Large language models (LLMs) increasingly mimic human cognition in various language-based tasks. However, their capacity for metacognition-particularly in predicting memory performance-remains unexplored. Here, we introduce a cross-agent prediction m...
While many mechanisms have been proposed to drive Alzheimer's disease, particularly the accumulation of amyloid plaques and hyperphosphorylation of tau proteins, emerging evidence suggests that they may be the byproducts of earlier damage rather than...
Alzheimer's disease is a progressive neurodegenerative disorder with no cure, making preventive strategies crucial. Dietary interventions, particularly the Mediterranean (MeDi) and MIND diets, have been associated with reduced cognitive decline, but ...
Mice are among the most prevalent animal models used in neuroscience, benefiting from the extensive physiological, imaging, and genetic tools available to study their brain. However, the development of novel and optimized behavioral paradigms for mic...
Reinforcement learning (RL) is a computational framework that models how agents learn from trial and error to make sequential decisions. Rooted in behavioural psychology, RL has become central to artificial intelligence and is increasingly applied in...
In the last decade, the free energy principle (FEP) and active inference (AIF) have achieved many successes connecting conceptual models of learning and cognition to mathematical models of perception and action. This effort is driven by a multidiscip...
Achieving a deep understanding of brain mechanisms requires multi-scale perspectives to capture the architecture of complex networks. In this study, we focused on patients with cognitive impairment and constructed individual brain networks from neuro...
Proceedings of the National Academy of Sciences of the United States of America
Aug 28, 2025
Human learning embodies a striking duality: Sometimes, we can rapidly infer and compose logical rules, benefiting from structured curricula (e.g., in formal education), while other times, we rely on an incremental approach or trial-and-error, learnin...
Extracting time-varying latent variables from computational cognitive models plays a key role in uncovering the dynamic cognitive processes that drive behaviors. However, existing methods are limited to inferring latent variable sequences in a relati...
Simultaneous interpreting (SI) enables real-time cross-language communication without significant delays and is vital for fast-paced environments such as multilingual conferences. Automatic subtitles, powered by artificial intelligence (AI), is an im...
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