AIMC Topic: Neurophysiology
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Contrastive functional connectivity defines neurophysiology-informed symptom dimensions in major depression.
Cell reports. Medicine
May 28, 2025
Major depressive disorder (MDD) is highly heterogeneous, posing challenges for effective treatment due to complex interactions between clinical symptoms and neurobiological features. To address this, we apply contrastive principal-component analysis ...
Of Pilots and Copilots: The Evolving Role of Artificial Intelligence in Clinical Neurophysiology.
The Neurodiagnostic journal
Feb 25, 2025
Artificial intelligence (AI) is revolutionizing clinical neurophysiology (CNP), particularly in its applications to electroencephalography (EEG), electromyography (EMG), and polysomnography (PSG). AI enhances diagnostic accuracy and efficiency while ...
Artificial Intelligence (AI): Why does it matter for clinical neurophysiology?
Neurophysiologie clinique = Clinical neurophysiology
Jun 14, 2024
Machine learning and clinical neurophysiology.
Journal of neurology
Jul 30, 2022
Clinical neurophysiology constructs a wealth of dynamic information pertaining to the integrity and function of both central and peripheral nervous systems. As with many technological fields, there has been an explosion of data in neurophysiology ove...
Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory.
Frontiers in neural circuits
Sep 20, 2021
Working memory function is severely limited. One key limitation that constrains the ability to maintain multiple items in working memory simultaneously is so-called swap errors. These errors occur when an inaccurate response is in fact accurate relat...
Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in -derived astrocytes ablated mice.
Journal of neurophysiology
Jan 27, 2021
Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been ...
Reachability Analysis of Neural Masses and Seizure Control Based on Combination Convolutional Neural Network.
International journal of neural systems
Aug 2, 2019
Epileptic seizures arise from synchronous firing of multiple spatially separated neural masses; therefore, many synchrony measures are used for seizure detection and characterization. However, synchrony measures reflect only the overall interaction s...
Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses.
Scientific reports
Nov 2, 2018
Neurophysiological features like event-related potentials (ERPs) have long been used to identify different cognitive sub-processes that may contribute to task performance. It has however remained unclear whether "classical" ERPs are truly the best re...
A glimpse into the future of clinical neurophysiology: Can we use machines to interpret EEG?
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jul 29, 2018
Multi-Domain Networks Association for Biological Data Using Block Signed Graph Clustering.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 25, 2018
Multi-domain biological network association and clustering have attracted a lot of attention in biological data integration and understanding, which can provide a more global and accurate understanding of biological phenomenon. In many problems, diff...
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