Trends in Cognitive Sciences最新文献

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.

Humans have a protracted postnatal helplessness period, typically attributed to human-specific maternal constraints causing an early birth when the brain is highly immature. By aligning neurodevelopmental events across species, however, it has been found that humans are not born with especially immature brains compared with animal species with a shorter helpless period. Consistent with this, the rapidly growing field of infant neuroimaging has found that brain connectivity and functional activation at birth share many similarities with the mature brain. Inspired by machine learning, where deep neural networks also benefit from a 'helpless period' of pre-training, we propose that human infants are learning a foundation model: a set of fundamental representations that underpin later cognition with high performance and rapid generalisation.

Many human behavioral and brain imaging studies have used narratively structured stimuli (e.g., written, audio, or audiovisual stories) to better emulate real-world experience in the laboratory. However, narratives are a special class of real-world experience, largely defined by their causal connections across time. Much contemporary neuroscience research does not consider this key property. We review behavioral and neuroscientific work that speaks to how causal structure shapes comprehension of and memory for narratives. We further draw connections between this work and reinforcement learning, highlighting how narratives help link causes to outcomes in complex environments. By incorporating the plausibility of causal connections between classes of actions and outcomes, reinforcement learning models may become more ecologically valid, while simultaneously elucidating the value of narratives.

People regularly encounter various types of conflict. Here, we ask if, and, if so, how, different types of conflict, from lab-based Stroop conflicts to everyday-life self-control or moral conflicts, are related to one other. We present a framework that assumes that action-goal representations are hierarchically organized, ranging from concrete actions to abstract goals. The framework's key assumption is that conflicts involving more abstract goals (e.g., self-control/moral conflict) are embedded in a more complex action space; thus, to resolve such conflicts, people need to consider more associated goals and actions. We discuss how differences in complexity impact conflict resolution mechanisms and the costs/benefits of resolving conflicts. Altogether, we offer a new way to conceptualize and analyze conflict regulation across different domains.

There is a major gap in our understanding of how childhood social isolation causes adult social dysfunction. To stimulate future developmental mechanistic studies, we present two conceptual models which highlight that isolation can disrupt developmental events that are concurrent (social deprivation model) or subsequent (developmental mismatch model) to adverse experience.

Behavior is guided by the compatibility of expectations based on past experience and the outcome. In a recent study, Fouragnan and colleagues report that absolute prediction error (PE)-related heart-evoked potentials (HEPs) differ according to the cardiac cycle phase at outcome, and that the magnitude of this effect positively correlates with reward learning in healthy adults.

The motivations to protect oneself and others have often been seen as conflicting. Here, we discuss recent evidence that self-defensive mechanisms may in fact be recruited to enable the helping of others. In some instances, the defensive response to a threat may even be more decisive in promoting helping than the response to a conspecific's distress (as predicted by empathy-altruism models). In light of this evidence, we propose that neural mechanisms implicated in self-defence may have been repurposed through evolution to enable the protection of others, and that defence and care may be convergent rather than conflicting functions. Finally, we present and discuss a working model of the shared brain mechanisms implicated in defence of both self and others.