Latest AI and machine learning research in seizures for healthcare professionals.
Understanding the neural dynamics underlying expressive musical performance remains a major challenge at the intersection of neuroscience, music cognition, and computational modeling. While EEG studies of emotion have largely focused on passive exposure to affective stimuli, comparatively little research has examined oscillatory brain activity during active musical expression. The present single-s...
The human visual system can identify objects in complex natural scenes, yet the mechanisms supporting robust perception under such variable conditions remain incompletely understood. Here, we investigate how the statistical structure of natural scenes shapes perceptual evidence formation and determines whether near-threshold stimuli are perceived correctly or incorrectly. We combine controlled psy...
Deep learning on physiological time series is interpreted through domain-specific features -- oscillatory rhythms in EEG, morphological complexes in E...
Despite substantial interest in how neural systems recover over time after acute neurological events, there is a dearth of longitudinal assessment fro...
The objective assessment of patients with disorders of consciousness (DOC) remains a significant clinical challenge. Behavioral scales like the Coma R...
Background: Selective attention enables the prioritization of behaviorally relevant information in complex sensory environments. Despite substantial e...
Electroencephalography (EEG) offers noninvasive, millisecond resolution recordings of neuronal activity and is widely used in neuroscience and healthc...
Objective. EEG foundation models (FMs) report strong accuracy on clinical resting-state EEG. However, high accuracy under subject-disjoint cross-valid...
Major depressive disorder (MDD) and other psychiatric diseases can greatly benefit from objective decision support in diagnosis and therapy. Machine l...
Reconstructing speech envelopes from electroencephalography(EEG) signals is a challenging but valuable task for brain-computer interfaces (BCIs), with...
Hibernating bears show remarkable metabolic suppression. Their decline in core body temperature (Tb) is moderate(from 38{degrees}C to 30-35{degrees}C)...
Background and Purpose: Drug resistant epilepsy (DRE) affects approximately 15 million people worldwide, and surgery remains the only curative option....
Background. This study examines a competition based model (Cmodel) designed to capture the temporal dynamics of successive brain microstates derived f...
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret in...
Brain-state-guided and closed-loop transcranial magnetic stimulation (TMS) protocols have emerged as methods for decreasing the variability and increa...
SCN2A-related disorders result from pathogenic variants in the gene encoding for the voltage-gated sodium channel Nav1.2. Collectively, these disorder...
The internal representations of large language models (LLMs) correlate, or "align" , with human neural activity during language comprehension. One vie...
Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including...
Mild traumatic brain injury (mTBI) is a prevalent condition that remains difficult to diagnose in its early stages. Oculomotor dysfunction is a well-e...
The detection of Alzheimers disease (AD) is considered crucial, as timely intervention can improve patient outcomes. Electroencephalogram (EEG)-based ...