly correlated with the global efficiencies of the dorsolateral superior frontal gyrus and the anterior cingulate cortex, which is consistent with the literature: the acute mTBI patients demonstrate abnormality in terms of motor speed, association, information processing speed, attention, and short-term memory function. Correlation analysis between the neuropsychological outcomes and the network efficiency for the mTBI group indicates that executive dysfunction might be caused by local brain changes. Our data support the idea that the cerebral internal network has compensatory reactions in response to sudden pathological and neurophysiological changes. In the future, multimode rs-fMRI analysis could be a valuable tool for evaluating dysfunctional brain regions after mTBI.

A roadmap of brain recovery in a mouse model of concussion: insights from neuroimaging

Concussion or mild traumatic brain injury is the most common form of traumatic brain injury with potentially long-term consequences. Current objective diagnosis and treatment options are limited to clinical assessment, cognitive rest, and symptom management, which raises the real danger of concussed patients being released back into activities where subsequent and cumulative injuries may cause disproportionate damages. This study conducted a cross-sectional multi-modal examination investigation of the temporal changes in behavioural and brain changes in a mouse model of concussion using magnetic resonance imaging. Sham and concussed mice were assessed at day 2, day 7, and day 14 post-sham or injury procedures following a single concussion event for motor deficits, psychological symptoms with open field assessment, T2-weighted structural imaging, diffusion tensor imaging (DTI), neurite orientation density dispersion imaging (NODDI), stimulus-evoked and resting-state functional magnetic resonance imaging (fMRI). Overall, a mismatch in the temporal onsets and durations of the behavioural symptoms and structural/functional changes in the brain was seen. Deficits in behaviour persisted until day 7 post-concussion but recovered at day 14 post-concussion. DTI and NODDI changes were most extensive at day 7 and persisted in some regions at day 14 post-concussion. A persistent increase in connectivity was seen at day 2 and day 14 on rsfMRI. Stimulus-invoked fMRI detected increased cortical activation at day 7 and 14 post-concussion. Our results demonstrate the capabilities of advanced MRI in detecting the effects of a single concussive impact in the brain, and highlight a mismatch in the onset and temporal evolution of behaviour, structure, and function after a concussion. These results have significant translational impact in developing methods for the detection of human concussion and the time course of brain recovery.

Resting-State Power and Regional Connectivity After Pediatric Mild Traumatic Brain Injury

BACKGROUND

Physiological recovery from pediatric mild traumatic brain injury (pmTBI) as a function of age remains actively debated, with the majority of studies relying on subjective symptom report rather than objective markers of brain physiology.

PURPOSE

To examine potential abnormalities in fractional amplitude of low-frequency fluctuations (fALFF) or regional homogeniety (ReHo) during resting-state fMRI following pmTBI.

STUDY TYPE

Prospective cohort.

POPULATION

Consecutively recruited pmTBI (N = 105; 8-18 years old) and age- and sex-matched healthy controls (HC; N = 113).

FIELD STRENGTH/SEQUENCE

3T multiecho gradient T1 -weighted and single-shot gradient-echo echo-planar imaging.

ASSESSMENT

All pmTBI participants were assessed 1 week and 4 months postinjury (HC assessed at equivalent timepoints after the first visit). Comprehensive demographic, clinical, and cognitive batteries were performed in addition to primary investigation of fALFF and ReHo. All pmTBI were classified as "persistent" or "recovered" based on both assessment periods.

STATISTICAL TESTS

Chi-square, nonparametric, and generalized linear models for demographic data. Generalized estimating equations for clinical and cognitive data. Voxelwise general linear models (AFNI's 3dMVM) for fALFF and ReHo assessment.

RESULTS

Evidence of recovery was observed for some, but not all, clinical and cognitive measures at 4 months postinjury. fALFF was increased in the left striatum for pmTBI relative to HC both at 1 week and 4 months postinjury; whereas no significant group differences (P > 0.001) were observed for ReHo. Age-at-injury did not moderate either resting-state metric across groups. In contrast to analyses of pmTBI as a whole, there were no significant (P > 0.001) differences in either fALFF or ReHo in patients with persistent postconcussive symptoms compared to recovered patients and controls at 4 months postinjury.

DATA CONCLUSIONS

Our findings suggest prolonged clinical recovery and alterations in the relative amplitude of resting-state fluctuations up to 4 months postinjury, but no clear relationship with age-at-injury or subjective symptom report.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: 2 J. MAGN. RESON. IMAGING 2020;52:1701-1713.

Neuroimaging and Psychometric Assessment of Mild Cognitive Impairment After Traumatic Brain Injury

Traumatic brain injury (TBI) can be serious partly due to the challenges of assessing and treating its neurocognitive and affective sequelae. The effects of a single TBI may persist for years and can limit patients’ activities due to somatic complaints (headaches, vertigo, sleep disturbances, nausea, light or sound sensitivity), affective sequelae (post-traumatic depressive symptoms, anxiety, irritability, emotional instability) and mild cognitive impairment (MCI, including social cognition disturbances, attention deficits, information processing speed decreases, memory degradation and executive dysfunction). Despite a growing amount of research, study comparison and knowledge synthesis in this field are problematic due to TBI heterogeneity and factors like injury mechanism, age at or time since injury. The relative lack of standardization in neuropsychological assessment strategies for quantifying sequelae adds to these challenges, and the proper administration of neuropsychological testing relative to the relationship between TBI, MCI and neuroimaging has not been reviewed satisfactorily. Social cognition impairments after TBI (e.g., disturbed emotion recognition, theory of mind impairment, altered self-awareness) and their neuroimaging correlates have not been explored thoroughly. This review consolidates recent findings on the cognitive and affective consequences of TBI in relation to neuropsychological testing strategies, to neurobiological and neuroimaging correlates, and to patient age at and assessment time after injury. All cognitive domains recognized by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) are reviewed, including social cognition, complex attention, learning and memory, executive function, language and perceptual-motor function. Affect and effort are additionally discussed owing to their relationships to cognition and to their potentially confounding effects. Our findings highlight non-negligible cognitive and affective impairments following TBI, their gravity often increasing with injury severity. Future research should study (A) language, executive and perceptual-motor function (whose evolution post-TBI remains under-explored), (B) the effects of age at and time since injury, and (C) cognitive impairment severity as a function of injury severity. Such efforts should aim to develop and standardize batteries for cognitive subdomains—rather than only domains—with high ecological validity. Additionally, they should utilize multivariate techniques like factor analysis and related methods to clarify which cognitive subdomains or components are indeed measured by standardized tests.

Resting-State fMRI Metrics in Acute Sport-Related Concussion and Their Association with Clinical Recovery: A Study from the NCAA-DOD CARE Consortium

There has been a recent call for longitudinal cohort studies to track the physiological recovery of sport-related concussion (SRC) and its relationship with clinical recovery. Resting-state functional magnetic resonance imaging (rs-fMRI) has shown potential for detecting subtle changes in brain function after SRC. We investigated the effects of SRC on rs-fMRI metrics assessing local connectivity (regional homogeneity; REHO), global connectivity (average nodal strength), and the relative amplitude of slow oscillations of rs-fMRI (fractional amplitude of low-frequency fluctuations; fALFF). Athletes diagnosed with SRC (n = 92) completed visits with neuroimaging at 24-48 h post-injury (24 h), after clearance to begin the return-to-play (RTP) progression (asymptomatic), and 7 days following unrestricted RTP (post-RTP). Non-injured athletes (n = 82) completed visits yoked to the schedule of matched injured athletes and served as controls. Concussed athletes had elevated symptoms, worse neurocognitive performance, greater balance deficits, and elevated psychological symptoms at the 24-h visit relative to controls. These deficits were largely recovered by the asymptomatic visit. Concussed athletes still reported elevated psychological symptoms at the asymptomatic visit relative to controls. Concussed athletes also had elevated REHO in the right middle and superior frontal gyri at the 24-h visit that returned to normal levels by the asymptomatic visit. Additionally, REHO in these regions at 24 h predicted psychological symptoms at the asymptomatic visit in concussed athletes. Current results suggest that SRC is associated with an acute alteration in local connectivity that follows a similar time course as clinical recovery. Our results do not indicate strong evidence that concussion-related alterations in rs-fMRI persist beyond clinical recovery.

Functional brain effects of acute concussion in Australian rules football players

Aim

To determine whether acute sport-related concussion is associated with functional brain changes in Australian rules footballers.

Methods

Twenty acutely concussed professional Australian footballers were studied with 3 T magnetic resonance imaging and compared to 20 age-matched control subjects. We statistically compared whole-brain local functional magnetic resonance imaging connectivity between acutely concussed footballers and controls using voxel-wise permutation testing.

Results

The acutely concussed football players had significantly decreased local functional magnetic resonance imaging connectivity in the right dorsolateral prefrontal cortex, right inferior parietal lobe, and right anterior insula, compared to controls. No functional brain changes between groups within the default mode network were observed.

Discussion

Acutely concussed footballers had in common decreased functional connectivity within the right lateralized “cognitive control network” of the brain that is involved in executive functions, and the “salience network” involved in switching between tasks. Dysfunction of these brain regions is a plausible explanation for typical clinical features of concussion.

Functional connectivity disruption of the substantia nigra associated with cognitive impairment in acute mild traumatic brain injury

PURPOSE

Mild traumatic brain injury is known to have frequent cognitive impairment. Accumulating evidence is pointing to the malfunctioning of the substantia nigra (SN) as an important factor for head trauma. However, it remains unknown whether changes in the SN-based resting state functional connectivity following mTBI at acute stage and its relationship with cognitive function.

MATERIALS AND METHODS

58 patients with mTBI and 30 age-, gender-, and years of education-matched healthy controls were enrolled in the current study. All of participants received resting state functional magnetic resonance imaging as well as neuropsychological assessment. The resting state functional MR imaging data were analyzed by using a standard seed-based whole-brain correlation method to characterize SN resting state networks. Student t tests were used to perform comparisons. The association between SN resting state networks and performance on neuropsychological measures was also investigated in patients with mTBI by using Pearson rank correlation.

RESULTS

Patients with mTBI at acute stage exhibited reduced left SN-based functional connectivity with right insula and caudate and increased left SN-based functional connectivity with left precuneus and left middle occipital gyrus, and reduced right SN-based functional connectivity with left insula. Increased functional connectivity of left precuneus was negatively associated with neurocognitive functions as well (r = -0.266; P =  0.049).

CONCLUSION

The present study indicated that patients with acute mTBI suffer from disruption in their SN resting state networks. Moreover, abnormal functional connectivity significantly correlated with cognitive function. Taking together, these results may better improve our understanding of the neuropathological mechanism underlying the neurocognitive symptoms associated with acute mTBI.

Investigating the effects of subconcussion on functional connectivity using mass-univariate and multivariate approaches

There are concerns about the effects of subconcussive head impacts in sport, but the effects of subconcussion on brain connectivity are not well understood. We hypothesized that college football players experience changes in brain functional connectivity not found in athletes competing in lower impact sports or healthy controls. These changes may be spatially heterogeneous across participants, requiring analysis methods that go beyond mass-univariate approaches commonly used in functional MRI (fMRI). To test this hypothesis, we analyzed resting-state fMRI data from college football (n = 15), soccer (n = 12), and lacrosse players (n = 16), and controls (n = 29) collected at preseason and postseason time points. Regional homogeneity (ReHo) and degree centrality (DC) were calculated as measures of local and long-range functional connectivity, respectively. Standard voxel-wise analysis and paired support vector machine (SVM) classification studied subconcussion's effects on local and global functional connectivity. Voxel-wise analyses yielded minimal findings, but SVM classification had high accuracy for college football's ReHo (87%, p = 0.009) and no other group. The findings suggest subconcussion results in spatially heterogeneous changes in local functional connectivity that may only be detectible with multivariate analyses. To determine if voxel-wise and SVM analyses had similar spatial patterns, region-average t-statistic and SVM weight values were compared using a measure of ranking distance. T-statistic and SVM weight rankings exhibited significantly low ranking distance values for all groups and metrics, demonstrating that the analyses converged on a similar underlying effect. Overall, this research suggests that subconcussion in football may produce local functional connectivity changes similar to concussion.

Functional MR Imaging: Blood Oxygen Level-Dependent and Resting State Techniques in Mild Traumatic Brain Injury

This article discusses mild traumatic brain injury (mTBI)-associated effects on brain functional connectivity assessed via resting-state functional MR (fMR) imaging. Several studies have reported acute post-injury default mode network hyperconnectivity, followed by a period of decreased connectivity before later connectivity normalization in some patients. Other studies have reported mTBI associated effects on connectivity that remain evident for up to 5-years or more. Discordance in the published literature regarding the direction of network connectivity changes (eg, increased versus decreased connectivity) may reflect differences in timing of data collection post-injury, as well as the need to standardize MR imaging acquisition protocols and processing methods.

Regional Homogeneity Changes in Nicotine Addicts by Resting-State fMRI

Objective

To reveal the brain functional changes of nicotine addicts compared with those of non-smokers and explore the objective biomarker for nicotine dependence evaluation.

Methods

A total of 14 smokers and 11 non-smoking controls were recruited for this study. Resting-state functional magnetic resonance imaging and regional homogeneity (ReHo) were applied in the neural activity analysis. Two-sample t-test was performed to examine the voxel-wise difference between the smokers and the controls. Correlation analysis between the ReHo values and the Fagerstrom Test for Nicotine Dependence (FTND) scores were performed to explore the biomarkers for the clinical characteristics of smokers.

Results

The ReHo values from the right superior frontal gyrus of the Brodmann’s area (BA) 9 to the right middle frontal gyrus and the ReHo value from the left and right precuneus (BA 23) to the left and right middle cingulum gyrus were lower in the smokers than in the non-smokers. The ReHo value in the precuneus (BA 23) was significantly and positively correlated with the FTND score of smokers.

Conclusion

The ReHo values in the right superior frontal gyrus and left precuneus can be used to separate the smokers from the non-smokers. In particular, the left precuneus is a potential neuroimaging biomarker for nicotine addicts.

Resting-State Magnetoencephalography Reveals Different Patterns of Aberrant Functional Connectivity in Combat-Related Mild Traumatic Brain Injury

Blast mild traumatic brain injury (mTBI) is a leading cause of sustained impairment in military service members and veterans. However, the mechanism of persistent disability is not fully understood. The present study investigated disturbances in brain functioning in mTBI participants using a source-imaging-based approach to analyze functional connectivity (FC) from resting-state magnetoencephalography (rs-MEG). Study participants included 26 active-duty service members or veterans who had blast mTBI with persistent post-concussive symptoms, and 22 healthy control active-duty service members or veterans. The source time courses from regions of interest (ROIs) were used to compute ROI to whole-brain (ROI-global) FC for different frequency bands using two different measures: 1) time-lagged cross-correlation and 2) phase-lock synchrony. Compared with the controls, blast mTBI participants showed increased ROI-global FC in beta, gamma, and low-frequency bands, but not in the alpha band. Sources of abnormally increased FC included the: 1) prefrontal cortex (right ventromedial prefrontal cortex [vmPFC], right rostral anterior cingulate cortex [rACC]), and left ventrolateral and dorsolateral prefrontal cortex; 2) medial temporal lobe (bilateral parahippocampus, hippocampus, and amygdala); and 3) right putamen and cerebellum. In contrast, the blast mTBI group also showed decreased FC of the right frontal pole. Group differences were highly consistent across the two different FC measures. FC of the left ventrolateral prefrontal cortex correlated with executive functioning and processing speed in mTBI participants. Altogether, our findings of increased and decreased regionalpatterns of FC suggest that disturbances in intrinsic brain connectivity may be the result of multiple mechanisms, and are associated with cognitive sequelae of the injury.

Connectomic and Surface-Based Morphometric Correlates of Acute Mild Traumatic Brain Injury

Reduced integrity of white matter (WM) pathways and subtle anomalies in gray matter (GM) morphology have been hypothesized as mechanisms in mild traumatic brain injury (mTBI). However, findings on structural brain changes in early stages after mTBI are inconsistent and findings related to early symptoms severity are rare. Fifty-one patients were assessed with multimodal neuroimaging and clinical methods exclusively within 7 days following mTBI and compared to 53 controls. Whole-brain connectivity based on diffusion tensor imaging was subjected to network-based statistics, whereas cortical surface area, thickness, and volume based on T1-weighted MRI scans were investigated using surface-based morphometric analysis. Reduced connectivity strength within a subnetwork of 59 edges located predominantly in bilateral frontal lobes was significantly associated with higher levels of self-reported symptoms. In addition, cortical surface area decreases were associated with stronger complaints in five clusters located in bilateral frontal and postcentral cortices, and in the right inferior temporal region. Alterations in WM and GM were localized in similar brain regions and moderately-to-strongly related to each other. Furthermore, the reduction of cortical surface area in the frontal regions was correlated with poorer attentive-executive performance in the mTBI group. Finally, group differences were detected in both the WM and GM, especially when focusing on a subgroup of patients with greater complaints, indicating the importance of classifying mTBI patients according to severity of symptoms. This study provides evidence that mTBI affects not only the integrity of WM networks by means of axonal damage but also the morphology of the cortex during the initial post-injury period. These anomalies might be greater in the acute period than previously believed and the involvement of frontal brain regions was consistently pronounced in both findings. The dysconnected subnetwork suggests that mTBI can be conceptualized as a dysconnection syndrome. It remains unclear whether reduced WM integrity is the trigger for changes in cortical surface area or whether tissue deformations are the direct result of mechanical forces acting on the brain. The findings suggest that rapid identification of high-risk patients with the use of clinical scales should be assessed acutely as part of the mTBI protocol.