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Schizophrenia (SZ) is a complex neuropsychiatric disorder characterized by heterogeneous symptoms, relatively poor clinical outcome, and widespread disruptions in neural connectivity and oscillatory dynamics. This article attempts to review current evidence linking genomic and proteomic alterations with aberrant neural oscillations observed in SZ, including aberrations in all oscillatory frequency bands obtained via human EEG. The numerous genes discussed are mainly involved in modulating synaptic transmission, synaptic function, interneuron excitability, and excitation/inhibition balance, thereby influencing the generation and synchronization of neural oscillations at specific frequency bands (e.g., gamma frequency band) critical for different cognitive, emotional, and perceptual processes in humans. The review highlights how polygenic influences and gene-circuit interactions underlie the neural oscillatory and connectivity abnormalities central to SZ pathophysiology, providing a framework for future research on common genetic-neural function interactions and on potential therapeutic interventions targeting local and global network-level neural dysfunction in SZ patients. As will be discussed, many of these genes affecting neural oscillations in SZ also affect other neurological disorders, ranging from autism to epilepsy. In time, it is hoped that future research will show why the same genetic anomaly leads to one illness in one person and to another illness in a different person.
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http://dx.doi.org/10.3390/ijms26157514 | DOI Listing |
J Neurophysiol
September 2025
Graduate School of Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda, Nagano 3868567, Japan.
This study investigated the correlation between the strength of correlated effective neural drive (END) to the antagonistic muscles and the fluctuations in neural/electrical and mechanical output around the joint during steady co-contraction, and whether the correlated END strength estimated from conventional surface EMG is correlated with that determined from motor unit (MU) discharges. Fourteen young male participants performed isometric steady co-contractions with their medial gastrocnemius and tibialis anterior muscles at 10% of maximal EMG while sitting. Correlated END strength was quantified as the maximum value of the cross-correlation function between the conventional surface EMG signals and between MU discharges decomposed from high-density surface EMG of each muscle.
View Article and Find Full Text PDFJ Neurophysiol
September 2025
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01307 Dresden, Germany.
Cognitive control - the ability to regulate information processing in line with current goals - is essential for cognitive functioning. We examined whether uncertainty in cognitive control demands leads to higher processing of cues that reduce uncertainty. Participants completed a Go/NoGo task with two NoGo:Go ratios (4:5 and 1:6).
View Article and Find Full Text PDFJ Pain Res
September 2025
Radiology Department, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China.
Purpose: Previous studies have revealed alterations of the functional connectivity of the brain networks in ankylosing spondylitis (AS). Fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) are both voxel-based functional metrics capable of estimating local spontaneous neural activities. This study aimed to investigate the local spontaneous neural activities in AS patients by utilizing the analytical approaches of fALFF and ReHo.
View Article and Find Full Text PDFDev Sci
November 2025
Department of Psychology and Neuroscience, University of St Andrews, St Andrews, UK.
Cognitive control shows two main developmental trends: greater self-directedness (i.e., children need less external scaffolding) and greater proactiveness (i.
View Article and Find Full Text PDFBrain Stimul
September 2025
Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom. Electronic address:
Background: Precisely timed brain stimulation, such as phase-locked deep brain stimulation (PLDBS), offers a promising approach to modulating dysfunctional neural networks by enhancing or suppressing specific oscillations. However, its clinical application has been hindered by the lack of user-friendly systems and the challenge of real-time phase estimation amid stimulation artifacts.
Material And Method: In this work, we developed a clinically translatable PLDBS framework that enables real-time, cycle-by-cycle stimulation using standard amplifiers and a computer-in-the-loop system.