Learning and memory are fundamental processes for an organism's normal physiological function. Learning can occur at any stage of the organism's physiological development. Imprinted memories formed during the early developmental stage, unlike learning and memory, can last a lifetime. It is not clear whether these two types of memories are interlinked. In this study, we investigated whether imprinted memory influences adult learning and memory in a C. elegans model system. We trained the worms for short-term (STAM) and long-term associated memory (LTAM) towards butanone (BT) after conditioning them for imprinted memory towards isoamyl alcohol (IAA). We observed that these worms had improved learning abilities. However, functional imaging revealed that the worms had a long-term depression in the firing pattern in the AIY interneuron, indicating that there were significant changes in neuronal excitation pattern after imprinting, which could explain the enhanced behavioural alterations in animals after imprinting.
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http://dx.doi.org/10.1016/j.bbrc.2023.07.002 | DOI Listing |
Geroscience
January 2025
Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea.
Background: Superagers, older adults with exceptional cognitive abilities, show preserved brain structure compared to typical older adults. We investigated whether superagers have biologically younger brains based on their structural integrity.
Methods: A cohort of 153 older adults (aged 61-93) was recruited, with 63 classified as superagers based on superior episodic memory and 90 as typical older adults, of whom 64 were followed up after two years.
Brain Inform
January 2025
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
Cognitive resilience (CR) describes the phenomenon of individuals evading cognitive decline despite prominent Alzheimer's disease neuropathology. Operationalization and measurement of this latent construct is non-trivial as it cannot be directly observed. The residual approach has been widely applied to estimate CR, where the degree of resilience is estimated through a linear model's residuals.
View Article and Find Full Text PDFNat Mater
January 2025
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
Machine learning algorithms have proven to be effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementation of these algorithms at cryogenic temperatures is essential. Here we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a cryogenic in-memory computing scheme based on the coexistence of a chiral edge state and a topological surface state.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
School of Psychological Sciences, University of Haifa, Haifa, Israel.
Cognitive training is a promising intervention for psychological distress; however, its effectiveness has yielded inconsistent outcomes across studies. This research is a pre-registered individual-level meta-analysis to identify factors contributing to cognitive training efficacy for anxiety and depression symptoms. Machine learning methods, alongside traditional statistical approaches, were employed to analyze 22 datasets with 1544 participants who underwent working memory training, attention bias modification, interpretation bias modification, or inhibitory control training.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China.
As a multivariate time series, the prediction of curling trajectories is crucial for athletes to devise game strategies. However, the wide prediction range and complex data correlations present significant challenges to this task. This paper puts forward an innovative deep learning approach, CasLSTM, by introducing integrated inter-layer memory, and establishes an encoder-predictor curling trajectory forecasting model accordingly.
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