Correlation between electroencephalographic markers in the healthy brain.

Sci Rep

Department of Health Technologies, School of Information Technology, Tallinn University of Technology, 5 Ehitajate Rd, 19086, Tallinn, Estonia.

Published: April 2023

Mental disorders have an increasing tendency and represent the main burden of disease to society today. A wide variety of electroencephalographic (EEG) markers have been successfully used to assess different symptoms of mental disorders. Different EEG markers have demonstrated similar classification accuracy, raising a question of their independence. The current study is aimed to investigate the hypotheses that different EEG markers reveal partly the same EEG features reflecting brain functioning and therefore provide overlapping information. The assessment of the correlations between EEG signal frequency band power, dynamics, and functional connectivity markers demonstrates that a statistically significant correlation is evident in 37 of 66 (56%) comparisons performed between 12 markers of different natures. A significant correlation between the majority of the markers supports the similarity of information in the markers. The results of the performed study confirm the hypotheses that different EEG markers reflect partly the same features in brain functioning. Higuchi's fractal dimension has demonstrated a significant correlation with the 82% of other markers and is suggested to reveal a wide spectrum of various brain disorders. This marker is preferable in the early detection of symptoms of mental disorders.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113388PMC
http://dx.doi.org/10.1038/s41598-023-33364-zDOI Listing

Publication Analysis

Top Keywords

eeg markers
16
mental disorders
12
markers
10
symptoms mental
8
hypotheses eeg
8
brain functioning
8
eeg
6
correlation
4
correlation electroencephalographic
4
electroencephalographic markers
4

Similar Publications

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions.

View Article and Find Full Text PDF

Complex auditory regularity processing across levels of consciousness in coma: Stage 1 Registered Report.

Brain Commun

December 2024

Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.

A key question for the scientific study of consciousness is whether it is possible to identify specific features in brain activity that are uniquely linked to conscious experience. This question has important implications for the development of markers to detect covert consciousness in unresponsive patients. In this regard, many studies have focused on investigating the neural response to complex auditory regularities.

View Article and Find Full Text PDF

Diagnosing Alzheimer's disease (AD) through pathological markers is typically costly and invasive. This study aims to find a noninvasive, cost-effective method using portable electroencephalography (EEG) to detect changes in AD-related biomarkers in cerebrospinal fluid (CSF). A total of 102 patients, both with and without AD-related biomarker changes (amyloid beta and phosphorylated tau), were recorded using a 2-minute resting-state portable EEG.

View Article and Find Full Text PDF

Cognitive control deficits and increased intra-subject variability have been well established as core characteristics of attention deficit hyperactivity disorder (ADHD), and there is a growing interest in their expression at the neural level. We aimed to study neural variability in ADHD, as reflected in theta inter-trial phase coherence (ITC) during error processing, a process that involves cognitive control. We examined both traditional event-related potential (ERP) measures of error processing (i.

View Article and Find Full Text PDF

Background: Repeat neurological assessment is standard in cases of severe acute brain injury. However, conventional measures rely on overt behavior. Unfortunately, behavioral responses may be difficult or impossible for some patients.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!