AIMC Topic: Electrocorticography

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Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Nov 19, 2024
INTRODUCTION: Precise localization of the epileptogenic zone is critical for successful epilepsy surgery. However, imbalanced datasets in terms of epileptic vs. normal electrode contacts and a lack of standardized evaluation guidelines hinder the con...
Machine Learning Female Young Adult Humans Adolescent Drug Resistant Epilepsy Electrocorticography Adult Male Middle Aged
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Machine learning for (non-)epileptic tissue detection from the intraoperative electrocorticogram.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Aug 24, 2024
OBJECTIVE: Clinical visual intraoperative electrocorticography (ioECoG) reading intends to localize epileptic tissue and improve epilepsy surgery outcome. We aimed to understand whether machine learning (ML) could complement ioECoG reading, how subgr...
Electrocorticography Intraoperative Neurophysiological Monitoring Epilepsy Young Adult Adult Male Middle Aged Adolescent Humans Machine Learning Female
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XDL-ESI: Electrophysiological Sources Imaging via explainable deep learning framework with validation on simultaneous EEG and iEEG.

NeuroImage Aug 22, 2024
Electroencephalography (EEG) or Magnetoencephalography (MEG) source imaging aims to estimate the underlying activated brain sources to explain the observed EEG/MEG recordings. Solving the inverse problem of EEG/MEG Source Imaging (ESI) is challenging...
Humans Algorithms Electrocorticography Magnetoencephalography Brain Deep Learning Electroencephalography
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Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

Journal of neuroscience methods Aug 14, 2024
BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing m...
Humans Electrocorticography Female Young Adult Adult Neural Networks, Computer Signal Processing, Computer-Assisted Male Machine Learning Fingers Epilepsy Movement
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Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework.

Nature communications Apr 16, 2024
Interictal Epileptiform Discharges (IED) and High Frequency Oscillations (HFO) in intraoperative electrocorticography (ECoG) may guide the surgeon by delineating the epileptogenic zone. We designed a modular spiking neural network (SNN) in a mixed-si...
Electroencephalography Electrocorticography Humans Neural Networks, Computer
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Timing matters for accurate identification of the epileptogenic zone.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Feb 18, 2024
OBJECTIVE: Interictal biomarkers of the epileptogenic zone (EZ) and their use in machine learning models open promising avenues for improvement of epilepsy surgery evaluation. Currently, most studies restrict their analysis to short segments of intra...
Electroencephalography Humans Middle Aged Brain Epilepsy Adolescent Adult Machine Learning Electrocorticography Female Sleep Stages Time Factors Male Young Adult
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Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models.

Journal of neural engineering Sep 20, 2023
Development of brain-computer interface (BCI) technology is key for enabling communication in individuals who have lost the faculty of speech due to severe motor paralysis. A BCI control strategy that is gaining attention employs speech decoding from...
Brain-Computer Interfaces Electrocorticography Sensorimotor Cortex Deep Learning Speech Humans Communication
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Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes.

NeuroImage Sep 15, 2023
Electromagnetic source imaging (ESI) offers unique capability of imaging brain dynamics for studying brain functions and aiding the clinical management of brain disorders. Challenges exist in ESI due to the ill-posedness of the inverse problem and th...
Magnetic Resonance Imaging Brain Mapping Electroencephalography Humans Brain Magnetoencephalography Deep Learning Epilepsy Drug Resistant Epilepsy Electrocorticography
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Genetic algorithm designed for optimization of neural network architectures for intracranial EEG recordings analysis.

Journal of neural engineering Jun 16, 2023
The current practices of designing neural networks rely heavily on subjective judgment and heuristic steps, often dictated by the level of expertise possessed by architecture designers. To alleviate these challenges and streamline the design process,...
Neural Networks, Computer Electroencephalography Signal Processing, Computer-Assisted Humans Electrocorticography
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Accessing the brain with soft deployable electrocorticography arrays.

Science robotics May 10, 2023
Soft robotics facilitates the deployment of large radial electrode arrays on the brain cortex through small craniotomies.
Brain Cerebral Cortex Robotics Electrocorticography
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