Trends in Cognitive Sciences最新文献

Large language models (LLMs), such as ChatGPT, flood the Internet with true and false information, crafted and delivered with techniques that psychological science suggests will encourage people to think that information is true. What's more, as people feed this misinformation back into the Internet, emerging LLMs will adopt it and feed it back in other models. Such a scenario means we could lose access to information that helps us tell what is real from unreal - to do 'reality monitoring.' If that happens, misinformation will be the new foundation we use to plan, to make decisions, and to vote. We will lose trust in our institutions and each other.

Dreams have long captivated human curiosity, but empirical research in this area has faced significant methodological challenges. Recent interdisciplinary advances have now opened up new opportunities for studying dreams. This review synthesizes these advances into three methodological frameworks and describes how they overcome historical barriers in dream research. First, with observable dreaming, neural decoding and real-time reporting offer more direct measures of dream content. Second, with dream engineering, targeted stimulation and lucidity provide routes to experimentally manipulate dream content. Third, with computational dream analysis, the generation and exploration of large dream-report databases offer powerful avenues to identify patterns in dream content. By enabling researchers to systematically observe, engineer, and analyze dreams, these innovations herald a new era in dream science.

Explaining brain plasticity in blindness is challenging because the early visual cortex (EVC) responds to many different tasks, each type supporting a different explanation. Can individual differences help unify the experimental findings into a coherent theory and clarify the nature of brain plasticity?

The study of human working memory (WM) holds significant importance in neuroscience; yet, exploring the role of the medial temporal lobe (MTL) in WM has been limited by the technological constraints of noninvasive methods. Recent advancements in human intracranial neural recordings have indicated the involvement of the MTL in WM processes. These recordings show that different regions of the MTL are involved in distinct aspects of WM processing and also dynamically interact with each other and the broader brain network. These findings support incorporating the MTL into models of the neural basis of WM. This integration can better reflect the complex neural mechanisms underlying WM and enhance our understanding of WM's flexibility, adaptability, and precision.

The ability to read others' intentions is crucial when pooling knowledge to form a collective decision. Decision-making improves when communication is allowed through words or touch. Coucke et al. show that visual information communicated through actions can convey not only a decision but also decision confidence, improving collective decision-making.

A recent study by Peysakhovich and colleagues reveals how the superior colliculus (SC), a deep brain structure commonly associated with spatial orienting and motor control, causally contributes to the abstraction of visual categories. This highlights how subcortical areas with motor-control labels may have central roles in high-level visual cognition and opens avenues for investigation.