Evidence for Maintained Post-Encoding Memory Consolidation Across the Adult Lifespan Revealed by Network Complexity

Major Role of Multiscale Entropy Evolution in Complex Systems and Data Science

Complex systems are prevalent in various disciplines encompassing the natural and social sciences, such as physics, biology, economics, and sociology. Leveraging data science techniques, particularly those rooted in artificial intelligence and machine learning, offers a promising avenue for comprehending the intricacies of complex systems without necessitating detailed knowledge of underlying dynamics. In this paper, we demonstrate that multiscale entropy (MSE) is pivotal in describing the steady state of complex systems. Introducing the multiscale entropy dynamics (MED) methodology, we provide a framework for dissecting system dynamics and uncovering the driving forces behind their evolution. Our investigation reveals that the MED methodology facilitates the expression of complex system dynamics through a Generalized Nonlinear Schrödinger Equation (GNSE) that thus demonstrates its potential applicability across diverse complex systems. By elucidating the entropic underpinnings of complexity, our study paves the way for a deeper understanding of dynamic phenomena. It offers insights into the behavior of complex systems across various domains.

Negative affect homogenizes and positive affect diversifies social memory consolidation across people

We are often surprised when an interaction we remember positively is recalled by a peer negatively. What colors social memories with positive versus negative hues? We show that when resting after a social experience, individuals showing similar default network responding subsequently remember more negative information, while individuals showing idiosyncratic default network responding remember more positive information. Results were specific to rest after the social experience (as opposed to before or during the social experience, or rest after a nonsocial experience). The results provide novel neural evidence in support of the "broaden and build" theory of positive emotion, which posits that while negative affect confines, positive affect broadens idiosyncrasy in cognitive processing. For the first time, we identified post-encoding rest as a key moment and the default network as a key brain system in which negative affect homogenizes, whereas positive affect diversifies social memories.

Using transcranial direct current stimulation (tDCS) on the dorsolateral prefrontal cortex to promote long-term foreign language vocabulary learning

Transcranial direct current stimulation (tDCS) on the dorsolateral prefrontal cortex (DLPFC) was used to improve foreign-langue learning while using mental imagery. Participants underwent two sessions of 1 mA, 1.5 mA, or sham stimulation prior to learning Swahili-English word pairs two consecutive days. During learning, participants were encouraged to create a mental image of the associated English word. Twenty-four hours after learning and one week later, participants received a cued recall test. A linear dose-response effect of stimulation was found across both tests that occurred long after the immediate effects of stimulation. Follow-up comparisons revealed that only the 1.5 mA condition differed from the sham group. Exploratory moderating effects revealed interactions with sleep quality and handedness. Those with poorer sleep and who were left-handed showed greater recall after 1.5 mA of stimulation than those with better sleep and right-handers. A follow-up behavioral study probing strategy usage indicated that mental imagery strategy use did not strongly impact learning but point to other possible mechanisms including the importance of attending to multimodal perceptual details and memory consolidation. This preliminary evidence supports the role of the DLPFC or connected regions in foreign language vocabulary learning and verbal memory encoding.

Multiscale Entropy Approaches and Their Applications

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