The aim of the study was to reveal longitudinal changes in electroencephalogram spectral power and frequency (percentage frequency composition of EEG and alpha peak frequency) patterns in normal children from northern Russia. Fifteen children (9 girls and 6 boys) participated in the study. The resting state (eyes closed) EEGs were recorded yearly (2005-2013) from age 8 to age 16-17 for each child. EEG frequency patterns were estimated as the percentages of waves with a 1 Hz step revealed by measuring the interval durations between points crossing zero (isoline) by a curve. EEG spectral power changes were analyzed for delta (1.5-4 Hz), theta (4-7.5 Hz), alpha-1 (7.5-9.5 Hz), alpha-2 (9.5-12.5 Hz), beta-1 (12.5-18 Hz) and beta-2 (18-30 Hz) bands. According to the frequency composition of the EEG signals fast synchronous, polymorphous synchronous, polymorphous desynchronous and slow synchronous types of children EEG were revealed. These EEG types were relatively stable during adolescence. In these EEG types, the frequency patterns and spectral power dynamics with age had several common and specific features. Slow wave percentage and spectral power in the delta band remarkably decreased with age in all groups. Starting from the theta band the EEG types were characterized by different EEG spectral power changes with age. In fast synchronous EEG type, the theta and alpha-1 EEG power decreased, and the alpha-2 power increased in the occipital and parietal areas. The polymorphous synchronous type was characterized by increased both the alpha-1 and alpha-2 power with regional peculiarities. In the polymorphous desynchronous type spectral power in all bands decreased with age, and in the slow synchronous type, the alpha-1 power massively increased with age. Obtained results suggest predictive strength of the spatial-frequency patterns in EEG for its following maturation through the years.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.ijdevneu.2014.08.012 | DOI Listing |
Front Psychiatry
January 2025
Feneryolu Medical Center, Üsküdar University, Istanbul, Türkiye.
Introduction: Major Depressive Disorder (MDD) leads to dysfunction and impairment in neurological structures and cognitive functions. Despite extensive research, the pathophysiological mechanisms and effects of MDD on the brain remain unclear. This study aims to assess the impact of MDD on brain activity using EEG power spectral analysis and asymmetry metrics.
View Article and Find Full Text PDFSpectral analysis is a widely used method for monitoring photosynthetic capacity. However, vegetation indices-based linear regression exhibits insufficient utilization of spectral information, while full spectra-based traditional machine learning has limited representational capacity (partial least squares regression) or uninterpretable (convolution). In this study, we proposed a deep learning model with enhanced interpretability based on attention and vegetation indices calculation for global spectral feature mining to accurately estimate photosynthetic capacity.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Department of Neurology Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, 1105AZ, NETHERLANDS.
Local field potential (LFP) recordings using chronically implanted sensing-enabled stimulators are a powerful tool for indexing symptom presence and severity in neurological and neuropsychiatric disorders, and for enhancing our neurophysiological understanding of brain processes. LFPs have gained interest as input signals for closed-loop deep brain stimulation (DBS) and can be used to inform DBS parameter selection. LFP recordings using chronically implanted sensing-enabled stimulators have various implementational challenges.
View Article and Find Full Text PDFStruct Dyn
January 2025
Department of Physics, University of Wisconsin-Milwaukee, 3135 N. Maryland Ave, Milwaukee, Wisconsin 53211, USA.
There is a growing understanding of the structural dynamics of biological molecules fueled by x-ray crystallography experiments. Time-resolved serial femtosecond crystallography (TR-SFX) with x-ray Free Electron Lasers allows the measurement of ultrafast structural changes in proteins. Nevertheless, this technique comes with some limitations.
View Article and Find Full Text PDFThe competition for resources is a defining feature of microbial communities. In many contexts, from soils to host-associated communities, highly diverse microbes are organized into metabolic groups or guilds with similar resource preferences. The resource preferences of individual taxa that give rise to these guilds are critical for understanding fluxes of resources through the community and the structure of diversity in the system.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!