AIMC Topic: Brain Waves

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Understanding the Spatio-Temporal Coupling of Spikes and Spindles in Focal Epilepsy Through a Network-Level Computational Model.

International journal of neural systems Mar 15, 2025
The electrophysiological findings have shown that epileptiform spikes triggering sleep spindles within 1[Formula: see text]s across multiple channels are commonly observed during sleep in focal epilepsy (FE). Such spatio-temporal couplings of spikes ...
Humans Neural Networks, Computer Computer Simulation Models, Neurological Brain Waves Nerve Net Thalamus Epilepsies, Partial Action Potentials Electroencephalography Cerebral Cortex
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The 'Sandwich' meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding.

Journal of neural engineering Jan 23, 2025
. Machine learning has enhanced the performance of decoding signals indicating human behaviour. Electroencephalography (EEG) brainwave decoding, as an exemplar indicating neural activity and human thoughts non-invasively, has been helpful in neural a...
Privacy Brain-Computer Interfaces Humans Deep Learning Brain Waves Neural Networks, Computer Machine Learning Electroencephalography Brain
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Detecting fast-ripples on both micro- and macro-electrodes in epilepsy: A wavelet-based CNN detector.

Journal of neuroscience methods Dec 14, 2024
BACKGROUND: Fast-ripples (FR) are short (∼10 ms) high-frequency oscillations (HFO) between 200 and 600 Hz that are helpful in epilepsy to identify the epileptogenic zone. Our aim is to propose a new method to detect FR that had to be efficient for in...
Humans Neural Networks, Computer Female Adult Electrocorticography Signal Processing, Computer-Assisted Wavelet Analysis Male Brain Waves Electroencephalography Epilepsy
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A Novel Real-time Phase Prediction Network in EEG Rhythm.

Neuroscience bulletin Nov 29, 2024
Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm to assess the real-time brain state and optimize the brain stimulation process, is becoming a hot research topic. Because the EEG signal is non-station...
Brain Adult Male Humans Neural Networks, Computer Machine Learning Electroencephalography Signal Processing, Computer-Assisted Brain Waves
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Predicting the effectiveness of binaural beats on working memory.

Neuroreport Sep 30, 2024
Working memory is vital for short-term information processing. Binaural beats can enhance working memory by improving attention and memory consolidation through neural synchronization. However, individual differences in cognitive and neuronal functio...
Male Electroencephalography Memory, Short-Term Brain Waves Auditory Perception Attention Acoustic Stimulation Female Young Adult Adult Humans Machine Learning Brain
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Subject-independent auditory spatial attention detection based on brain topology modeling and feature distribution alignment.

Hearing research Aug 14, 2024
Auditory spatial attention detection (ASAD) seeks to determine which speaker in a surround sound field a listener is focusing on based on the one's brain biosignals. Although existing studies have achieved ASAD from a single-trial electroencephalogra...
Signal Processing, Computer-Assisted Attention Acoustic Stimulation Sound Localization Auditory Perception Brain Auditory Pathways Humans Models, Neurological Brain Waves Neural Networks, Computer Electroencephalography
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A causal perspective on brainwave modeling for brain-computer interfaces.

Journal of neural engineering May 3, 2024
. Machine learning (ML) models have opened up enormous opportunities in the field of brain-computer Interfaces (BCIs). Despite their great success, they usually face severe limitations when they are employed in real-life applications outside a contro...
Humans Machine Learning Electroencephalography Brain-Computer Interfaces Algorithms Brain Brain Waves
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Differentiating ischemic stroke patients from healthy subjects using a large-scale, retrospective EEG database and machine learning methods.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Apr 16, 2024
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which featu...
Brain Waves Ischemic Stroke Retrospective Studies Time Factors Electroencephalography Diagnosis, Differential Female Male Humans Signal Processing, Computer-Assisted Predictive Value of Tests Reproducibility of Results Middle Aged Aged Machine Learning Case-Control Studies Aged, 80 and over Databases, Factual Diagnosis, Computer-Assisted Adult Brain
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LightSeizureNet: A Lightweight Deep Learning Model for Real-Time Epileptic Seizure Detection.

IEEE journal of biomedical and health informatics Apr 4, 2023
The monitoring of epilepsy patients in non-hospital environment is highly desirable, where ultra-low power wearable seizure detection devices are essential in such a system. The state-of-the-art epileptic seizure detection algorithms targeting such d...
Humans Brain Waves Epilepsy Algorithms Seizures Deep Learning
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Critically synchronized brain waves form an effective, robust and flexible basis for human memory and learning.

Scientific reports Mar 16, 2023
The effectiveness, robustness, and flexibility of memory and learning constitute the very essence of human natural intelligence, cognition, and consciousness. However, currently accepted views on these subjects have, to date, been put forth without a...
Algorithms Humans Brain Neural Networks, Computer Brain Waves Artificial Intelligence
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