Search academic resources

RESUMO O uso do eletroencefalograma - EEG, com abordagem quantitativa, tem servido ao propósito de compreender o funcionamento do cérebro durante tarefas linguísticas. Há estudos que discutem o papel das frequências...

Preschool children show neural responses and make behavioral adjustments immediately following an error. However, there is a lack of evidence regarding how neural responses to error predict subsequent behavioral adjustme...

"The Electroencephalography (EEG) is not just a mere clinical tool anymore. It has become the de-facto mobile, portable, non-invasive brain imaging sensor to harness brain information in real time. It is now being used t...

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 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...

The estimation of the instant location and strength of sources takes a considerable importance for many areas of sensor space-array processing, e.g., brain activity in non-invasive electro-medicine. State-space models a...

Electroencephalography (EEG) and magnetoencephalography (MEG) are the only two methods to study the functional organization of the brain with a temporal resolution close to 1 ms. This unique feature seems to be useful to...

The framework of this project is the so-called brain topography. The main purpose of brain topography is to map the internal structure of the brain and to localize areas of certain function or dysfunction using non-invas...

"The use of Brain-Computer Interfaces can provide substantial improvements to the quality of life of patients with diseases such as severe Amyotrophic lateral sclerosis that cause Locked-in syndrome, by creating new aven...

Reading fluency depends on rapid integration of print and speech, yet the spatiotemporal mechanisms supporting this integration in school aged children remain poorly understood. This study combined fMRI and EEG to examin...

The electroencephalogram (EEG) is an electrophysiological monitoring method that allows us to glimpse the electrical activity of the brain. Neural oscillations patterns are perhaps the best salient feature of EEG as they...

We present a methodological framework for evaluating temporal sensitivity in frontal EEG recordings during cycling. The approach departs from randomized train–test splits and instead implements contiguous temporal with...

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...

The training in neurofeedback (NF) consists of teaching individuals to modify, adjust and enhance their brain activity pattern. The aim of our research was to evaluate the effect of training on cognitive processes, speci...

Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...

Abstract The current work on emotion recognition considering EEG signals has attracted significant attention due to its advantages in fields like mental health, neural computing, and human-computer interaction. Nonethele...

Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

Abstract Objectives To explore the efficacy and potential neurophysiological mechanisms of 77.5 Hz transcranial alternating current stimulation (tACS) in the treatment of female adolescent non-suicidal self-injury (NSSI...

Abstract Background Chronic Insomnia Disorder (CID) is a prevalent condition. This study examines microbaric oxygen therapy (MOT) as a non-pharmacological intervention for CID patients, utilizing EEG to investigate its e...

Stress can affect both physical and mental health, and it is important to support faster intervention. EEG can record brain activity directly, but EEG signals are complex, noisy, and difficult to handle. This study explo...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

Sleep plays an important role in physical health, cognition, and emotional well-being. Since sleep disorders can affect all these aspects, accurately detecting sleep stages is key to proper diagnosis and monitoring. Auto...

Purpose: This study aims to describe the total EEG energy during episodes of intracranial hy- pertension (IH) and evaluate its potential as a classification feature for IH. New methods: We computed the sample correlation...