Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study

Micron-resolution fiber mapping in histology independent of sample preparation

Detailed knowledge of the brain's nerve fiber network is crucial for understanding its function in health and disease. However, mapping fibers with high resolution remains prohibitive in most histological sections because state-of-the-art techniques are incompatible with their preparation. Here, we present a micron-resolution light-scattering-based technique that reveals intricate fiber networks independent of sample preparation for extended fields of view. We uncover fiber structures in both label-free and stained, paraffin-embedded and deparaffinized, newly-prepared and archived, animal and human brain tissues - including whole-brain sections from the BigBrain atlas. We identify altered microstructures in demyelination and hippocampal neurodegeneration, and show key advantages over diffusion magnetic resonance imaging, polarization microscopy, and structure tensor analysis. We also reveal structures in non-brain tissues - including muscle, bone, and blood vessels. Our cost-effective, versatile technique enables studies of intricate fiber networks in any type of histological tissue section, offering a new dimension to neuroscientific and biomedical research.

Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study

Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.

Knowledge and attitudes toward mild traumatic brain injury among patients and family members

Introduction

Mild traumatic brain injury (mTBI) is a prevalent health issue with significant effects on patients' lives. Understanding and attitudes toward mTBI among patients and their families can influence management and outcomes. This study aimed to assess knowledge and attitudes toward mTBI in these groups.

Methods

A cross-sectional study was conducted at Zhejiang Hospital from July 1, 2023, to September 30, 2023. Patients with mTBI and their family members participated. Data were collected via an online questionnaire covering demographic information and mTBI knowledge and attitudes. Knowledge scores ranged from 0 to 20 and attitude scores from 8 to 40. Multivariate logistic regression identified factors influencing these scores.

Results

A total of 573 valid questionnaires were analyzed (289 males, 50.44%; 284 females, 49.56%). Among respondents, 258 (45.03%) had experienced a concussion. Mean knowledge and attitude scores were 11.00 ± 2.75 and 27.78 ± 4.07, respectively. Monthly per capita income of 5,000-10,000 RMB was negatively associated with knowledge and attitude scores (β = 0.160, 95% CI: [3.245 to 0.210], P = 0.026). Middle school education decreased the likelihood of positive attitudes toward mTBI (OR = 0.378, 95% CI: [0.1630.874], P = 0.023). mTBI due to falls was associated with increased likelihood of positive attitudes (OR = 3.588, 95% CI: [1.274-10.111], P = 0.016).

Discussion

Significant gaps in knowledge and attitudes toward mTBI exist among patients and their families, influenced by income and education levels. Personal experience with mTBI from falls correlates with more positive attitudes. These findings highlight the need for targeted educational interventions to improve understanding and attitudes, ultimately enhancing patient care and management. Comprehensive, accessible mTBI education is crucial for fostering positive attitudes and better knowledge among patients and their families.

Graph Analysis of the Visual Cortical Network during Naturalistic Movie Viewing Reveals Increased Integration and Decreased Segregation Following Mild TBI

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain's processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.

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.

Puberty, brain network connectivity and neuropsychiatric outcomes following pediatric traumatic brain injury in females: A research protocol

BACKGROUND

Examining the role of sex on recovery from pediatric TBI (pTBI) is a complex task, specifically when referring to injuries occurring during critical developmental and maturation periods. The effect of sex hormones on neurological and neuropsychiatric outcomes has been studied among adult TBI females, but not in children. During development, puberty is considered a key milestone accompanied by changes in physical growth, neuronal maturation, sex hormones, and psychological symptoms. Following pTBI, such changes might have a significant effect on brain re-organization and on long-term neuropsychiatric outcomes. While hormonal dysfunction is a common consequence following pTBI, only few studies have systematically evaluated hormonal changes following pTBI.

AIMS

To describe a multimodal protocol aimed to examine the effect of puberty on brain connectivity and long-term neuropsychiatric outcomes following TBI in female girls and adolescents.

METHODS

A case-control longitudinal prospective design will be used. 120 female participants aged 9 to 16 years (N = 60 per group) will be recruited. In the acute phase (T0-1 month), participants will undergo an MRI protocol for brain connectivity, as well as a clinical evaluation for puberty stage and hormonal levels. In the chronic phase (T1-18-24 months), participants will complete a neuropsychiatric assessment in addition to the MRI and puberty evaluations. Hormonal levels will be monitored at T0 and T1. A moderation-mediation model will be used to examine the moderating effects of puberty on the association between pTBI and neuropsychiatric symptoms in female girls and adolescents, through the mediating effect of brain network connectivity.

SIGNIFICANCE

This study will highlight sex-specific factors related to outcomes among females following pTBI and enhance our understanding of the unique challenges they face. Such information has a substantial potential to guide future directions for research, policy and practice.

ECoG spiking activity and signal dimension are early predictive measures of epileptogenesis in a translational mouse model of traumatic brain injury

The latency between traumatic brain injury (TBI) and the onset of epilepsy (PTE) represents an opportunity for counteracting epileptogenesis. Antiepileptogenesis trials are hampered by the lack of sensitive biomarkers that allow to enrich patient's population at-risk for PTE. We aimed to assess whether specific ECoG signals predict PTE in a clinically relevant mouse model with ∼60% epilepsy incidence. TBI was provoked in adult CD1 male mice by controlled cortical impact on the left parieto-temporal cortex, then mice were implanted with two perilesional cortical screw electrodes and two similar electrodes in the hemisphere contralateral to the lesion site. Acute seizures and spikes/sharp waves were ECoG-recorded during 1 week post-TBI. These early ECoG events were analyzed according to PTE incidence as assessed by measuring spontaneous recurrent seizures (SRS) at 5 months post-TBI. We found that incidence, number and duration of acute seizures during 3 days post-TBI were similar in PTE mice and mice not developing epilepsy (No SRS mice). Control mice with cortical electrodes (naïve, n = 5) or with electrodes and craniotomy (sham, n = 5) exhibited acute seizures but did not develop epilepsy. The daily number of spikes/sharp waves at the perilesional electrodes was increased similarly in PTE (n = 15) and No SRS (n = 8) mice vs controls (p < 0.05, n = 10) from day 2 post-injury. Differently, the daily number of spikes/sharp waves at both contralateral electrodes showed a progressive increase in PTE mice vs No SRS and control mice. In particular, spikes number was higher in PTE vs No SRS mice (p < 0.05) at 6 and 7 days post-TBI, and this measure predicted epilepsy development with high accuracy (AUC = 0.77, p = 0.03; CI 0.5830-0.9670). The cut-off value was validated in an independent cohort of TBI mice (n = 12). The daily spike number at the contralateral electrodes showed a circadian distribution in PTE mice which was not observed in No SRS mice. Analysis of non-linear dynamics at each electrode site showed changes in dimensionality during 4 days post-TBI. This measure yielded the best discrimination between PTE and No SRS mice (p < 0.01) at the cortical electrodes contralateral to injury. Data show that epileptiform activity contralateral to the lesion site has the the highest predictive value for PTE in this model reinforcing the hypothesis that the hemisphere contralateral to the lesion core may drive epileptogenic networks after TBI.

Structural-functional connectivity bandwidth predicts processing speed in mild traumatic brain Injury: A multiplex network analysis

An emerging body of work has revealed alterations in structural (SC) and functional (FC) brain connectivity following mild TBI (mTBI), with mixed findings. However, these studies seldom integrate complimentary neuroimaging modalities within a unified framework. Multilayer network analysis is an emerging technique to uncover how white matter organization enables functional communication. Using our novel graph metric (SC-FC Bandwidth), we quantified the information capacity of synchronous brain regions in 53 mild TBI patients (46 females; age mean = 40.2 years (y), σ = 16.7 (y), range: 18-79 (y). Diffusion MRI and resting state fMRI were administered at the acute and chronic post-injury intervals. Moreover, participants completed a cognitive task to measure processing speed (30 Seconds and Counting Task; 30-SACT). Processing speed was significantly increased at the chronic, relative to the acute post-injury intervals (p = <0.001). Nonlinear principal components of direct (t = -1.84, p = 0.06) and indirect SC-FC Bandwidth (t = 3.86, p = <0.001) predicted processing speed with a moderate effect size (R2 = 0.43, p < 0.001), while controlling for age. A subnetwork of interhemispheric edges with increased SC-FC Bandwidth was identified at the chronic, relative to the acute mTBI post-injury interval (pFDR = 0.05). Increased interhemispheric SC-FC Bandwidth of this network corresponded with improved processing speed at the chronic post-injury interval (partial r = 0.32, p = 0.02). Our findings revealed that mild TBI results in complex reorganization of brain connectivity optimized for maximum information flow, supporting improved cognitive performance as a compensatory mechanism. Moving forward, this measurement may complement clinical assessment as an objective marker of mTBI recovery.

Volumetric MRI Findings in Mild Traumatic Brain Injury (mTBI) and Neuropsychological Outcome

Region of interest (ROI) volumetric assessment has become a standard technique in quantitative neuroimaging. ROI volume is thought to represent a coarse proxy for making inferences about the structural integrity of a brain region when compared to normative values representative of a healthy sample, adjusted for age and various demographic factors. This review focuses on structural volumetric analyses that have been performed in the study of neuropathological effects from mild traumatic brain injury (mTBI) in relation to neuropsychological outcome. From a ROI perspective, the probable candidate structures that are most likely affected in mTBI represent the target regions covered in this review. These include the corpus callosum, cingulate, thalamus, pituitary-hypothalamic area, basal ganglia, amygdala, and hippocampus and associated structures including the fornix and mammillary bodies, as well as whole brain and cerebral cortex along with the cerebellum. Ventricular volumetrics are also reviewed as an indirect assessment of parenchymal change in response to injury. This review demonstrates the potential role and limitations of examining structural changes in the ROIs mentioned above in relation to neuropsychological outcome. There is also discussion and review of the role that post-traumatic stress disorder (PTSD) may play in structural outcome in mTBI. As emphasized in the conclusions, structural volumetric findings in mTBI are likely just a single facet of what should be a multimodality approach to image analysis in mTBI, with an emphasis on how the injury damages or disrupts neural network integrity. The review provides an historical context to quantitative neuroimaging in neuropsychology along with commentary about future directions for volumetric neuroimaging research in mTBI.

Decreased homotopic functional connectivity in traumatic brain injury

INTRODUCTION

Homotopic functional connectivity (HoFC), the synchrony in activity patterns between homologous brain regions, is a fundamental characteristic of resting-state functional connectivity (RsFC).

METHODS

We examined the difference in HoFC, computed as the correlation between atlas-based regions and their counterpart on the opposite hemisphere, in 16 moderate-severe traumatic brain injury patients (msTBI) and 36 healthy controls. Regions of decreased HoFC in msTBI patients were further used as seeds for examining differences between groups in correlations with other brain regions. Finally, we computed logistic regression models of regional HoFC and fractional anisotropy (FA) of the corpus callosum (CC).

RESULTS

TBI patients exhibited decreased HoFC in the middle and posterior cingulate cortex, thalamus, superior temporal pole, and cerebellum III. Furthermore, decreased RsFC was found between left cerebellum III and right parahippocampal cortex and vermis, between superior temporal pole and left caudate and medial left and right frontal orbital gyri. Thalamic HoFC and FA of the CC discriminate patients as msTBI with a high accuracy of 96%.

CONCLUSION

TBI is associated with regionally decreased HoFC. Moreover, a multimodality model of interhemispheric connectivity allowed for a high degree of accuracy in disease discrimination and enabled a deeper understanding of TBI effects on brain interhemispheric reorganization post-TBI.

Exploring personalized structural connectomics for moderate to severe traumatic brain injury

Graph theoretical analysis of the structural connectome has been employed successfully to characterize brain network alterations in patients with traumatic brain injury (TBI). However, heterogeneity in neuropathology is a well-known issue in the TBI population, such that group comparisons of patients against controls are confounded by within-group variability. Recently, novel single-subject profiling approaches have been developed to capture inter-patient heterogeneity. We present a personalized connectomics approach that examines structural brain alterations in five chronic patients with moderate to severe TBI who underwent anatomical and diffusion magnetic resonance imaging. We generated individualized profiles of lesion characteristics and network measures (including personalized graph metric GraphMe plots, and nodal and edge-based brain network alterations) and compared them against healthy reference cases (N = 12) to assess brain damage qualitatively and quantitatively at the individual level. Our findings revealed alterations of brain networks with high variability between patients. With validation and comparison to stratified, normative healthy control comparison cohorts, this approach could be used by clinicians to formulate a neuroscience-guided integrative rehabilitation program for TBI patients, and for designing personalized rehabilitation protocols based on their unique lesion load and connectome.

Impaired self-awareness and denial of disability in a community sample of people with traumatic brain injury

PURPOSE

To examine the nature and severity of impaired self-awareness (ISA) and denial of disability (DD) in a community-dwelling traumatic brain injury (TBI) population. Additionally, to investigate reliability, internal consistency, and feasibility of the Clinician's Rating Scale for evaluating Impaired Self-Awareness and Denial of Disability after brain injury (CRS-ISA-DD).

MATERIALS AND METHODS

ISA and DD were studied using the CRS-ISA-DD in a cross-sectional study with 78 TBI patients (3.1 years post-injury).

RESULTS

42% of individuals approached consented to participate in this study. Most participants showed one or more symptoms of ISA and DD, but severity scores were in the lower range (ISA: 13.2 ± 16.2; DD: 9.4 ± 10.7). The CRS-ISA-DD takes <10 min to complete, has excellent inter-rater reliability (ISA: ICC(2,1) = 0.928; DD: ICC(2,1) = 0.835), and acceptable-good internal consistency (ISA: α = 0.819; DD: α = 0.645). ISA severity correlated with neuropsychological test scores (r_s = -0.30 to -0.47) and injury severity. DD severity correlated with anxiety (r_s = -0.22) but not with avoidance coping or defense mechanisms.

CONCLUSIONS

Low levels of ISA and DD occurred in this sample of TBI patients. The CRS-ISA-DD is a reliable and feasible instrument. We recommend using it as a diagnostic tool to differentiate between ISA and DD once self-awareness problems have been identified.IMPLICATIONS FOR REHABILITATIONUnawareness of deficits can persist into the chronic stage when rehabilitation treatment has ended.The two main factors of unawareness, impaired self-awareness and denial of disability, are related to different neurological and psychological mechanisms.The Clinician's Rating Scale for evaluating Impaired Self-Awareness and Denial of Disability after brain injury (CRS-ISA-DD) can be used to distinguish the two main factors of unawareness.

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.

Brain architecture-based vulnerability to traumatic injury

The white matter tracts forming the intricate wiring of the brain are subject-specific; this heterogeneity can complicate studies of brain function and disease. Here we collapse tractography data from the Human Connectome Project (HCP) into structural connectivity (SC) matrices and identify groups of similarly wired brains from both sexes. To characterize the significance of these architectural groupings, we examined how similarly wired brains led to distinct groupings of neural activity dynamics estimated with Kuramoto oscillator models (KMs). We then lesioned our networks to simulate traumatic brain injury (TBI) and finally we tested whether these distinct architecture groups’ dynamics exhibited differing responses to simulated TBI. At each of these levels we found that brain structure, simulated dynamics, and injury susceptibility were all related to brain grouping. We found four primary brain architecture groupings (two male and two female), with similar architectures appearing across both sexes. Among these groupings of brain structure, two architecture types were significantly more vulnerable than the remaining two architecture types to lesions. These groups suggest that mesoscale brain architecture types exist, and these architectural differences may contribute to differential risks to TBI and clinical outcomes across the population.

Mapping cognitive deficits in cancer patients after chemotherapy: An Activation Likelihood Estimation meta-analysis of task-related fMRI studies

Recent neuroimaging studies have reported alterations in brain activation during cognitive tasks in cancer patients who have undergone chemotherapy treatment. However, the location of these altered brain activation patterns after chemotherapy varies considerably across studies. The aim of the present meta-analysis was to quantitatively synthesise this body of evidence using Activation Likelihood Estimation to identify reliable regions of altered brain activation in cancer patients treated with chemotherapy, compared to healthy controls and no chemotherapy controls. Our systematic search identified 12 studies that adopted task-related fMRI on non-central nervous system cancer patients who received chemotherapy relative to controls. All studies were included in the analyses and were grouped into four contrasts. Cancer patients treated with chemotherapy showed reduced activation in the left superior parietal lobe/precuneus (family-wise error corrected p < .05) compared to no chemotherapy controls. No significant clusters were found in three of our contrasts. The majority of studies did not support an association between altered brain activation and cognitive performance after chemotherapy. Findings point towards a possible chemotherapy-induced alteration, which could inform targeted treatment strategies. With continued work in this field using homogenous task-related protocols and cancer populations, fMRI may be used as a biomarker of cognitive deficits in the future.

Symptoms reported by Canadians posted in Havana are linked with reduced white matter fibre density

Diplomats representing the USA have reported with unusual neurologic symptoms and MRI changes after being posted in Havana, Cuba between late 2016 and 2018. Here, we examined white matter microstructure and network connectivity of individuals stationed in Havana, using diffusion-weighted MRI, fixel-based analysis and structural connectomics as implemented in MRtrix3. MRI data acquisition and clinical assessments were done in a total of 24 diplomats and their family members and 40 healthy controls. The diplomat data were grouped into an exposed cohort (n = 16) and an unexposed cohort (n = 10), and among these, two individuals were assessed before and after potential exposure. Fixel-based analysis revealed a reduction in fibre density in two specific regions: the fornix and the splenium, in exposed individuals, relative to unexposed individuals and healthy controls. Post hoc analyses showed the effect remained present (P < 0.05) in both regions when comparing exposed and unexposed diplomats; and reduced fibre density was correlated with longer time period stationed in Cuba after age correction. Reduction of fibre density was also found to be linked with clinical symptoms of persistent migraine, tinnitus, sound sensitivity and fatigue. Network statistical comparisons revealed decreased structural connectivity in two distinct networks, comprising subcortical and cortical systems in exposed individuals, relative to unexposed and normative data. While the cause for the differences between the groups remains unknown, our results reveal region-specific white matter injury, that is, significantly correlated with clinical symptoms.

General additive models address statistical issues in diffusion MRI: An example with clinically anxious adolescents

Statistical models employed to test for group differences in quantized diffusion-weighted MRI white matter tracts often fail to account for the large number of data points per tract in addition to the distribution, type, and interdependence of the data. To address these issues, we propose the use of Generalized Additive Models (GAMs) and supply code and examples to aid in their implementation. Specifically, using diffusion data from 73 periadolescent clinically anxious and no-psychiatric-diagnosis control participants, we tested for group tract differences and show that a GAM allows for the identification of differences within a tract while accounting for the nature of the data as well as covariates and group factors. Further, we then used these tract differences to investigate their association with performance on a memory test. When comparing our high versus low anxiety groups, we observed a positive association between the left uncinate fasciculus and memory overgeneralization for negatively valenced stimuli. This same association was not evident in the right uncinate or anterior forceps. These findings illustrate that GAMs are well-suited for modeling diffusion data while accounting for various aspects of the data, and suggest that the adoption of GAMs will be a powerful investigatory tool for diffusion-weighted analyses.

Examining brain white matter after pediatric mild traumatic brain injury using neurite orientation dispersion and density imaging: An A-CAP study

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We examined white matter microstructure after pediatric mTBI using NODDI and DTI.

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Children with mTBI did not significantly differ from those with OI on any metrics.

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Minor alterations, if any, may be present in children at the post-acute stage after mTBI.

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Large longitudinal studies are needed to understand long-term brain changes post injury.

Background

Pediatric mild traumatic brain injury (mTBI) affects millions of children annually. Diffusion tensor imaging (DTI) is sensitive to axonal injuries and white matter microstructure and has been used to characterize the brain changes associated with mild traumatic brain injury (mTBI). Neurite orientation dispersion and density imaging (NODDI) is a diffusion model that can provide additional insight beyond traditional DTI metrics, but has not been examined in pediatric mTBI. The goal of this study was to employ DTI and NODDI to gain added insight into white matter alterations in children with mTBI compared to children with mild orthopedic injury (OI).

Methods

Children (mTBI n = 320, OI n = 176) aged 8–16.99 years (12.39 ± 2.32 years) were recruited from emergency departments at five hospitals across Canada and underwent 3 T MRI on average 11 days post-injury. DTI and NODDI metrics were calculated for seven major white matter tracts and compared between groups using univariate analysis of covariance controlling for age, sex, and scanner type. False discovery rate (FDR) was used to correct for multiple comparisons.

Results

Univariate analysis revealed no significant group main effects or interactions in DTI or NODDI metrics. Fractional anisotropy and neurite density index in all tracts exhibited a significant positive association with age and mean diffusivity in all tracts exhibited a significant negative association with age in the whole sample.

Conclusions

Overall, there were no significant differences between mTBI and OI groups in brain white matter microstructure from either DTI or NODDI in the seven tracts. This indicates that mTBI is associated with relatively minor white matter differences, if any, at the post-acute stage. Brain differences may evolve at later stages of injury, so longitudinal studies with long-term follow-up are needed.

Structure can predict function in the human brain: a graph neural network deep learning model of functional connectivity and centrality based on structural connectivity

Although functional connectivity and associated graph theory measures (e.g., centrality; how centrally important to the network a region is) are widely used in brain research, the full extent to which these functional measures are related to the underlying structural connectivity is not yet fully understood. Graph neural network deep learning methods have not yet been applied for this purpose, and offer an ideal model architecture for working with connectivity data given their ability to capture and maintain inherent network structure. Here, we applied this model to predict functional connectivity from structural connectivity in a sample of 998 participants from the Human Connectome Project. Our results showed that the graph neural network accounted for 89% of the variance in mean functional connectivity, 56% of the variance in individual-level functional connectivity, 99% of the variance in mean functional centrality, and 81% of the variance in individual-level functional centrality. These results represent an important finding that functional centrality can be robustly predicted from structural connectivity. Regions of particular importance to the model's performance as determined through lesioning are discussed, whereby regions with higher centrality have a higher impact on model performance. Future research on models of patient, demographic, or behavioural data can also benefit from this graph neural network method as it is ideally-suited for depicting connectivity and centrality in brain networks. These results have set a new benchmark for prediction of functional connectivity from structural connectivity, and models like this may ultimately lead to a way to predict functional connectivity in individuals who are unable to do fMRI tasks (e.g., non-responsive patients).

Cortical disconnection in temporal lobe epilepsy

A critical concept in neurology is cortical disconnection, in which seemingly normal gray matter can have reduced function due to loss of white matter (WM) connections. White matter damage has been extensively described in temporal lobe epilepsy (TLE), but the anatomical distribution of cortical disconnection in TLE is not fully characterized. Here, we studied 221 participants (64 left-TLE, 55 right-TLE, 102 controls) from three different epilepsy treatment centers. We employed a group connectometry diffusion imaging tractography approach to identify WM fibers with reduced integrity in TLE. We then assessed the anatomical distribution of the gray matter endpoint projections of abnormal fibers to map the anatomical pattern of disconnections. As expected, left- and right-TLE were associated with multiple WM pathways with reduced integrity, which were associated with extensive cortical disconnection involving predominantly limbic structures. Controlling for medial temporal gray matter atrophy, cortical disconnection of the left cingulum and the thalamus as well as disconnection of the bilateral putamen and the amygdala was associated with lower verbal memory immediate recall. In conclusion, our results support that cortical disconnection is an underappreciated but pervasive phenomenon in TLE, and cortical disconnection of limbic structures beyond the medial temporal regions is related to verbal memory performance.

The Connectomes: Methods of White Matter Tractography and Contributions of Resting State fMRI

A comprehensive mapping of the structural and functional circuitry of the brain is a major unresolved problem in contemporary neuroimaging research. Diffusion-weighted and functional MRI have provided investigators with the capability to assess structural and functional connectivity in-vivo, driven primarily by methods of white matter tractography and resting-state fMRI, respectively. These techniques have paved the way for the construction of the functional and structural connectomes, which are quantitative representations of brain architecture as neural networks, comprised of nodes and edges. The connectomes, typically depicted as matrices or graphs, possess topological properties that inherently characterize the strength, efficiency, and organization of the connections between distinct brain regions. Graph theory, a general mathematical framework for analyzing networks, can be implemented to derive metrics from the connectomes that are sensitive to changes in brain connectivity associated with age, sex, cognitive function, and disease. These quantities can be assessed at either the global (whole brain) or local levels, allowing for the identification of distinct regional connectivity hubs and associated localized brain networks, which together serve crucial roles in establishing the structural and functional architecture of the brain. As a result, structural and functional connectomes have each been employed to study the brain circuitry underlying early brain development, neuroplasticity, developmental disorders, psychopathology, epilepsy, aging, neurodegenerative disorders, and traumatic brain injury. While these studies have yielded important insights into brain structure, function, and pathology, a precise description of the innate relationship between functional and structural networks across the brain remains unachieved. To date, connectome research has merely scratched the surface of potential clinical applications and related characterizations of brain-wide connectivity. Continued advances in diffusion and functional MRI acquisition, the delineation of functional and structural networks, and the quantification of neural network properties in specific brain regions, will be invaluable to future progress in neuroimaging science.

Application of neuropsychology and imaging to brain injury and use of the integrative cognitive rehabilitation psychotherapy model

BACKGROUND

An early approach to cognitive rehabilitation therapy (CRT) was developed based on A. R. Luria's theory of brain function. Expanding upon this approach, the Integrative Cognitive Rehabilitation Psychotherapy model (ICRP) was advanced.

OBJECTIVE

To describe the ICRP approach to treatment of clients post brain injury and provide a comprehensive list of evaluation tools to determine the client's abilities and needs. Finally, to provide a link between CRT and functional imaging studies designed to improve rehabilitation efforts.

METHODS

History of cognitive rehabilitation and neuropsychological testing is reviewed and description of cognitive, academic, psychiatric, and substance abuse tools are provided. Cognitive and emotional treatment techniques are fully described. Additionally, a method of determining the client's stage of recovery and pertinent functional imaging studies is detailed.

RESULTS

Authors have been able to provide a set of tools and techniques to use in comprehensive treatment of clients with brain injury.

CONCLUSIONS

Inclusive treatment which is outlined in the ICRP model is optimal for the client's recovery and return to a full and satisfying life post brain injury. The model provides a framework for neuropsychologists to integrate issues that tend to co-occur in clients living with brain injury into a unified treatment plan.

Attenuation of tonic inhibition prevents chronic neurovascular impairments in a Thy1-ChR2 mouse model of repeated, mild traumatic brain injury

Rationale: Mild traumatic brain injury (mTBI), the most common type of brain trauma, frequently leads to chronic cognitive and neurobehavioral deficits. Intervening effectively is impeded by our poor understanding of its pathophysiological sequelae.

Methods: To elucidate the long-term neurovascular sequelae of mTBI, we combined optogenetics, two-photon fluorescence microscopy, and intracortical electrophysiological recordings in mice to selectively stimulate peri-contusional neurons weeks following repeated closed-head injury and probe individual vessel's function and local neuronal reactivity.

Results: Compared to sham-operated animals, mTBI mice showed doubled cortical venular speeds (115 ± 25%) and strongly elevated cortical venular reactivity (53 ± 17%). Concomitantly, the pericontusional neurons exhibited attenuated spontaneous activity (-57 ± 79%) and decreased reactivity (-47 ± 28%). Post-mortem immunofluorescence revealed signs of peri-contusional senescence and DNA damage, in the absence of neuronal loss or gliosis. Alteration of neuronal and vascular functioning was largely prevented by chronic, low dose, systemic administration of a GABA-A receptor inverse agonist (L-655,708), commencing 3 days following the third impact.

Conclusions: Our findings indicate that repeated mTBI leads to dramatic changes in the neurovascular unit function and that attenuation of tonic inhibition can prevent these alterations. The sustained disruption of the neurovascular function may underlie the concussed brain's long-term susceptibility to injury, and calls for development of better functional assays as well as of neurovascularly targeted interventions.

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.

Topological Aberrance of Structural Brain Network Provides Quantitative Substrates of Post-Traumatic Brain Injury Attention Deficits in Children

Background: Traumatic brain injury (TBI)-induced attention deficits are among the most common long-term cognitive consequences in children. Most of the existing studies attempting to understand the neuropathological underpinnings of cognitive and behavioral impairments in TBI have utilized heterogeneous samples and resulted in inconsistent findings. The current research proposed to investigate topological properties of the structural brain network in children with TBI and their relationship with post-TBI attention problems in a more homogeneous subgroup of children who had severe post-TBI attention deficits (TBI-A). Materials and Methods: A total of 31 children with TBI-A and 35 group-matched controls were involved in the study. Diffusion tensor imaging-based probabilistic tractography and graph theoretical techniques were used to construct the structural brain network in each subject. Network topological properties were calculated in both global level and regional (nodal) level. Between-group comparisons among the topological network measures and analyses for searching brain-behavioral were all corrected for multiple comparisons using Bonferroni method. Results: Compared with controls, the TBI-A group showed significantly higher nodal local efficiency and nodal clustering coefficient in left inferior frontal gyrus and right transverse temporal gyrus, whereas significantly lower nodal clustering coefficient in left supramarginal gyrus and lower nodal local efficiency in left parahippocampal gyrus. The temporal lobe topological alterations were significantly associated with the post-TBI inattentive and hyperactive symptoms in the TBI-A group. Conclusion: The results suggest that TBI-related structural re-modularity in the white matter subnetworks associated with temporal lobe may play a critical role in the onset of severe post-TBI attention deficits in children. These findings provide valuable input for understanding the neurobiological substrates of post-TBI attention deficits, and have the potential to serve as quantitatively measurable criteria guiding the development of more timely and tailored strategies for diagnoses and treatments to the affected individuals. Impact statement This study provides a new insight into the neurobiological substrates associated with post-traumatic brain injury attention deficits (TBI-A) in children, by evaluating topological alterations of the structural brain network. The results demonstrated that relative to group-matched controls, the children with TBI-A had significantly altered nodal local efficiency and nodal clustering coefficient in temporal lobe, which strongly linked to elevated inattentive and hyperactive symptoms in the TBI-A group. These findings suggested that white matter structural re-modularity in subnetworks associated with temporal lobe may serve as quantitatively measurable biomarkers for early prediction and diagnosis of post-TBI attention deficits in children.

Characterizing changes in network connectivity following chronic head trauma in special forces military personnel: a combined resting-fMRI and DTI study

BACKGROUND

Soldiers are exposed to significant repetitive head trauma, which may disrupt functional and structural brain connectivity patterns.

PURPOSE/HYPOTHESIS

Integrate resting-state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI) to characterize changes in connectivity biomarkers within Canadian Special Operations Forces (CANSOF), hypothesizing that alterations in architectural organization of cortical hubs may follow chronic repetitive head trauma.

METHODS

Fifteen CANSOFs with a history of chronic exposure to sub-concussive head trauma and concussive injuries (1.9 ± 2.0 concussions (range: [0-6])), as well as an equal age-matched cohort of controls (CTLs) were recruited. BOLD-based rs-fMRI was combined with DTI to reconstruct functional and structural networks using independent component analyses and probabilistic tractography. Connectivity markers were computed based on the distance between functional seeds to assess for possible differences in injury susceptibility of short- and long-range connections.

RESULTS/DISCUSSION

Significant hyper- and hypo-connectivity differences in cortical connections were observed suggesting that chronic head trauma may predispose soldiers to changes in the functional organization of brain networks. Significant structural alterations in axonal fibers directly connecting disrupted functional nodes were specific to hyper-connected long-range connections, suggesting a potential relationship between axonal injury and increases in neural recruitment following repetitive head trauma from high-exposure military duties.

Factors associated with recurrent transient global amnesia: systematic review and pathophysiological insights

The examination of the risk factors that affect the recurrence of transient global amnesia (TGA) may shed light on the pathophysiological substrate of the disease. A systematic review was performed to identify the factors associated with the recurrence of TGA. MEDLINE, EMBASE, CENTRAL and PsycINFO were meticulously searched. Observational controlled studies involving patients with single (s-TGA) and recurrent TGA (r-TGA) according to Hodges and Warlow's criteria were retrieved. Differences in the demographic characteristics, personal and family medical history, previous exposure to precipitating events and laboratory findings were examined. Retrieved evidence was assessed in the context of the individual article validity, based on the numerical power and methodological quality of each study. Nine cohort studies with retrospective, prospective or mixed design were retrieved. In total, 1989 patients with TGA were included, 269 of whom suffered from r-TGA (13.5%). R-TGA presented an earlier age of onset. Evidence was suggestive of a relationship between recurrence and a family or personal history of migraine, as well as a personal history of depression. There was weaker evidence that associated recurrence with a positive family history of dementia, a personal history of head injury and hippocampal lesions in diffusion-weighted MRI. On the other hand, no connection was found between recurrence and electroencephalographic abnormalities, impaired jugular venous drainage, cardiovascular risk factors, atrial fibrillation, previous cerebrovascular events, exposure to precipitating events, a positive family history of TGA and hypothyroidism. Important pathophysiological insights that arised from these findings were discussed.