Trends in Cognitive Sciences最新文献

Serotonergic psychedelics are being explored as treatments for a range of psychiatric conditions. Promising results in mood disorders indicate that their effects on emotional processing may play a central role in their therapeutic potential. However, mechanistic and clinical studies paint a complex picture of the impact of psychedelics on emotions and mood. Here, we review recent findings on the effects of psychedelics on emotion, emotional empathy, and mood. We discuss how psychedelics may impact long-term emotion management strategies, the significance of challenging experiences, and neuroplastic changes. More precise characterization of emotional states and greater attention to the temporal dynamics of psychedelic-induced effects will be critical for clarifying their mechanisms of action and optimizing their therapeutic impact.

The cognitive neuroscience community using M/EEG has not converged on measures of task-related inter-regional brain connectivity that generalize across tasks and laboratories. We call for community-driven efforts to systematically test and validate connectivity metrics using shared datasets and protocols, aiming to establish robust, replicable frameworks for cognitive and clinical applications.

For most mammals, the ability to form, maintain, retrieve, and reshape memories of social experience is essential for individual survival and cooperative behavior. Considerable recent progress has been made in understanding how the hippocampus forms internal representations of social experience, with the CA2 region having emerged as an important integrator of multiple socially relevant inputs. In this review, we discuss recent studies exploring neural substrates of social recognition with a focus on the potential role of plasticity mechanisms in hippocampal circuits and their downstream targets. We also consider the neural bases of binding social with nonsocial and abstract features of the environment to create multidimensional representations that support adaptive social behavior.

Recent advances in artificial intelligence (AI) have generated enthusiasm for using AI simulations of human research participants to generate new knowledge about human cognition and behavior. This vision of 'AI Surrogates' promises to enhance research in cognitive science by addressing longstanding challenges to the generalizability of human subjects research. AI Surrogates are envisioned as expanding the diversity of populations and contexts that we can feasibly study with the tools of cognitive science. Here, we caution that investing in AI Surrogates risks entrenching research practices that narrow the scope of cognitive science research, perpetuating 'illusions of generalizability' where we believe our findings are more generalizable than they actually are. Taking the vision of AI Surrogates seriously helps illuminate a path toward a more inclusive cognitive science.

Perceptual experience depends on recurrent interactions between lower and higher cortices. One theory, predictive coding, posits that feedback from higher to lower brain regions decreases neuronal activity predicted by higher-level representations. Despite the widespread adoption of predictive coding in neuroscience, the correspondence to neurophysiological findings in sensory cortices remains elusive. Here, we review how the canonical patterns of intra- and inter-cortical interactions that occur during perception and shifts of attention deviate from those predicted by predictive coding. We argue that these circuit interactions are better captured by alternative theories, which we summarize under the umbrella term BELIEF. We review how BELIEF theories account for the inter-areal interactions during attentive perception.

Affect labeling can shape how emotions are experienced and shared, with important consequences for both well-being and relationships. While decades of research have explored the impact of articulating emotions through language, the labeling process itself has received limited attention until recently. We suggest that affect labeling can be considered analogous to perceptual decision making, as both involve accumulating evidence toward a decision. Building on perceptual theories of emotion, we explore how this perspective provides new insights into the mechanisms underlying affect labeling. We then review existing research applying sequential sampling models to affect labeling, illustrating how it accounts for the different processes involved in labeling and may explain mechanisms underlying individual differences in the labeling process.