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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Benjamin H. Brinkmann; Philippa J. Karoly; Ewan S. Nurse; Ewan S. Nurse; +10 Authors

    It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic-clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via long-term use of these systems. Copyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Article . 2021
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    Frontiers in Neurology
    Article . 2021
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    Frontiers in Neurology
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    Frontiers in Neurology
    Article . 2021 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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      Frontiers in Neurology
      Article . 2021
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      Frontiers in Neurology
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      Frontiers in Neurology
      Article . 2021 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Olivier eDarbin; Elizabeth eAdams; Anthony eMartino; Leslie eNaritoku; +2 Authors

    Over the last 30 years, the functions (and dysfunctions) of the sensory-motor circuitry have been mostly conceptualized using linear modelizations which have resulted in two main models: the “rate hypothesis” and the “oscillatory hypothesis.” In these two models, the basal ganglia data stream is envisaged as a random temporal combination of independent simple patterns issued from its probability distribution of interval interspikes or its spectrum of frequencies respectively. More recently, non-linear analyses have been introduced in the modelization of motor circuitry activities, and they have provided evidences that complex temporal organizations exist in basal ganglia neuronal activities. Regarding movement disorders, these complex temporal organizations in the basal ganglia data stream differ between conditions (i.e., parkinsonism, dyskinesia, healthy control) and are responsive to treatments (i.e., l-DOPA, deep brain stimulation). A body of evidence has reported that basal ganglia neuronal entropy (a marker for complexity/irregularity in time series) is higher in hypokinetic state. In line with these findings, an entropy-based model has been recently formulated to introduce basal ganglia entropy as a marker for the alteration of motor processing and a factor of motor inhibition. Importantly, non-linear features have also been identified as a marker of condition and/or treatment effects in brain global signals (EEG), muscular activities (EMG), or kinetic of motor symptoms (tremor, gait) of patients with movement disorders. It is therefore warranted that the non-linear dynamics of motor circuitry will contribute to a better understanding of the neuronal dysfunctions underlying the spectrum of parkinsonian motor symptoms including tremor, rigidity, and hypokinesia.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    DOAJ
    Article . 2013
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    Frontiers in Neurology
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    Frontiers in Neurology
    Article . 2013 . Peer-reviewed
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neurology
    Article . 2013
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      Frontiers in Neurology
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      Frontiers in Neurology
      Article . 2013 . Peer-reviewed
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      Frontiers in Neurology
      Article . 2013
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Tatjana Traub-Weidinger; Otto Muzik; Lalith Kumar Shiyam Sundar; Susanne Aull-Watschinger; +14 Authors

    The purpose of this study was to establish a non-invasive clinical PET/MR protocol using [18F]-labeled deoxyglucose (FDG) that provides physicians with regional metabolic rate of glucose (MRGlc) values and to clarify the contribution of absolute quantification to clinical management of patients with non-lesional extratemporal lobe epilepsy (ETLE). The study included a group of 15 patients with non-lesional ETLE who underwent a dynamic FDG PET study using a fully-integrated PET/MRI system (Siemens Biograph). FDG tracer uptake images were converted to MRGlc (μmol/100 g/min) maps using an image derived input function that was extracted based on the combined analysis of PET and MRI data. In addition, the same protocol was applied to a group of healthy controls, yielding a normative database. Abnormality maps for ETLE patients were created with respect to the normative database, defining significant hypo- or hyper-metabolic regions that exceeded ±2 SD of normal regional mean MRGlc values. Abnormality maps derived from MRGlc images of ETLE patients contributed to the localization of hypo-metabolic areas against visual readings in 53% and increased the confidence in the original clinical readings in 33% of all cases. Moreover, quantification allowed identification of hyper-metabolic areas that are associated with frequently spiking cortex, rarely acknowledged in clinical readings. Overall, besides providing some confirmatory information to visual readings, quantitative PET imaging demonstrated only a moderate impact on clinical management of patients with complex pathology that leads to epileptic seizures, failing to provide new decisive information that would have changed classification of patients from being rejected to being considered for surgical intervention.

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    Article . 2020
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    Frontiers in Neurology
    Article . 2020
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    Authors: Robert Todd Constable; Dustin eScheinost; Emily S. Finn; Xilin eShen; +4 Authors

    This review focuses on the use of resting-state functional magnetic resonance imaging data to assess functional connectivity in the human brain for surgical planning in intractable epilepsy. This approach has the potential to predict outcomes for a given surgical procedure based on the pre-surgical functional organization of the brain. Functional connectivity can also identify cortical regions that are organized differently in epilepsy patients either as a direct function of the disease or through indirect compensatory responses. Functional connectivity mapping can also potentially help identify epileptogenic tissue, whether this is a single focal location or a network of seizure-generating tissues and this information can assist in guiding the implantation of electrodes for invasive monitoring. This review covers the basics of connectivity analysis and discusses particular issues associated with analyzing such data. These issues include how to define nodes, as well as differences between connectivity analyses of individual nodes, groups of nodes, and whole-brain assessment at the voxel level. The need for arbitrary thresholds in some connectivity analyses is discussed and a solution to this problem is reviewed. Overall, functional connectivity analysis is becoming an important tool for assessing functional brain organization in surgical planning in epilepsy.

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    Frontiers in Neurology
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    Frontiers in Neurology
    Article . 2013
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    Article . 2013
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    Frontiers in Neurology
    Article . 2013 . Peer-reviewed
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      Frontiers in Neurology
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      Frontiers in Neurology
      Article . 2013 . Peer-reviewed
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    Authors: Maurizio Bergamino; Elizabeth G. Keeling; Elizabeth G. Keeling; Virendra R. Mishra; +2 Authors

    Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest–based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

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    Frontiers in Neurology
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      Frontiers in Neurology
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    Authors: Ana Carolina Rodrigues; Ana Carolina Rodrigues; Mariana Drummond Martins Lima; Leonardo Cruz de Souza; +7 Authors

    Although the scientific community has focused on the effects of concussions in contact sports, the role of subconcussive impacts, as it can occur during soccer heading, has recently gained attention, considering that it may represent an additional mechanism of cumulative brain injury. The aim of this study is to investigate the effects of soccer heading on cognitive functioning in active professional soccer players. Male soccer players (n = 44), from two soccer teams that play in the Brazilian A Series Championship, and non-athletes (n = 47), comparable in age and education, were submitted to cognitive assessment, consisting of computerized and conventional neuropsychological testing (Neupsilin battery). In the computerized cognitive assessment, soccer players performed better than controls on reaction time measures in general motor coordination, executive functioning and memory tests, and on accuracy measures in executive functioning tests. There were no significant differences between groups on the Neupsilin battery. A comparison between two sub-groups of soccer players, based on the self-reported number of headings, did not show significant differences on tests performance. No significant correlations were found between an estimate of exposure to heading during professional soccer career and cognitive performance. Our data demonstrate no evidence of cognitive impairment in soccer players, compared to non-athletes, and no association between heading exposure and performance on neuropsychological tests. Longitudinal investigations, including neuroimaging assessment, will help to clarify whether soccer heading may be associated with brain injury and cognitive dysfunction.

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    Frontiers in Neurology
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    Authors: Pan Li; Pan Li; Pan Li; Yuanyuan Y; +11 Authors

    TANK1-binding kinase 1 (TBK1) is mainly involved in the regulation of various cellular pathways through the autophagic lysosomal system, and the loss of function or hypofunction caused by TBK1 gene mutation mainly leads to frontotemporal lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS), and ALS-FTLD. Alzheimer's disease (AD) due to TBK1 gene mutation is extremely rare, and only one case has been reported in China so far. In this report, we described a patient with early-onset AD (EOAD) in whom a new probable pathogenic variant c.704A>T (p.Tyr235Phe) in the TBK1 gene was identified by a whole-genome sequencing analysis. It is suggested that FTLD gene mutation may exist in patients with clinical manifestations of AD.

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    Frontiers in Neurology
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    Authors: Kristina J. Pfeifer; Alex J. Cook; Jessica K. Yankulova; Bruce J. P. Mortimer; +4 Authors

    Enhanced neuronal synchronization of the subthalamic nucleus (STN) is commonly found in PD patients and corresponds to decreased motor ability. Coordinated reset (CR) was developed to decouple synchronized states causing long lasting desynchronization of neural networks. Vibrotactile CR stimulation (vCR) was developed as non-invasive therapeutic that delivers gentle vibrations to the fingertips. A previous study has shown that vCR can desynchronize abnormal brain rhythms within the sensorimotor cortex of PD patients, corresponding to sustained motor relief after 3 months of daily treatment. To further develop vCR, we created a protocol that has two phases. Study 1, a double blinded randomized sham-controlled study, is designed to address motor and non-motor symptoms, sensorimotor integration, and potential calibration methods. Study 2 examines dosing effects of vCR using a remote study design. In Study 1, we will perform a 7-month double-blind sham-controlled study including 30 PD patients randomly placed into an active vCR or inactive (sham) vCR condition. Patients will receive stimulation for 4 h a day in 2-h blocks for 6 months followed by a 1-month pause in stimulation to assess long lasting effects. Our primary outcome measure is the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III off medication after 6 months of treatment. Secondary measures include a freezing of gait (FOG) questionnaire, objective motor evaluations, sensorimotor electroencephalography (EEG) results, a vibratory temporal discrimination task (VTDT), non-motor symptom evaluations/tests such as sleep, smell, speech, quality of life measurements and Levodopa Equivalent Daily Dose (LEDD). Patients will be evaluated at baseline, 3, 6, and 7 months. In the second, unblinded study phase (Study 2), all patients will be given the option to receive active vCR stimulation at a reduced dose for an additional 6 months remotely. The remote MDS-UPDRS part III off medication will be our primary outcome measure. Secondary measures include sleep, quality of life, objective motor evaluations, FOG and LEDD. Patients will be evaluated in the same time periods as the first study. Results from this study will provide clinical efficacy of vCR and help validate our investigational vibrotactile device for the purpose of obtaining FDA clearance.Clinical Trial Registration:ClinicalTrials.gov, identifier: NCT04877015.

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      Frontiers in Neurology
      Article . 2021 . Peer-reviewed
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    Authors: Sarah Tabrizi; Blair leavitt; Rachael Scahill; Sarah Gregory; +1 Authors

    The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure grey matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilises a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a grey matter segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3T MRI data from 20 controls, 40 premanifest Huntington’s disease (HD) and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical and lobular grey matter was investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalised least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software.

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    Frontiers in Neurology; OpenAPC Global Initiative
    Article . Conference object . 2017 . Peer-reviewed
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      Frontiers in Neurology; OpenAPC Global Initiative
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    Authors: Robert J. Zhou; Hossein M. Hondori; Maryam Khademi; Jessica M. Cassidy; +14 Authors

    The heterogeneity of stroke prompts the need for predictors of individual treatment response to rehabilitation therapies. We previously studied healthy subjects with EEG and identified a frontoparietal circuit in which activity predicted training-related gains in visuomotor tracking. Here we asked whether activity in this same frontoparietal circuit also predicts training-related gains in visuomotor tracking in patients with chronic hemiparetic stroke. Subjects (n = 12) underwent dense-array EEG recording at rest, then received 8 sessions of visuomotor tracking training delivered via home-based telehealth methods. Subjects showed significant training-related gains in the primary behavioral endpoint, Success Rate score on a standardized test of visuomotor tracking, increasing an average of 24.2 ± 21.9% (p = 0.003). Activity in the circuit of interest, measured as coherence (20–30 Hz) between leads overlying ipsilesional frontal (motor cortex) and parietal lobe, significantly predicted training-related gains in visuomotor tracking change, measured as change in Success Rate score (r = 0.61, p = 0.037), supporting the main study hypothesis. Results were specific to the hypothesized ipsilesional motor-parietal circuit, as coherence within other circuits did not predict training-related gains. Analyses were repeated after removing the four subjects with injury to motor or parietal areas; this increased the strength of the association between activity in the circuit of interest and training-related gains. The current study found that (1) Eight sessions of training can significantly improve performance on a visuomotor task in patients with chronic stroke, (2) this improvement can be realized using home-based telehealth methods, (3) an EEG-based measure of frontoparietal circuit function predicts training-related behavioral gains arising from that circuit, as hypothesized and with specificity, and (4) incorporating measures of both neural function and neural injury improves prediction of stroke rehabilitation therapy effects.

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    Frontiers in Neurology
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    Frontiers in Neurology
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      Frontiers in Neurology
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    Authors: Benjamin H. Brinkmann; Philippa J. Karoly; Ewan S. Nurse; Ewan S. Nurse; +10 Authors

    It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic-clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via long-term use of these systems. Copyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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    Frontiers in Neurology
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    Authors: Olivier eDarbin; Elizabeth eAdams; Anthony eMartino; Leslie eNaritoku; +2 Authors

    Over the last 30 years, the functions (and dysfunctions) of the sensory-motor circuitry have been mostly conceptualized using linear modelizations which have resulted in two main models: the “rate hypothesis” and the “oscillatory hypothesis.” In these two models, the basal ganglia data stream is envisaged as a random temporal combination of independent simple patterns issued from its probability distribution of interval interspikes or its spectrum of frequencies respectively. More recently, non-linear analyses have been introduced in the modelization of motor circuitry activities, and they have provided evidences that complex temporal organizations exist in basal ganglia neuronal activities. Regarding movement disorders, these complex temporal organizations in the basal ganglia data stream differ between conditions (i.e., parkinsonism, dyskinesia, healthy control) and are responsive to treatments (i.e., l-DOPA, deep brain stimulation). A body of evidence has reported that basal ganglia neuronal entropy (a marker for complexity/irregularity in time series) is higher in hypokinetic state. In line with these findings, an entropy-based model has been recently formulated to introduce basal ganglia entropy as a marker for the alteration of motor processing and a factor of motor inhibition. Importantly, non-linear features have also been identified as a marker of condition and/or treatment effects in brain global signals (EEG), muscular activities (EMG), or kinetic of motor symptoms (tremor, gait) of patients with movement disorders. It is therefore warranted that the non-linear dynamics of motor circuitry will contribute to a better understanding of the neuronal dysfunctions underlying the spectrum of parkinsonian motor symptoms including tremor, rigidity, and hypokinesia.

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