Seizures

Age and Social Observation Effects on Theta Synchrony and Its Role in Adolescent Post-Error Control: A Computational Approach

Error monitoring allows for detecting mistakes and adapting behavior. Error monitoring is associated with increased theta (4-7 Hz) EEG activity recorded at midfrontal electrode sites located over the medial frontal cortex. Increases in theta synchrony after errors between midfrontal and lateral electrode sites, located over lateral prefrontal, motor, and sensory/parietal brain regions, are associa...

EEG biomarkers of reinforcement learning and motivation: A multi-task battery

Serotonin and dopamine make dissociable contributions to reinforcement learning (RL) sub-components, yet we lack neural biomarkers capable of detecting their differential effects. Here, we report the development of a five-task EEG battery designed to probe these dissociable RL mechanisms. Using a model-free analytical approach in healthy volunteers, we identify distinct neural markers across proba...

Teaching LLMs to Recommend and Defer in Underrepresented Epilepsy Care

Specialist epilepsy expertise is scarce in resource-constrained settings, making LLM-based decision support attractive for frontline clinicians managi...

EEG-Based Identification of Adolescent Non-Suicidal Self-Injury and Neurophysiological Interpretation Using an Explainable Deep Learning Framework

Non-suicidal self-injury (NSSI) among adolescents is a prevalent mental health problem and an important indicator of potential suicide risk. Early obj...

Healthy-to-Stroke Translation of EEG-Based BMIs: EEG Characterization and Reinforcement Learning-Based Decoder Evaluation

Purpose: EEG-based brain-machine interfaces (BMIs) may support assistive technologies for individuals with stroke-related motor impairment by translat...

Automated EEG Classification to Track Levels of Consciousness

Precise prognostication in acute brain injury is limited by a lack of reliable biomarkers of consciousness available to clinicians at the bedside. The...

TinyCNNDeep: Lightweight Attention-Based CNN for EEG Classification of Eye States and Sleep Deprivation

Sleep deprivation impairs vigilance and cognitive function, yet jointly identifying the sleep condition (normal vs deprived) and the eye state (open v...

Interpretable Concept-Guided Polynomial Tabular Kolmogorov-Arnold Network for EEG-Based Mild Cognitive Impairment Detection

Early and scalable detection of mild cognitive impairment (MCI) remains an unresolved clinical challenge. Existing EEG-based screening approaches are ...

Towards Robust EEG Decoding Based on Riemannian Self-Attention

Brain-Computer Interface (BCI) based on electroencephalography (EEG) enables direct interaction between the brain and external environments and has si...

What Does the Brain See? Multiview Neural Representations to Demystify the Brain-Visual Alignment

Zero-shot visual decoding from electroencephalography (EEG) aims to infer visual semantics from non-invasive neural recordings, but remains challengin...

Foundation Models for Epileptogenic Zone Identification in Drug-Resistant Epilepsy

Accurate identification of the epileptogenic zone (EZ) is essential for seizure freedom after resective surgery in drug-resistant epilepsy, yet seizur...

Quantum machine learning for detection of sleep deprivation from EEG signals

Approximately 50% of the population in India is estimated to experience sleep-related disorders. Sleep deprivation is a prevalent condition that adver...

Evaluation of EEG Foundation Models for Event-Based Burst-Suppression Detection in ICU

Burst suppression (BS) is a clinically relevant electroencephalographic (EEG) pattern used to monitor sedation depth and brain activity in critically ...

Invariant Neural Representation of Parts of Speech in the Human Brain

Elucidating the internal representation of language in the brain has major implications for cognitive science, brain disorders, and artificial intelli...

DynFS-MoE: Dynamic Functional-Structural Mixture-of-Experts for Post-Traumatic Epilepsy Diagnosis

Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI), yet early identification remains challenging due to the comple...

DynFS-MoE: Dynamic Functional-Structural Mixture-of-Experts for Post-Traumatic Epilepsy Diagnosis

Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI), yet early identification remains challenging due to the comple...

EEGDash: An open-source platform for machine learning on public neurophysiological data

Public neurophysiological datasets are increasingly accessible but remain hard to reuse: turning one into a trained model still takes thousands of lin...

Reducing the Complexity of Deep Learning Models for EEG Analysis on Wearable Devices

Wearable healthcare devices are the fastest-growing Internet of Things (IoT) sector. Many automated healthcare services rely on two crucial biological...

End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS

The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics. Conv...

Sleep EEG Signal Criticality as a Non-Invasive Predictor of Cognitive Decline in Dementia

Early detection of neurodegeneration remains a critical clinical challenge. This study investigates whether sleep EEG signal criticality, quantified v...