Several findings underlined that the electrophysiological (EEG) background of the last segment of sleep before awakenings may predict the presence/absence of dream recall (DR) in young subjects. However, little is known about the EEG correlates of DR in elderly people. Only an investigation found differences between recall and non-recall conditions during NREM sleep EEG in older adults, while-surprisingly-no EEG predictor of DR was found for what concerns REM sleep. Considering REM sleep as a privileged to produce mental sleep activity related to cognitive processes, our study aimed to investigate whether specific EEG topography and frequency changes during REM sleep in elderly people may predict a subsequent recall of mental sleep activity. Twenty-one healthy older volunteers (mean age 69.2 ± 6.07 SD) and 20 young adults (mean age 23.4 ± 2.76 SD) were recorded for one night from 19 scalp derivations. Dreams were collected upon morning awakenings from REM sleep. EEG signals of the last 5 min were analyzed by the Better OSCillation algorithm to detect the peaks of oscillatory activity in both groups. Statistical comparisons revealed that older as well as young individuals recall their dream experience when the last segment of REM sleep is characterized by frontal theta oscillations. No Recall (Recall vs. Non-Recall) × Age (Young vs. Older) interaction was found. This result replicated the previous evidence in healthy young subjects, as shown in within- and between-subjects design. The findings are completely original for older individuals, demonstrating that theta oscillations are crucial for the retrieval of dreaming also in this population. Furthermore, our results did not confirm a greater presence of the theta activity in healthy aging. Conversely, we found a greater amount of rhythmic theta and alpha activity in young than older participants. It is worth noting that the theta oscillations detected are related to cognitive functioning. We emphasize the notion that the oscillatory theta activity should be distinguished from the non-rhythmic theta activity identified in relation to other phenomena such as (a) sleepiness and hypoarousal conditions during the waking state and (b) cortical slowing, considered as an EEG alteration in clinical samples.
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http://dx.doi.org/10.3389/fneur.2019.00985 | DOI Listing |
Sensors (Basel)
December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Understanding sleep stages is crucial for diagnosing sleep disorders, developing treatments, and studying sleep's impact on overall health. With the growing availability of affordable brain monitoring devices, the volume of collected brain data has increased significantly. However, analyzing these data, particularly when using the gold standard multi-lead electroencephalogram (EEG), remains resource-intensive and time-consuming.
View Article and Find Full Text PDFBiomedicines
December 2024
Department of Physiology, College of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea.
(1) Background: Gamma-aminobutyric acid (GABA) is an amino acid and the primary inhibitory neurotransmitter in the brain. GABA has been shown to reduce stress and promote sleep. GABALAGEN (GBL) is the product of fermented fish collagen by Lactobacillus brevis BJ20 and Lactobacillus plantarum BJ21, naturally enriched with GABA through the fermentation process and characterized by low molecular weight.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
Institute of Physics, University of Zielona Góra, 65-069 Zielona Góra, Poland.
This study investigates whether heart rate asymmetry (HRA) parameters offer insights into sleep stages beyond those provided by conventional heart rate variability (HRV) and complexity measures. Utilizing 31 polysomnographic recordings, we focused exclusively on electrocardiogram (ECG) data, specifically the RR interval time series, to explore heart rate dynamics associated with different sleep stages. Employing both statistical techniques and machine learning models, with the Generalized Estimating Equation model as the foundational approach, we assessed the effectiveness of HRA in identifying and differentiating sleep stages and transitions.
View Article and Find Full Text PDFNPJ Parkinsons Dis
January 2025
Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.
This study explores the effect of risk factors on the progression of idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) to α-synucleinopathies in a Chinese cohort. Patients with iRBD were enrolled and assessed for environmental factors and lifestyle using standardized structured questionnaires at baseline. All patients were prospectively followed for phenoconversion monitoring.
View Article and Find Full Text PDFBrain
January 2025
The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC H3A 2B4, Canada.
Blood-based biomarkers for Alzheimer's disease (AD) pathology have been intensively investigated as markers for AD-related neurodegeneration. Comorbid AD pathology is common in dementia with Lewy bodies (DLB). Accordingly, we hypothesized that plasma biomarkers associated with AD pathology might be useful to predict DLB in a cohort of idiopathic/isolated REM sleep behavior disorder (iRBD), an incipient synucleinopathy.
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