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Abstract Objective To accurately predict neurological outcomes among survivors after cardiac arrest (CA), we aim to analyze the experimental data of epileptiform electroencephalography (EEG) in CA survivors to explore th...

Abstract Background Electroencephalography (EEG) recording protocols have been standardized for humans. Although the utilization of techniques in veterinary medicine is increasing, a standard protocol has not yet been es...

# Background The countermovement jump (CMJ) is commonly used to assess neuromuscular performance in athletic populations; however, force plate–derived mechanical metrics may not fully reflect central nervous system (CN...

Abstract Background Lesions causing refractory epilepsy, often associated with temporal lobe epilepsy (TLE), can be undetectable on standard magnetic resonance imaging (MRI) in dogs. Automated brain volumetry, widely use...

BackgroundDespite growing evidence supporting deep brain stimulation (DBS) for treatment- resistant depression (TRD), how stimulation delivered across hemispheres or across multiple targets interact to shape large-scale ...

ObjectiveTo explore the differences in heartbeat-evoked response (HER) under drug-related cues and neutral cues in individuals with heroin use disorder (HUD), and analyze the correlation between HER potentials and immedi...

Abstract Restorative sleep and morning sleepiness are essential factors associated with daytime functioning among workers, yet their variability and determinants remain unclear. Previous studies have primarily focused on...

Abstract Monitoring actions and outcomes is essential for flexible adaptation to environmental demands. Information about errors is important regardless of whether it is internally generated or externally signaled. Follo...

Implicit learning is a fundamental cognitive process whose identification is critical for understanding human cognition and developing innovative training methodologies. We propose a generalizable feature selection and s...

Abstract Salient sounds in the environment automatically capture our attention, causing a shift of focus away from ongoing goal-directed tasks. Studies of cognitive flexibility can employ such paradigms to examine how th...

Abstract Epilepsy is a chronic neurological disease that profoundly impacts patients’ daily lives. Electroencephalography (EEG) serves as a crucial tool for the clinical diagnosis of epilepsy and other brain disorders....

Abstract This study presents an automated systematic review of augmented reality research within educational neuroscience, utilizing PubMedBERT, a domain-specific natural language processing model, to extract and analyze...

BackgroundCaffeine is one of the most frequently administered medicines in neonatology—prescribed for the management of apnoea of prematurity, to aid extubation and increasingly for conditions such as bronchopulmonary ...

Brain–computer interfaces (BCIs) based on motor imagery (MI) provide a transformative direct communication pathway for patients with severe motor disabilities. However, the high inter-subject variability and non-statio...

Abstract Hybrid Brain–Computer Interface (BCI) systems that combine electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) achieve higher classification accuracy but face computational bottlenec...

Abstract Social decision-making involves intricate and dynamic interactions between brains, yet prior hyperscanning research primarily concentrated on investigating the overall patterns of interbrain synchrony (IBS), lea...

Understanding neural responses to varying physical loads is essential for developing ergonomic designs. Conventional methods for analyzing peripheral muscle activity, such as electromyography (EMG) and kinematic analysis...

Abstract Background Mild cognitive impairment (MCI) is an intermediate stage between normal cognitive aging and dementia. People with MCI have a higher risk of developing dementia than normal healthy people. Improving th...

Abstract Background A standardized protocol for electroencephalography (EEG) under standing sedation for the investigation of epilepsy in foals is needed. Hypothesis/Objectives To evaluate a modified standardized EEG pro...

Abstract Background Psychopathic characteristics are associated with an elevated risk for violent behavior and are therefore of interest in research studies. Despite extensive research, the role of emotional and attentio...

"This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computat...

Abstract Background In the neurorehabilitation framework of treadmill-based robot-assisted gait training (t-RAGT), a threefold relationship among physiotherapist (Pht), patient (Pt), and the selected robotic device shoul...

This study presents a novel machine learning approach to assess human well-being through the analysis of brain wave activities. We developed a Random Forest classifier to categorize brain wave patterns into three states ...

Language and action systems are functionally coupled in the brain as demonstrated by converging evidence using Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), transcranial magnetic stimulation...