The scope of human consciousness includes states departing from what most of us experience as ordinary wakefulness. These altered states of consciousness constitute a prime opportunity to study how global changes in brain activity relate to different...
Objective: To describe a novel measure of EEG signal variability that distinguishes cognitive brain states. Method: We describe a novel characterization of amplitude variability in the EEG signal termed “High Variability Periods” or &ldqu...
Transcranial magnetic stimulation (TMS) enables non-invasive, focal modulation of cortical circuits by inducing electric currents in the brain through electromagnetic induction, thereby influencing neuronal excitability and synaptic plasticity. High...
The aim of this work is to find a good mathematical model for the classification of brain states during visual perception with a focus on the interpretability of the results. To achieve it, we use the deep learning models with different activation fu...
Estimation of human emotions plays an important role in the development of modern brain-computer interface devices like the Emotiv EPOC+ headset. In this paper, we present an experiment to assess the classification accuracy of the emotional states pr...
The effects of Transcranial Magnetic Stimulation (TMS) depend on stimulation parameters such as intensity, location, frequency, and duration. In clinical practice, these parameters are often adapted from studies carried out in healthy individuals. Ho...
The self has been proposed to be grounded in interoceptive processing, with heartbeat-evoked cortical activity as a neurophysiological marker of this processing. However, inconsistent findings have been reported on the relationship between heartbeat-...
Post-stroke epilepsy (PSE) is one of the most common long-term neurological complications of stroke and represents a major contributor to disability, reduced quality of life, and increased healthcare burden. Although numerous risk factors and biomark...
Probiotics can alter brain function via the gut–brain axis. We investigated the effect of a probiotic mixture containing Bifidobacterium longum, Lactobacillus helveticus and Lactiplantibacillus plantarum. In a randomized, placebo-controlled, do...
In this study, we investigated the feasibility of using electroencephalogram (EEG) signals to differentiate between four distinct subject-driven cognitive states: resting state, narrative memory, music, and subtraction tasks. EEG data were collected...
Background: Monitoring and evaluating dynamic changes in brain states during electroencephalography (EEG) neurofeedback training (NFT) for post-traumatic stress disorder (PTSD) patients remains challenging when using traditional methods. Method: This...
This study develops a predictive model to assess the impacts of urban water blue visual index (BVI) and flow velocity on human brain states using EEG and HRV data in virtual reality simulations. By integrating Gaussian process regression (GPR) and ar...
Previous research has shown that resting-state functional connectivity (rsFC) between different brain regions (seeds) is related to motor learning and motor memory consolidation. Using high-density electroencephalography (hdEEG), we addressed this qu...
Substantial developments have been established in the past few years for enhancing the performance of brain–computer interface (BCI) based on steady-state visual evoked potential (SSVEP). The past SSVEP-BCI studies utilized different target fre...
Three-dimensional constructive interference in steady state (3D CISS) is a steady-state gradient-echo sequence in magnetic resonance imaging (MRI) that has been used in an increasing number of applications in the study of brain disease in recent year...
Background: Mild traumatic brain injury (mTBI) is frequently followed by persistent cognitive, affective, and sensory complaints despite unremarkable conventional structural imaging. Resting-state functional MRI (rs-fMRI) has been increasingly employ...
Major depressive disorder (MDD) represents a heterogeneous condition lacking reliable neurobiological biomarkers and a mechanistic understanding. Time-resolved characterization of brain dynamics reveals that mental health is associated with a charact...
In glioblastoma (GBM), brain tumor stem cells (BTSCs) encompass heterogenous populations of multipotent, self-renewing, and tumorigenic cells, which have been proposed to be at the root of therapeutic resistance and recurrence. While the functional s...
In this brief overview paper, we analyse information flow in the brain. Although Shannon’s information concept, in its pure algebraic form, has made a number of valuable contributions to neuroscience, information dynamics within the brain is not full...
Brain–computer interface (BCI) systems aim to establish direct communication pathways between neural activity and external devices, enabling interaction without relying on conventional neuromuscular mechanisms. This study investigates the feasi...
The absence of clinically objective methods to evaluate adenomyosis-associated pain and the poor understanding of its pathophysiology lead to treatment limitations. We conducted a resting-state functional magnetic resonance imaging study with 49 pati...
Parkinson’s disease (PD) may benefit from non-pharmacological motor–cognitive rehabilitation, but sensitive neuroimaging markers of training-related brain changes remain limited. This study investigated whether 4 weeks of daily Quadrato M...
During the operation of Unmanned Aerial Vehicles (UAVs), the cognitive state of operators is prone to decline, posing a risk to task performance. However, many existing cognitive state assessment methods rely directly on raw electroencephalography (E...
As a spatial selective attention-based brain-computer interface (BCI) paradigm, steady-state visual evoked potential (SSVEP) BCI has the advantages of high information transfer rate, high tolerance to artifacts, and robust performance across users. H...
Background/Objectives: Congenital heart disease (CHD) is associated with altered brain development and an increased risk of neurodevelopmental difficulties, particularly in more severe forms of the condition. Although alterations in functional brain...
Chronic pain is a dynamic, brain-wide condition that eludes effective management by conventional, static treatment approaches. Transcutaneous Electrical Nerve Stimulation (TENS), traditionally perceived as a simple and generic modality, is on the ver...
In this paper, a bibliometric review is conducted on brain–computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An explo...
The topology of spiking neural networks (SNNs) plays an important role in determining their dynamic representation ability, recognition performance, and biological interpretability in speech recognition. However, most existing SNN reservoirs are cons...
Brain state varies from moment to moment. While brain state can be defined by ongoing neuronal population activity, such as neuronal oscillations, this is tightly coupled with certain behavioural or vigilant states. In recent decades, abnormalities i...
In this paper, we present a method to quantify the coupling between brain regions under vigilance and enhanced mental states by utilizing partial directed coherence (PDC) and graph theory analysis (GTA). The vigilance state is induced using a modifie...
Motion-based visual evoked potentials (mVEP) is a new emerging trend in the field of steady-state visual evoked potentials (SSVEP)-based brain–computer interfaces (BCI). In this paper, we introduce different movement-based stimulus patterns (st...
Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has...
The wearable electroencephalogram (EEG) dry electrode acquisition system has shown great application prospects in mental state monitoring, the brain–computer interface (BCI), and other fields due to advantages such as being small in volume, lig...
Brain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) m...
In the human body, the central regulatory system of homeostasis is maintained by the brain. Its complexity is mesmerizing and many of its functions are largely uncharted. Unfortunately, its functionality is often impaired through neoplastic growths,...
Traumatic brain injury (TBI) is one of the common injuries when the human head receives an impact due to an accident or fall and is one of the most frequently submitted insurance claims. However, it is often always misused when individuals attempt an...
With the recent development of low-cost wearable electroencephalogram (EEG) recording systems, passive brain–computer interface (pBCI) applications are being actively studied for a variety of application areas, such as education, entertainment,...
Brain–computer interfaces (BCIs) are widely utilized in control applications for people with severe physical disabilities. Several researchers have aimed to develop practical brain-controlled wheelchairs. An existing electroencephalogram (EEG)-...
Traumatic brain injury (TBI), a leading cause of mortality and disability, recognizes a primary, immediate injury due to external forces, and a secondary phase that includes inflammation that can lead to complications such as the post-traumatic confu...
Accurate and generalizable classification of brain states is essential for understanding their neural underpinnings and improving clinical diagnostics. Traditionally, functional connectivity patterns and graph-theoretic metrics have been utilized. Ho...
Background: The relationship between axial symptoms in Parkinson’s disease (PD) and subthalamic deep brain stimulation (STN-DBS) is still unclear. Purpose: We searched for particular clinical characteristics before STN-DBS linked to on-state ax...
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Most current research on Alzheimer’s disease (AD) is based on transverse measurements. Given the nature of neurodegeneration in AD progression, observing longitudinal changes in the structural features of brain networks over time may improve th...
Canonical correlation analysis (CCA) has been used for the steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) for a long time. However, the reference signal of CCA is relatively simple and lacks subject-specific informa...
Brain tumors, both malignant and non-malignant, represent a persistent global health challenge. Differences in diagnosis, treatment, and outcomes are influenced by race, ethnicity, socioeconomic status (SES), and geographical location. Brain and cent...
Amyotrophic lateral sclerosis (ALS) causes people to have difficulty communicating with others or devices. In this paper, multi-task learning with denoising and classification tasks is used to develop a robust steady-state visual evoked potential-bas...
Brain–computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEPs) have been well researched due to their easy system configuration, little or no user training and high information transfer rates. To elicit an SSVEP, a r...
The steady-state visual evoked potential (SSVEP), measured by the electroencephalograph (EEG), has high rates of information transfer and signal-to-noise ratio, and has been used to construct brain–computer interface (BCI) spellers. In BCI spellers,...
Background/Objectives: With the globalization of companies, the cross-cultural adjustment of expatriates working overseas is becoming an increasingly important topic. However, little research has been carried out on the brain, which is the source of...
Brain–computer interfaces (BCIs) enable people to communicate with others or devices, and improving BCI performance is essential for developing real-life applications. In this study, a steady-state visual evoked potential-based BCI (SSVEP-based...
The goal of this study was to develop and validate a hybrid brain-computer interface (BCI) system for home automation control. Over the past decade, BCIs represent a promising possibility in the field of medical (e.g., neuronal rehabilitation), educa...
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