We investigated memory encoding and retrieval during a quasinaturalistic spatial-episodic memory task in which subjects delivered items to landmarks in a desktop virtual environment and later recalled the delivered items. Transition probabilities and latencies revealed the spatial and temporal organization of memory. As subjects gained experience with the town, their improved spatial knowledge led to more efficient navigation and increased spatial organization during recall. Subjects who exhibited stronger spatial organization exhibited weaker temporal organization. Scalp-recorded electroencephalographic signals revealed spectral correlates of successful encoding and retrieval. Increased theta power (T+) and decreased alpha/beta power (A-) accompanied successful encoding, with the addition of increased gamma (G+) accompanying successful retrieval. Logistic regression classifiers trained on spectral features reliably predicted mnemonic success in held-out sessions. Univariate and multivariate electroencephalographic analyses revealed a similar spectral T+A-G+ of successful memory. These findings extend behavioral and neural signatures of successful encoding and retrieval to a naturalistic task in which learning occurs within a spatiotemporal context. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Br J Dev Psychol
January 2025
Department of Psychology, Trinity University, San Antonio, Texas, USA.
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View Article and Find Full Text PDFNeurogenetics
January 2025
Department of Surgery, Surgical Research Section, Hamad Medical Corporation, Doha, Qatar.
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View Article and Find Full Text PDFEntropy (Basel)
December 2024
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Differential Computation Analysis (DCA) leverages memory traces to extract secret keys, bypassing countermeasures employed in white-box designs, such as encodings. Although researchers have made great efforts to enhance security against DCA, most solutions considerably decrease algorithmic efficiency. In our approach, the Feistel cipher SM4 is implemented by a series of table-lookup operations, and the input and output of each table are protected by affine transformations and nonlinear encodings generated randomly.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Center for Digital Health, Mayo Clinic, Rochester, MN 55905, USA.
Current clinical care relies heavily on complex, rule-based systems for tasks like diagnosis and treatment. However, these systems can be cumbersome and require constant updates. This study explores the potential of the large language model (LLM), LLaMA 2, to address these limitations.
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