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NeuroImage. Clinical 2022Post-stroke aphasia is a consequence of localized stroke-related damage as well as global disturbances in a highly interactive and bilaterally-distributed language...
Post-stroke aphasia is a consequence of localized stroke-related damage as well as global disturbances in a highly interactive and bilaterally-distributed language network. Aphasia is increasingly accepted as a network disorder and it should be treated as such when examining the reorganization and recovery mechanisms after stroke. In the current study, we sought to investigate reorganized patterns of electrophysiological connectivity, derived from resting-state magnetoencephalography (rsMEG), in post-stroke chronic (>6 months after onset) aphasia. We implemented amplitude envelope correlations (AEC), a metric of connectivity commonly used to describe slower aspects of interregional communication in resting-state electrophysiological data. The main focus was on identifying the oscillatory frequency bands and frequency-specific spatial topology of connections associated with preserved language abilities after stroke. RsMEG was recorded for 5 min in 21 chronic stroke survivors with aphasia and in 20 matched healthy controls. Source-level MEG activity was reconstructed and summarized within 72 atlas-defined brain regions (or nodes). A 72 × 72 leakage-corrected connectivity (of AEC) matrix was obtained for frequencies from theta to low-gamma (4-50 Hz). Connectivity was compared between groups, and, the correlations between connectivity and subscale scores from the Western Aphasia Battery (WAB) were evaluated in the stroke group, using partial least squares analyses. Posthoc multiple regression analyses were also conducted on a graph theory measure of node strengths, derived from significant connectivity results, to control for node-wise properties (local spectral power and lesion sizes) and demographic and stroke-related variables. Connectivity among the left hemisphere regions, i.e. those ipsilateral to the stroke lesion, was greatly reduced in stroke survivors with aphasia compared to matched healthy controls in the alpha (8-13 Hz; p = 0.011) and beta (15-30 Hz; p = 0.001) bands. The spatial topology of hypoconnectivity in the alpha vs. beta bands was distinct, revealing a greater involvement of ventral frontal, temporal and parietal areas in alpha, and dorsal frontal and parietal areas in beta. The node strengths from alpha and beta group differences remained significant after controlling for nodal spectral power. AEC correlations with WAB subscales of object naming and fluency were significant. Greater alpha connectivity was associated with better naming performance (p = 0.045), and greater connectivity in both the alpha (p = 0.033) and beta (p = 0.007) bands was associated with better speech fluency performance. The spatial topology was distinct between these frequency bands. The node strengths remained significant after controlling for age, time post stroke onset, nodal spectral power and nodal lesion sizes. Our findings provide important insights into the electrophysiological connectivity profiles (frequency and spatial topology) potentially underpinning preserved language abilities in stroke survivors with aphasia.
Topics: Aphasia; Brain; Brain Mapping; Humans; Language; Magnetic Resonance Imaging; Magnetoencephalography; Stroke
PubMed: 35561556
DOI: 10.1016/j.nicl.2022.103036 -
NeuroImage Feb 2022Beamforming is a popular method for functional source reconstruction using magnetoencephalography (MEG) and electroencephalography (EEG) data. Beamformers, which were...
Beamforming is a popular method for functional source reconstruction using magnetoencephalography (MEG) and electroencephalography (EEG) data. Beamformers, which were first proposed for MEG more than two decades ago, have since been applied in hundreds of studies, demonstrating that they are a versatile and robust tool for neuroscience. However, certain characteristics of beamformers remain somewhat elusive and there currently does not exist a unified documentation of the mathematical underpinnings and computational subtleties of beamformers as implemented in the most widely used academic open source software packages for MEG analysis (Brainstorm, FieldTrip, MNE, and SPM). Here, we provide such documentation that aims at providing the mathematical background of beamforming and unifying the terminology. Beamformer implementations are compared across toolboxes and pitfalls of beamforming analyses are discussed. Specifically, we provide details on handling rank deficient covariance matrices, prewhitening, the rank reduction of forward fields, and on the combination of heterogeneous sensor types, such as magnetometers and gradiometers. The overall aim of this paper is to contribute to contemporary efforts towards higher levels of computational transparency in functional neuroimaging.
Topics: Adult; Brain Mapping; Cerebral Cortex; Electroencephalography; Humans; Magnetoencephalography; Models, Theoretical
PubMed: 34890794
DOI: 10.1016/j.neuroimage.2021.118789 -
The British Journal of Radiology Sep 2019Autism spectrum disorder (ASD) currently affects 1 in 59 children, although the aetiology of this disorder remains unknown. Faced with multiple seemingly disparate and... (Review)
Review
Autism spectrum disorder (ASD) currently affects 1 in 59 children, although the aetiology of this disorder remains unknown. Faced with multiple seemingly disparate and noncontiguous neurobiological alterations, Rubenstein and Merzenich hypothesized that imbalances between excitatory and inhibitory neurosignaling (E/I imbalance) underlie ASD. Since this initial statement, there has been a major focus examining this exact topic spanning both clinical and preclinical realms. The purpose of this article is to review the neuroimaging literature surrounding E/I imbalance as an aetiology of ASD. Evidence for E/I imbalance is presented from several complementary clinical techniques including magnetic resonance spectroscopy, magnetoencephalography and transcranial magnetic stimulation. Additionally, two GABAergic potential interventions for ASD, which explicitly attempt to remediate E/I imbalance, are reviewed. The current literature suggests E/I imbalance as a useful framework for discussing the neurobiological etiology of ASD in at least a subset of affected individuals. While not constituting a completely unifying aetiology, E/I imbalance may be relevant as one of several underlying neuropathophysiologies that differentially affect individuals with ASD. Such statements do not diminish the value of the E/I imbalance concept-instead they suggest a possible role for the characterization of E/I imbalance, as well as other underlying neuropathophysiologies, in the biologically-based subtyping of individuals with ASD for potential applications including clinical trial enrichment as well as treatment triage.
Topics: Autism Spectrum Disorder; Brain; Child; Humans; Magnetic Resonance Spectroscopy; Magnetoencephalography; Transcranial Magnetic Stimulation
PubMed: 31124710
DOI: 10.1259/bjr.20180944 -
Current Biology : CB Feb 2021A new study has used magnetoencephalography to track cortical responses to color as they emerge in time. Similarities and differences within these neural responses...
A new study has used magnetoencephalography to track cortical responses to color as they emerge in time. Similarities and differences within these neural responses parallel characteristics of the perceptual experience of color.
Topics: Color Perception; Color Vision; Humans; Magnetoencephalography
PubMed: 33561408
DOI: 10.1016/j.cub.2020.11.056 -
NeuroImage Aug 2023We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using...
We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.
Topics: Adult; Humans; Magnetoencephalography; Bayes Theorem; Reproducibility of Results; Neurochemistry; Magnetic Resonance Spectroscopy; Models, Neurological; Magnetic Resonance Imaging
PubMed: 37244323
DOI: 10.1016/j.neuroimage.2023.120193 -
Annals of Clinical and Translational... Mar 2020We demonstrate the first use of Optically Pumped Magnetoencephalography (OP-MEG) in an epilepsy patient with unrestricted head movement. Current clinical MEG uses a...
We demonstrate the first use of Optically Pumped Magnetoencephalography (OP-MEG) in an epilepsy patient with unrestricted head movement. Current clinical MEG uses a traditional SQUID system, where sensors are cryogenically cooled and housed in a helmet in which the patient's head is fixed. Here, we use a different type of sensor (OPM), which operates at room temperature and can be placed directly on the patient's scalp, permitting free head movement. We performed OP-MEG recording in a patient with refractory focal epilepsy. OP-MEG-identified analogous interictal activity to scalp EEG, and source localized this activity to an appropriate brain region.
Topics: Drug Resistant Epilepsy; Electroencephalography; Epilepsies, Partial; Female; Humans; Magnetoencephalography; Middle Aged
PubMed: 32112610
DOI: 10.1002/acn3.50995 -
Towards Best Practices in Clinical Magnetoencephalography: Patient Preparation and Data Acquisition.Journal of Clinical Neurophysiology :... Nov 2020A magnetoencephalography (MEG) recording for clinical purposes requires a different level of attention and detail than that for research. As contrasted with a research... (Review)
Review
A magnetoencephalography (MEG) recording for clinical purposes requires a different level of attention and detail than that for research. As contrasted with a research subject, the MEG technologist must work with a patient who may not fully cooperate with instructions. The patient is on a clinical schedule, with generally no opportunity to return due to an erroneous or poor acquisition. The data will generally be processed by separate MEG analysts, who require a consistent and high-quality recording to complete their analysis and clinical report. To assure a quality recording, (1) MEG technologists must immediately recheck their scalp measurement data during the patient preparation, to catch disturbances and ensure registration accuracy of the patient fiducials, electrodes, and head position indicator coils. During the recording, (2) the technologist must ensure that the patient remains quiet and as far as possible into the helmet. After the recording, (3) the technologist must consistently prepare the data for subsequent clinical analysis. This article aims to comprehensively address these matters for practitioners of clinical MEG in a helpful and practical way. Based on the authors' experiences in recording over three thousand patients between them, presented here are a collection of techniques for implementation into daily routines that ensure good operation and high data quality. The techniques address a gap in the clinical literature addressing the multitude of potential sources of error during patient preparation and data acquisition, and how to prevent, recognize, or correct those.
Topics: Brain Mapping; Data Analysis; Electrodes; Electroencephalography; Humans; Magnetoencephalography; Patient Positioning; Patient Selection; Practice Guidelines as Topic; Scalp
PubMed: 33165223
DOI: 10.1097/WNP.0000000000000542 -
NeuroImage Oct 2019Optically Pumped Magnetometers (OPMs) have emerged as a viable and wearable alternative to cryogenic, superconducting MEG systems. This new generation of sensors has the... (Review)
Review
Optically Pumped Magnetometers (OPMs) have emerged as a viable and wearable alternative to cryogenic, superconducting MEG systems. This new generation of sensors has the advantage of not requiring cryogenic cooling and as a result can be flexibly placed on any part of the body. The purpose of this review is to provide a neuroscience audience with the theoretical background needed to understand the physical basis for the signal observed by OPMs. Those already familiar with the physics of MRI and NMR should note that OPMs share much of the same theory as the operation of OPMs rely on magnetic resonance. This review establishes the physical basis for the signal equation for OPMs. We re-derive the equations defining the bounds on OPM performance and highlight the important trade-offs between quantities such as bandwidth, sensor size and sensitivity. These equations lead to a direct upper bound on the gain change due to cross-talk for a multi-channel OPM system.
Topics: Humans; Magnetic Phenomena; Magnetoencephalography; Optical Phenomena
PubMed: 31141737
DOI: 10.1016/j.neuroimage.2019.05.063 -
NeuroImage Nov 2021Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from non-neuronal sources...
Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from non-neuronal sources can corrupt the data. Eye-blinks, saccades, and cardiac activity are three of the most common sources of non-neuronal artifacts. They can be measured by affixing eye proximal electrodes, as in electrooculography (EOG), and chest electrodes, as in electrocardiography (ECG), however this complicates imaging setup, decreases patient comfort, and can induce further artifacts from movement. This work proposes an EOG- and ECG-free approach to identify eye-blinks, saccades, and cardiac activity signals for automated artifact suppression. The contribution of this work is three-fold. First, using a data driven, multivariate decomposition approach based on Independent Component Analysis (ICA), a highly accurate artifact classifier is constructed as an amalgam of deep 1-D and 2-D Convolutional Neural Networks (CNNs) to automate the identification and removal of ubiquitous whole brain artifacts including eye-blink, saccade, and cardiac artifacts. The specific architecture of this network is optimized through an unbiased, computer-based hyperparameter random search. Second, visualization methods are applied to the learned abstraction to reveal what features the model uses and to bolster user confidence in the model's training and potential for generalization. Finally, the model is trained and tested on both resting-state and task MEG data from 217 subjects, and achieves a new state-of-the-art in artifact detection accuracy of 98.95% including 96.74% sensitivity and 99.34% specificity on the held out test-set. This work automates MEG processing for both clinical and research use, adapts to the acquired acquisition time, and can obviate the need for EOG or ECG electrodes for artifact detection.
Topics: Adolescent; Adult; Aged; Artifacts; Blinking; Brain; Child; Female; Humans; Magnetoencephalography; Male; Middle Aged; Neural Networks, Computer; Signal Processing, Computer-Assisted; Young Adult
PubMed: 34274419
DOI: 10.1016/j.neuroimage.2021.118402 -
ELife Sep 2022In the natural environment, we often form stable perceptual experiences from ambiguous and fleeting sensory inputs. Which neural activity underlies the content of...
In the natural environment, we often form stable perceptual experiences from ambiguous and fleeting sensory inputs. Which neural activity underlies the content of perception and which neural activity supports perceptual stability remains an open question. We used a bistable perception paradigm involving ambiguous images to behaviorally dissociate perceptual content from perceptual stability, and magnetoencephalography to measure whole-brain neural dynamics in humans. Combining multivariate decoding and neural state-space analyses, we found frequency-band-specific neural signatures that underlie the content of perception and promote perceptual stability, respectively. Across different types of images, non-oscillatory neural activity in the slow cortical potential (<5 Hz) range supported the content of perception. Perceptual stability was additionally influenced by the amplitude of alpha and beta oscillations. In addition, neural activity underlying perceptual memory, which supports perceptual stability when sensory input is temporally removed from view, also encodes elapsed time. Together, these results reveal distinct neural mechanisms that support the content versus stability of visual perception.
Topics: Brain; Humans; Magnetoencephalography; Visual Perception
PubMed: 36125242
DOI: 10.7554/eLife.78108