-
Brain Sciences Nov 2023Traumatic brain injury (TBI) is a significant public health concern, often leading to long-lasting impairments in cognitive, motor and sensory functions. The rapid... (Review)
Review
Traumatic brain injury (TBI) is a significant public health concern, often leading to long-lasting impairments in cognitive, motor and sensory functions. The rapid development of non-invasive systems has revolutionized the field of TBI rehabilitation by offering modern and effective interventions. This narrative review explores the application of non-invasive technologies, including electroencephalography (EEG), quantitative electroencephalography (qEEG), brain-computer interface (BCI), eye tracking, near-infrared spectroscopy (NIRS), functional near-infrared spectroscopy (fNIRS), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) in assessing TBI consequences, and repetitive transcranial magnetic stimulation (rTMS), low-level laser therapy (LLLT), neurofeedback, transcranial direct current stimulation (tDCS), transcranial alternative current stimulation (tACS) and virtual reality (VR) as therapeutic approaches for TBI rehabilitation. In pursuit of advancing TBI rehabilitation, this narrative review highlights the promising potential of non-invasive technologies. We emphasize the need for future research and clinical trials to elucidate their mechanisms of action, refine treatment protocols, and ensure their widespread adoption in TBI rehabilitation settings.
PubMed: 38002552
DOI: 10.3390/brainsci13111594 -
Nature Reviews. Neurology Dec 2023Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us... (Review)
Review
Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG-magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.
Topics: Humans; Amyotrophic Lateral Sclerosis; Biomarkers; Prognosis; Disease Progression; Drug Development
PubMed: 37949994
DOI: 10.1038/s41582-023-00891-2 -
Frontiers in Neuroscience 2023Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by pervasive deficits in social interaction, communication impairments, and the presence... (Review)
Review
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by pervasive deficits in social interaction, communication impairments, and the presence of restricted and repetitive behaviors. This complex disorder is a significant public health concern due to its escalating incidence and detrimental impact on quality of life. Currently, extensive investigations are underway to identify prospective susceptibility or predictive biomarkers, employing a physiological biomarker-based framework. However, knowledge regarding physiological biomarkers in relation to Autism is sparse. We performed a scoping review to explore putative changes in physiological activities associated with behaviors in individuals with Autism. We identified studies published between January 2000 and June 2023 from online databases, and searched keywords included electroencephalography (EEG), magnetoencephalography (MEG), electrodermal activity markers (EDA), eye-tracking markers. We specifically detected social-related symptoms such as impaired social communication in ASD patients. Our results indicated that the EEG/ERP N170 signal has undergone the most rigorous testing as a potential biomarker, showing promise in identifying subgroups within ASD and displaying potential as an indicator of treatment response. By gathering current data from various physiological biomarkers, we can obtain a comprehensive understanding of the physiological profiles of individuals with ASD, offering potential for subgrouping and targeted intervention strategies.
PubMed: 37746140
DOI: 10.3389/fnins.2023.1269880 -
Journal of Clinical Neurophysiology :... Sep 2023In this review, the semiology, and characteristics of noninvasive investigations suggestive of anterior cingulate and anterior midcingulate epilepsy are detailed by the... (Review)
Review
In this review, the semiology, and characteristics of noninvasive investigations suggestive of anterior cingulate and anterior midcingulate epilepsy are detailed by the authors. The clinical presentation is representative of a recently recognized rostrocaudal gradient of functional connectivity with seizures of the anterior cingulate cortex manifesting emotional and interoceptive aura followed by a hyperkinetic or complex motor seizures. The few reports of anterior midcingulate epilepsy show a trend toward a higher proportion of sensory auras and premotor semiology. Ictal pouting, vocalizations, and, in particular, laughter are strong indicators of epilepsy arising or spreading to this region. Although scalp EEG was traditionally thought to provide little information, the data provided in this review demonstrate that most patients will have abnormalities over the frontal or frontotemporal regions. Frontotemporal abnormalities at least interictally provide valuable information regarding lateralization. The etiology of epilepsy arising from the anterior cingulate region seems to be most frequently secondary to focal cortical dysplasia (FCD), followed by neoplasms and vascular lesions, particularly cavernomas, although one cannot rule out a publication bias. Findings of nuclear medicine imaging is seldomly reported but both positron emission tomography and ictal single-photon computed tomography can identify the generator or the network often showing abnormalities extending to the frontal regions. The few available magnetoencephalography (MEG) studies reveal mixed results, sometimes providing false lateralization of the focus. Anterior cingulate epilepsy is difficult to recognize, but the features summarized in this review should prompt suspicion in clinical practice.
Topics: Humans; Gyrus Cinguli; Epilepsy, Frontal Lobe; Seizures; Electroencephalography; Magnetoencephalography; Magnetic Resonance Imaging
PubMed: 36930222
DOI: 10.1097/WNP.0000000000000973 -
ELife Mar 2024Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration...
Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.
Topics: Humans; Alzheimer Disease; Amyloid beta-Peptides; tau Proteins; Benchmarking; Brain
PubMed: 38546337
DOI: 10.7554/eLife.91044 -
Frontiers in Neuroscience 2023Epilepsy is a chronic central nervous system disorder characterized by recurrent seizures. Not only does epilepsy severely affect the daily life of the patient, but the... (Review)
Review
Epilepsy is a chronic central nervous system disorder characterized by recurrent seizures. Not only does epilepsy severely affect the daily life of the patient, but the risk of premature death in patients with epilepsy is three times higher than that of the normal population. Magnetoencephalography (MEG) is a non-invasive, high temporal and spatial resolution electrophysiological data that provides a valid basis for epilepsy diagnosis, and used in clinical practice to locate epileptic foci in patients with epilepsy. It has been shown that MEG helps to identify MRI-negative epilepsy, contributes to clinical decision-making in recurrent seizures after previous epilepsy surgery, that interictal MEG can provide additional localization information than scalp EEG, and complete excision of the stimulation area defined by the MEG has prognostic significance for postoperative seizure control. However, due to the complexity of the MEG signal, it is often difficult to identify subtle but critical changes in MEG through visual inspection, opening up an important area of research for biomedical engineers to investigate and implement intelligent algorithms for epilepsy recognition. At the same time, the use of manual markers requires significant time and labor costs, necessitating the development and use of computer-aided diagnosis (CAD) systems that use classifiers to automatically identify abnormal activity. In this review, we discuss in detail the results of applying various different feature extraction methods on MEG signals with different classifiers for epilepsy detection, subtype determination, and laterality classification. Finally, we also briefly look at the prospects of using MEG for epilepsy-assisted localization (spike detection, high-frequency oscillation detection) due to the unique advantages of MEG for functional area localization in epilepsy, and discuss the limitation of current research status and suggestions for future research. Overall, it is hoped that our review will facilitate the reader to quickly gain a general understanding of the problem of MEG-based epilepsy classification and provide ideas and directions for subsequent research.
PubMed: 37502686
DOI: 10.3389/fnins.2023.1183391 -
Ageing Research Reviews Jul 2023With an aging population, cognitive decline and neurodegenerative disorders are an emerging public health crises with enormous, yet still under-recognized burdens.... (Review)
Review
With an aging population, cognitive decline and neurodegenerative disorders are an emerging public health crises with enormous, yet still under-recognized burdens. Alzheimer's disease (AD) is the most common type of dementia, and the number of cases is expected to dramatically rise in the upcoming decades. Substantial efforts have been placed into understanding the disease. One of the primary avenues of research is neuroimaging, and while positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) are most common, crucial recent advancements in electrophysiological methods such as magnetoencephalography (MEG) and electroencephalography (EEG) have provided novel insight into the aberrant neural dynamics at play in AD pathology. In this review, we outline task-based M/EEG studies published since 2010 using paradigms probing the cognitive domains most affected by AD, including memory, attention, and executive functioning. Furthermore, we provide important recommendations for adapting cognitive tasks for optimal use in this population and adjusting recruitment efforts to improve and expand future neuroimaging work.
Topics: Humans; Aged; Alzheimer Disease; Neuroimaging; Cognitive Dysfunction; Magnetic Resonance Imaging; Positron-Emission Tomography; Cognition; Brain
PubMed: 37156399
DOI: 10.1016/j.arr.2023.101950 -
NeuroImage Nov 2023Multivariate pattern analysis (MVPA) of Magnetoencephalography (MEG) and Electroencephalography (EEG) data is a valuable tool for understanding how the brain represents...
Multivariate pattern analysis (MVPA) of Magnetoencephalography (MEG) and Electroencephalography (EEG) data is a valuable tool for understanding how the brain represents and discriminates between different stimuli. Identifying the spatial and temporal signatures of stimuli is typically a crucial output of these analyses. Such analyses are mainly performed using linear, pairwise, sliding window decoding models. These allow for relative ease of interpretation, e.g. by estimating a time-course of decoding accuracy, but have limited decoding performance. On the other hand, full epoch multiclass decoding models, commonly used for brain-computer interface (BCI) applications, can provide better decoding performance. However interpretation methods for such models have been designed with a low number of classes in mind. In this paper, we propose an approach that combines a multiclass, full epoch decoding model with supervised dimensionality reduction, while still being able to reveal the contributions of spatiotemporal and spectral features using permutation feature importance. Crucially, we introduce a way of doing supervised dimensionality reduction of input features within a neural network optimised for the classification task, improving performance substantially. We demonstrate the approach on 3 different many-class task-MEG datasets using image presentations. Our results demonstrate that this approach consistently achieves higher accuracy than the peak accuracy of a sliding window decoder while estimating the relevant spatiotemporal features in the MEG signal.
Topics: Humans; Magnetoencephalography; Brain; Electroencephalography; Brain Mapping; Neural Networks, Computer; Brain-Computer Interfaces; Algorithms
PubMed: 37805019
DOI: 10.1016/j.neuroimage.2023.120396 -
Current Neurology and Neuroscience... Feb 2024Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with... (Review)
Review
PURPOSE OF THE REVIEW
Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with subcentimeter accuracy. Its capability to provide high resolution in both of these domains makes it a powerful tool both in basic neuroscience as well as clinical applications. In neurology, it has proven useful in its ability to record and localize epileptiform activity. Epilepsy workup typically begins with scalp electroencephalography (EEG), but in many situations, EEG-based localization of the epileptogenic zone is inadequate. The complementary sensitivity of MEG can be crucial in such cases, and MEG has been adopted at many centers as an important resource in building a surgical hypothesis. In this paper, we review recent work evaluating the extent of MEG influence of presurgical evaluations, novel analyses of MEG data employed in surgical workup, and new MEG instrumentation that will likely affect the field of clinical MEG.
RECENT FINDINGS
MEG consistently contributes to presurgical evaluation and these contributions often change the plan for epilepsy surgery. Extensive work has been done to develop new analytic methods for localizing the source of epileptiform activity with MEG. Systems using optically pumped magnetometry (OPM) have been successfully deployed to record and localize epileptiform activity. MEG remains an important noninvasive tool for epilepsy presurgical evaluation. Continued improvements in analytic methodology will likely increase the diagnostic yield of the test. Novel instrumentation with OPM may contribute to this as well, and may increase accessibility of MEG by decreasing cost.
Topics: Humans; Magnetoencephalography; Epilepsy; Electroencephalography; Neuroimaging; Functional Neuroimaging
PubMed: 38148387
DOI: 10.1007/s11910-023-01328-5