Trends in Cognitive Sciences最新文献

In complex tasks requiring cognitive control, humans show trial-by-trial alterations in response time (RT), which are evident even when sensory-motor or other contextual aspects of the task remain stable. Exaggerated intra-individual RT variability is associated with brain injuries and frequently seen in aging and neuropsychological disorders. In this opinion, we discuss recent electrophysiology and imaging studies in humans and neurobiological studies in monkeys that indicate RT variability is linked with executive control fluctuation and that prefrontal cortical regions play essential, but dissociable, roles in such fluctuation of control and the resulting behavioral variability. We conclude by discussing emerging models proposing that both extremes of behavioral variability (significantly higher or lower) might reflect aberrant alterations in various aspects of decision-making processes.

We discuss recent findings suggesting that non-human animals lack memory for stimulus sequences, and therefore do not represent the order of stimuli faithfully. These observations have far-reaching consequences for animal cognition, neuroscience, and studies of the evolution of language and culture. This is because, if non-human animals do not remember or process information about order faithfully, then it is unlikely that non-human animals perform mental simulations, construct mental world models, have episodic memory, or transmit culture faithfully. If this suggested sequence bottleneck proves to be a prevalent characteristic of animal memory systems, as suggested by recent work, it would require a re-examination of some influential concepts and ideas.

Cognition arises from neural operations at multiple spatial scales, from individual neurons to large-scale networks. Despite extensive research on coding principles and emergent cognitive processes across brain areas, investigation across scales has been limited. Here, we propose ways to test the idea that different cognitive processes emerge from distinct information coding principles at various scales, which collectively give rise to complex behavior. This approach involves comparing brain-behavior associations and the underlying neural geometry across scales, alongside an investigation of global and local scale interactions. Bridging findings across species and techniques through open science and collaborations is essential to comprehensively understand the multiscale brain and its functions.

Given the fundamental role of working memory (WM) in all domains of cognition, a central question has been whether WM is domain-general. However, the term 'domain-general' has been used in different, and sometimes misleading, ways. By reviewing recent evidence and biologically plausible models of WM, we show that the level of domain-generality varies substantially between three facets of WM: in terms of computations, WM is largely domain-general. In terms of neural correlates, it contains both domain-general and domain-specific elements. Finally, in terms of application, it is mostly domain-specific. This variance encourages a shift of focus towards uncovering domain-general computational principles and away from domain-general approaches to the analysis of individual differences and WM training, favoring newer perspectives, such as training-as-skill-learning.

Cognitive economics is an emerging interdisciplinary field that uses the tools of cognitive science to study economic and social decision-making. Although most strains of cognitive economics share commitments to bridging levels of analysis (cognitive, behavioral, and systems) and embracing interdisciplinary approaches, we review a newer strand of cognitive economic thinking with a further commitment: conceptualizing minds and markets each as complex adaptive systems. We describe three ongoing research programs that strive toward these goals: (i) studying narratives as a cognitive and social representation used to guide decision-making; (ii) building cognitively informed agent-based models; and (iii) understanding markets as an extended mind - the Market Mind Hypothesis - analyzed using the concepts, methods, and tools of Coordination Dynamics.

Many magic tricks rely solely on vision, but there are few, if any, that rely on auditory perception alone. Here, we question why this is so and argue that research focusing on this issue could provide deeper theoretical insights into the similarities and differences between our senses.

Ji et al. investigated the unit of working memory manipulation. Participants were asked to update either the color or location of memorized information. Task difficulty depended on the number of Boolean maps involved, rather than the number of objects, suggesting that Boolean maps, not objects, are the units of manipulation.

Canonical cases of learning involve novel observations external to the mind, but learning can also occur through mental processes such as explaining to oneself, mental simulation, analogical comparison, and reasoning. Recent advances in artificial intelligence (AI) reveal that such learning is not restricted to human minds: artificial minds can also self-correct and arrive at new conclusions by engaging in processes of 'learning by thinking' (LbT). How can elements already in the mind generate new knowledge? This article aims to resolve this paradox, and in so doing highlights an important feature of natural and artificial minds - to navigate uncertain environments with variable goals, minds with limited resources must construct knowledge representations 'on demand'. LbT supports this construction.