Formation of episodic memories is linked to cortico-hippocampal interactions during learning, practice, and post-learning rest, although the role of cortical activity itself in such processes remains elusive. Behaviorally, long-term retention of episodic memories has been shown to be aided by several different practice strategies involving memory reencounters, such as repeated retrieval and repeated study. In a two-session resting state electroencephalography (EEG) experiment, using data from 68 participants, we investigated the electrophysiological predictors of long-term memory success in situations where such reencounters occurred after learning. Participants learned word pairs which were subsequently practiced either by cued recall or repeated studying in a between-subjects design. Participants' cortical activity was recorded before learning (baseline) and after practice during 15-min resting periods. Long-term memory retention after a 7-day period was measured. To assess cortical activity, we analyzed the change in spectral power from the pre-learning baseline to the post-practice resting state recordings. From baseline to post-practice, changes in alpha and beta power were negatively, while slow frequency power change was positively associated with long-term memory performance, regardless of practice strategy. These results are in line with previous observations pointing to the role of specific frequency bands in memory formation and extend them to situations where memory reencounters occur after learning. Our results also highlight that the effectiveness of practice by repeated testing seems to be independent from the beneficial neural mechanisms mirrored by EEG frequency power changes.
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http://dx.doi.org/10.1016/j.cortex.2024.11.012 | DOI Listing |
Immun Ageing
January 2025
State Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
Background: Older people living with HIV-1 (PLWH) experience a dual burden from the combined effects of aging and HIV-1 infection, resulting in significant immune dysfunction. Despite receiving HAART, immune reconstitution is not fully optimized. The objective of this study was to investigate the impact of aging and HAART on T cell subsets and function in PLWH across different age groups, thereby providing novel insights into the prognosis of older PLWH.
View Article and Find Full Text PDFJ Neuroinflammation
January 2025
Department of Neuroscience and Experimental Therapeutics, School of Medicine, Texas A&M Health Science Center, Bryan, TX, 77807-3260, USA.
Background: Disturbances of the sleep-wake cycle and other circadian rhythms typically precede the age-related deficits in learning and memory, suggesting that these alterations in circadian timekeeping may contribute to the progressive cognitive decline during aging. The present study examined the role of immune cell activation and inflammation in the link between circadian rhythm dysregulation and cognitive impairment in aging.
Methods: C57Bl/6J mice were exposed to shifted light-dark (LD) cycles (12 h advance/5d) during early adulthood (from ≈ 4-6mo) or continuously to a "fixed" LD12:12 schedule.
Sci Rep
January 2025
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.
This paper proposes an advanced Load Frequency Control (LFC) strategy for two-area hydro-wind power systems, using a hybrid Long Short-Term Memory (LSTM) neural network combined with a Genetic Algorithm-optimized PID (GA-PID) controller. Traditional PID controllers, while extensively used, often face limitations in handling the nonlinearities and uncertainties inherent in interconnected power systems, leading to slower settling time and higher overshoot during load disturbances. The LSTM + GA-PID controller mitigates these issues by utilizing LSTM's capacity to learn from historical data by using gradient descent to forecast the future disturbances, while the GA optimizes the PID parameters in real time, ensuring dynamic adaptability and improved control precision.
View Article and Find Full Text PDFThe Hybrid-Brain Computer Interface (BCI) has shown improved performance, especially in classifying multi-class data. Two non-invasive BCI modules are combined to achieve an improved classification which are Electroencephalogram (EEG) and functional Near Infra-red Spectroscopy (fNIRS). Classifying contralateral and ipsilateral motor movements is found challenging among the other mental activity signals.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt.
Heart disease is a category of various conditions that affect the heart, which includes multiple diseases that influence its structure and operation. Such conditions may consist of coronary artery disease, which is characterized by the narrowing or clotting of the arteries that supply blood to the heart muscle, with the resulting threat of heart attacks. Heart rhythm disorders (arrhythmias), heart valve problems, congenital heart defects present at birth, and heart muscle disorders (cardiomyopathies) are other types of heart disease.
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