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Neurology India 2017In selected patients with drug-resistant focal epilepsies (DRFE), who otherwise are likely to be excluded from epilepsy surgery (ES) because of the absence of a magnetic... (Review)
Review
In selected patients with drug-resistant focal epilepsies (DRFE), who otherwise are likely to be excluded from epilepsy surgery (ES) because of the absence of a magnetic resonance imaging (MRI)-demonstrable lesion or discordant anatomo-electro-clinical (AEC) data, magnetoencephalography (MEG) may help to generate an AEC hypothesis and stereo-electroencephalography (SEEG) may help to verify the hypothesis and proceed with ES. The sensitivity of MEG is much better in localizing the spiking zone in relation to lateral temporal and extratemporal cortical regions compared to the mesial temporal structures. MEG has a dominant role in the presurgical evaluation of patients with MRI-negative DRFEs, insular epilepsies, and recurrent seizures after failed epilepsy surgeries, and in guiding placement of invasive electrodes. Moreover, postoperative seizure freedom is better if MEG spike source localized cortical region is included in the resection. When compared to subdural grid electrode recording, SEEG is less invasive and safer. Those who are otherwise destined to suffer from uncontrolled seizures and their consequences, SEEG guided ES is a worthwhile and a cost-effective option. Depending on the substrate pathology, there is > 80-90% chance of undergoing ES and 60-80% chance of becoming seizure-free following SEEG. Recent noninvasive techniques aimed at better structural imaging, delineating brain connectivity and recording specific intracerebral EEG patterns such as high frequency oscillations might decrease the need for SEEG; but more importantly, make SEEG exploration more goal-directed and hypothesis-driven.
Topics: Brain; Brain Mapping; Drug Resistant Epilepsy; Electroencephalography; Humans; Magnetic Resonance Imaging; Magnetoencephalography
PubMed: 28281494
DOI: 10.4103/0028-3886.201680 -
Brain, Behavior, and Immunity Nov 2023Inflammatory processes help protect the body from potential threats such as bacterial or viral invasions. However, when such inflammatory processes become chronically...
INTRODUCTION
Inflammatory processes help protect the body from potential threats such as bacterial or viral invasions. However, when such inflammatory processes become chronically engaged, synaptic impairments and neuronal cell death may occur. In particular, persistently high levels of C-reactive protein (CRP) and tumor necrosis factor-alpha (TNF-α) have been linked to deficits in cognition and several psychiatric disorders. Higher-order cognitive processes such as fluid intelligence (Gf) are thought to be particularly vulnerable to persistent inflammation. Herein, we investigated the relationship between elevated CRP and TNF-α and the neural oscillatory dynamics serving Gf.
METHODS
Seventy adults between the ages of 20-66 years (Mean = 45.17 years, SD = 16.29, 21.4% female) completed an abstract reasoning task that probes Gf during magnetoencephalography (MEG) and provided a blood sample for inflammatory marker analysis. MEG data were imaged in the time-frequency domain, and whole-brain regressions were conducted using each individual's plasma CRP and TNF-α concentrations per oscillatory response, controlling for age, BMI, and education.
RESULTS
CRP and TNF-α levels were significantly associated with region-specific neural oscillatory responses. In particular, elevated CRP concentrations were associated with altered gamma activity in the right inferior frontal gyrus and right cerebellum. In contrast, elevated TNF-α levels scaled with alpha/beta oscillations in the left anterior cingulate and left middle temporal, and gamma activity in the left intraparietal sulcus.
DISCUSSION
Elevated inflammatory markers such as CRP and TNF-α were associated with aberrant neural oscillations in regions important for Gf. Linking inflammatory markers with regional neural oscillations may hold promise in identifying mechanisms of cognitive and psychiatric disorders.
Topics: Adult; Humans; Female; Young Adult; Middle Aged; Aged; Male; Tumor Necrosis Factor-alpha; Brain; Magnetoencephalography; Cognition; Intelligence; C-Reactive Protein
PubMed: 37716379
DOI: 10.1016/j.bbi.2023.09.012 -
NeuroImage Jul 2020The cerebellum plays a key role in the regulation of motor learning, coordination and timing, and has been implicated in sensory and cognitive processes as well.... (Review)
Review
The cerebellum plays a key role in the regulation of motor learning, coordination and timing, and has been implicated in sensory and cognitive processes as well. However, our current knowledge of its electrophysiological mechanisms comes primarily from direct recordings in animals, as investigations into cerebellar function in humans have instead predominantly relied on lesion, haemodynamic and metabolic imaging studies. While the latter provide fundamental insights into the contribution of the cerebellum to various cerebellar-cortical pathways mediating behaviour, they remain limited in terms of temporal and spectral resolution. In principle, this shortcoming could be overcome by monitoring the cerebellum's electrophysiological signals. Non-invasive assessment of cerebellar electrophysiology in humans, however, is hampered by the limited spatial resolution of electroencephalography (EEG) and magnetoencephalography (MEG) in subcortical structures, i.e., deep sources. Furthermore, it has been argued that the anatomical configuration of the cerebellum leads to signal cancellation in MEG and EEG. Yet, claims that MEG and EEG are unable to detect cerebellar activity have been challenged by an increasing number of studies over the last decade. Here we address this controversy and survey reports in which electrophysiological signals were successfully recorded from the human cerebellum. We argue that the detection of cerebellum activity non-invasively with MEG and EEG is indeed possible and can be enhanced with appropriate methods, in particular using connectivity analysis in source space. We provide illustrative examples of cerebellar activity detected with MEG and EEG. Furthermore, we propose practical guidelines to optimize the detection of cerebellar activity with MEG and EEG. Finally, we discuss MEG and EEG signal contamination that may lead to localizing spurious sources in the cerebellum and suggest ways of handling such artefacts. This review is to be read as a perspective review that highlights that it is indeed possible to measure cerebellum with MEG and EEG and encourages MEG and EEG researchers to do so. Its added value beyond highlighting and encouraging is that it offers useful advice for researchers aspiring to investigate the cerebellum with MEG and EEG.
Topics: Auditory Perception; Cerebellum; Electroencephalography; Humans; Magnetoencephalography; Patient Positioning; Psychomotor Performance; Visual Perception
PubMed: 32278092
DOI: 10.1016/j.neuroimage.2020.116817 -
Human Brain Mapping Mar 2021Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge...
Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.
Topics: Adult; Amygdala; Cerebellum; Cerebral Cortex; Corpus Striatum; Electroencephalography; Evoked Potentials, Somatosensory; Hippocampus; Humans; Magnetic Resonance Imaging; Magnetoencephalography; Reproducibility of Results; Signal-To-Noise Ratio; Thalamus
PubMed: 33156569
DOI: 10.1002/hbm.25272 -
Current Biology : CB Feb 2021The geometry that describes the relationship among colors, and the neural mechanisms that support color vision, are unsettled. Here, we use multivariate analyses of...
The geometry that describes the relationship among colors, and the neural mechanisms that support color vision, are unsettled. Here, we use multivariate analyses of measurements of brain activity obtained with magnetoencephalography to reverse-engineer a geometry of the neural representation of color space. The analyses depend upon determining similarity relationships among the spatial patterns of neural responses to different colors and assessing how these relationships change in time. We evaluate the approach by relating the results to universal patterns in color naming. Two prominent patterns of color naming could be accounted for by the decoding results: the greater precision in naming warm colors compared to cool colors evident by an interaction of hue and lightness, and the preeminence among colors of reddish hues. Additional experiments showed that classifiers trained on responses to color words could decode color from data obtained using colored stimuli, but only at relatively long delays after stimulus onset. These results provide evidence that perceptual representations can give rise to semantic representations, but not the reverse. Taken together, the results uncover a dynamic geometry that provides neural correlates for color appearance and generates new hypotheses about the structure of color space.
Topics: Color; Color Perception; Color Vision; Magnetoencephalography; Semantics
PubMed: 33202253
DOI: 10.1016/j.cub.2020.10.062 -
PloS One 2021Accurate and efficient source analysis in electro- and magnetoencephalography using sophisticated realistic head geometries requires advanced numerical approaches. This...
Accurate and efficient source analysis in electro- and magnetoencephalography using sophisticated realistic head geometries requires advanced numerical approaches. This paper presents DUNEuro, a free and open-source C++ software toolbox for the numerical computation of forward solutions in bioelectromagnetism. Building upon the DUNE framework, it provides implementations of modern fitted and unfitted finite element methods to efficiently solve the forward problems of electro- and magnetoencephalography. The user can choose between a variety of different source models that are implemented. The software's aim is to provide interfaces that are extendable and easy-to-use. In order to enable a closer integration into existing analysis pipelines, interfaces to Python and MATLAB are provided. The practical use is demonstrated by a source analysis example of somatosensory evoked potentials using a realistic six-compartment head model. Detailed installation instructions and example scripts using spherical and realistic head models are appended.
Topics: Cortical Excitability; Electroencephalography; Humans; Magnetoencephalography; Models, Neurological; Software
PubMed: 34086715
DOI: 10.1371/journal.pone.0252431 -
NeuroImage Apr 2021Optically-pumped magnetometers (OPMs) offer the potential for a step change in magnetoencephalography (MEG) enabling wearable systems that provide improved data quality,...
Optically-pumped magnetometers (OPMs) offer the potential for a step change in magnetoencephalography (MEG) enabling wearable systems that provide improved data quality, accommodate any subject group, allow data capture during movement and potentially reduce cost. However, OPM-MEG is a nascent technology and, to realise its potential, it must be shown to facilitate key neuroscientific measurements, such as the characterisation of brain networks. Networks, and the connectivities that underlie them, have become a core area of neuroscientific investigation, and their importance is underscored by many demonstrations of their disruption in brain disorders. Consequently, a demonstration of network measurements using OPM-MEG would be a significant step forward. Here, we aimed to show that a wearable 50-channel OPM-MEG system enables characterisation of the electrophysiological connectome. To this end, we measured connectivity in the resting state and during a visuo-motor task, using both OPM-MEG and a state-of-the-art 275-channel cryogenic MEG device. Our results show that resting-state connectome matrices from OPM and cryogenic systems exhibit a high degree of similarity, with correlation values >70%. In addition, in task data, similar differences in connectivity between individuals (scanned multiple times) were observed in cryogenic and OPM-MEG data, again demonstrating the fidelity of the OPM-MEG device. This is the first demonstration of network connectivity measured using OPM-MEG, and results add weight to the argument that OPMs will ultimately supersede cryogenic sensors for MEG measurement.
Topics: Adult; Brain; Equipment Design; Female; Humans; Magnetoencephalography; Magnetometry; Male; Psychomotor Performance; Wearable Electronic Devices; Young Adult
PubMed: 33524584
DOI: 10.1016/j.neuroimage.2021.117815 -
Human Brain Mapping Dec 2023Decoding brain imaging data are gaining popularity, with applications in brain-computer interfaces and the study of neural representations. Decoding is typically...
Decoding brain imaging data are gaining popularity, with applications in brain-computer interfaces and the study of neural representations. Decoding is typically subject-specific and does not generalise well over subjects, due to high amounts of between subject variability. Techniques that overcome this will not only provide richer neuroscientific insights but also make it possible for group-level models to outperform subject-specific models. Here, we propose a method that uses subject embedding, analogous to word embedding in natural language processing, to learn and exploit the structure in between-subject variability as part of a decoding model, our adaptation of the WaveNet architecture for classification. We apply this to magnetoencephalography data, where 15 subjects viewed 118 different images, with 30 examples per image; to classify images using the entire 1 s window following image presentation. We show that the combination of deep learning and subject embedding is crucial to closing the performance gap between subject- and group-level decoding models. Importantly, group models outperform subject models on low-accuracy subjects (although slightly impair high-accuracy subjects) and can be helpful for initialising subject models. While we have not generally found group-level models to perform better than subject-level models, the performance of group modelling is expected to be even higher with bigger datasets. In order to provide physiological interpretation at the group level, we make use of permutation feature importance. This provides insights into the spatiotemporal and spectral information encoded in the models. All code is available on GitHub (https://github.com/ricsinaruto/MEG-group-decode).
Topics: Humans; Deep Learning; Brain; Magnetoencephalography; Brain Mapping; Brain-Computer Interfaces
PubMed: 37753636
DOI: 10.1002/hbm.26500 -
Neuroinformatics Jan 2021Brain activity pattern recognition from EEG or MEG signal analysis is one of the most important method in cognitive neuroscience. The SUPFUNSIM library is a new MATLAB...
Brain activity pattern recognition from EEG or MEG signal analysis is one of the most important method in cognitive neuroscience. The SUPFUNSIM library is a new MATLAB toolbox which generates accurate EEG forward model and implements a collection of spatial filters for EEG source reconstruction, including the linearly constrained minimum-variance (LCMV), eigenspace LCMV, nulling (NL), and minimum-variance pseudo-unbiased reduced-rank (MV-PURE) filters in various versions. It also enables source-level directed connectivity analysis using partial directed coherence (PDC) measure. The SUPFUNSIM library is based on the well-known FIELDTRIP toolbox for EEG and MEG analysis and is written using object-oriented programming paradigm. The resulting modularity of the toolbox enables its simple extensibility. This paper gives a complete overview of the toolbox from both developer and end-user perspectives, including description of the installation process and use cases.
Topics: Algorithms; Brain; Electroencephalography; Humans; Magnetoencephalography; Signal Processing, Computer-Assisted; Software
PubMed: 32564239
DOI: 10.1007/s12021-020-09464-w -
Journal of the Association For Research... Dec 2023Tinnitus has been widely investigated in order to draw conclusions about the underlying causes and altered neural activity in various brain regions. Existing studies... (Review)
Review
Tinnitus has been widely investigated in order to draw conclusions about the underlying causes and altered neural activity in various brain regions. Existing studies have based their work on different tinnitus frameworks, ranging from a more local perspective on the auditory cortex to the inclusion of broader networks and various approaches towards tinnitus perception and distress. Magnetoencephalography (MEG) provides a powerful tool for efficiently investigating tinnitus and aberrant neural activity both spatially and temporally. However, results are inconclusive, and studies are rarely mapped to theoretical frameworks. The purpose of this review was to firstly introduce MEG to interested researchers and secondly provide a synopsis of the current state. We divided recent tinnitus research in MEG into study designs using resting state measurements and studies implementing tone stimulation paradigms. The studies were categorized based on their theoretical foundation, and we outlined shortcomings as well as inconsistencies within the different approaches. Finally, we provided future perspectives on how to benefit more efficiently from the enormous potential of MEG. We suggested novel approaches from a theoretical, conceptual, and methodological point of view to allow future research to obtain a more comprehensive understanding of tinnitus and its underlying processes.
Topics: Humans; Magnetoencephalography; Tinnitus; Brain; Auditory Cortex
PubMed: 38015287
DOI: 10.1007/s10162-023-00916-z