Modulation of MEG signals during overt and imagined wrist movement for brain-computer interfaces

This work uses Magnetoencephalography (MEG) to investigate movement-related neural activity in the cerebral cortex. MEG is an efficient non-invasive tool to study cortical activity because it has higher temporal and spatial resolutions than other non-invasive methods, such as fMRI and EEG. One objective of the proposed study is to characterize MEG signal modulation during overt and imagined movements. Such characterization can then be implemented to study motor control and cortical plasticity. In the future, this information can be used to aid the mapping of motor regions of the brain prior to surgical implantation of electrodes for a brain-computer interface (BCI). For the current experiments, four right-handed subjects were asked to perform wrist movements with their dominant hand in four directions (radial deviation, ulnar deviation, flexion, and extension) following a visual cue (up, down, left, and right, respectively). In separate sessions, subjects were then asked to imagine performing the same movements following the visual cue. Frequency-domain analysis of the MEG signals reveals consistent modulation during both overt and imagined movements on sensors overlaying sensorimotor areas of the brain. Modulation preceded movement onset and was characterized as an inhibition in low frequency bands (10-30Hz) and excitation of lower bands (0-10Hz), starting 200 ms after the visual cue and lasting 500 ms, which was accompanied by an increase of power in the 65-90Hz band during the same period. This sequence is followed by an increase in power in the 10-30Hz band. Several of these modulations in cortical activity were also significantly tuned (p < 0.05) to the direction of movement in both overt and imaginary tasks. Two methods were used for decoding: Optimal Linear Estimator (OLE) and Bayesian. The decoding accuracy of a given target for the imagined wrist movement data varied among subjects from 29.4% to 49.75% (mean: 41.4%) correct trials for OLE, and 30.1% to 50.9% (mean: 41.5%) for Bayesian. For overt wrist movement data, decoding accuracy for a given target ranged from 34.1% to 67.4% (mean: 48.3%) correct trials for OLE, and 33.1% to 66.9% (mean: 48.0%) for Bayesian. MEG can detect cortical areas that show directionally tuned modulation during overt and imagined wrist movement. We conclude that MEG may be an important tool for the development of BCIs, and for the identification of regions for future insertion of electrodes for neuroprosthetic control

The anatomy of friendship:neuroanatomic homophily of the social brain among classroom friends

Homophily refers to the tendency to like similar others. Here, we ask if homophily extends to brain structure. Specifically: do children who like one another have more similar brain structures? We hypothesized that neuroanatomic similarity tied to friendship is most likely to pertain to brain regions that support social cognition. To test this hypothesis, we analyzed friendship network data from 1186 children in 49 classrooms. Within each classroom, we identified “friendship distance”—mutual friends, friends-of-friends, and more distantly connected or unconnected children. In total, 125 children (mean age = 7.57 years, 65 females) also had good quality neuroanatomic magnetic resonance imaging scans from which we extracted properties of the “social brain.” We found that similarity of the social brain varied by friendship distance: mutual friends showed greater similarity in social brain networks compared with friends-of-friends (β = 0.65, t = 2.03, P = 0.045) and even more remotely connected peers (β = 0.77, t = 2.83, P = 0.006); friends-of-friends did not differ from more distantly connected peers (β = −0.13, t = −0.53, P = 0.6). We report that mutual friends have similar “social brain” networks, adding a neuroanatomic dimension to the adage that “birds of a feather flock together.

rtMEG: A Real-Time Software Interface for Magnetoencephalography

To date, the majority of studies using magnetoencephalography (MEG) rely on off-line analysis of the spatiotemporal properties of brain activity. Real-time MEG feedback could potentially benefit multiple areas of basic and clinical research: brain-machine interfaces, neurofeedback rehabilitation of stroke and spinal cord injury, and new adaptive paradigm designs, among others. We have developed a software interface to stream MEG signals in real time from the 306-channel Elekta Neuromag MEG system to an external workstation. The signals can be accessed with a minimal delay (≤45 ms) when data are sampled at 1000 Hz, which is sufficient for most real-time studies. We also show here that real-time source imaging is possible by demonstrating real-time monitoring and feedback of alpha-band power fluctuations over parieto-occipital and frontal areas. The interface is made available to the academic community as an open-source resource

Functional connectivity measured with magnetoencephalography identifies persons with HIV disease

There is need for a valid and reliable biomarker for HIV Associated Neurocognitive Disorder (HAND). The purpose of the present study was to provide preliminary evidence of the potential utility of neuronal functional connectivity measures obtained using magnetoencephalography (MEG) to identify HIV-associated changes in brain function. Resting state, eyes closed, MEG data from 10 HIV-infected individuals and 8 seronegative controls were analyzed using mutual information (MI) between all pairs of MEG sensors to ..

Magnetoencephalography as a Putative Biomarker for Alzheimer's Disease

Alzheimer's Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer's Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities

Brain structural and functional recovery following initiation of combination antiretroviral therapy

NeuroAIDS persists in the era of combination antiretroviral therapies. We describe here the recovery of brain structure and function following 6 months of therapy in a treatment-naive patient presenting with HIV-associated dementia. The patient’s neuropsychological test performance improved and his total brain volume increased by more than 5 %. Neuronal functional connectivity measured by magnetoencephalography changed from a pattern identical to that observed in other HIV-infected individuals to one that was indistinguishable from that of uninfected control subjects. These data suggest that at least some of the effects of HIV on the brain can be fully reversed with treatment

Tracking brain development and dimensional psychiatric symptoms in children

__Objective:__ Psychiatric symptomatology during childhood predicts persistent mental illness later in life. While neuroimaging methodologies are routinely applied cross-sectionally to the study of child and adolescent psychopathology, the nature of the relationship between childhood symptoms and the underlying neurodevelopmental processes remains unclear. The authors used a prospective population-based cohort to delineate the longitudinal relationship between childhood psychiatric problems and brain development. __Methods:__ A total of 845 children participated in the study. Psychiatric symptoms were measured with the parent-rated Child Behavior Checklist at ages 6 and 10. MRI data were collected at ages 8 and 10. Cross-lagged panel models and linear mixed-effects models were used to determine the associations between psychiatric symptom ratings and quantitative anatomic and white matter microstructural measures over time. __Results:__ Higher ratings for externalizing and internalizing symptoms at baseline predicted smaller increases in both subcortical gray matter volume and global fractional anisotropy over time. The reverse relationship did not hold; thus, baseline measures of gray matter and white matter were not significantly related to changes in symptom ratings over time. __Conclusions:__ Children presenting with behavioral problems at an early age show differential subcortical and white matter development. Most neuroimaging models tend to explain brain differences observed in psychopathology as an underlying (causal) neurobiological substrate. However, the present work suggests that future neuroimaging studies showing effects that are pathogenic in nature should additionally explore the possibility of the downstream effects of psychopathology on the brain

Brain imaging of the cortex in ADHD: a coordinated analysis of large-scale clinical and population-based samples

Objective: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. Methods: Cortical thickness and surface area (based on the Desikan–Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). Results: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen’s d=−0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. Conclusions: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis