We report here studies of comparative measures of spectral density and cortical interactions in EEG rhythms in health and schizophrenia. In healthy subjects, all rhythms were symmetrical and synchronous. In "acute" schizophrenia, unlike the situation in health, there was asymmetry (predominantly right-sided) in the distribution of the spectral power of EEG rhythms. In chronic patients, asymmetry was less marked, though the power of most EEG rhythms was significantly lower than in the other two study groups. "Acute" patients showed a lack of interhemisphere interactions for all rhythms apart from the alpha rhythm, while the number of cortical interactions in chronic patients was rather lower than that in the "acute" patients, though there were significantly fewer than in healthy subjects. In addition, the gamma range showed only one interhemisphere association in the posterior areas. These neurophysiological characteristics may underlie a number of the impairments of mental activity in patients with schizophrenia. These data may also indicate that the linkage between power characteristics and synchronization of EEG rhythms is a necessary condition for normal perceptive and cognitive activity and the organization of behavior.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s11055-006-0070-4 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
No significant relationship found between spontaneous motor tempo, heartbeat, and individual alpha frequency: an analysis of internal tempos.
Sci Rep
January 2025
Department of Life Sciences, The University of Tokyo, Tokyo, Japan.
Many theories of time perception propose the existence of an internal pacemaker, and studies across behavioral, physiological, and neuroscience fields have explored this concept. Specifically, Spontaneous Motor Tempo (SMT), the most comfortable and natural tapping tempo for each individual, is thought to reflect this internal pacemaker's tempo. Changes in heart rate are also linked to time estimation, while Individual Alpha Frequency (IAF), the peak in the alpha range (8-13 Hz) observed in EEG, is reported to reflect the brain's temporal processing.
View Article and Find Full Text PDFWorking-memory load decoding model inspired by brain cognition based on cross-frequency coupling.
Brain Res Bull
January 2025
School of Life and Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Institute for Advanced Sciences, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Guangyang Bay Laboratory, Chongqing Institute for Brain and Intelligence, Chongqing 400064, China. Electronic address:
Working memory, a fundamental cognitive function of the brain, necessitates the evaluation of cognitive load intensity due to limited cognitive resources. Optimizing cognitive load can enhance task performance efficiency by preventing resource waste and overload. Therefore, identifying working memory load is an essential area of research.
View Article and Find Full Text PDFSpontaneous oxycodone withdrawal disrupts sleep, diurnal, and electrophysiological dynamics in rats.
PLoS One
January 2025
Dept. of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts, United States of America.
Opioid dependence is defined by an aversive withdrawal syndrome upon drug cessation that can motivate continued drug-taking, development of opioid use disorder, and precipitate relapse. An understudied but common opioid withdrawal symptom is disrupted sleep, reported as both insomnia and daytime sleepiness. Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions.
View Article and Find Full Text PDFPrecision data-driven modeling of cortical dynamics reveals person-specific mechanisms underpinning brain electrophysiology.
Proc Natl Acad Sci U S A
January 2025
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130.
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 PDFThe role of beta band phase resetting in audio-visual temporal order judgment.
Cogn Neurodyn
December 2025
Department of Psychology, Graduate School of Humanities, Kobe University, 1-1 Rokkodai- cho, Nada, Kobe, 657-8501 Japan.
Unlabelled: The integration of auditory and visual stimuli is essential for effective language processing and social perception. The present study aimed to elucidate the mechanisms underlying audio-visual (A-V) integration by investigating the temporal dynamics of multisensory regions in the human brain. Specifically, we evaluated inter-trial coherence (ITC), a neural index indicative of phase resetting, through scalp electroencephalography (EEG) while participants performed a temporal-order judgment task that involved auditory (beep, A) and visual (flash, V) stimuli.
View Article and Find Full Text PDFWant 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!