AIMC Topic: Magnetoencephalography

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Feature optimization method for machine learning-based diagnosis of schizophrenia using magnetoencephalography.

Journal of neuroscience methods Mar 19, 2020
BACKGROUND: When many features and a small number of clinical data exist, previous studies have used a few top-ranked features from the Fisher's discriminant ratio (FDR) for feature selection. However, there are many similarities between selected fea...
Brain Brain Mapping Schizophrenia Magnetoencephalography Humans Machine Learning
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Somatosensory evoked fields predict response to vagus nerve stimulation.

NeuroImage. Clinical Feb 4, 2020
There is an unmet need to develop robust predictive algorithms to preoperatively identify pediatric epilepsy patients who will respond to vagus nerve stimulation (VNS). Given the similarity in the neural circuitry between vagus and median nerve affer...
Drug Resistant Epilepsy Magnetoencephalography Evoked Potentials, Somatosensory Somatosensory Cortex Treatment Outcome Support Vector Machine Median Nerve Connectome Humans Afferent Pathways Retrospective Studies Vagus Nerve Stimulation Female Male Adolescent Child
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EMS-Net: A Deep Learning Method for Autodetecting Epileptic Magnetoencephalography Spikes.

IEEE transactions on medical imaging Dec 10, 2019
Epilepsy is a neurological disorder characterized by sudden and unpredictable epileptic seizures, which incurs significant negative impacts on patients' physical, psychological and social health. A practical approach to assist with the clinical asses...
Epilepsy Seizures Magnetoencephalography Humans Deep Learning Electroencephalography
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Two Distinct Neural Timescales for Predictive Speech Processing.

Neuron Dec 2, 2019
During speech listening, the brain could use contextual predictions to optimize sensory sampling and processing. We asked if such predictive processing is organized dynamically into separate oscillatory timescales. We trained a neural network that us...
Humans Uncertainty Magnetoencephalography Male Speech Time Factors Brain Waves Neural Networks, Computer Brain Female
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Anomaly Detection of Moderate Traumatic Brain Injury Using Auto-Regularized Multi-Instance One-Class SVM.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Oct 24, 2019
Detection and quantification of functional deficits due to moderate traumatic brain injury (mTBI) is crucial for clinical decision-making and timely commencement of functional therapy. In this work, we explore magnetoencephalography (MEG) based funct...
Automation Neural Pathways Magnetoencephalography Beta Rhythm Adolescent Support Vector Machine Magnetic Resonance Imaging Brain Injuries, Traumatic Glasgow Coma Scale Algorithms Databases, Factual Brain Female Young Adult Adult Sensitivity and Specificity Male Humans
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Connectomic Profiling Identifies Responders to Vagus Nerve Stimulation.

Annals of neurology Aug 27, 2019
OBJECTIVE: Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using struc...
Drug Resistant Epilepsy Magnetoencephalography Vagus Nerve Stimulation Image Interpretation, Computer-Assisted Connectome Diffusion Tensor Imaging Female Male Adolescent Child, Preschool Child Treatment Outcome Support Vector Machine Patient Selection Humans
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Spectral signatures of serotonergic psychedelics and glutamatergic dissociatives.

NeuroImage Jun 24, 2019
Classic serotonergic psychedelics are remarkable for their capacity to induce reversible alterations in consciousness of the self and the surroundings, mediated by agonism at serotonin 5-HT receptors. The subjective effects elicited by dissociative d...
Humans Machine Learning Adult Ketamine Hallucinogens Receptors, N-Methyl-D-Aspartate Connectome Excitatory Amino Acid Antagonists Lysergic Acid Diethylamide Psilocybin Brain Waves Nerve Net Magnetoencephalography Serotonin 5-HT2 Receptor Agonists
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Adaptive neural network classifier for decoding MEG signals.

NeuroImage May 4, 2019
We introduce two Convolutional Neural Network (CNN) classifiers optimized for inferring brain states from magnetoencephalographic (MEG) measurements. Network design follows a generative model of the electromagnetic (EEG and MEG) brain signals allowin...
Touch Perception Evoked Potentials Visual Perception Auditory Perception Magnetoencephalography Brain Mapping Electroencephalography Brain Signal Processing, Computer-Assisted Female Adult Humans Male Neural Networks, Computer Algorithms
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Automatic diagnosis of neurological diseases using MEG signals with a deep neural network.

Scientific reports Mar 25, 2019
The application of deep learning to neuroimaging big data will help develop computer-aided diagnosis of neurological diseases. Pattern recognition using deep learning can extract features of neuroimaging signals unique to various neurological disease...
Brain Mapping Magnetoencephalography Diagnosis, Differential Humans Male Epilepsy Neural Networks, Computer Nervous System Diseases Case-Control Studies Female Image Processing, Computer-Assisted Reproducibility of Results Computational Biology Sensitivity and Specificity
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Machine learning for MEG during speech tasks.

Scientific reports Feb 7, 2019
We consider whether a deep neural network trained with raw MEG data can be used to predict the age of children performing a verb-generation task, a monosyllable speech-elicitation task, and a multi-syllabic speech-elicitation task. Furthermore, we ar...
Child Male Signal Processing, Computer-Assisted Speech Humans Magnetoencephalography Adolescent Machine Learning Child, Preschool Female
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