A5045993645- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Complex Systems and Time Series Analysis
- Neuroscience and Neural Engineering
- Optical Imaging and Spectroscopy Techniques
- Heart Rate Variability and Autonomic Control
- Advanced Memory and Neural Computing
- Muscle activation and electromyography studies
- Transcranial Magnetic Stimulation Studies
- Fractal and DNA sequence analysis
- Gaze Tracking and Assistive Technology
- Nonlinear Dynamics and Pattern Formation
- Spaceflight effects on biology
- Conducting polymers and applications
- Climate Change and Health Impacts
- Traumatic Brain Injury and Neurovascular Disturbances
- Healthcare Technology and Patient Monitoring
- Thermoregulation and physiological responses
- Cardiovascular Health and Risk Factors
- Health, Environment, Cognitive Aging
- Electrochemical Analysis and Applications
The University of Texas at Austin
2022-2025
Semmelweis University
2017-2024
Subject training is crucial for acquiring brain-computer interface (BCI) control. Typically, this requires collecting user-specific calibration data due to high inter-subject neural variability that limits the usability of generic decoders. However, cumbersome and may produce inadequate building decoders, especially with naïve subjects. Here, we show a decoder trained on single expert readily transferrable inexperienced users via domain adaptation techniques allowing calibration-free BCI...
In this study, functional near-infrared spectroscopy (fNIRS) and the graph theory approach were used to access connectivity (FC) of prefrontal cortex (PFC) in a resting state during increased mental workload.For very purpose, pattern recognition-based test was developed, which elicited strong response throughout PFC condition.FC parameters obtained stimulation found compared those after correlation based signal improvement (CBSI), can attenuate components fNIRS signals are unrelated neural...
Dynamic functional connectivity (DFC) was established in the past decade as a potent approach to reveal non-trivial, time-varying properties of neural interactions – such their multifractality or information content –, that otherwise remain hidden from conventional static methods. Several neuropsychiatric disorders were shown be associated with altered DFC, schizophrenia (SZ) being one most intensely studied among conditions. Here we analyzed resting-state electroencephalography recordings...
Abstract Impaired cerebrovascular function contributes to the genesis of age‐related cognitive decline. In this study, hypothesis is tested that impairments in neurovascular coupling (NVC) responses and brain network predict dysfunction older adults. Cerebromicrovascular working memory healthy young ( n = 21, 33.2±7.0 years) aged 30, 75.9±6.9 participants are assessed. To determine NVC functional connectivity (FC) during a (n‐back) paradigm, oxy‐ deoxyhemoglobin concentration changes from...
Abstract Objective. A motor imagery (MI)-based brain-computer interface (BCI) enables users to engage with external environments by capturing and decoding electroencephalography (EEG) signals associated the imagined movement of specific limbs. Despite significant advancements in BCI technologies over past 40 years, a notable challenge remains: many lack proficiency, unable produce sufficiently distinct reliable MI brain patterns, hence leading low classification rates their BCIs. The...
Abstract Introduction Alterations in narrow‐band spectral power of electroencephalography (EEG) recordings are commonly reported patients with schizophrenia (SZ). It is well established however that electrophysiological signals comprise a broadband scale‐free (or fractal) component generated by mechanisms different from those producing oscillatory neural activity. Despite this known feature, it has not yet been investigated if abnormalities found SZ could be attributed to or brain function....
Assessing the functional connectivity (FC) of brain has proven valuable in enhancing our understanding function. Recent developments field demonstrated that FC fluctuates even resting state, which not been taken into account by widely applied static approaches introduced earlier. In a recent study using near-infrared spectroscopy (fNIRS) global dynamic (DFC) also found to fluctuate according scale-free i.e., fractal dynamics evidencing true multifractal (MF) nature DFC human prefrontal...
Abstract Sleep deprivation (SD) is known to be associated with decreased cognitive performance; however, the underlying mechanisms are poorly understood. As interactions between distinct brain regions depend on mental state, functional networks established by these connections typically show a reorganization during task. Hence, analysis of connectivity (FC) could reveal task‐related change in examined frontal networks. Our objective was assess impact SD static FC prefrontal and motor...
Abstract Analysis of brain functional connectivity (FC) could provide insight in how and why cognitive functions decline even healthy aging (HA). Despite FC being established as fluctuating over time the resting state (RS), dynamic (DFC) studies involving elderly individuals assessing these patterns relate to performance are yet scarce. In our recent study we showed that fractal temporal scaling connections RS is not only reduced HA, but also predicts increased response latency task solving...
Riemannian geometry-based classification (RGBC) gained popularity in the field of brain-computer interfaces (BCIs) lately, due to its ability deal with non-stationarities arising electroencephalography (EEG) data. Domain adaptation, however, is most often performed on sample covariance matrices (SCMs) obtained from EEG data, and thus might not fully account for components affecting estimation itself, such as regional trends. Detrended cross-correlation analysis (DCCA) can be utilized...
Brain function is organized as a network of functional connections between different neuronal populations with connection strengths dynamically changing in time and space. Studies investigating connectivity (FC) usually follow static approach when describing FC by considering the constant, however dynamic seems more reasonable, this way spatio-temporal dynamics underlying system can also be captured. Objective: The scale-free, i.e. fractal nature neural an inherent property nervous system....
Abstract Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations global functional network topology and those individual connections between regions expressed multifractal scaling. To expand on these findings, this study we investigated if multifractality was indeed an inherent property dynamic (DFC) regional level as well. Furthermore, explored local DFC showed region-specific differences its entropy-related features....
Fluctuations in resting-state cerebral hemodynamics show scale-free behavior over two distinct scaling ranges. Changes such bimodal (multi)fractal pattern give insight to altered cerebrovascular or neural function. Our main goal was assess the distribution of local properties characterizing and disentangle influence aging on these multifractal parameters. To this end, we obtained extended records (N=214) oxyhemoglobin (HbO), deoxyhemoglobin (HbR) total hemoglobin (HbT) concentration time...
Abstract Injuries affecting the central nervous system may disrupt neural pathways to muscles causing motor deficits. Yet brain exhibits sensorimotor rhythms (SMRs) during movement intents, and brain-computer interfaces (BCIs) can decode SMRs control assistive devices promote functional recovery. However, non-invasive BCIs suffer from instability of SMRs, requiring longitudinal training for users learn proper SMR modulation. Here, we accelerate this skill learning process by applying...
Abstract Objective. A motor imagery (MI)-based brain-computer interface (BCI) enables users to engage with external environments by capturing and decoding electroencephalography (EEG) signals associated the imagined movement of specific limbs. Despite significant advancements in BCI technologies over past 40 years, a notable challenge remains: many lack proficiency, unable produce sufficiently distinct reliable MI brain patterns, hence leading low classification rates their BCIs. The...
Abstract Altered neural excitation/inhibition (E/I) balance has long been suspected as a potential underlying cause for clinical symptoms in schizophrenia (SZ). Recent methodological advancements linking the spectral slope ( β ) of neurophysiological recordings – such them electroencephalogram (EEG) to E/I ratio provided much-needed tools better understand this plausible relationship. Importantly, most approaches treat stationary feature single scaling range. On other hand, previous research...
Assessing power-law cross-correlations between a pair - or among set of processes is great significance in diverse fields analyses ranging from neuroscience to financial markets. In most cases such are computationally expensive and thus carried out offline once the entire signal obtained. However, many applications as mental state monitoring forecasting call for fast algorithms capable estimating scale-free coupling real time. Detrended cross-correlation analysis (DCCA), generalization...
Abstract Aging affects cognitive functions even in the absence of ongoing pathologies. The neurophysiological basis age-related decline (CD), however, is not completely understood. Alterations both functional brain connectivity and fractal scaling neuronal dynamics have been linked to aging performance. Recently, (FrC) has proposed — combining two concepts for capturing long-term interactions among regions. FrC was shown be influenced by increased mental workload; no prior studies...
Investigating how the brain adapts to increased mental workload through large-scale functional reorganization appears as an important research question. Functional connectivity (FC) aims at capturing disparate regions of dynamically interact, while graph theory provides tools for topological characterization reconstructed networks. Although numerous studies investigated FC is altered in response working memory (WM) demand, current results are still contradictory few confirmed robustness...
While most connectivity studies investigate functional (FC) in a scale-dependent manner, coupled neural processes may also exhibit broadband dynamics, manifesting as power-law scaling of their measures interdependence. Here we introduce the bivariate focus-based multifractal (BFMF) analysis robust tool for capturing such scale-free relations and use resting-state electroencephalography (EEG) recordings 12 subjects to demonstrate its performance reconstructing physiological networks. BFMF was...
Background. Aging is a major risk factor for range of chronic diseases. Oxidative stress theory aging has been previously proposed as one the mechanisms responsible age-related decline in organ/tissue function and development Urine contains rich biological information on health status every organ system can be an important noninvasive source biomarkers systemic oxidative aging. Aims. The objective this cross-sectional study was to validate novel panel urinary biomarkers. Methods. Nucleic...
Dopaminergic treatment (DT), the standard therapy for Parkinson's disease (PD), alters dynamics of functional brain networks at specific time scales. Here, we explore scale-free connectivity (FC) in PD population and how it is affected by DT. We analyzed electroencephalogram of: (i) 15 patients during DT (ON) after washout (OFF) (ii) 16 healthy control individuals (HC). estimated FC using bivariate focus-based multifractal analysis, which evaluated long-term memory (H(2)) strength (ΔH15)...
The human brain consists of anatomically distant neuronal assemblies that are interconnected via a myriad synapses. This anatomical network provides the neurophysiological wiring framework for functional connectivity (FC), which is essential higher-order functions. While several studies have explored scale-specific FC, scale-free (i.e., multifractal) aspect remains largely neglected. Here we examined reorganization during visual pattern recognition paradigm, using bivariate focus-based...
Abstract Confluent recent evidence indicates that the spectral slope of 1 /f neurophysiological recordings is correspondent to cortical excitation/inhibition (E/I) ratio. In this framework, a steeper power spectrum (i.e., one with larger exponent β ) indicative stronger inhibitory tone and thus lower E/I ratio, vice versa. While tools commonly utilized for estimating are mostly consistent, there appears be lack standardization among data processing protocols analysis. work our goal draw...