Resting state magnetoencephalography functional connectivity in traumatic brain injury

Use of magnetic source imaging to assess recovery after severe traumatic brain injury-an MEG pilot study

Rationale

Severe TBI (sTBI) is a devastating neurological injury that comprises a significant global trauma burden. Early comprehensive neurocritical care and rehabilitation improve outcomes for such patients, although better diagnostic and prognostic tools are necessary to guide personalized treatment plans.

Methods

In this study, we explored the feasibility of conducting resting state magnetoencephalography (MEG) in a case series of sTBI patients acutely after injury (~7 days), and then about 1.5 and 8 months after injury. Synthetic aperture magnetometry (SAM) was utilized to localize source power in the canonical frequency bands of delta, theta, alpha, beta, and gamma, as well as DC-80 Hz.

Results

At the first scan, SAM source maps revealed zones of hypofunction, islands of preserved activity, and hemispheric asymmetry across bandwidths, with markedly reduced power on the side of injury for each patient. GCS scores improved at scan 2 and by scan 3 the patients were ambulatory. The SAM maps for scans 2 and 3 varied, with most patients showing increasing power over time, especially in gamma, but a continued reduction in power in damaged areas and hemispheric asymmetry and/or relative diminishment in power at the site of injury. At the group level for scan 1, there was a large excess of neural generators operating within the delta band relative to control participants, while the number of neural generators for beta and gamma were significantly reduced. At scan 2 there was increased beta power relative to controls. At scan 3 there was increased group-wise delta power in comparison to controls.

Conclusion

In summary, this pilot study shows that MEG can be safely used to monitor and track the recovery of brain function in patients with severe TBI as well as to identify patient-specific regions of decreased or altered brain function. Such MEG maps of brain function may be used in the future to tailor patient-specific rehabilitation plans to target regions of altered spectral power with neurostimulation and other treatments.

Relaxed Alert Electroencephalography Screening for Mild Traumatic Brain Injury in Athletes

Due to the mildness of initial injury, many athletes with recurrent mild traumatic brain injury (mTBI) are misdiagnosed with other neuropsychiatric illnesses. This study was designed as a proof-of-principle feasibility trial for athletic trainers at a sports facility to generate electroencephalograms (EEGs) from student athletes for discriminating (mTBI) associated EEGs from uninjured ones. A total of 47 EEGs were generated, with 30 athletes recruited at baseline (BL) pre-season, after a concussive injury (IN), and post-season (PS). Outcomes included: 1) visual analyses of EEGs by a neurologist; 2) support vector machine (SVM) classification for inferences about whether particular groups belonged to the three subgroups of BL, IN, or PS; and 3) analyses of EEG synchronies including phase locking value (PLV) computed between pairs of distinct electrodes. All EEGs were visually interpreted as normal. SVM classification showed that BL and IN could be discriminated with 81% accuracy using features of EEG synchronies combined. Frontal inter-hemispheric phase synchronization measured by PLV was significantly lower in the IN group. It is feasible for athletic trainers to record high quality EEGs from student athletes. Also, spatially localized metrics of EEG synchrony can discriminate mTBI associated EEGs from control EEGs.

An Evaluation of the Emerging Techniques in Sports-Related Concussion

SUMMARY

Sports-related concussion is now in public awareness more than ever before. Investigations into underlying pathophysiology and methods of assessment have correspondingly increased at an exponential rate. In this review, we aim to highlight some of the evidence supporting emerging techniques in the fields of neurophysiology, neuroimaging, vestibular, oculomotor, autonomics, head sensor, and accelerometer technology in the setting of the current standard: clinical diagnosis and management. In summary, the evidence we reviewed suggests that (1) head impact sensors and accelerometers may detect possible concussions that would not otherwise receive evaluation; (2) clinical diagnosis may be aided by sideline vestibular, oculomotor, and portable EEG techniques; (3) clinical decisions on return-to-play eligibility are currently not sensitive at capturing the neurometabolic, cerebrovascular, neurophysiologic, and microstructural changes that biomarkers have consistently detected days and weeks after clinical clearance. Such biomarkers include heart rate variability, quantitative electroencephalography, as well as functional, metabolic, and microstructural neuroimaging. The current challenge is overcoming the lack of consistency and replicability of any one particular technique to reach consensus.

ACR White Paper on Magnetoencephalography and Magnetic Source Imaging: A Report from the ACR Commission on Neuroradiology

Magnetoencephalography, the extracranial detection of tiny magnetic fields emanating from intracranial electrical activity of neurons, and its source modeling relation, magnetic source imaging, represent a powerful functional neuroimaging technique, able to detect and localize both spontaneous and evoked activity of the brain in health and disease. Recent years have seen an increased utilization of this technique for both clinical practice and research, in the United States and worldwide. This report summarizes current thinking, presents recommendations for clinical implementation, and offers an outlook for emerging new clinical indications.

A Precision Medicine Agenda in Traumatic Brain Injury

Traumatic brain injury remains a leading cause of death and disability across the globe. Substantial uncertainty in outcome prediction continues to be the rule notwithstanding the existing prediction models. Additionally, despite very promising preclinical data, randomized clinical trials (RCTs) of neuroprotective strategies in moderate and severe TBI have failed to demonstrate significant treatment effects. Better predictive models are needed, as the existing validated ones are more useful in prognosticating poor outcome and do not include biomarkers, genomics, proteonomics, metabolomics, etc. Invasive neuromonitoring long believed to be a "game changer" in the care of TBI patients have shown mixed results, and the level of evidence to support its widespread use remains insufficient. This is due in part to the extremely heterogenous nature of the disease regarding its etiology, pathology and severity. Currently, the diagnosis of traumatic brain injury (TBI) in the acute setting is centered on neurological examination and neuroimaging tools such as CT scanning and MRI, and its treatment has been largely confronted using a "one-size-fits-all" approach, that has left us with many unanswered questions. Precision medicine is an innovative approach for TBI treatment that considers individual variability in genes, environment, and lifestyle and has expanded across the medical fields. In this article, we briefly explore the field of precision medicine in TBI including biomarkers for therapeutic decision-making, multimodal neuromonitoring, and genomics.

Wavelet-based neurovascular coupling can predict brain abnormalities in neonatal encephalopathy

BACKGROUND

Hypoxic-ischemic encephalopathy (HIE) is a leading cause of morbidity and mortality in neonates, but quantitative methods to predict outcomes early in their course of illness remain elusive. Real-time physiologic biomarkers of neurologic injury are needed in order to predict which neonates will benefit from therapies. Neurovascular coupling (NVC) describes the correlation of neural activity with cerebral blood flow, and the degree of impairment could predict those at risk for poor outcomes.

OBJECTIVE

To determine if neurovascular coupling (NVC) calculated in the first 24-hours of life based on wavelet transform coherence analysis (WTC) of near-infrared spectroscopy (NIRS) and amplitude-integrated electroencephalography (aEEG) can predict abnormal brain MRI in neonatal HIE.

METHODS

WTC analysis was performed between dynamic oscillations of simultaneously recorded aEEG and cerebral tissue oxygen saturation (SctO2) signals for the first 24 h after birth. The squared cross-wavelet coherence, R2, of the time-frequency domain described by the WTC, is a localized correlation coefficient (ranging between 0 and 1) between these two signals in the time-frequency domain. Statistical analysis was based on Monte Carlo simulation with a 95% confidence interval to identify the time-frequency areas from the WTC scalograms. Brain MRI was performed on all neonates and classified as normal or abnormal based on an accepted classification system for HIE. Wavelet metrics of % significant SctO2-aEEG coherence was compared between the normal and abnormal MRI groups.

RESULT

This prospective study recruited a total of 36 neonates with HIE. A total of 10 had an abnormal brain MRI while 26 had normal MRI. The analysis showed that the SctO2-aEEG coherence between the group with normal and abnormal MRI were significantly different (p = 0.0007) in a very low-frequency (VLF) range of 0.06-0.2 mHz. Using receiver operating characteristic (ROC) curves, the use of WTC-analysis of NVC had an area under the curve (AUC) of 0.808, and with a cutoff of 10% NVC. Sensitivity was 69%, specificity was 90%, positive predictive value (PPV) was 94%, and negative predictive value (NPV) was 52% for predicting brain injury on MRI. This was superior to the clinical Total Sarnat score (TSS) where AUC was 0.442 with sensitivity 61.5%, specificity 30%, PPV 75%, and NPV 31%.

CONCLUSION

NVC is a promising neurophysiological biomarker in neonates with HIE, and in our prospective cohort was superior to the clinical Total Sarnat score for prediction of abnormal brain MRI.

Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy

To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.

Alterations in the Magnetoencephalography Default Mode Effective Connectivity following Concussion

BACKGROUND AND PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents

Mild traumatic brain injury is highly prevalent in paediatric populations, and can result in chronic physical, cognitive and emotional impairment, known as persistent post-concussive symptoms. Magnetoencephalography has been used to investigate neurophysiological dysregulation in mild traumatic brain injury in adults; however, whether neural dysrhythmia persists in chronic mild traumatic brain injury in children and adolescents is largely unknown. We predicted that children and adolescents would show similar dysfunction as adults, including pathological slow-wave oscillations and maladaptive, frequency-specific, alterations to neural connectivity. Using magnetoencephalography, we investigated regional oscillatory power and distributed brain-wide networks in a cross-sectional sample of children and adolescents in the chronic stages of mild traumatic brain injury. Additionally, we used a machine learning pipeline to identify the most relevant magnetoencephalography features for classifying mild traumatic brain injury and to test the relative classification performance of regional power versus functional coupling. Results revealed that the majority of participants with chronic mild traumatic brain injury reported persistent post-concussive symptoms. For neurophysiological imaging, we found increased regional power in the delta band in chronic mild traumatic brain injury, predominantly in bilateral occipital cortices and in the right inferior temporal gyrus. Those with chronic mild traumatic brain injury also showed dysregulated neuronal coupling, including decreased connectivity in the delta range, as well as hyper-connectivity in the theta, low gamma and high gamma bands, primarily involving frontal, temporal and occipital brain areas. Furthermore, our multivariate classification approach combined with functional connectivity data outperformed regional power in terms of between-group classification accuracy. For the first time, we establish that local and large-scale neural activity are altered in youth in the chronic phase of mild traumatic brain injury, with the majority presenting persistent post-concussive symptoms, and that dysregulated interregional neural communication is a reliable marker of lingering paediatric ‘mild’ traumatic brain injury.

Magnetoencephalography in the Detection and Characterization of Brain Abnormalities Associated with Traumatic Brain Injury: A Comprehensive Review

Magnetoencephalography (MEG) is a functional brain imaging technique with high temporal resolution compared with techniques that rely on metabolic coupling. MEG has an important role in traumatic brain injury (TBI) research, especially in mild TBI, which may not have detectable features in conventional, anatomical imaging techniques. This review addresses the original research articles to date that have reported on the use of MEG in TBI. Specifically, the included studies have demonstrated the utility of MEG in the detection of TBI, characterization of brain connectivity abnormalities associated with TBI, correlation of brain signals with post-concussive symptoms, differentiation of TBI from post-traumatic stress disorder, and monitoring the response to TBI treatments. Although presently the utility of MEG is mostly limited to research in TBI, a clinical role for MEG in TBI may become evident with further investigation.

Atypical neuromagnetic resting activity associated with thalamic volume and cognitive outcome in very preterm children

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Preterm birth is associated with higher risk of negative neurocognitive outcomes.

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At school age, preterm children have atypical frequency-specific power at rest.

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Thalamic volume reduction is associated with atypical power in preterm birth.

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Thalamic matter intensity is associated with negative neurocognitive outcomes.

Children born very preterm, even in the absence of overt brain injury or major impairment, are at increased risk of cognitive difficulties. This risk is associated with developmental disruptions of the thalamocortical system during critical periods while in the neonatal intensive care unit. The thalamus is an important structure that not only relays sensory information but acts as a hub for integration of cortical activity which regulates cortical power across a range of frequencies. In this study, we investigate the association between atypical power at rest in children born very preterm at school age using magnetoencephalography (MEG), neurocognitive function and structural alterations related to the thalamus using MRI. Our results indicate that children born extremely preterm have higher power at slow frequencies (delta and theta) and lower power at faster frequencies (alpha and beta), compared to controls born full-term. A similar pattern of spectral power was found to be associated with poorer neurocognitive outcomes, as well as with normalized T1 intensity and the volume of the thalamus. Overall, this study provides evidence regarding relations between structural alterations related to very preterm birth, atypical oscillatory power at rest and neurocognitive difficulties at school-age children born very preterm.

Effect of Zolpidem in the Aftermath of Traumatic Brain Injury: An MEG Study

In the past two decades, many studies have shown the paradoxical efficacy of zolpidem, a hypnotic used to induce sleep, in transiently alleviating various disorders of consciousness such as traumatic brain injury (TBI), dystonia, and Parkinson's disease. The mechanism of action of this effect of zolpidem is of great research interest. In this case study, we use magnetoencephalography (MEG) to investigate a fully conscious, ex-coma patient who suffered from neurological difficulties for a few years due to traumatic brain injury. For a few years after injury, the patient was under medication with zolpidem that drastically improved his symptoms. MEG recordings taken before and after zolpidem showed a reduction in power in the theta-alpha (4–12 Hz) and lower beta (15–20 Hz) frequency bands. An increase in power after zolpidem intake was found in the higher beta/lower gamma (20–43 Hz) frequency band. Source level functional connectivity measured using weighted-phase lag index showed changes after zolpidem intake. Stronger connectivity between left frontal and temporal brain regions was observed. We report that zolpidem induces a change in MEG resting power and functional connectivity in the patient. MEG is an informative and sensitive tool to detect changes in brain activity for TBI.

Spatiotemporal dynamics of postoperative functional plasticity in patients with brain tumors in language areas

Postoperative functional neuroimaging provides a unique opportunity to investigate the neural mechanisms that facilitate language network reorganization. Previous studies in patients with low grade gliomas (LGGs) in language areas suggest that postoperative recovery is likely due to functional neuroplasticity in peritumoral and contra-tumoral healthy regions, but have attributed varying degrees of importance to specific regions. In this study, we used Magnetoencephalography (MEG) to investigate functional connectivity changes in peritumoral and contra-tumoral regions after brain tumor resection. MEG recordings of cortical activity during resting-state were obtained from 12 patients with LGGs in left-hemisphere language brain areas. MEG data were recorded before (Pre session), and 3 (Post_1 session) and 6 (Post_2 session) months after awake craniotomy. For each MEG session, we measured the functional connectivity of the peritumoral and contra-tumoral regions to the rest of the brain across the 1-100 Hz frequency band. We found that functional connectivity in the Post_1 and Post_2 sessions was higher than in the Pre session only in peritumoral regions and within the alpha frequency band. Functional connectivity in peritumoral regions did not differ between the Post_1 and Post_2 sessions. Alpha connectivity enhancement in peritumoral regions was observed in all patients regardless of the LGG location. Together, these results suggest that postoperative language functional reorganization occurs in peritumoral regions regardless of the location of the tumor and mostly develops within 3 months after surgery.

Low-Field Magnetic Stimulation Restores Cognitive and Motor Functions in the Mouse Model of Repeated Traumatic Brain Injury: Role of Cellular Prion Protein

Traumatic brain injury (TBI)/concussion is a growing epidemic throughout the world. Memory and neurobehavioral dysfunctions are among the sequelae of TBI. Dislodgement of cellular prion protein (PrPc) and disruption of circadian rhythm have been linked to TBI. Low-field magnetic stimulation (LFMS) is a new noninvasive repetitive transcranial magnetic stimulation (rTMS) technique that generates diffused and low-intensity magnetic stimulation to deep cortical and subcortical areas. The role of LFMS on PrPc, proteins related to the circadian rhythm, and behavior alterations in a repeated TBI mouse model were studied in the present study. TBI was induced to the mice (right hemisphere) using weight-drop method, once daily for 3 days. LFMS treatment was given for 20 min once daily for 4 days (immediately after each TBI induction). The results showed that LFMS-treated TBI mice significantly improved cognitive and motor function as evidenced by open field exploration, rotarod, and novel location recognition tasks. In addition, a significant increase in PrPc and decreased glial fibrillary acidic protein levels were observed in cortical and hippocampal regions of LFMS-treated TBI mice brain compared with sham-treated TBI mice, while neuronal nuclei level was significantly increased in cortical region. In LFMS-treated mice, a decrease in proteins related to circadian rhythm were observed, compared with sham-treated TBI mice. The results obtained from the study demonstrated the neuroprotective effect of LFMS, which may be through regulating PrPc and/or proteins related to circadian rhythm. Thus, the present study suggests that LFMS may improve the subject's neurological condition following TBI.

The frequency of alpha oscillations: Task-dependent modulation and its functional significance

Power (amplitude) and frequency are two important characteristics of EEG alpha oscillations (8-12 Hz). There is an extensive literature showing that alpha power can be modulated in a goal-oriented manner to either enhance or suppress sensory information processing. Only a few studies to date have examined the task-dependent modulation of alpha frequency. Instead, alpha frequency is often viewed as a trait variable, and used to characterize individual differences in cognitive functioning. We performed two experiments to examine the task-dependent modulation of alpha frequency and its functional significance. In the first experiment, high-density EEG was recorded from 21 participants performing a Sternberg working memory task. The results showed that: (1) during memory encoding, alpha frequency decreased with increasing memory load, whereas during memory retention and retrieval, alpha frequency increased with increasing memory load, (2) higher alpha frequency prior to the onset of probe was associated with longer reaction time, and (3) higher alpha frequency prior to the onset of cue or probe was associated with weaker early cue-evoked or probe-evoked neural responses. In the second experiment, simultaneous EEG-fMRI was recorded from 59 participants during resting state. An EEG-informed fMRI analysis revealed that the spontaneous fluctuations of alpha frequency, but not alpha power, were inversely associated with BOLD activity in the visual cortex. Taken together, these findings suggest that alpha frequency is task-dependent, may serve as an indicator of cortical excitability, and along with alpha power, provides more comprehensive indexing of sensory gating.

Source Connectivity Analysis Can Assess Recovery of Acute Mild Traumatic Brain Injury Patients

In this study we investigated whether source connectivity analysis of resting-state Magnetoencephalographic (MEG) activity could separate mild traumatic brain injury (mTBI) patients from age-and sex-matched controls. For each subject, we used artifact-free data recorded on three sessions to estimate intracranial sources which were then projected onto a standardized brain atlas for common reference. The statistical and topological properties of functional brain networks, estimated using Granger causality, were analyzed using MANOVA, with group and recording session as the independent variables and number of in-going and out-going connections in each atlas region as dependent variables. Overall, mTBI subjects showed a larger number of stronger connections compared to controls. The number and topology of in-going and out-going connections were significantly different across the two groups in areas involved with spatial memory, perception of visual space, emotion formation and processing, learning, and memory. Additionally, differences between patients and controls were decreasing across the three sessions indicating patient improvement. Our results suggest that connectivity analysis may be used as a reliable biomarker of mTBI and can also help with the diagnosis and assessment of patient recovery.

Neuroimaging of deployment-associated traumatic brain injury (TBI) with a focus on mild TBI (mTBI) since 2009

OBJECTIVES

A substantial body of recent research has aimed to better understand the clinical sequelae of military trauma through the application of advanced brain imaging procedures in Veteran populations. The primary objective of this review was to highlight a portion of these recent studies to demonstrate how imaging tools can be used to understand military-associated brain injury.

METHODS

We focus here on the phenomenon of mild traumatic brain injury (mTBI) given its high prevalence in the Veteran population and current recognition of the need to better understand the clinical implications of this trauma. This is intended to provide readers with an initial exposure to the field of neuroimaging of mTBI with a brief introduction to the concept of traumatic brain injury, followed by a summary of the major imaging techniques that have been applied to the study of mTBI.

RESULTS

Taken together, the collection of studies reviewed demonstrates a clear role for neuroimaging towards understanding the various neural consequences of mTBI as well as the clinical complications of such brain changes.

CONCLUSIONS

This information must be considered in the larger context of research into mTBI, including the potentially unique nature of blast exposure and the long-term consequences of mTBI.

Default Mode Network Oscillatory Coupling Is Increased Following Concussion

Concussion is a common form of mild traumatic brain injury. Despite the descriptor "mild," a single injury can leave long-lasting and sustained alterations to brain function, including changes to localized activity and large-scale interregional communication. Cognitive complaints are thought to arise from such functional deficits. We investigated the impact of injury on neurophysiological and functionally specialized resting networks, known as intrinsic connectivity networks (ICNs), using magnetoencephalography. We assessed neurophysiological connectivity in 40 males, 20 with concussion and 20 without. Regions-of-interest that comprise nodes of ICNs were defined, and their time courses derived using a beamformer approach. Pairwise fluctuations and covariations in band-limited amplitude envelopes were computed reflecting measures of functional connectivity. Intra-network connectivity was compared between groups using permutation testing and correlated with symptoms. We observed increased resting spectral connectivity in the default mode network (DMN) and motor networks (MOTs) in our concussion group when compared with controls, across alpha through gamma ranges. Moreover, these differences were not explained by power spectrum density within the ICNs. Furthermore, this increased coupling was significantly associated with symptoms in the DMN and MOTs-but once accounting for comorbidities (including, depression, anxiety, and ADHD) only the DMN continued to be associated with symptoms. The DMN plays a critical role in shifting between cognitive tasks. These data suggest even a single concussion can perturb the intrinsic coupling of this functionally specialized network in the brain, and may explain persistent and wide-ranging symptomatology.

Applications of Resting State Functional MR Imaging to Traumatic Brain Injury

Traumatic brain injury (TBI) is an important public health issue. TBI includes a broad spectrum of injury severities and abnormalities. Functional MR imaging (fMR imaging), both resting state (rs) and task, has been used often in research to study the effects of TBI. Although rs-fMR imaging is not currently applicable in clinical diagnosis of TBI, computer-aided tools are making this a possibility for the future. Specifically, graph theory is being used to study the change in networks after TBI. Machine learning methods allow researchers to build models capable of predicting injury severity and recovery trajectories.

Disrupted Gamma Synchrony after Mild Traumatic Brain Injury and Its Correlation with White Matter Abnormality

Mild traumatic brain injury (mTBI) has been firmly associated with disrupted white matter integrity due to induced white matter damage and degeneration. However, comparatively less is known about the changes of the intrinsic functional connectivity mediated via neural synchronization in the brain after mTBI. Moreover, despite the presumed link between structural and functional connectivity, no existing studies in mTBI have demonstrated clear association between the structural abnormality of white matter axons and the disruption of neural synchronization. To investigate these questions, we recorded resting state EEG and diffusion tensor imaging (DTI) from a cohort of military service members. A newly developed synchronization measure, the weighted phase lag index was applied on the EEG data for estimating neural synchronization. Fractional anisotropy was computed from the DTI data for estimating white matter integrity. Fifteen service members with a history of mTBI within the past 3 years were compared to 22 demographically similar controls who reported no history of head injury. We observed that synchronization at low-gamma frequency band (25–40 Hz) across scalp regions was significantly decreased in mTBI cases compared with controls. The synchronization in theta (4–7 Hz), alpha (8–13 Hz), and beta (15–23 Hz) frequency bands were not significantly different between the two groups. In addition, we found that across mTBI cases, the disrupted synchronization at low-gamma frequency was significantly correlated with the white matter integrity of the inferior cerebellar peduncle, which was also significantly reduced in the mTBI group. These findings demonstrate an initial correlation between the impairment of white matter integrity and alterations in EEG synchronization in the brain after mTBI. The results also suggest that disruption of intrinsic neural synchronization at low-gamma frequency may be a characteristic functional pathology following mTBI and may prove useful for developing better methods of diagnosis and treatment.

Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction

Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed.

Altered Rich-Club and Frequency-Dependent Subnetwork Organization in Mild Traumatic Brain Injury: A MEG Resting-State Study

Functional brain connectivity networks exhibit “small-world” characteristics and some of these networks follow a “rich-club” organization, whereby a few nodes of high connectivity (hubs) tend to connect more densely among themselves than to nodes of lower connectivity. The Current study followed an “attack strategy” to compare the rich-club and small-world network organization models using Magnetoencephalographic (MEG) recordings from mild traumatic brain injury (mTBI) patients and neurologically healthy controls to identify the topology that describes the underlying intrinsic brain network organization. We hypothesized that the reduction in global efficiency caused by an attack targeting a model's hubs would reveal the “true” underlying topological organization. Connectivity networks were estimated using mutual information as the basis for cross-frequency coupling. Our results revealed a prominent rich-club network organization for both groups. In particular, mTBI patients demonstrated hyper-synchronization among rich-club hubs compared to controls in the δ band and the δ-γ₁, θ-γ₁, and β-γ₂ frequency pairs. Moreover, rich-club hubs in mTBI patients were overrepresented in right frontal brain areas, from θ to γ₁ frequencies, and underrepresented in left occipital regions in the δ-β, δ-γ₁, θ-β, and β-γ₂ frequency pairs. These findings indicate that the rich-club organization of resting-state MEG, considering its role in information integration and its vulnerability to various disorders like mTBI, may have a significant predictive value in the development of reliable biomarkers to help the validation of the recovery from mTBI. Furthermore, the proposed approach might be used as a validation tool to assess patient recovery.

Brain activation profiles in mTBI: evidence from ERP activity of working memory response

In this study we analyzed event related potentials (ERPs) obtained in an N-back working memory test that varied in difficulty from 0- to 2-back. We collected 21 channels of activity from 11 mild traumatic brain injury (mTBI) patients and 7 normal controls, on three different visits, and used the amplitude and latency of the P300 component to characterize the subjects. A preprocessing procedure based on independent component analysis was used first to identify and eliminate electrophysiological noise on a single trial basis. Then to obtain more reliable statistics, the recording electrodes were lumped into five main groups corresponding roughly to frontal, central, parietal, and left and right temporal brain regions. For each subject, the P300 amplitude and latency were measured after averaging the activity of all channels in each group. Group analyses showed that latencies in the central region were significantly shorter in controls, at every visit for the 2-back test. The lack of significant differences across the three visits for the mTBI group indicates that mTBI subjects are not improving at the rate that might have been expected, confirming previous reports that mTBI deficits may persist for years.

Enhanced prefrontal functional-structural networks to support postural control deficits after traumatic brain injury in a pediatric population

Traumatic brain injury (TBI) affects structural connectivity, triggering the reorganization of structural-functional circuits in a manner that remains poorly understood. We focus here on brain network reorganization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severe TBI, comparing them to young, typically developing control participants. TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: (1) a subcortical network, including parts of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulate gyrus, and precuneus; and (2) a task-positive network, involving regions of the dorsal attention system, together with dorsolateral and ventrolateral prefrontal regions. We also found that the increased prefrontal connectivity in TBI patients was correlated with some postural control indices, such as the amount of body sway, whereby patients with worse balance increased their connectivity in frontal regions more strongly. The increased prefrontal connectivity found in TBI patients may provide the structural scaffolding for stronger cognitive control of certain behavioral functions, consistent with the observations that various motor tasks are performed less automatically following TBI and that more cognitive control is associated with such actions.

The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs.

New Wavelet Neurovascular Bundle for Bedside Evaluation of Cerebral Autoregulation and Neurovascular Coupling in Newborns with Hypoxic-Ischemic Encephalopathy

Neonatal encephalopathy (NE) resulting from birth asphyxia constitutes a major global public health burden for millions of infants every year, and despite therapeutic hypothermia, half of these neonates have poor neurological outcomes. As new neuroprotective interventions are being studied in clinical trials, there is a critical need to establish physiological surrogate markers of therapeutic efficacy, to guide patient selection and/or to modify the therapeutic intervention. The challenge in the field of neonatal brain injury has been the difficulty of clinically discerning NE severity within the short therapeutic window after birth or of analyzing the dynamic aspects of the cerebral circulation in sick NE newborns. To address this roadblock, we have recently developed a new "wavelet neurovascular bundle" analytical system that can measure cerebral autoregulation (CA) and neurovascular coupling (NVC) at multiple time scales under dynamic, nonstationary clinical conditions. This wavelet analysis may allow noninvasive quantification at the bedside of (1) CA (combining metrics of blood pressure and cerebral near-infrared spectroscopy, NIRS) and (2) NVC (combining metrics obtained from NIRS and EEG) in newborns with encephalopathy without mathematical assumptions of linear and stationary systems. In this concept paper, we present case examples of NE using the proposed physiological wavelet metrics of CA and NVC. The new approach, once validated in large NE studies, has the potential to optimize the selection of candidates for therapeutic decision-making, and the prediction of neurocognitive outcomes.

Contrasting Effects of Posttraumatic Stress Disorder and Mild Traumatic Brain Injury on the Whole-Brain Resting-State Network: A Magnetoencephalography Study

The aim of this study was to evaluate alterations in whole-brain resting-state networks associated with posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI). Networks were constructed from locations of peak statistical power on an individual basis from magnetoencephalography (MEG) source series data by applying the weighted phase lag index and surrogate data thresholding procedures. Networks representing activity in the alpha bandwidth as well as wideband activity (DC-80 Hz) were created. Statistical comparisons were adjusted for age and education level. Alpha network results demonstrate reductions in network structure associated with PTSD, but no differences associated with mTBI. Wideband network results demonstrate a shift in connectivity from the alpha to theta bandwidth in both PTSD and mTBI. Also, contrasting alterations in network structure are noted, with increased randomness associated with PTSD and increased structure associated with mTBI. These results demonstrate the potential of the analysis of MEG resting-state networks to differentiate two highly comorbid conditions. The importance of the alpha bandwidth to resting-state connectivity is also highlighted, while demonstrating the necessity of considering activity in other bandwidths during network construction.

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

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

Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity

Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI.

Detecting concussion is typically not possible using currently clinically used brain imaging, such as MRI and CT scans. Magnetoencephalographic (MEG) imaging is able to directly measure brain activity at fast time scales, and this can be used to map how various areas of the brain interact. We recorded MEG from individuals who had suffered a concussion, as well as control subjects who had not. We found characteristic alterations of inter-regional interactions associated with concussion. Moreover, using a machine learning approach, we were able to detect concussion with 88% accuracy from MEG connectivity, and confidence of classification correlated with symptom severity. This potentially provides new quantitative and objective methods for detecting and assessing the severity of concussion using neuroimaging.

Traumatic brain injuries

Traumatic brain injuries (TBIs) are clinically grouped by severity: mild, moderate and severe. Mild TBI (the least severe form) is synonymous with concussion and is typically caused by blunt non-penetrating head trauma. The trauma causes stretching and tearing of axons, which leads to diffuse axonal injury - the best-studied pathogenetic mechanism of this disorder. However, mild TBI is defined on clinical grounds and no well-validated imaging or fluid biomarkers to determine the presence of neuronal damage in patients with mild TBI is available. Most patients with mild TBI will recover quickly, but others report persistent symptoms, called post-concussive syndrome, the underlying pathophysiology of which is largely unknown. Repeated concussive and subconcussive head injuries have been linked to the neurodegenerative condition chronic traumatic encephalopathy (CTE), which has been reported post-mortem in contact sports athletes and soldiers exposed to blasts. Insights from severe injuries and CTE plausibly shed light on the underlying cellular and molecular processes involved in mild TBI. MRI techniques and blood tests for axonal proteins to identify and grade axonal injury, in addition to PET for tau pathology, show promise as tools to explore CTE pathophysiology in longitudinal clinical studies, and might be developed into diagnostic tools for CTE. Given that CTE is attributed to repeated head trauma, prevention might be possible through rule changes by sports organizations and legislators.

Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity

In this study, we compared the brain activation profiles obtained from resting state Electroencephalographic (EEG) and Magnetoencephalographic (MEG) activity in six mild traumatic brain injury (mTBI) patients and five orthopedic controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar EEG/MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of mTBI patients into z-scores in eight distinct frequency bands. We found that mTBI patients exhibited statistically significant overactivation in the delta, theta, and low alpha bands. Additionally, the MEG modality seemed to better characterize the group of individual subjects. These findings suggest that resting-state EEG/MEG activation maps may be used as specific biomarkers that can help with the diagnosis of and assess the efficacy of intervention in mTBI patients.

Callosal dysfunction explains injury sequelae in a computational network model of axonal injury

Mild traumatic brain injury (mTBI) often results in neurobehavioral aberrations such as impaired attention and increased reaction time. Diffusion imaging and postmortem analysis studies suggest that mTBI primarily affects myelinated axons in white matter tracts. In particular, corpus callosum, mediating interhemispheric information exchange, has been shown to be affected in mTBI. Yet little is known about the mechanisms linking the injury of myelinated callosal axons to the neurobehavioral sequelae of mTBI. To address this issue, we devised and studied a large, biologically plausible neuronal network model of cortical tissue. Importantly, the model architecture incorporated intra- and interhemispheric organization, including myelinated callosal axons and distance-dependent axonal conduction delays. In the resting state, the intact model network exhibited several salient features, including alpha-band (8-12 Hz) collective activity with low-frequency irregular spiking of individual neurons. The network model of callosal injury captured several clinical observations, including 1) "slowing down" of the network rhythms, manifested as an increased resting-state theta-to-alpha power ratio, 2) reduced response to attention-like network stimulation, manifested as a reduced spectral power of collective activity, and 3) increased population response time in response to stimulation. Importantly, these changes were positively correlated with injury severity, supporting proposals to use neurobehavioral indices as biomarkers for determining the severity of injury. Our modeling effort helps to understand the role played by the injury of callosal myelinated axons in defining the neurobehavioral sequelae of mTBI.

Mapping the Connectome Following Traumatic Brain Injury

There is a paucity of accurate and reliable biomarkers to detect traumatic brain injury, grade its severity, and model post-traumatic brain injury (TBI) recovery. This gap could be addressed via advances in brain mapping which define injury signatures and enable tracking of post-injury trajectories at the individual level. Mapping of molecular and anatomical changes and of modifications in functional activation supports the conceptual paradigm of TBI as a disorder of large-scale neural connectivity. Imaging approaches with particular relevance are magnetic resonance techniques (diffusion weighted imaging, diffusion tensor imaging, susceptibility weighted imaging, magnetic resonance spectroscopy, functional magnetic resonance imaging, and positron emission tomographic methods including molecular neuroimaging). Inferences from mapping represent unique endophenotypes which have the potential to transform classification and treatment of patients with TBI. Limitations of these methods, as well as future research directions, are highlighted.

Magnetoencephalography-based identification of functional connectivity network disruption following mild traumatic brain injury

Mild traumatic brain injury (mTBI) leads to long-term cognitive sequelae in a significant portion of patients. Disruption of normal neural communication across functional brain networks may explain the deficits in memory and attention observed after mTBI. In this study, we used magnetoencephalography (MEG) to examine functional connectivity during a resting state in a group of mTBI subjects (n = 9) compared with age-matched control subjects (n = 15). We adopted a data-driven, exploratory analysis in source space using phase locking value across different frequency bands. We observed a significant reduction in functional connectivity in band-specific networks in mTBI compared with control subjects. These networks spanned multiple cortical regions involved in the default mode network (DMN). The DMN is thought to subserve memory and attention during periods when an individual is not engaged in a specific task, and its disruption may lead to cognitive deficits after mTBI. We further applied graph theoretical analysis on the functional connectivity matrices. Our data suggest reduced local efficiency in different brain regions in mTBI patients. In conclusion, MEG can be a potential tool to investigate and detect network alterations in patients with mTBI. The value of MEG to reveal potential neurophysiological biomarkers for mTBI patients warrants further exploration.

Identifying preoperative language tracts and predicting postoperative functional recovery using HARDI q-ball fiber tractography in patients with gliomas

OBJECT

Diffusion MRI has uniquely enabled in vivo delineation of white matter tracts, which has been applied to the segmentation of eloquent pathways for intraoperative mapping. The last decade has also seen the development from earlier diffusion tensor models to higher-order models, which take advantage of high angular resolution diffusion-weighted imaging (HARDI) techniques. However, these advanced methods have not been widely implemented for routine preoperative and intraoperative mapping.

The authors report on the application of residual bootstrap q-ball fiber tracking for routine mapping of potentially functional language pathways, the development of a system for rating tract injury to evaluate the impact on clinically assessed language function, and initial results predicting long-term language deficits following glioma resection.

METHODS

The authors have developed methods for the segmentation of 8 putative language pathways including dorsal phonological pathways and ventral semantic streams using residual bootstrap q-ball fiber tracking. Furthermore, they have implemented clinically feasible preoperative acquisition and processing of HARDI data to delineate these pathways for neurosurgical application. They have also developed a rating scale based on the altered fiber tract density to estimate the degree of pathway injury, applying these ratings to a subset of 35 patients with pre- and postoperative fiber tracking. The relationships between specific pathways and clinical language deficits were assessed to determine which pathways are predictive of long-term language deficits following surgery.

RESULTS

This tracking methodology has been routinely implemented for preoperative mapping in patients with brain gliomas who have undergone awake brain tumor resection at the University of California, San Francisco (more than 300 patients to date). In this particular study the authors investigated the white matter structure status and language correlation in a subcohort of 35 subjects both pre- and postsurgery. The rating scales developed for fiber pathway damage were found to be highly reproducible and provided significant correlations with language performance. Preservation of the left arcuate fasciculus (AF) and the temporoparietal component of the superior longitudinal fasciculus (SLF-tp) was consistent in all patients without language deficits (p < 0.001) at the long-term follow-up. Furthermore, in patients with short-term language deficits, the AF and/or SLF-tp were affected, and damage to these 2 pathways was predictive of a long-term language deficit (p = 0.005).

CONCLUSIONS

The authors demonstrated the successful application of q-ball tracking in presurgical planning for language pathways in brain tumor patients and in assessing white matter tract integrity postoperatively to predict long-term language dysfunction. These initial results predicting long-term language deficits following tumor resection indicate that postoperative injury to dorsal language pathways may be prognostic for long-term clinical language deficits.

Study results suggest the importance of dorsal stream tract preservation to reduce language deficits in patients undergoing glioma resection, as well as the potential prognostic value of assessing postoperative injury to dorsal language pathways to predict long-term clinical language deficits.

Advanced neuroimaging applied to veterans and service personnel with traumatic brain injury: state of the art and potential benefits

Traumatic brain injury (TBI) remains one of the most prevalent forms of morbidity among Veterans and Service Members, particularly for those engaged in the conflicts in Iraq and Afghanistan. Neuroimaging has been considered a potentially useful diagnostic and prognostic tool across the spectrum of TBI generally, but may have particular importance in military populations where the diagnosis of mild TBI is particularly challenging, given the frequent lack of documentation on the nature of the injuries and mixed etiologies, and highly comorbid with other disorders such as post-traumatic stress disorder, depression, and substance misuse. Imaging has also been employed in attempts to understand better the potential late effects of trauma and to evaluate the effects of promising therapeutic interventions. This review surveys the use of structural and functional neuroimaging techniques utilized in military studies published to date, including the utilization of quantitative fluid attenuated inversion recovery (FLAIR), susceptibility weighted imaging (SWI), volumetric analysis, diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), positron emission tomography (PET), magnetoencephalography (MEG), task-based and resting state functional MRI (fMRI), arterial spin labeling (ASL), and magnetic resonance spectroscopy (MRS). The importance of quality assurance testing in current and future research is also highlighted. Current challenges and limitations of each technique are outlined, and future directions are discussed.

Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury

Cross-frequency coupling (CFC) is thought to represent a basic mechanism of functional integration of neural networks across distant brain regions. In this study, we analyzed CFC profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 30 mild traumatic brain injury (mTBI) patients and 50 controls. We used mutual information (MI) to quantify the phase-to-amplitude coupling (PAC) of activity among the recording sensors in six nonoverlapping frequency bands. After forming the CFC-based functional connectivity graphs, we employed a tensor representation and tensor subspace analysis to identify the optimal set of features for subject classification as mTBI or control. Our results showed that controls formed a dense network of stronger local and global connections indicating higher functional integration compared to mTBI patients. Furthermore, mTBI patients could be separated from controls with more than 90% classification accuracy. These findings indicate that analysis of brain networks computed from resting-state MEG with PAC and tensorial representation of connectivity profiles may provide a valuable biomarker for the diagnosis of mTBI.

Reduced brain connectivity and mental flexibility in mild traumatic brain injury

OBJECTIVE

A mild traumatic brain injury (mTBI), or concussion, has known neuropsychological sequelae, and neuroimaging shows disturbed brain connectivity during the resting state. We hypothesized that task-based functional connectivity measures, using magnetoencephalography (MEG), would better link the neurobiological underpinnings of cognitive deficits to specific brain damage.

METHODS

We used a mental flexibility task in the MEG and compared brain connectivity between adults with and without mTBI.

RESULTS

Affected individuals showed significant reductions in connectivity. When challenged with a more difficult task, these individuals were not able to "boost" their connectivity, and as such, showed deterioration in performance.

INTERPRETATION

We discuss these findings in the context of limitations in cognitive reserve as a consequence of a mTBI.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI.

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We analyzed resting state connectivity profiles in 31 mTBI patients and 55 controls.

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We quantified frequency-specific connectivity couplings using phase-locking values.

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Normal control networks showed dense local and sparse long-range connections.

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TBI patient networks showed sparse local and dense long-range connections.

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Tensor subspace analysis could classify subjects with 100% accuracy in the α band

Delayed and disorganised brain activation detected with magnetoencephalography after mild traumatic brain injury

BACKGROUND

Awareness to neurocognitive issues after mild traumatic brain injury (mTBI) is increasing, but currently no imaging markers are available for mTBI. Advanced structural imaging recently showed microstructural tissue changes and axonal injury, mild but likely sufficient to lead to functional deficits. Magnetoencephalography (MEG) has high temporal and spatial resolution, combining structural and electrophysiological information, and can be used to examine brain activation patterns of regions involved with specific tasks.

METHODS

16 adults with mTBI and 16 matched controls were submitted to neuropsychological testing (Wechsler Abbreviated Scale of Intelligence (WASI); Conners; Alcohol Use Disorders Identification Test (AUDIT); Generalised Anxiety Disorder Seven-item Scale (GAD-7); Patient Health Questionnaire (PHQ-9); Symptom Checklist and Symptom Severity Score (SCAT2)) and MEG while tested for mental flexibility (Intra-Extra Dimensional set-shifting tasks). Three-dimensional maps were generated using synthetic aperture magnetometry beamforming analyses to identify differences in regional activation and activation times. Reaction times and accuracy between groups were compared using 2×2 mixed analysis of variance.

FINDINGS

While accuracy was similar, patients with mTBI reaction time was delayed and sequence of activation of brain regions disorganised, with involvement of extra regions such as the occipital lobes, not used by controls. Examination of activation time showed significant delays in the right insula and left posterior parietal cortex in patients with mTBI.

CONCLUSIONS

Patients with mTBI showed significant delays in the activation of important areas involved in executive function. Also, more regions of the brain are involved in an apparent compensatory effort. Our study suggests that MEG can detect subtle neural changes associated with cognitive dysfunction and thus, may eventually be useful for capturing and tracking the onset and course of cognitive symptoms associated with mTBI.

The Role of Thalamic Damage in Mild Traumatic Brain Injury

There is growing alarm in the United States about an epidemiologically large occurrence of mild traumatic brain injury with serious long lasting consequences. Although conventional imaging has been unable to identify damage capable of explaining its organic origin or discerning patients at risk of developing long-term or permanently disabling neurological impairment, most disease models assume that diffuse axonal injury in white matter must be present but is difficult to resolve. The few histopathological investigations conducted, however, show only limited evidence of such damage, which cannot account for the stereotypical globalized nature of symptoms generally reported in patients. This review examines recent proposals that in addition to white matter, the thalamus may be another important further site of injury. Although its possible role still remains largely under-investigated, evidence from experimental human and animal models, as well as simulational and analytical representations of mild head injury and other related conditions, suggest that this strategically vital region of the brain, which has reciprocal projections to the entire cerebral cortex, could feasibly play an important role in understanding pathology and predicting outcome.

Increased Network Excitability Due to Altered Synaptic Inputs to Neocortical Layer V Intact and Axotomized Pyramidal Neurons after Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) can produce long lasting cognitive dysfunction. There is typically no cell death and only diffuse structural injury after mTBI. Thus, functional changes in intact neurons may contribute to symptoms. We have previously shown altered intrinsic properties of axotomized and intact neurons within 2 d after a central fluid percussion injury in mice expressing yellow fluorescent protein (YFP) that allow identification of axonal state prior to recording. Here, whole-cell patch clamp recordings were used to examine synaptic properties of YFP(+) layer V pyramidal neurons. An increased frequency of spontaneous and miniature excitatory postsynaptic currents (EPSCs) was recorded from axotomized neurons at 1 d and intact neurons at 2 d after injury, likely reflecting an increased number of afferents. This also was reflected in the increased amplitude of the EPSC evoked by local extracellular stimulation for all neurons from injured cortex and increased likelihood of producing an action potential for intact cells. Field potentials recorded in superficial layers after online deep layer stimulation contained a single negative peak in controls but multiple negative peaks in injured tissue. The amplitude of this evoked negativity was significantly larger than controls over a series of stimulus intensities at both the 1 d and 2 d survival times. Interictal-like spikes never occurred in the field potential recordings from controls but were observed in 20-80% of stimulus presentations in injured cortex. Together, these results suggest an overall increase in network excitability and the production of particularly powerful (intact) neurons that have both increased intrinsic and synaptic excitability.

What's New in Traumatic Brain Injury: Update on Tracking, Monitoring and Treatment

Traumatic brain injury (TBI), defined as an alteration in brain functions caused by an external force, is responsible for high morbidity and mortality around the world. It is important to identify and treat TBI victims as early as possible. Tracking and monitoring TBI with neuroimaging technologies, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), positron emission tomography (PET), and high definition fiber tracking (HDFT) show increasing sensitivity and specificity. Classical electrophysiological monitoring, together with newly established brain-on-chip, cerebral microdialysis techniques, both benefit TBI. First generation molecular biomarkers, based on genomic and proteomic changes following TBI, have proven effective and economical. It is conceivable that TBI-specific biomarkers will be developed with the combination of systems biology and bioinformation strategies. Advances in treatment of TBI include stem cell-based and nanotechnology-based therapy, physical and pharmaceutical interventions and also new use in TBI for approved drugs which all present favorable promise in preventing and reversing TBI.

Global and regional functional connectivity maps of neural oscillations in focal epilepsy

Intractable focal epilepsy is a devastating disorder with profound effects on cognition and quality of life. Epilepsy surgery can lead to seizure freedom in patients with focal epilepsy; however, sometimes it fails due to an incomplete delineation of the epileptogenic zone. Brain networks in epilepsy can be studied with resting-state functional connectivity analysis, yet previous investigations using functional magnetic resonance imaging or electrocorticography have produced inconsistent results. Magnetoencephalography allows non-invasive whole-brain recordings, and can be used to study both long-range network disturbances in focal epilepsy and regional connectivity at the epileptogenic zone. In magnetoencephalography recordings from presurgical epilepsy patients, we examined: (i) global functional connectivity maps in patients versus controls; and (ii) regional functional connectivity maps at the region of resection, compared to the homotopic non-epileptogenic region in the contralateral hemisphere. Sixty-one patients were studied, including 30 with mesial temporal lobe epilepsy and 31 with focal neocortical epilepsy. Compared with a group of 31 controls, patients with epilepsy had decreased resting-state functional connectivity in widespread regions, including perisylvian, posterior temporo-parietal, and orbitofrontal cortices (P < 0.01, t-test). Decreased mean global connectivity was related to longer duration of epilepsy and higher frequency of consciousness-impairing seizures (P < 0.01, linear regression). Furthermore, patients with increased regional connectivity within the resection site (n = 24) were more likely to achieve seizure postoperative seizure freedom (87.5% with Engel I outcome) than those with neutral (n = 15, 64.3% seizure free) or decreased (n = 23, 47.8% seizure free) regional connectivity (P < 0.02, chi-square). Widespread global decreases in functional connectivity are observed in patients with focal epilepsy, and may reflect deleterious long-term effects of recurrent seizures. Furthermore, enhanced regional functional connectivity at the area of resection may help predict seizure outcome and aid surgical planning.

Low-frequency connectivity is associated with mild traumatic brain injury

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

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Patients with mTBI display increased connectivity in low-frequency resting state.

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Elevated low-frequency power observed in temporal and deep-grey regions in mTBI

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Frontal, temporal and deep-grey regions show increased amplitude correlations in mTBI.

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Disorders of attention, anxiety and depression are associated with distinct, frequency-specific networks across the brain.

Traumatic brain injury imaging research roadmap

The past decade has seen impressive advances in the types of neuroimaging information that can be acquired in patients with traumatic brain injury. However, despite this increase in information, understanding of the contribution of this information to prognostic accuracy and treatment pathways for patients is limited. Available techniques often allow us to infer the presence of microscopic changes indicative of alterations in physiology and function in brain tissue. However, because histologic confirmation is typically lacking, conclusions reached by using these techniques remain solely inferential in almost all cases. Hence, a need exists for validation of these techniques by using data from large population samples that are obtained in a uniform manner, analyzed according to well-accepted procedures, and correlated with closely monitored clinical outcomes. At present, many of these approaches remain confined to population-based research rather than diagnosis at an individual level, particularly with regard to traumatic brain injury that is mild or moderate in degree. A need and a priority exist for patient-centered tools that will allow advanced neuroimaging tools to be brought into clinical settings. One barrier to developing these tools is a lack of an age-, sex-, and comorbidities-stratified, sequence-specific, reference imaging data base that could provide a clear understanding of normal variations across populations. Such a data base would provide researchers and clinicians with the information necessary to develop computational tools for the patient-based interpretation of advanced neuroimaging studies in the clinical setting. The recent "Joint ASNR-ACR HII-ASFNR TBI Workshop: Bringing Advanced Neuroimaging for Traumatic Brain Injury into the Clinic" on May 23, 2014, in Montreal, Quebec, Canada, brought together neuroradiologists, neurologists, psychiatrists, neuropsychologists, neuroimaging scientists, members of the National Institute of Neurologic Disorders and Stroke, industry representatives, and other traumatic brain injury stakeholders to attempt to reach consensus on issues related to and develop consensus recommendations in terms of creating both a well-characterized normative data base of comprehensive imaging and ancillary data to serve as a reference for tools that will allow interpretation of advanced neuroimaging tests at an individual level of a patient with traumatic brain injury. The workshop involved discussions concerning the following: 1) designation of the policies and infrastructure needed for a normative data base, 2) principles for characterizing normal control subjects, and 3) standardizing research neuroimaging protocols for traumatic brain injury. The present article summarizes these recommendations and examines practical steps to achieve them.

Different Neural Mechanisms Underlie Deficits in Mental Flexibility in Post-Traumatic Stress Disorder Compared to Mild Traumatic Brain Injury

Mental flexibility is a core executive function that underlies the ability to adapt to changing situations and respond to new information. Individuals with post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) complain of a number of executive function difficulties, one of which is mental inflexibility or an inability to switch between concepts. While the behavioral presentation of mental inflexibility is similar in those with PTSD or mTBI, we hypothesized that the differences in their etiology would manifest as differences in their underlying brain processing. The neural substrates of mental flexibility have been examined with a number of neuroimaging modalities. Functional magnetic resonance imaging has elucidated the brain regions involved, whereas electroencephalography has been applied to understand the timing of the brain activations. Magnetoencephalography, with its high temporal and spatial resolution, has more recently been used to delineate the spatiotemporal progression of brain processes involved in mental flexibility and has been applied to the study of clinical populations. In a number of separate studies, our group has compared the source localization and brain connectivity during a mental flexibility set-shifting task in a group of soldiers with PTSD and civilians with an acute mTBI. In this article, we review the results from these studies and integrate the data between groups to compare and contrast differences in behavioral, neural, and connectivity findings. We show that the different etiologies of PTSD and mTBI are expressed as distinct neural profiles for mental flexibility that differentiate the groups despite their similar clinical presentations.