AIMC Topic: Electrocorticography
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Uncovering phase-coupled oscillatory networks in electrophysiological data.
Human brain mapping
Apr 12, 2015
Phase consistent neuronal oscillations are ubiquitous in electrophysiological recordings, and they may reflect networks of phase-coupled neuronal populations oscillating at different frequencies. Because neuronal oscillations may reflect rhythmic mod...
Multifractal Analysis and Relevance Vector Machine-Based Automatic Seizure Detection in Intracranial EEG.
International journal of neural systems
Apr 7, 2015
Automatic seizure detection technology is of great significance for long-term electroencephalogram (EEG) monitoring of epilepsy patients. The aim of this work is to develop a seizure detection system with high accuracy. The proposed system was mainly...
Annotating neurophysiologic data at scale with optimized human input.
Journal of neural engineering
Jul 3, 2025
Neuroscience experiments and devices are generating unprecedented volumes of data, but analyzing and validating them presents practical challenges, particularly in annotation. While expert annotation remains the gold standard, it is time consuming to...
Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning.
Scientific reports
May 22, 2025
Functional connectivity (FC) analyses of intracranial EEG (iEEG) signals can potentially improve the mapping of epileptic networks in drug-resistant focal epilepsy. However, it remains unclear whether FC-based metrics provide additional value beyond ...
Naturalistic acute pain states decoded from neural and facial dynamics.
Nature communications
May 11, 2025
Pain remains poorly understood in task-free contexts, limiting our understanding of its neurobehavioral basis in naturalistic settings. Here, we use a multimodal, data-driven approach with intracranial electroencephalography, pain self-reports, and f...
Neural Mosaics: Detecting Aberrant Brain Interactions using Algebraic Topology and Generative Artificial Intelligence.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
Epilepsy affects over 50 million persons worldwide, with less than 50% achieving long-term success following surgery. Traditional electrophysiology signal-based seizure detection methods are resource-intensive, laborious, and overlook multifocal brai...
Classification of Seizure Termination Patterns using Deep Learning on intracranial EEG.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Seizure termination has received significantly less attention than initiation and propagation and consequently, remains a poorly understood phase of seizure evolution. Yet, its study may have a significant impact on the development of efficient inter...
Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria.
The New England journal of medicine
Jul 15, 2021
BACKGROUND: Technology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of...
Deep learning approaches for neural decoding across architectures and recording modalities.
Briefings in bioinformatics
Mar 22, 2021
Decoding behavior, perception or cognitive state directly from neural signals is critical for brain-computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method i...
Robot-Assisted Stereotaxy Reduces Target Error: A Meta-Analysis and Meta-Regression of 6056 Trajectories.
Neurosurgery
Jan 13, 2021
BACKGROUND: The pursuit of improved accuracy for localization and electrode implantation in deep brain stimulation (DBS) and stereoelectroencephalography (sEEG) has fostered an abundance of disparate surgical/stereotactic practices. Specific practice...
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