AIMC Topic: Brain Waves

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Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System.

Annals of biomedical engineering Feb 15, 2019
Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneou...
Humans Models, Neurological Signal Processing, Computer-Assisted Neurofeedback Brain Waves Machine Learning Female Male
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Accuracy of robot-assisted versus optical frameless navigated stereoelectroencephalography electrode placement in children.

Journal of neurosurgery. Pediatrics Jan 4, 2019
OBJECTIVE The aim of this study was to compare the accuracy of optical frameless neuronavigation (ON) and robot-assisted (RA) stereoelectroencephalography (SEEG) electrode placement in children, and to identify factors that might increase the risk of...
Optical Devices Neuronavigation Tomography Scanners, X-Ray Computed Stereotaxic Techniques Drug Resistant Epilepsy Electrodes, Implanted Child, Preschool Child Imaging, Three-Dimensional Electroencephalography Brain Waves Magnetic Resonance Imaging Humans Robotics Retrospective Studies Brain Female Male
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Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.

Journal of neural engineering Oct 24, 2018
OBJECTIVE: Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulat...
Neural Networks, Computer Action Potentials Neurons Brain Waves Thalamus
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Application of identity vectors for EEG classification.

Journal of neuroscience methods Sep 19, 2018
BACKGROUND: Finding an optimal EEG subject verification algorithm is a long standing goal within the EEG community. For every advancement made, another feature set, classifier, or dataset is often introduced; tracking improvements in classification w...
Unsupervised Machine Learning Data Interpretation, Statistical Electroencephalography Humans Brain Signal Processing, Computer-Assisted Pattern Recognition, Automated Brain Waves
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Slow wave detection in sleeping mice: Comparison of traditional and machine learning methods.

Journal of neuroscience methods Aug 17, 2018
BACKGROUND: During slow-wave sleep the electroencephalographic (EEG) and local field potential (LFP) recordings reveal the presence of large amplitude slow waves. Systematic extraction of individual slow waves is not trivial.
Sleep, Slow-Wave Humans Neural Networks, Computer Animals Brain Waves Electrocorticography Mice Pattern Recognition, Automated
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Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy.

Seizure Jul 10, 2018
PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. Using machine learning techniques we explored if abnormalities in microstates can identify patients ...
Electroencephalography Brain Waves Epilepsy, Temporal Lobe Humans Machine Learning Brain Mapping
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Automated detection of electroencephalography artifacts in human, rodent and canine subjects using machine learning.

Journal of neuroscience methods Jun 23, 2018
BACKGROUND: Electroencephalography (EEG) invariably contains extra-cranial artifacts that are commonly dealt with based on qualitative and subjective criteria. Failure to account for EEG artifacts compromises data interpretation.
Rats Rats, Sprague-Dawley Electroencephalography Signal Processing, Computer-Assisted Artifacts Machine Learning Dogs Brain Waves Animals ROC Curve Humans
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Resting-state functional connectivity predicts the ability to adapt arm reaching in a robot-mediated force field.

NeuroImage Mar 26, 2018
Motor deficits are common outcomes of neurological conditions such as stroke. In order to design personalised motor rehabilitation programmes such as robot-assisted therapy, it would be advantageous to predict how a patient might respond to such trea...
Prefrontal Cortex Robotics Electroencephalography Brain Waves Motor Activity Arm Neural Pathways Adult Adaptation, Physiological Biomechanical Phenomena Humans Male Motor Cortex Female Young Adult
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Ongoing brain rhythms shape I-wave properties in a computational model.

Brain stimulation Mar 20, 2018
BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous studies have observed a dependence of TMS-induced responses on ongoing brain activity, for instance sensorimotor rhythms. This suggests an opportunity...
Female Adult Male Humans Neural Networks, Computer Brain Neurons Brain Waves Motor Cortex Transcranial Magnetic Stimulation Computational Biology Longitudinal Studies Electroencephalography
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Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework.

Artificial intelligence in medicine Feb 1, 2018
Recent technological advances in machine learning offer the possibility of decoding complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines (LSM) to recognize the emotional state of an individual based on EEG data....
Emotions Predictive Value of Tests Electroencephalography Humans Brain Waves Signal Processing, Computer-Assisted Computer Simulation Pattern Recognition, Automated Machine Learning Photic Stimulation Reproducibility of Results Time Factors Brain
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