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The study aims to (1) examine the spatiotemporal map of magnetoencephalography-evoked responses during an Auditory Memory Retrieval and Silent Repeating (AMRSR) task, and determine the hemispheric dominance for language, and (2) evaluate the accuracy of the AMRSR task in Wernicke and Broca area localization.In 30 patients with brain tumors and/or epilepsies, the AMRSR task was used to evoke magnetoencephalography responses. We applied Fast VEctor-based Spatial-Temporal Analyses with minimum L1-norm source imaging method to the magnetoencephalography responses for localizing the brain areas evoked by the AMRSR task.The Fast-VEctor-based Spatial-Temporal Analysis found consistent activation in the posterior superior temporal gyrus around 300 to 500 ms, and another activation in the frontal cortex (pars opercularis and/or pars triangularis) around 600 to 900 ms, which were localized to the Wernicke area (BA 22) and Broca area (BA 44 and BA 45), respectively. The language-dominant hemispheric laterization elicited by the AMRSR task was comparable with the result from an Auditory Dichotic task result given to the same patient, with the exception that AMRSR is more sensitive on bilateral language laterization cases on finding the Wernicke and Broca areas.For all patients who successfully finished the AMRSR task, Fast-VEctor-based Spatial-Temporal Analysis could establish accurate and robust localizations of Broca and Wernicke area and determine hemispheric dominance. For subjects with normal auditory functionality, the AMRSR paradigm evaluation showed significant promise in providing reliable assessments of cerebral language dominance and language network localization.

At rest, 8 to 12 Hz alpha rhythms are the dominant rhythm in the brain, with a common peak alpha frequency (PAF = the frequency at which alpha generators show maximum power) observed across brain regions. Although a common PAF across brain regions should result in high between-region connectivity, especially connectivity measures assessing the phase-similarity between alpha generators, high inter-regional alpha connectivity has not been observed. The present study was conducted as an initial step toward identifying mechanisms that allow brain regions to maintain functional independence in the presence of a common PAF.MEG data were obtained from 16 healthy control male adults (mean age = 24 years; range 21 to 30 years). A task requiring participants to alternate between a 10 s eyes-closed condition and a 5 s eyes-open condition was used to drive parietal-occipital alpha generators, with the 10 s eyes-closed condition eliciting large-amplitude alpha activity and thus providing alpha measures with good signal-to-noise ratio for source localization. Alpha source-space measures were obtained using Vector-based Spatial-Temporal Analysis using L1-minimum-norm. In each participant, the four strongest parietal-occipital alpha generators were identified. Connectivity between sources was assessed via a measure of phase-based connectivity called inter-site phase clustering (ISPC).Intra-class correlations (ICC) showed very high similarity in the average PAF (=computed using all eyes-closed data) between the four alpha sources (ICC single measure = 0.88, p 0.001). Despite a common average PAF, across participants, significant ISPC was often observed no more than that expected by chance. Examination of the alpha time course data indicated that low ISPC was often due to instantaneous changes in alpha phase (phase slips). ISPC analyses removing data with phase slips indicated that low ISPC was also due to slight continuous changes in the alpha frequency, with frequency drift more likely in non-significant than significant ISPC trials.The present exploratory effort suggested two processes underlying the lack of observed inter-regional alpha phase coherence that may help maintain regional functional independence even in the presence of a common PAF. In particular, although the alpha generators were observed to oscillate at the same rate on average, across time each alpha generator oscillated a little slower or faster, and about every one and a half seconds an alpha generator abruptly lost the beat. Because of this, functional independence among alpha generators (and thus brain regions) was the rule rather than the exception. Studies replicating these processes that allow brain regions to maintain functional independence, using different source localization methods and in different conditions (e.g., a true resting state), are warranted.Using source localization to measure parietal-occipital alpha generator activity, two properties that limit between-region alpha functional connectivity are proposed. In particular, a model of alpha generator activity is offered where via transient phase slips occurring approximately every 1.5 s, as well as slight non-stationarity in the alpha frequency, brain regions retain a common alpha frequency while also maintaining regional identity and presumably functionality. Findings also suggest novel markers for use in studies examining changes in alpha activity across maturation as well as in studies examining alpha activity in patient populations where alpha abnormalities have been reported.

Advancements in deep learning algorithms over the past decade have led to extensive developments in brain–computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging technique. The present study developed a MEG sensor-based BCI neural network to decode Rock-Paper-scissors gestures (MEG-RPSnet). Unique preprocessing pipelines in tandem with convolutional neural network deep-learning models accurately classified gestures. On a single-trial basis, we found an average of 85.56% classification accuracy in 12 subjects. Our MEG-RPSnet model outperformed two state-of-the-art neural network architectures for electroencephalogram-based BCI as well as a traditional machine learning method, and demonstrated equivalent and/or better performance than machine learning methods that have employed invasive, electrocorticography-based BCI using the same task. In addition, MEG-RPSnet classification performance using an intra-subject approach outperformed a model that used a cross-subject approach. Remarkably, we also found that when using only central-parietal-occipital regional sensors or occipitotemporal regional sensors, the deep learning model achieved classification performances that were similar to the whole-brain sensor model. The MEG-RSPnet model also distinguished neuronal features of individual hand gestures with very good accuracy. Altogether, these results show that noninvasive MEG-based BCI applications hold promise for future BCI developments in hand-gesture decoding.

Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.

The pain experience is a complex process that involves the activation of multiple neuronal signaling pathways that originate in the peripheral nervous system and are transmitted to the central nervous system. In the peripheral nervous system, specialized peripheral nociceptor (unmyelinated C fibers and lightly myelinated Aδ fibers) depolarization results in afferent transmission of noxious signals. Small Fiber Neuropathy (SFN) can result in chronic neuropathic pain with significant lifetime morbidity if not promptly treated. Current technological and operator limitations may delay SFN diagnosis and prolong appropriate treatment. Therefore, there is an unmet need for robust and non-invasive ways to accurately measure small fiber function. It is well known that the propagation of action potentials along a nerve is the result of ionic current flow which, according to Ampere’s Law, generates a small magnetic field that is detectable by magnetometers such as superconducting quantum interference device (SQUID) Magnetoencephalography (MEG) systems. Optically pumped magnetometers (OPM) are an emerging class of quantum magnetic sensors with a demonstrated sensitivity of 1 fT/√Hz level, capable of cortical action potential detection. However, they have not as of yet been implemented for peripheral nerve action potential detection. We demonstrate for the first time, compelling evidence that OPMs can detect the magnetic signature of travelling peripheral nerve action potentials that indicate OPM’s use as a potential technique for SFN diagnosis.

Decline in semantic cognition in early stages of Parkinson’s disease (PD) is a leading risk factor for future dementia, yet the underlying neural mechanisms are not understood. The present study addressed this gap by investigating the functional connectivity of regions involved in semantic recollection. We further examined whether microtubule-associated protein tau (MAPT) risk variants, which may accelerate cognitive decline, altered the strength of regional functional connections. Cognitively normal PD and healthy elder controls underwent fMRI while performing a fame-discrimination task, which activates the semantic network. Analyses focused on disturbances in fame-modulated functional connectivity in PD for regions that govern semantic recollection and interrelated processes. Group differences were found in multiple connectivity features, which were reduced into principal components that reflected the strength of fame-modulated regional couplings with other brain areas. Despite the absence of group differences in semantic cognition, two aberrant connectivity patterns were uncovered in PD. One pattern was related to a loss in frontal, parietal, and temporal connection topologies that governed semantic recollection in older controls. Another pattern was characterized by functional reconfiguration, wherein frontal, parietal, temporal and caudate couplings were strengthened with areas that were not recruited by controls. Correlations between principal component scores and cognitive measures suggested that reconfigured frontal coupling topologies in PD supported compensatory routes for accessing semantic content, whereas reconfigured parietal, temporal, and caudate connection topologies were detrimental or unrelated to cognition. Increased tau transcription diminished recruitment of compensatory frontal topologies but amplified recruitment of parietal topologies that were unfavorable for cognition. Collectively, the findings provide a new understanding of early vulnerabilities in the functional architecture of regional connectivity during semantic recollection in cognitively normal PD. The findings also have implications for tracking cognitive progression and selecting patients who stand to benefit from therapeutic interventions.

Well-established in the field of bioelectronic medicine, Spinal Cord Stimulation (SCS) offers an implantable, non-pharmacologic treatment for patients with intractable chronic pain conditions. Chronic pain is a widely heterogenous syndrome with regard to both pathophysiology and the resultant phenotype. Despite advances in our understanding of SCS-mediated antinociception, there still exists limited evidence clarifying the pathways recruited when patterned electric pulses are applied to the epidural space. The rapid clinical implementation of novel SCS methods including burst, high frequency and dorsal root ganglion SCS has provided the clinician with multiple options to treat refractory chronic pain. While compelling evidence for safety and efficacy exists in support of these novel paradigms, our understanding of their mechanisms of action (MOA) dramatically lags behind clinical data. In this review, we reconstruct the available basic science and clinical literature that offers support for mechanisms of both paresthesia spinal cord stimulation (P-SCS) and paresthesia-free spinal cord stimulation (PF-SCS). While P-SCS has been heavily examined since its inception, PF-SCS paradigms have recently been clinically approved with the support of limited preclinical research. Thus, wide knowledge gaps exist between their clinical efficacy and MOA. To close this gap, many rich investigative avenues for both P-SCS and PF-SCS are underway, which will further open the door for paradigm optimization, adjunctive therapies and new indications for SCS. As our understanding of these mechanisms evolves, clinicians will be empowered with the possibility of improving patient care using SCS to selectively target specific pathophysiological processes in chronic pain.

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members and veterans. Recent animal studies show that GABA-ergic parvalbumin-positive interneurons are susceptible to brain injury, with damage causing abnormal increases in spontaneous gamma-band (30–80 Hz) activity. We investigated spontaneous gamma activity in individuals with mTBI using high-resolution resting-state magnetoencephalography source imaging. Participants included 25 symptomatic individuals with chronic combat-related blast mTBI and 35 healthy controls with similar combat experiences. Compared with controls, gamma activity was markedly elevated in mTBI participants throughout frontal, parietal, temporal, and occipital cortices, whereas gamma activity was reduced in ventromedial prefrontal cortex. Across groups, greater gamma activity correlated with poorer performances on tests of executive functioning and visuospatial processing. Many neurocognitive associations, however, were partly driven by the higher incidence of mTBI participants with both higher gamma activity and poorer cognition, suggesting that expansive upregulation of gamma has negative repercussions for cognition particularly in mTBI. This is the first human study to demonstrate abnormal resting-state gamma activity in mTBI. These novel findings suggest the possibility that abnormal gamma activities may be a proxy for GABA-ergic interneuron dysfunction and a promising neuroimaging marker of insidious mild head injuries.

Background In the U.S. 3.8 million people have a Traumatic Brain Injury (TBI) each year. Rapid brain training exercises to improve cognitive function after a mild TBI are needed. Objective This study determines whether cognitive remediation by discriminating the direction a test pattern moves relative to a stationary background (movement figure-ground discrimination) improves the vision and cognitive deficits that result from a TBI, providing a paradigm shift in treatment methods. Methods Movement-discrimination neurotraining was used to remediate low-level visual timing deficits in the dorsal stream to determine whether it improved high-level cognitive functions, such as processing speed, reading fluency, and the executive control functions of attention and working memory in four men with a TBI between the ages of 15-68. Standardized tests, as well as Magnetoencephalography (MEG) brain imaging, were administered at the beginning and end of 8-16 weeks of intervention training to evaluate improvements in cognitive skills. Results Movement-discrimination cognitive neurotraining remediated both low-level visual timing deficits and high-level cognitive functioning, including selective and sustained attention, reading fluency, processing speed, and working memory for all TBI patients we studied. MEG brain imaging, using the Fast-VESTAL procedure, showed that this movement-discrimination training improved time-locked activity in the dorsal stream, attention, and executive control networks. Conclusions Remediating visual timing deficits in the dorsal stream revealed the causal role of visual movement discrimination training in improving high-level cognitive functions such as focusing and switching attention, working memory, processing speed, and reading. This study found that movement-discrimination training was very rapid and effective in remediating cognitive deficits, providing a new approach that is very beneficial for treating a mild TBI.

(1) Background: Substantial evidence that neural timing deficits are prevalent in developmental disorders, aging, and concussions resulting from a mild Traumatic Brain Injury (mTBI) is presented. We show that if timing deficits are remediated using low-level movement discrimination training, then high-level cognitive skills, including reading, attention, processing speed, and working memory improve substantially. (2) Methods: Two case studies are presented using MEG source imaging on an adult dyslexic, and a healthy older adult observed before and after training on movement discrimination two times/week for 8 weeks for adult dyslexic. (3) Results: We found improvements in reading, attention, processing speed, and working memory on neuropsychological tests. Substantial MEG signal increases in visual Motion Networks (V1, V3, MT, MST), Attention Networks (ACC, dlPFC, vlPFC and precuneous/ PCC areas) and Memory Networks (dlPFC). (4) Conclusions: Improving neural timing deficits before cognitive exercises to improve specific cognitive skills provides a rapid and effective method to improve cognitive skills. Improving the timing and sensitivity of low-level dorsal pathways, improving feedforward and feedback pathways, is essential to improve high-level cognitive skills. This adaptive training with substantial feedback shows cognitive transfer to tasks not trained on, significantly improving a person’s quality of life rapidly and effectively.

Combat‐related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active‐duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep‐learning neural network method, 3D‐MEGNET, and applied it to resting‐state magnetoencephalography (rs‐MEG) source‐magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat‐deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All‐frequency model, which combined delta‐theta (1–7 Hz), alpha (8–12 Hz), beta (15–30 Hz), and gamma (30–80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D‐MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver‐operator‐characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta‐theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta‐theta and gamma‐band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta‐band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source‐imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all‐frequency model offered more discriminative power than each frequency‐band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders., This study developed a novel resting‐state magnetoencephalography (rs‐MEG) source‐magnitude imaging method, 3D‐MEGNET, using deep learning. The optimized 3D‐MEGNET method combining rs‐MEG data from all frequency bands distinguished individuals with combat‐related mild traumatic brain injury (cmTBI) from combat‐deployed healthy controls with high sensitivity, specificity, and diagnostic accuracy. This study provides an integrated framework for condensing large source‐imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI.

Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.

Mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) are leading causes of sustained physical, cognitive, emotional, and behavioral deficits in the general population, active-duty military personnel, and veterans. However, the underlying pathophysiology of mTBI/PTSD and the mechanisms that support functional recovery for some, but not all individuals is not fully understood. Conventional MR imaging and computed tomography are generally negative in mTBI and PTSD, so there is interest in the development of alternative evaluative strategies. Of particular note are magnetoencephalography (MEG) -based methods, with mounting evidence that MEG can provide sensitive biomarkers for abnormalities in mTBI and PTSD.

Noninvasive functional brain imaging with magnetoencephalography (MEG) is regularly used to map the eloquent cortex associated with somatosensory, motor, auditory, visual, and language processing before a surgical resection to determine if the functional areas have been reorganized. Most tasks can also be performed in the pediatric population. To acquire an optimal MEG study for any of these modalities, the patient needs to be well rested and attending to the stimulation.

Mild traumatic brain injury (mTBI) accounts for the vast majority of all pediatric TBI. An important minority of children who have suffered an mTBI have enduring cognitive and emotional symptoms. However, the mechanisms of chronic symptoms in children with pediatric mTBI are not fully understood. This is in part due to the limited sensitivity of conventional neuroimaging technologies. The present study examined resting-state magnetoencephalography (rs-MEG) source images in 12 children who had mTBI and 12 age-matched control children. The rs-MEG exams were performed in children with mTBI 6 months after injury when they reported no clinically significant post-injury psychiatric changes and few if any somatic sensorimotor symptoms but did report cognitive symptoms. MEG source magnitude images were obtained for different frequency bands in alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. In contrast to the control participants, rs-MEG source imaging in the children with mTBI showed: 1) hyperactivity from the bilateral insular cortices in alpha, beta, and low-frequency bands, from the left amygdala in alpha band, and from the left precuneus in beta band; 2) hypoactivity from the bilateral dorsolateral prefrontal cortices (dlPFC) in alpha and beta bands, from the ventromedial prefrontal cortex (vmPFC) in beta band, from the ventrolateral prefrontal cortex (vlPFC) in gamma band, from the anterior cingulate cortex (ACC) in alpha band, and from the right precuneus in alpha band. The present study showed that MEG source imaging technique revealed abnormalities in the resting-state electromagnetic signals from the children with mTBI.

Objective To identify amygdalar volumetric differences associated with posttraumatic stress disorder (PTSD) in individuals with comorbid mild traumatic brain injury (mTBI) compared with those with mTBI-only and to examine the effects of intracranial volume (ICV) on amygdala volumetric measures. Setting Marine Corps Base and VA Healthcare System. Participants A cohort of veterans and active-duty military personnel with combat-related mTBI (N = 89). Design Twenty-nine participants were identified with comorbid PTSD and mTBI. The remaining 60 formed the mTBI-only control group. Structural images of brains were obtained with a 1.5-T MRI scanner using a T1-weighted 3D-IR-FSPGR pulse sequence. Automatic segmentation was performed in Freesurfer. Main measures Amygdala volumes with/without normalizations to ICV. Results The comorbid mTBI/PTSD group had significantly larger amygdala volumes, when normalized to ICV, compared with the mTBI-only group. The right and left amygdala volumes after normalization to ICV were 0.122% ± 0.012% and 0.118% ± 0.011%, respectively, in the comorbid group compared with 0.115% ± 0.012% and 0.112% ± 0.009%, respectively, in the mTBI-only group (corrected P Conclusions The ICV normalization analysis performed here may resolve previous literature discrepancies. This is an intriguing structural finding, given the role of the amygdala in the challenging neuroemotive symptoms witnessed in casualties of combat-related mTBI and PTSD.

Background Auditory encoding abnormalities, gray-matter loss, and cognitive deficits are all candidate schizophrenia (SZ) endophenotypes. This study evaluated associations between and heritability of auditory network attributes (function and structure) and attention in healthy controls (HC), SZ patients, and unaffected relatives (UR). Methods Whole-brain maps of M100 auditory activity from magnetoencephalography recordings, cortical thickness (CT), and a measure of attention were obtained from 70 HC, 69 SZ patients, and 35 UR. Heritability estimates (h2r) were obtained for M100, CT at each group-difference region, and the attention measure. Results SZ patients had weaker bilateral superior temporal gyrus (STG) M100 responses than HC and a weaker right frontal M100 response than UR. Abnormally large M100 responses in left superior frontal gyrus were observed in UR and SZ patients. SZ patients showed smaller CT in bilateral STG and right frontal regions. Interrelatedness between 3 putative SZ endophenotypes was demonstrated, although in the left STG the M100 and CT function−structure associations observed in HC and UR were absent in SZ patients. Heritability analyses also showed that right frontal M100 and bilateral STG CT measures are significantly heritable. Conclusions Present findings indicated that the 3 SZ endophenotypes examined are not isolated markers of pathology but instead are connected. The pattern of auditory encoding group differences and the pattern of brain function−structure associations differ as a function of brain region, indicating the need for regional specificity when studying these endophenotypes, and with the presence of left STG function−structure associations in HC and UR but not in SZ perhaps reflecting disease-associated damage to gray matter that disrupts function−structure relationships in SZ.

Although the 40 Hz auditory steady-state response (ASSR) is of clinical interest, the construct validity of EEG and MEG measures of 40 Hz ASSR cortical microcircuits is unclear. This study evaluated several MEG and EEG metrics by leveraging findings of (a) an association between the 40 Hz ASSR and age in the left but not right hemisphere, and (b) right- > left-hemisphere differences in the strength of the 40 Hz ASSR. The contention is that, if an analysis method does not demonstrate a left 40 Hz ASSR and age relationship or hemisphere differences, then the obtained measures likely have low validity. Fifty-three adults were presented 500 Hz stimuli modulated at 40 Hz while MEG and EEG were collected. ASSR activity was examined as a function of phase similarity (intertrial coherence) and percent change from baseline (total power). A variety of head models (spherical and realistic) and a variety of dipole source modeling strategies (dipole source localization and dipoles fixed to Heschl's gyri) were compared. Several sensor analysis strategies were also tested. EEG sensor measures failed to detect left 40 Hz ASSR and age associations or hemisphere differences. A comparison of MEG and EEG head-source models showed similarity in the 40 Hz ASSR measures and in estimating age and left 40 Hz ASSR associations, indicating good construct validity across models. Given a goal of measuring the 40 Hz ASSR cortical microcircuits, a source-modeling approach was shown to be superior in measuring this construct versus methods that rely on EEG sensor measures.

Visuospatial working memory impairments are common in Parkinson's disease (PD), yet the underlying neural mechanisms are poorly understood. The present study investigated abnormalities in context-dependent functional connectivity of working memory hubs in PD. Cognitively normal PD and control participants underwent fMRI while performing a visuospatial working memory task. To identify sources of dysfunction, distraction, and load-modulated connectivity were disentangled for encoding and retrieval phases of the task. Despite normal working memory performance in PD, two features of abnormal connectivity were observed, one due to a loss in normal context-related connectivity and another related to upregulated connectivity of hubs for which the controls did not exhibit context-dependent connectivity. During encoding, striatal-prefrontal coupling was lost in PD, both during distraction and high memory loads. However, long-range connectivity of prefrontal, medial temporal and occipital hubs was upregulated in a context-specific manner. Memory retrieval was characterized by different aberrant connectivity patterns, wherein precuneus connectivity was upregulated during distraction, whereas prefrontal couplings were lost as memory load approached capacity limits. Features of abnormal functional connectivity in PD had pathological and compensatory influences as they correlated with poorer working memory or better visuospatial skills. The results offer new insights into working memory-related signatures of aberrant cortico-cortical and corticostriatal functional connections, which may portend future declines in different facets of working memory.

Objective Localizing expressive language function has been challenging using the conventional magnetoencephalography (MEG) source modeling methods. The present MEG study presents a new accurate and precise approach in localizing the language areas using a high-resolution MEG source imaging method. Methods In 32 patients with brain tumors and/or epilepsies, an object-naming task was used to evoke MEG responses. Our Fast-VESTAL source imaging method was then applied to the MEG data in order to localize the brain areas evoked by the object-naming task. Results The Fast-VESTAL results showed that Broca’s area was accurately localized to the pars opercularis (BA 44) and/or the pars triangularis (BA 45) in all patients. Fast-VESTAL also accurately localized Wernicke’s area to the posterior aspect of the superior temporal gyri in BA 22, as well as several additional brain areas. Furthermore, we found that the latency of the main peak of the response in Wernicke’s area was significantly earlier than that of Broca’s area. Conclusion In all patients, Fast-VESTAL analysis established accurate and precise localizations of Broca’s area, as well as other language areas. The responses in Wernicke’s area were also shown to significantly precede those of Broca’s area. Significance The present study demonstrates that using Fast-VESTAL, MEG can serve as an accurate and reliable functional imaging tool for presurgical mapping of language functions in patients with brain tumors and/or epilepsies.

Summary Background Pervasive use of improvised explosive devices (IEDs), rocket-propelled grenades, and land mines in the recent conflicts in Iraq and Afghanistan has brought traumatic brain injury (TBI) and its impact on health outcomes into public awareness. Blast injuries have been deemed signature wounds of these wars. War-related TBI is not new, having become prevalent during WWI and remaining medically relevant in WWII and beyond. Medicine's past attempts to accurately diagnose and disentangle the pathophysiology of war-related TBI parallels current lines of inquiry and highlights limitations in methodology and attribution of symptom etiology, be it organic, psychological, or behavioral. New approaches and biomarkers are needed. Preclinical Serological biomarkers and biomarkers of injury obtained with imaging techniques represent cornerstones in the translation between experimental data and clinical observations. Experimental models for blast related TBI and PTSD can generate critical data on injury threshold, for example for white matter injury from acceleration. Carefully verified and validated models can be evaluated with gene expression arrays and proteomics to identify new candidates for serological biomarkers. Such models can also be analyzed with diffusion MRI and microscopy in order to identify criteria for detection of diffuse white matter injuries, such as DAI (diffuse axonal injury). The experimental models can also be analyzed with focus on injury outcome in brain stem regions, such as locus coeruleus or nucleus raphe magnus that can be involved in response to anxiety changes. Clinical Mild (and some moderate) TBI can be difficult to diagnose because the injuries are often not detectable on conventional MRI or CT. There is accumulating evidence that injured brain tissues in TBI patients generate abnormal low-frequency magnetic activity (ALFMA, peaked at 1–4 Hz) that can be measured and localized by magnetoencephalography (MEG). MEG imaging detects TBI abnormalities at the rates of 87% for the mild TBI, group (blast-induced plus non-blast causes) and 100% for the moderate group. Among the mild TBI patients, the rates of abnormalities are 96% and 77% for the blast and non-blast TBI groups, respectively. There is emerging evidence based on fMRI and MEG studies showing hyper-activity in the amygdala and hypo-activity in pre-frontal cortex in individuals with PTSD. MEG signal may serve as a sensitive imaging marker for mTBI, distinguishable from abnormalities generated in association with PTSD. More work is needed to fully describe physiological mechanisms of post-concussive symptoms.

Introduction Mild TBI (TBI) is associated with up to a 75.7% incidence of tinnitus, and 33.0% of tinnitus patients at the US Veterans Administration carry a diagnosis of post-traumatic stress syndrome (PTSD). Yet factors contributing to new onset or exacerbation of tinnitus remain unclear. Materials and Methods Here we measure intermittent and constant tinnitus at two time points to ascertain whether pre-existing or co-occurring traumatic brain injury (TBI), hearing loss, or post-traumatic stress disorder (PTSD) predicts new onset, lack of recovery and/or worsening of tinnitus in 2,600 United States Marines who were assessed before and after a combat deployment. Results Ordinal regression revealed that constant tinnitus before deployment was likely to continue after deployment (odds ratio [OR] = 28.62, 95% confidence interval [CI]: 9.84,83.26). Prior intermittent tinnitus increased risk of post-deployment constant tinnitus (OR = 4.95, CI: 2.97,8.27). Likelihood of tinnitus progression increased with partial PTSD (OR = 2.39, CI: 1.50,3.80) and TBI (OR = 1.59, CI: 1.13,2.23), particularly for blast TBI (OR = 2.01, CI: 1.27,3.12) and moderate to severe TBI (OR = 2.57, CI: 1.46,4.51). Tinnitus progression also increased with low frequency hearing loss (OR = 1.94, CI: 1.05,3.59), high frequency loss (OR = 3.01, CI: 1.91,4.76) and loss across both low and high frequency ranges (OR = 5.73, CI: 2.67,12.30). Conclusions Screening for pre-existing or individual symptoms of PTSD, TBI, and hearing loss may allow for more focused treatment programs of comorbid disorders. Identification of those personnel vulnerable to tinnitus or its progression may direct increased acoustic protection for those at risk.

The mechanisms by which noninvasive vagal nerve stimulation (nVNS) affect central and peripheral neural circuits that subserve pain and autonomic physiology are not clear, and thus remain an area of intense investigation. Effects of nVNS vs sham stimulation on subject responses to five noxious thermal stimuli (applied to left lower extremity), were measured in 30 healthy subjects (n=15 sham and n=15 nVNS), with fMRI and physiological galvanic skin response (GSR). With repeated noxious thermal stimuli a group × time analysis showed a significantly (p < .001) decreased response with nVNS in bilateral primary and secondary somatosensory cortices (SI and SII), left dorsoposterior insular cortex, bilateral paracentral lobule, bilateral medial dorsal thalamus, right anterior cingulate cortex, and right orbitofrontal cortex. A group × time × GSR analysis showed a significantly decreased response in nVNS group (p < .0005) in bilaterally in SI, lower and mid medullary brainstem, and inferior occipital cortex. Finally, nVNS treatment showed decreased activity in pronociceptive brainstem nuclei (e.g. the reticular nucleus and rostral ventromedial medulla) and key autonomic integration nuclei (e.g. the rostroventrolateral medulla, nucleus ambiguous, and dorsal motor nucleus of the vagus nerve). In aggregate, noninvasive vagal nerve stimulation reduced the physiological response to noxious thermal stimuli and impacted neural circuits important for pain processing and autonomic output.

The hierarchical nature of language requires human brain to internally parse connected-speech and incrementally construct abstract linguistic structures. Recent research revealed multiple neural processing timescales underlying grammar-based configuration of linguistic hierarchies. However, little is known about where in the whole cerebral cortex such temporally scaled neural processes occur. This study used novel magnetoencephalography source imaging techniques combined with a unique language stimulation paradigm to segregate cortical maps synchronized to 3 levels of linguistic units (i.e., words, phrases, and sentences). Notably, distinct ensembles of cortical loci were identified to feature structures at different levels. The superior temporal gyrus was found to be involved in processing all 3 linguistic levels while distinct ensembles of other brain regions were recruited to encode each linguistic level. Neural activities in the right motor cortex only followed the rhythm of monosyllabic words which have clear acoustic boundaries, whereas the left anterior temporal lobe and the left inferior frontal gyrus were selectively recruited in processing phrases or sentences. Our results ground a multi-timescale hierarchical neural processing of speech in neuroanatomical reality with specific sets of cortices responsible for different levels of linguistic units.

Posttraumatic Stress Disorder (PTSD) and Traumatic Brain Injury (TBI) commonly co-occur in general and military populations and have a number of overlapping symptoms. While research suggests that TBI is risk factor for PTSD and that PTSD may mediate TBI-related outcomes, the mechanisms of these relationships are not well understood. Neuroimaging may help elucidate patterns of neurocircuity both specific and common to PTSD and TBI, and thus help define the nature of their interaction, refine diagnostic classification, and may potentially yield opportunities for targeted treatments. In this review, we provide a summary of some of the most common and the most innovative neuroimaging approaches used to characterize the neural circuits associated with PTSD, TBI, and their comorbidity. We summarize the state of the science for each disorder, and describe the few studies that have explicitly attempted to characterize the neural substrates of their shared and dissociable influence. While some promising targets in the medial frontal lobes exist, there is not currently a comprehensive understanding of the neurocircuitry mediating the interaction of PTSD and TBI. Future studies should exploit innovative neuroimaging approaches and longitudinal designs to specifically target the neural mechanisms driving PTSD-TBI related outcomes.

Mild traumatic brain injury (mTBI) is common in the United States, accounting for as many as 75–80% of all TBIs. It is recognized as a significant public health concern, but there are ongoing controversies regarding the etiology of persistent symptoms post-mTBI. This constellation of nonspecific symptoms is referred to as postconcussive syndrome (PCS). The present study combined results from magnetoencephalography (MEG) and cognitive assessment to examine group differences and relationships between brain activity and cognitive performance in 31 military and civilian individuals with a history of mTBI+PCS and 33 matched healthy control subjects. An operator-free analysis was used for MEG data to increase reliability of the technique. Subjects completed a comprehensive neuropsychological assessment, and measures of abnormal slow-wave activity from MEG were collected. Results demonstrated significant group differences on measures of executive functioning and processing speed. In addition, significant correlations between slow-wave activity on MEG and patterns of cognitive functioning were found in cortical areas, consistent with cognitive impairments on exams. Results provide more objective evidence that there may be subtle changes to the neurobiological integrity of the brain that can be detected by MEG. Further, these findings suggest that these abnormalities are associated with cognitive outcomes and may account, at least in part, for long-term PCS in those who have sustained an mTBI.

Mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members, Veterans, and civilians. However, few treatments are available for mTBI, partially because the mechanism of persistent mTBI deficits is not fully understood.We used magnetoencephalography (MEG) to investigate neuronal changes in individuals with mTBI following a passive neurofeedback-based treatment programme called IASIS. This programme involved applying low-intensity pulses using transcranial electrical stimulation (LIP-tES) with electroencephalography monitoring. Study participants included six individuals with mTBI and persistent post-concussive symptoms (PCS). MEG exams were performed at baseline and follow-up to evaluate the effect of IASIS on brain functioning.At the baseline MEG exam, all participants had abnormal slow-waves. In the follow-up MEG exam, the participants showed significantly reduced abnormal slow-waves with an average reduction of 53.6 ± 24.6% in slow-wave total score. The participants also showed significant reduction of PCS scores after IASIS treatment, with an average reduction of 52.76 ± 26.4% in PCS total score.The present study demonstrates, for the first time, the neuroimaging-based documentation of the effect of LIP-tES treatment on brain functioning in mTBI. The mechanisms of LIP-tES treatment are discussed, with an emphasis on LIP-tES's potentiation of the mTBI healing process.

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.

Background: Although the 40-Hz auditory steady state response (ASSR) is of clinical interest, particularly studies of auditory gamma neural circuits in schizophrenia, the construct validity of measures of EEG and MEG 40-Hz ASSR is unclear. The present study sought to make progress on this issue by leveraging findings of (1) an association in adults between the STG 40 Hz ASSR and age in the left but not right hemisphere, and (2) right- > left-hemisphere differences in the strength of the 40-Hz ASSR. The present contention is that, if a 40-Hz ASSR analysis method does not demonstrate a left STG 40 Hz ASSR and age relationship or hemisphere differences, then the obtained 40-Hz ASSR measures likely have low validity, and thus the analysis method is not optimal.

Superparamagnetic relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using super-conducting quantum interference device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: (1) remove trials contaminated with artifacts, (2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, (3) automatically detect and correct flux jumps, and (4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings.

Alpha circuits (8-12 Hz), necessary for basic and complex brain processes, are abnormal in autism spectrum disorder (ASD). The present study obtained estimates of resting-state (RS) alpha activity in children with ASD and examined associations between alpha activity, age, and clinical symptoms. Given that the thalamus modulates cortical RS alpha rhythms, associations between thalamic structure and alpha activity were examined. RS magnetoencephalography was obtained from 47 typically-developing children (TDC) and 41 children with ASD. RS alpha activity was measured using distributed source localization. Left and right thalamic volume measurements were also obtained. In both groups, the strongest alpha activity was observed in Calcarine Sulcus regions. In Calcarine regions, only TDC showed the expected association between age and alpha peak frequency. ASD had more alpha activity than TDC in regions bordering the Central Sulcus as well as parietal association cortices. In ASD, whereas greater left Central Sulcus relative alpha activity was associated with higher Social Responsiveness Scale (SRS) scores, greater Calcarine region relative alpha activity was associated with lower SRS scores. Although thalamic volume group differences were not observed, relationships between thalamic volume and Calcarine alpha power were unique to TDC. The present study also identified a failure to shift peak alpha frequency as a function of age in primary alpha-generating areas in children with ASD. Findings suggested that increased RS alpha activity in primary motor and somatosensory as well as parietal multimodal areas-with increased alpha thought to reflect greater inhibition-might impair the ability to identify or interpret social cues. Finally, to our knowledge, this is the first study to report associations between thalamic volume and alpha power, an association observed only in TDC. The lack of thalamic and alpha associations in ASD suggests thalamic contributions to RS alpha abnormalities in ASD.

Introduction Although brain rhythms depend on brain structure (e.g., gray and white matter), to our knowledge associations between brain oscillations and structure have not been investigated in healthy controls (HC) or in individuals with schizophrenia (SZ). Observing function–structure relationships, for example establishing an association between brain oscillations (defined in terms of amplitude or phase) and cortical gray matter, might inform models on the origins of psychosis. Given evidence of functional and structural abnormalities in primary/secondary auditory regions in SZ, the present study examined how superior temporal gyrus (STG) structure relates to auditory STG low-frequency and 40 Hz steady-state activity. Given changes in brain activity as a function of age, age-related associations in STG oscillatory activity were also examined. Methods Thirty-nine individuals with SZ and 29 HC were recruited. 40 Hz amplitude-modulated tones of 1 s duration were presented. MEG and T1-weighted sMRI data were obtained. Using the sources localizing 40 Hz evoked steady-state activity (300 to 950 ms), left and right STG total power and inter-trial coherence were computed. Time–frequency group differences and associations with STG structure and age were also examined. Results Decreased total power and inter-trial coherence in SZ were observed in the left STG for initial post-stimulus low-frequency activity (~ 50 to 200 ms, ~ 4 to 16 Hz) as well as 40 Hz steady-state activity (~ 400 to 1000 ms). Left STG 40 Hz total power and inter-trial coherence were positively associated with left STG cortical thickness in HC, not in SZ. Left STG post-stimulus low-frequency and 40 Hz total power were positively associated with age, again only in controls. Discussion Left STG low-frequency and steady-state gamma abnormalities distinguish SZ and HC. Disease-associated damage to STG gray matter in schizophrenia may disrupt the age-related left STG gamma-band function–structure relationships observed in controls., Highlights • Associations between brain oscillations and structure were investigated in SZ • The present study examined how superior temporal gyrus (STG) structure and agerelate to auditory STG low-frequency and 40 Hz steady-state activity • Decreased total power and inter-trial coherence in SZ were observed in the left STG for early low-frequency activity (~ 50 to 200 ms, ~ 4 to 16 Hz) as well as 40 Hz steady-state activity (~ 400 to 1000 ms) • Left STG 40 Hz total power and inter-trial coherence were positively associated with left STG cortical thickness in HC, not in SZ • Disease-associated damage to STG gray matter in schizophrenia may disrupt the age-related left STG function-structure relationships observed in controls.