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Brain Imaging and Behavior Apr 2022Magnetoencephalography (MEG) records brain activity with excellent temporal and good spatial resolution, while functional magnetic resonance imaging (fMRI) offers good...
Magnetoencephalography (MEG) records brain activity with excellent temporal and good spatial resolution, while functional magnetic resonance imaging (fMRI) offers good temporal and excellent spatial resolution. The aim of this study is to implement a Bayesian framework to use fMRI data as spatial priors for MEG inverse solutions. We used simulated MEG data with both evoked and induced activity and experimental MEG data from sixteen participants to examine the effectiveness of using fMRI spatial priors in MEG source reconstruction. For simulated MEG data, incorporating the prior information from fMRI increased the spatial resolution of MEG source reconstruction by 3 mm on average. For experimental MEG data, fMRI spatial information reduced the spurious clusters for evoked activity and showed more left-lateralized activation pattern for induced activity. The use of fMRI spatial priors greatly reduced location error for induced source in MEG data. Our results provide empirical evidence that the use of fMRI spatial priors improves the accuracy of MEG source reconstruction. The combined MEG and fMRI approach can provide neuroimaging data with better spatial and temporal resolutions to add another perspective to our understanding of the neurobiology of language. The potential clinical applications include pre-surgical evaluation of language function for epilepsy patients and evaluation of language network for children with language disorders.
Topics: Bayes Theorem; Brain Mapping; Child; Electroencephalography; Humans; Language; Magnetic Resonance Imaging; Magnetoencephalography
PubMed: 34561780
DOI: 10.1007/s11682-021-00550-4 -
NeuroImage Oct 2021Individual characterization of subjects based on their functional connectome (FC), termed "FC fingerprinting", has become a highly sought-after goal in contemporary...
Individual characterization of subjects based on their functional connectome (FC), termed "FC fingerprinting", has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have demonstrated unique characterization and accurate identification of individuals as an accomplished task. However, FC fingerprinting in magnetoencephalography (MEG) data is still widely unexplored. Here, we study resting-state MEG data from the Human Connectome Project to assess the MEG FC fingerprinting and its relationship with several factors including amplitude- and phase-coupling functional connectivity measures, spatial leakage correction, frequency bands, and behavioral significance. To this end, we first employ two identification scoring methods, differential identifiability and success rate, to provide quantitative fingerprint scores for each FC measurement. Secondly, we explore the edgewise and nodal MEG fingerprinting patterns across the different frequency bands (delta, theta, alpha, beta, and gamma). Finally, we investigate the cross-modality fingerprinting patterns obtained from MEG and fMRI recordings from the same subjects. We assess the behavioral significance of FC across connectivity measures and imaging modalities using partial least square correlation analyses. Our results suggest that fingerprinting performance is heavily dependent on the functional connectivity measure, frequency band, identification scoring method, and spatial leakage correction. We report higher MEG fingerprinting performances in phase-coupling methods, central frequency bands (alpha and beta), and in the visual, frontoparietal, dorsal-attention, and default-mode networks. Furthermore, cross-modality comparisons reveal a certain degree of spatial concordance in fingerprinting patterns between the MEG and fMRI data, especially in the visual system. Finally, the multivariate correlation analyses show that MEG connectomes have strong behavioral significance, which however depends on the considered connectivity measure and temporal scale. This comprehensive, albeit preliminary investigation of MEG connectome test-retest identifiability offers a first characterization of MEG fingerprinting in relation to different methodological and electrophysiological factors and contributes to the understanding of fingerprinting cross-modal relationships. We hope that this first investigation will contribute to setting the grounds for MEG connectome identification.
Topics: Adult; Brain; Connectome; Female; Humans; Magnetic Resonance Imaging; Magnetoencephalography; Male; Nerve Net
PubMed: 34237444
DOI: 10.1016/j.neuroimage.2021.118331 -
Cortex; a Journal Devoted To the Study... Jul 2016Repetition suppression paradigms allow a more detailed look at brain functioning than classical paradigms and have been applied vigorously in adult cognitive... (Review)
Review
Repetition suppression paradigms allow a more detailed look at brain functioning than classical paradigms and have been applied vigorously in adult cognitive neuroscience. These paradigms are well suited for studies in the field of developmental cognitive neuroscience as they can be applied without collecting a behavioral response and across all age groups. Furthermore, repetition suppression paradigms can be employed in various neuroscience techniques, such as functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG) and magnetoencephalography (MEG). In the present article we review studies using repetition suppression paradigms in developmental cognitive neuroscience covering the age range from infancy to adolescence. Our first goal is to point out characteristics of developmental repetition suppression effects. In doing so, we discuss the relationship of the direction of repetition effects (suppression vs enhancement) with developmental factors, and address the question how the direction of repetition effects might be related to looking-time effects in behavioral infant paradigms, the most prominently used behavioral measure in infant research. To highlight the potential of repetition suppression paradigms, our second goal is to provide an overview on the insights recently obtained by applying repetition paradigms in neurodevelopmental studies, including research on children with autism spectrum disorders (ASDs). We conclude that repetition suppression paradigms are valuable tools for investigating neurodevelopmental processes, while at the same time we highlight the necessity for further studies that disentangle methodological and developmental factors.
Topics: Age Factors; Animals; Brain; Cognitive Neuroscience; Electroencephalography; Humans; Infant; Magnetic Resonance Imaging; Magnetoencephalography
PubMed: 27161033
DOI: 10.1016/j.cortex.2016.04.002 -
Trends in Neurosciences Aug 2022Magnetoencephalography (MEG) measures human brain function via assessment of the magnetic fields generated by electrical activity in neurons. Despite providing... (Review)
Review
Magnetoencephalography (MEG) measures human brain function via assessment of the magnetic fields generated by electrical activity in neurons. Despite providing high-quality spatiotemporal maps of electrophysiological activity, current MEG instrumentation is limited by cumbersome field sensing technologies, resulting in major barriers to utility. Here, we review a new generation of MEG technology that is beginning to lift many of these barriers. By exploiting quantum sensors, known as optically pumped magnetometers (OPMs), 'OPM-MEG' has the potential to dramatically outperform the current state of the art, promising enhanced data quality (better sensitivity and spatial resolution), adaptability to any head size/shape (from babies to adults), motion robustness (participants can move freely during scanning), and a less complex imaging platform (without reliance on cryogenics). We discuss the current state of this emerging technique and describe its far-reaching implications for neuroscience.
Topics: Adult; Brain; Functional Neuroimaging; Humans; Magnetoencephalography
PubMed: 35779970
DOI: 10.1016/j.tins.2022.05.008 -
Clinical Neurophysiology : Official... Aug 2017Alzheimer's disease (AD) is accompanied by functional brain changes that can be detected in imaging studies, including electromagnetic activity recorded with... (Review)
Review
Alzheimer's disease (AD) is accompanied by functional brain changes that can be detected in imaging studies, including electromagnetic activity recorded with magnetoencephalography (MEG). Here, we systematically review the studies that have examined resting-state MEG changes in AD and identify areas that lack scientific or clinical progress. Three levels of MEG analysis will be covered: (i) single-channel signal analysis, (ii) pairwise analyses over time series, which includes the study of interdependencies between two time series and (iii) global network analyses. We discuss the findings in the light of other functional modalities, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Overall, single-channel MEG results show consistent changes in AD that are in line with EEG studies, but the full potential of the high spatial resolution of MEG and advanced functional connectivity and network analysis has yet to be fully exploited. Adding these features to the current knowledge will potentially aid in uncovering organizational patterns of brain function in AD and thereby aid the understanding of neuronal mechanisms leading to cognitive deficits.
Topics: Alzheimer Disease; Brain; Brain Mapping; Humans; Magnetoencephalography; Nerve Net; Rest
PubMed: 28622527
DOI: 10.1016/j.clinph.2017.05.012 -
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 -
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 -
Journal of Neural Engineering Dec 2022Magneto- and electroencephalography (M/EEG) measurements record a mix of signals from the brain, eyes, and muscles. These signals can be disentangled for artifact...
Magneto- and electroencephalography (M/EEG) measurements record a mix of signals from the brain, eyes, and muscles. These signals can be disentangled for artifact cleaning e.g. using spatial filtering techniques. However, correctly localizing and identifying these components relies on head models that so far only take brain sources into account.We thus developed the Head Artifact Model using Tripoles (HArtMuT). This volume conduction head model extends to the neck and includes brain sources as well as sources representing eyes and muscles that can be modeled as single dipoles, symmetrical dipoles, and tripoles. We compared a HArtMuT four-layer boundary element model (BEM) with the EEGLAB standard head model on their localization accuracy and residual variance (RV) using a HArtMuT finite element model (FEM) as ground truth. We also evaluated the RV on real-world data of mobile participants, comparing different HArtMuT BEM types with the EEGLAB standard head model.We found that HArtMuT improves localization for all sources, especially non-brain, and localization error and RV of non-brain sources were in the same range as those of brain sources. The best results were achieved by using cortical dipoles, muscular tripoles, and ocular symmetric dipoles, but dipolar sources alone can already lead to convincing results.We conclude that HArtMuT is well suited for modeling eye and muscle contributions to the M/EEG signal. It can be used to localize sources and to identify brain, eye, and muscle components. HArtMuT is freely available and can be integrated into standard software.
Topics: Humans; Magnetoencephalography; Artifacts; Brain Mapping; Electroencephalography; Muscles
PubMed: 36536595
DOI: 10.1088/1741-2552/aca8ce -
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 -
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