Distinct Mechanisms of Multiple Alpha‐Band Activities in Frontal Regions Following an 8‐Week Medium‐ (Yoga) and High‐Intensity (Pamela) Exercise Intervention

CNS Neuroscience & Therapeutics, Год журнала: 2025, Номер 31(5)

Опубликована: Май 1, 2025

ABSTRACT Aim Long‐term moderate‐ to high‐intensity exercise has been shown significantly enhance overall health such as the improvement of physiological indicators and brain functions. One key aspect activity is alpha‐band activity, which encompasses various sub‐oscillations within alpha frequency band. However, precise functions these following different regimens remain unclear. Methods We recruited 58 healthy college students divided them into four groups: Pamela (high‐intensity interval training, HIIT), yoga (moderate‐intensity continuous MICT), their corresponding matched control group (no exercise) for each intervention group. Participants in groups underwent training up 8 weeks (HIIT or MICT). Resting‐state EEG data were collected before after both with eyes open closed. Results Following HIIT, experienced a significant reduction body fat percentage notable increase skeletal muscle mass. In terms neural main difference was observed mid‐frequency range frontoparietal region during eyes‐open resting state. Conversely, 8‐week participants demonstrated duration maintaining balance sleep quality, reflected low‐ high‐frequency band activities bilateral frontotemporal regions eyes‐closed Conclusion This study, first time, differentiates effects long‐term on oscillation states, highlights that sub‐frequency bands would represent exercise‐related

Язык: Английский

Aging amplifies sex differences in low alpha and low beta EEG oscillations

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 1, 2024

Abstract Biological sex profoundly shapes brain function, yet its precise influence on neural oscillations was poorly understood. Despite decades of research, studies investigating sex-based variations in electroencephalographic (EEG) signals have yielded inconsistent findings that obstructs what may be a potentially crucial source inter-individual variability function. To address this, we analyzed five publicly available resting-state datasets, comprising EEG data (n=445) and iEEG (n=103). Our results revealed striking age-dependent differences: older adults (30-80 years) exhibited robust differences, with males showing heightened low alpha (8-9 Hz) activity temporal regions attenuated beta (16-20 parietal-occipital areas compared to females. Intriguingly, these sex-specific patterns were absent younger (20-30 years), suggesting complex interplay between aging shaping dynamics. Furthermore, identified consistent sex-related the precentral gyrus scalp EEG, driving observed differences. This multi-level analysis allowed us bridge gap cortical scalp- level observations, providing more comprehensive picture further investigate functional implications oscillatory conducted correlation analyses uncover significant associations several lifestyle factors (behavioral anthropometric measures) adults. investigation demonstrates sex, age, oscillations, revealing And our highlight importance careful demographic consideration research design ensure fairness capturing full spectrum neurophysiological diversity. Significance statement The biological age had been long- standing, unresolved question largely unaddressed due limited sample sizes simplistic matching. study leverages large-scale, open datasets tackle this issue, analyzing hundreds participants across datasets. demonstrate substantial sex- based differences even baselines, particularly bands, uncovering activity. By connecting age-related potential circuit mechanisms factors, experimental accurately capture rich lifespan.

Язык: Английский

Monitoring Sleep Quality Through Low α-Band Activity in the Prefrontal Cortex Using a Portable Electroencephalogram Device: Longitudinal Study (Preprint)

Опубликована: Окт. 4, 2024

The pursuit of sleep quality has become an important aspect people’s global quest for overall health. However, the objective neurobiological features corresponding to subjective perceptions remain poorly understood. Although previous studies have investigated relationship between electroencephalogram (EEG) and sleep, lack longitudinal follow-up raises doubts about reproducibility their findings. Currently, there is a gap in research regarding stable associations EEG data assessed through multiple collection sessions, which could help identify potential targets related quality. In this study, we used portable device collect resting-state prefrontal cortex over 3-month period from 42 participants (27 first month, 25 second 40 third month). Each participants’ was using Pittsburgh Sleep Quality Index (PSQI) estimate recent We found that significant consistent positive correlation low α band activity PSQI scores (<i>r</i>=0.45, <i>P</i>&lt;.001). More importantly, remained across all recordings (<i>P</i>&lt;.05), regardless whether considered same cohort or expanded sample size. Furthermore, discovered periodic component primarily contributed association with PSQI. These findings represent identification reliable target sessions. Our results provide solid foundation future applications devices monitoring screening disorders broad population.

Язык: Английский