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

EEG Oscillatory Activity and Resting-State Networks Associated with Neurocognitive Function in Mild Traumatic Brain Injury

This study aimed to investigate the characteristics of resting-state electroencephalography (EEG) activity and brain networks in patients with mild traumatic brain injury (mTBI) and their association with neurocognitive function (NCF). We analyzed 26 patients with subacute mTBI and 21 healthy controls. The subacute mTBI group (9 females, 17 males) had a mean age of 29.9 ± 9.9 years, and the healthy controls (11 females, 10 males) had a mean age of 29.7 ± 11.5 years. Current source density, lagged phase synchronization, and resting-state network activity were analyzed using exact low-resolution electromagnetic tomography (eLORETA) with 60 s resting-state EEG data. In addition, a correlation analysis was performed between these EEG parameters and NCF in patients with mTBI. We used the statistical nonparametric mapping method in eLORETA to correct for multiple comparisons. There were no significant differences in EEG parameters between the patients with mTBI and healthy controls. However, in patients with mTBI, correlation analysis revealed negative correlations between theta activity in the anterior cingulate cortex and verbal short-term memory and between activity in the memory perception network and verbal memory. Our findings suggest that resting-state EEG may be clinically useful in investigating the mechanism of NCF decline in patients with mTBI.

Subclinical brain manifestations of repeated mild traumatic brain injury are changed by chronic exposure to sleep loss, caffeine, and sleep aids

INTRODUCTION

After mild traumatic brain injury (mTBI), the brain is labile for weeks and months and vulnerable to repeated concussions. During this time, patients are exposed to everyday circumstances that, in themselves, affect brain metabolism and blood flow and neural processing. How commonplace activities interact with the injured brain is unknown. The present study in an animal model investigated the extent to which three commonly experienced exposures-daily caffeine usage, chronic sleep loss, and chronic sleep aid medication-affect the injured brain in the chronic phase.

METHODS

Subclinical trauma by repeated mTBIs was produced by our head rotational acceleration injury model, which causes brain injury consistent with the mechanism of concussion in humans. Forty-eight hours after a third mTBI, chronic administrations of caffeine, sleep restriction, or zolpidem (sedative hypnotic) began and were continued for 70 days. On Days 30 and 60 post injury, resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed.

RESULTS

Chronic caffeine, sleep restriction, and zolpidem each changed the subclinical brain characteristics of mTBI at both 30 and 60 days post injury, detected by different MRI modalities. Each treatment caused microstructural alterations in DTI metrics in the insular cortex and retrosplenial cortex compared with mTBI, but also uniquely affected other gray and white matter regions. Zolpidem administration affected the largest number of individual structures in mTBI at both 30 and 60 days, and not necessarily toward normalization (sham treatment). Chronic sleep restriction changed local functional connectivity at 30 days in diametrical opposition to chronic caffeine ingestion, and both treatment outcomes were different from sham, mTBI-only and zolpidem comparisons. The results indicate that commonly encountered exposures modify subclinical brain activity and structure long after healing is expected to be complete.

CONCLUSIONS

Changes in activity and structure detected by fMRI are widely understood to reflect changes in the functions of the affected region which conceivably underlie mTBI neuropathology and symptomatology in the chronic phase after injury.

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.

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.

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.

Sleep loss, caffeine, sleep aids and sedation modify brain abnormalities of mild traumatic brain injury

Little evidence exists about how mild traumatic brain injury (mTBI) is affected by commonly encountered exposures of sleep loss, sleep aids, and caffeine that might be potential therapeutic opportunities. In addition, while propofol sedation is administered in severe TBI, its potential utility in mild TBI is unclear. Each of these exposures is known to have pronounced effects on cerebral metabolism and blood flow and neurochemistry. We hypothesized that they each interact with cerebral metabolic dynamics post-injury and change the subclinical characteristics of mTBI. MTBI in rats was produced by head rotational acceleration injury that mimics the biomechanics of human mTBI. Three mTBIs spaced 48 h apart were used to increase the likelihood that vulnerabilities induced by repeated mTBI would be manifested without clinically relevant structural damage. After the third mTBI, rats were immediately sleep deprived or administered caffeine or suvorexant (an orexin antagonist and sleep aid) for the next 24 h or administered propofol for 5 h. Resting state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) were performed 24 h after the third mTBI and again after 30 days to determine changes to the brain mTBI phenotype. Multi-modal analyses on brain regions of interest included measures of functional connectivity and regional homogeneity from rs-fMRI, and mean diffusivity (MD) and fractional anisotropy (FA) from DTI. Each intervention changed the mTBI profile of subclinical effects that presumably underlie healing, compensation, damage, and plasticity. Sleep loss during the acute post-injury period resulted in dramatic changes to functional connectivity. Caffeine, propofol sedation and suvorexant were especially noteworthy for differential effects on microstructure in gray and white matter regions after mTBI. The present results indicate that commonplace exposures and short-term sedation alter the subclinical manifestations of repeated mTBI and therefore likely play roles in symptomatology and vulnerability to damage by repeated mTBI.

Attention Please! Unravelling the Link Between Brain Network Connectivity and Cognitive Attention Following Acquired Brain Injury: A Systematic Review of Structural and Functional Measures

Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.

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.

Treatment effects of N-acetyl cysteine on resting-state functional MRI and cognitive performance in patients with chronic mild traumatic brain injury: a longitudinal study

Mild traumatic brain injury (mTBI) is a significant public health concern, specially characterized by a complex pattern of abnormal neural activity and functional connectivity. It is often associated with a broad spectrum of short-term and long-term cognitive and behavioral symptoms including memory dysfunction, headache, and balance difficulties. Furthermore, there is evidence that oxidative stress significantly contributes to these symptoms and neurophysiological changes. The purpose of this study was to assess the effect of N-acetylcysteine (NAC) on brain function and chronic symptoms in mTBI patients. Fifty patients diagnosed with chronic mTBI participated in this study. They were categorized into two groups including controls (CN, n = 25), and patients receiving treatment with N-acetyl cysteine (NAC, n = 25). NAC group received 50 mg/kg intravenous (IV) medication once a day per week. In the rest of the week, they took one 500 mg NAC tablet twice per day. Each patient underwent rs-fMRI scanning at two timepoints including the baseline and 3 months later at follow-up, while the NAC group received a combination of oral and IV NAC over that time. Three rs-fMRI metrics were measured including fractional amplitude of low frequency fluctuations (fALFF), degree centrality (DC), and functional connectivity strength (FCS). Neuropsychological tests were also assessed at the same day of scanning for each patient. The alteration of rs-fMRI metrics and cognitive scores were measured over 3 months treatment with NAC. Then, the correlation analysis was executed to estimate the association of rs-fMRI measurements and cognitive performance over 3 months (p < 0.05). Two significant group-by-time effects demonstrated the changes of rs-fMRI metrics particularly in the regions located in the default mode network (DMN), sensorimotor network, and emotional circuits that were significantly correlated with cognitive function recovery over 3 months treatment with NAC (p < 0.05). NAC appears to modulate neural activity and functional connectivity in specific brain networks, and these changes could account for clinical improvement. This study confirmed the short-term therapeutic efficacy of NAC in chronic mTBI patients that may contribute to understanding of neurophysiological effects of NAC in mTBI. These findings encourage further research on long-term neurobehavioral assessment of NAC assisting development of therapeutic plans in mTBI.

Investigating cognitive reserve, symptom resolution and brain connectivity in mild traumatic brain injury

BACKGROUND

A proportion of patients with mild traumatic brain injury (mTBI) suffer long-term consequences, and the reasons behind this are still poorly understood. One factor that may affect outcomes is cognitive reserve, which is the brain's ability to maintain cognitive function despite injury. It is often assessed through educational level or premorbid IQ tests. This study aimed to explore whether there were differences in post-concussion symptoms and symptom resolution between patients with mTBI and minor orthopedic injuries one week and three months after injury. Additional aims were to explore the relationship between cognitive reserve and outcome, as well as functional connectivity according to resting state functional magnetic resonance imaging (rs-fMRI).

METHOD

Fifteen patients with mTBI and 15 controls with minor orthopedic injuries were recruited from the emergency department. Assessments, including Rivermead Post-Concussion Questionnaire (RPQ), neuropsychological testing, and rs-fMRI scans, were conducted on average 7 days (SD = 2) and 122 days (SD = 51) after injury.

RESULTS

At the first time point, significantly higher rates of post-concussion symptoms (U = 40.0, p = 0.003), state fatigue (U = 56.5, p = 0.014), and fatigability (U = 58.5, p = 0.025) were observed among the mTBI group than among the controls. However, after three months, only the difference in post-concussion symptoms remained significant (U = 27.0, p = 0.003). Improvement in post-concussion symptoms was found to be significantly correlated with cognitive reserve, but only in the mTBI group (Spearman's rho = -0.579, p = .038). Differences in the trajectory of recovery were also observed for fatigability between the two groups (U = 36.5, p = 0.015). Moreover, functional connectivity differences in the frontoparietal network were observed between the groups, and for mTBI patients, functional connectivity differences in an executive control network were observed over time.

CONCLUSION

The findings of this pilot study suggest that mTBI, compared to minor orthopedic trauma, is associated to both functional connectivity changes in the brain and concussion-related symptoms. While there is improvement in these symptoms over time, a small subgroup with lower cognitive reserve appears to experience more persistent and possibly worsening symptoms over time. This, however, needs to be validated in larger studies.

TRIAL REGISTRATION

NCT05593172. Retrospectively registered.

Extracting the most discriminating functional connections in mild traumatic brain injury based on machine learning

BACKGROUND

Mild traumatic brain injury (mTBI) is characterized as brain microstructural damage, which may cause a wide range of brain functional disturbances and emotional problems. Brain network analysis based on machine learning is an important means of neuroimaging research. Obtaining the most discriminating functional connection is of great significance to analyze the pathological mechanism of mTBI.

METHODS

To better obtain the most discriminating features of functional connection networks, this study proposes a hierarchical feature selection pipeline (HFSP) composed of Variance Filtering (VF), Lasso, and Principal Component Analysis (PCA). Ablation experiments indicate that each module plays a positive role in classification, validating the robustness and reliability of the HFSP. Furthermore, the HFSP is compared with recursive feature elimination (RFE), elastic net (EN), and locally linear embedding (LLE), verifying its superiority. In addition, this study also utilizes random forest (RF), SVM, Bayesian, linear discriminant analysis (LDA), and logistic regression (LR) as classifiers to evaluate the generalizability of HFSP.

RESULTS

The results show that the indexes obtained from RF are the highest, with accuracy = 89.74%, precision = 91.26%, recall = 89.74%, and F1 score = 89.42%. The HFSP selects 25 pairs of the most discriminating functional connections, mainly distributed in the frontal lobe, occipital lobe, and cerebellum. Nine brain regions show the largest node degree.

LIMITATIONS

The number of samples is small. This study only includes acute mTBI.

CONCLUSIONS

The HFSP is a useful tool for extracting discriminating functional connections and may contribute to the diagnostic processes.

Multi-Mechanistic Approaches to the Treatment of Traumatic Brain Injury: A Review

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Despite extensive research efforts, the majority of trialed monotherapies to date have failed to demonstrate significant benefit. It has been suggested that this is due to the complex pathophysiology of TBI, which may possibly be addressed by a combination of therapeutic interventions. In this article, we have reviewed combinations of different pharmacologic treatments, combinations of non-pharmacologic interventions, and combined pharmacologic and non-pharmacologic interventions for TBI. Both preclinical and clinical studies have been included. While promising results have been found in animal models, clinical trials of combination therapies have not yet shown clear benefit. This may possibly be due to their application without consideration of the evolving pathophysiology of TBI. Improvements of this paradigm may come from novel interventions guided by multimodal neuromonitoring and multimodal imaging techniques, as well as the application of multi-targeted non-pharmacologic and endogenous therapies. There also needs to be a greater representation of female subjects in preclinical and clinical studies.

Effects of Kisspeptin on Sexual Brain Processing and Penile Tumescence in Men With Hypoactive Sexual Desire Disorder: A Randomized Clinical Trial

IMPORTANCE

The human physiological sexual response is crucial for reward, satisfaction, and reproduction. Disruption of the associated neurophysiological pathways predisposes to low sexual desire; the most prevalent psychological form is hypoactive sexual desire disorder (HSDD), which affects 8% of men but currently has no effective pharmacological treatment options. The reproductive neuropeptide kisspeptin offers a putative therapeutic target, owing to emerging understanding of its role in reproductive behavior.

OBJECTIVE

To determine the physiological, behavioral, neural, and hormonal effects of kisspeptin administration in men with HSDD.

DESIGN, SETTING, AND PARTICIPANTS

This double-blind, 2-way crossover, placebo-controlled randomized clinical trial was performed at a single academic research center in the UK. Eligible participants were right-handed heterosexual men with HSDD. Physiological, behavioral, functional magnetic resonance imaging (fMRI), and hormonal analyses were used to investigate the clinical and mechanistic effects of kisspeptin administration in response to visual sexual stimuli (short and long video tasks). The trial was conducted between January 11 and September 15, 2021, and data analysis was performed between October and November 2021.

INTERVENTIONS

Participants attended 2 study visits at least 7 days apart, in balanced random order, for intravenous infusion of kisspeptin-54 (1 nmol/kg/h) for 75 minutes or for administration of a rate-matched placebo.

MAIN OUTCOMES AND MEASURES

Changes in (1) brain activity on whole-brain analysis, as determined by fMRI blood oxygen level-dependent activity in response to visual sexual stimuli during kisspeptin administration compared with placebo, (2) physiological sexual arousal (penile tumescence), and (3) behavioral measures of sexual desire and arousal.

RESULTS

Of the 37 men randomized, 32 completed the trial. Participants had a mean (SD) age of 37.9 (8.6) years and a mean (SD) body mass index of 24.9 (5.4). On viewing sexual videos, kisspeptin significantly modulated brain activity in key structures of the sexual-processing network on whole-brain analysis compared with placebo (mean absolute change [Cohen d] = 0.81 [95% CI, 0.41-1.21]; P =  .003). Furthermore, improvements in several secondary analyses were observed, including significant increases in penile tumescence in response to sexual stimuli (by up to 56% more than placebo; mean difference = 0.28 units [95% CI, 0.04-0.52 units]; P = .02) and behavioral measures of sexual desire-most notably, increased happiness about sex (mean difference = 0.63 points [95% CI, 0.10-1.15 points]; P = .02).

CONCLUSIONS AND RELEVANCE

Collectively, this randomized clinical trial provides the first evidence to date showing that kisspeptin administration substantially modulates sexual brain processing in men with HSDD, with associated increases in penile tumescence and behavioral measures of sexual desire and arousal. These data suggest that kisspeptin has potential as the first pharmacological treatment for men with low sexual desire.

TRIAL REGISTRATION

isrctn.org Identifier: ISRCTN17271094.

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].

Multimodal magnetic resonance imaging of youth sport-related concussion reveals acute changes in the cerebellum, basal ganglia, and corpus callosum that resolve with recovery

Magnetic resonance imaging (MRI) can provide a number of measurements relevant to sport-related concussion (SRC) symptoms; however, most studies to date have used a single MRI modality and whole-brain exploratory analyses in attempts to localize concussion injury. This has resulted in highly variable findings across studies due to wide ranging symptomology, severity and nature of injury within studies. A multimodal MRI, symptom-guided region-of-interest (ROI) approach is likely to yield more consistent results. The functions of the cerebellum and basal ganglia transcend many common concussion symptoms, and thus these regions, plus the white matter tracts that connect or project from them, constitute plausible ROIs for MRI analysis. We performed diffusion tensor imaging (DTI), resting-state functional MRI, quantitative susceptibility mapping (QSM), and cerebral blood flow (CBF) imaging using arterial spin labeling (ASL), in youth aged 12-18 years following SRC, with a focus on the cerebellum, basal ganglia and white matter tracts. Compared to controls similar in age, sex and sport (N = 20), recent SRC youth (N = 29; MRI at 8 ± 3 days post injury) exhibited increased susceptibility in the cerebellum (p = 0.032), decreased functional connectivity between the caudate and each of the pallidum (p = 0.035) and thalamus (p = 0.021), and decreased diffusivity in the mid-posterior corpus callosum (p < 0.038); no changes were observed in recovered asymptomatic youth (N = 16; 41 ± 16 days post injury). For recent symptomatic-only SRC youth (N = 24), symptom severity was associated with increased susceptibility in the superior cerebellar peduncles (p = 0.011) and reduced activity in the cerebellum (p = 0.013). Fewer days between injury and MRI were associated with reduced cerebellar-parietal functional connectivity (p < 0.014), reduced activity of the pallidum (p = 0.002), increased CBF in the caudate (p = 0.005), and reduced diffusivity in the central corpus callosum (p < 0.05). Youth SRC is associated with acute cerebellar inflammation accompanied by reduced cerebellar activity and cerebellar-parietal connectivity, as well as structural changes of the middle regions of the corpus callosum accompanied by functional changes of the caudate, all of which resolve with recovery. Early MRI post-injury is important to establish objective MRI-based indicators for concussion diagnosis, recovery assessment and prediction of outcome.

An exploratory study on functional connectivity after mild traumatic brain injury: Preserved global but altered local organization

INTRODUCTION

This study aimed to investigate alterations in whole-brain functional connectivity after a concussion using graph-theory analysis from global and local perspectives and explore the association between changes in the functional network properties and cognitive performance.

METHODS

Individuals with mild traumatic brain injury (mTBI, n = 29) within a month after injury, and age- and sex-matched healthy controls (n = 29) were included. Graph-theory measures on functional connectivity assessed using resting state functional magnetic resonance imaging data were acquired from each participant. These included betweenness centrality, strength, clustering coefficient, local efficiency, and global efficiency. Multi-domain cognitive functions were correlated with the graph-theory measures.

RESULTS

In comparison to the controls, the mTBI group showed preserved network characteristics at a global level. However, in the local network, we observed decreased betweenness centrality, clustering coefficient, and local efficiency in several brain areas, including the fronto-parietal attention network. Network strength at the local level showed mixed-results in different areas. The betweenness centrality of the right parahippocampus showed a significant positive correlation with the cognitive scores of the verbal learning test only in the mTBI group.

CONCLUSION

The intrinsic functional connectivity after mTBI is preserved globally, but is suboptimally organized locally in several areas. This possibly reflects the neurophysiological sequelae of a concussion. The present results may imply that the network property could be used as a potential indicator for clinical outcomes after mTBI.

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.

Functional Magnetic Resonance Imaging Study of Electroacupuncture Stimulating Uterine Acupoints

Objective

Based on resting-state functional magnetic resonance imaging (rs-fMRI), to observe the changes of brain function of bilateral uterine points stimulated by electroacupuncture, so as to provide imaging basis for acupuncture in the treatment of gynecological and reproductive diseases.

Methods

20 healthy female subjects were selected to stimulate bilateral uterine points (EX-CA1) by electroacupuncture. FMRI data before and after acupuncture were collected. The ReHo values before and after acupuncture were compared by using the analysis method of regional homogeneity (ReHo) of the whole brain, so as to explore the regulatory effect of acupuncture intervention on brain functional activities of healthy subjects.

Results

Compared with before acupuncture, the ReHo values of the left precuneus lobe, left central posterior gyrus, calcarine, left lingual gyrus, and cerebellum decreased significantly after acupuncture.

Conclusion

Electroacupuncture at bilateral uterine points can induce functional activities in brain areas such as the precuneus, cerebellum, posterior central gyrus, talform sulcus, and lingual gyrus. The neural activities in these brain areas may be related to reproductive hormone level, emotional changes, somatic sensation, and visual information. It can clarify the neural mechanism of acupuncture at uterine points in the treatment of reproductive and gynecological diseases to a certain extent.

Discriminating mild traumatic brain injury using sparse dictionary learning of functional network dynamics

Mild traumatic brain injury (mTBI) is usually caused by a bump, blow, or jolt to the head or penetrating head injury, and carries the risk of inducing cognitive disorders. However, identifying the biomarkers for the diagnosis of mTBI is challenging as evident abnormalities in brain anatomy are rarely found in patients with mTBI. In this study, we tested whether the alteration of functional network dynamics could be used as potential biomarkers to better diagnose mTBI. We propose a sparse dictionary learning framework to delineate spontaneous fluctuation of functional connectivity into the subject-specific time-varying evolution of a set of overlapping group-level sparse connectivity components (SCCs) based on the resting-state functional magnetic resonance imaging (fMRI) data from 31 mTBI patients in the early acute phase (<3 days postinjury) and 31 healthy controls (HCs). The identified SCCs were consistently distributed in the cohort of subjects without significant inter-group differences in connectivity patterns. Nevertheless, subject-specific temporal expression of these SCCs could be used to discriminate patients with mTBI from HCs with a classification accuracy of 74.2% (specificity 64.5% and sensitivity 83.9%) using leave-one-out cross-validation. Taken together, our findings indicate neuroimaging biomarkers for mTBI individual diagnosis based on the temporal expression of SCCs underlying time-resolved functional connectivity.