A long-standing question in cognitive sciences concerns the specific contribution of linguistic and sensorimotor experience in shaping conceptual knowledge. A new study by Xu et al. shows that large language models (LLMs) represent a powerful tool to advance this debate, helping to disentangle the relative contribution of different experiential modalities.

Does including emotions improve reinforcement-learning models? A recent EEG study by Heffner and colleagues presents separate neural signatures for reward and emotion prediction errors. This advance invites questions about, and even holds clues to, which ingredients of emotion and prediction errors most improve reinforcement-learning models.

Bumblebees have been used to study various aspects of complex cognition and behavior, yet unlike many purely lab-based systems, we also possess rich knowledge of their natural history. We highlight how integrating these perspectives has provided insights into both the underlying mechanisms and functions of cognitive abilities.

The ubiquity of extraordinary beliefs across human societies, such as conspiracy theories, pseudoscience, and supernatural beliefs, is a long-standing puzzle in cognitive science. Prevailing accounts emphasize cognitive biases and social dynamics but often neglect a key factor: experience. We synthesize recent evidence and identify three pathways by which experience can shape these convictions: by filtering which beliefs feel perceptually plausible, by sparking new beliefs through anomalous and emotionally charged events, and by being engineered through immersive cultural technologies that simulate sensory evidence. These pathways function alongside cognitive biases and social processes, helping explain why certain extraordinary beliefs recur, why they often accompany vivid rituals, and why they can feel convincing despite evidence that challenges their veracity.

Despite decades of progress, gender inequalities in workplace authority and compensation persist. This review reveals recent advances in understanding how gendered careers emerge through three psychological mechanisms prevalent in organizations: (i) intrapersonal gender biases, (ii) interpersonal power dynamics, and (iii) intergroup gender relations. Because power is perceived as masculine, women in authority face systematic backlash. While status offers women an alternative leadership route, it proves less valuable than power - lacking resource control and requiring constant social validation rather than conferring formal authority. We suggest that mindsets about human malleability moderate these dynamics: fixed mindsets amplify stereotyping and power-based challenges for women leaders, while growth mindsets attenuate barriers. Our framework aims to illuminate gender disparities and to suggest promising intervention pathways.

In recent years, scientific interest in sensory processing sensitivity (SPS), a personality trait reflecting increased sensitivity, reactivity, and deeper processing of stimuli, has grown exponentially. Building on this momentum, we synthesise recent SPS literature to discuss several central themes, including SPS assessment, relations to other personality traits and diverse positive and negative outcomes. We propose a novel account of SPS grounded in predictive processing, that bridges cognitive, neural, and computational domains. Specifically, we posit that brains of high-SPS individuals consistently assign high precision to incoming sensory signals. This account offers a unified explanation for the phenotypic consequences of heightened sensory sensitivity. We review behavioural and neural evidence that indirectly supports this account, and delineate important avenues for future research.

Electrophysiological markers of spontaneous thought are well established, yet less is known regarding the timescales of two core dimensions: task relatedness and thought orientation. In a recent study, Hua and colleagues reported dissociable timescales in the behavioral and neural correlates of these thought dimensions, offering insights into their distinct temporal dynamics.

The human brain undergoes a protracted course of development that provides prolonged opportunities to be sculpted by experience. Yet, persistent definitional and measurement challenges have complicated efforts to understand how experience interacts with neuroplasticity during human development. Here, we synthesize previously siloed perspectives to propose an integrative framework defining key dimensions along which adversity interacts with neuroplasticity. We discuss how the state of neuroplasticity during the timing of exposure may modulate how adversity shapes brain development. We also outline how adversity may accelerate or delay the timing of neuroplasticity and amplify or dampen its magnitude. Identifying how, where, and when experience calibrates the brain's capacity for change may inform how neuroplasticity dynamics can be harnessed to promote healthy development.

Blindsight patients lack conscious visual perception yet perform visual tasks effectively, suggesting many animals may similarly rely on non-conscious vision. Here, we discuss how to investigate visual consciousness in miniature brains, using bees as a case study. This new endeavor can reveal the minimal neural requirements for visual awareness.

Mental life is filled with thoughts about the social world and one's place in it. Mentalizing, or ascribing mental content (e.g., preferences, beliefs, visuospatial perspectives) to others and oneself, often requires considering self-representations and target representations in relation to each other. We propose a model of mentalizing wherein simulation, which, minimally, involves activating a self-representation, facilitates two phenomena: projection (using self-representations to construct target representations) is an inherent element of simulation-driven mentalizing, and introjection (using target representations to shift self-representations) arises incidentally from simulating another's mind. We review evidence primarily from adults supporting this model, identify theoretically-relevant factors that amplify and attenuate projection and introjection, and discuss implications for questions of longstanding interest in cognitive science (e.g., Is the self special?).

A widespread observation is that people avoid mentally effortful courses of action, and much recent work examining cognitive effort has explained subjective effort evaluation - and, consequently, preferences - in economic terms, which assumes that the expenditure of cognitive effort is experienced as costly. However, this economic perspective is largely tacit about the source of these costs. Here, we review recent theoretical treatments of effort costs, which take vastly different perspectives (information-theoretic, psychological, and biological) to explain how the subjective experience of cognitive effort arises from controlled information processing, exploring their predictions concerning the simple observation that people experience tasks with high (versus low) working memory demands as costly. Finally, we identify open questions that might help bridge across these accounts.

Empathy is central to social cognition, yet efforts to link it with neurodiverse and clinical conditions have yielded contradictory findings, often reinforcing a deficit-focused narrative that conflicts with individuals' experiences. While traditional models distinguish cognitive (understanding others' emotions) from emotional empathy (being affected by others' emotions), they often neglect how their interplay shapes individual outcomes. Addressing these limitations, this article focuses on the emerging concept of empathic disequilibrium, the intrapersonal imbalance between cognitive and emotional empathy. We synthesise current evidence linking empathic disequilibrium with individual differences in autistic traits and mental health, discuss its potential mechanisms, and propose a framework that recognises empathy as a multifaceted system with interacting components, with implications for advancing theory and practice across cognitive sciences.

Language is often regarded as a defining trait of our species, but what are its core properties? In 1960, Hockett published 'The origin of speech' enumerating 13 design features presumed to be common to all languages, and which, taken together, separate language from other communication systems. Here. we review which features still hold true in light of new evidence from cognitive science, linguistics, animal cognition, and anthropology, and demonstrate how a revised understanding of language highlights three core aspects: that language is inherently multimodal and semiotically diverse; that it functions as a tool for semantic, pragmatic, and social inference, as well as facilitating categorization; and that the processes of interaction and transmission give rise to central design features of language.

Episodic memories are highly dynamic and change in nonlinear ways over time. This dynamism is not captured by existing systems consolidation theories that predict a unidirectional process where memories are first supported by the hippocampus and then the neocortex. Here, I propose a 3D state space for episodic memories. The first two dimensions relate to whether episodic retrieval is driven by the hippocampus and the neocortex, critically allowing for independent and additive contributions from both regions. The third dimension relates to the episodic specificity of retrieval. Memories can be located at any point in this state space and move to any other location. The state space captures the dynamic nature of episodic memory and broadens the search space of possible memory states and transformations across time.

Rapid progress in artificial intelligence (AI) capabilities has drawn fresh attention to the prospect of consciousness in AI. There is an urgent need for rigorous methods to assess AI systems for consciousness, but significant uncertainty about relevant issues in consciousness science. We present a method for assessing AI systems for consciousness that involves exploring what follows from existing or future neuroscientific theories of consciousness. Indicators derived from such theories can be used to inform credences about whether particular AI systems are conscious. This method allows us to make meaningful progress because some influential theories of consciousness, notably including computational functionalist theories, have implications for AI that can be investigated empirically.

Nature contact has long been considered salutary. Recently, scientists from a variety of home disciplines have begun to systematically document these benefits through new assessment approaches and considerations of a wide range of negative and positive affective outcomes. They also have expanded the scale of their investigations, increasing their capacity to understand specifics about the characteristics, magnitude, and timing of effects. Although much remains to be learned about why these affective benefits occur, impressive progress has been made in identifying some of the mechanisms linking nature contact to human functioning. In this review, we focus specifically on mechanisms and outcomes related to affective functioning. We discuss emerging insights and highlight promising directions for future research in this rapidly evolving field.

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.

Humans exhibit a striking tendency to persist with chosen goals. This strong attachment to goals can often appear irrational - a perspective captured by terms such as perseverance or sunk-cost biases. In this review, we explore how goal commitment could stem from several adaptive mechanisms, including those that optimise cognitive resources, shield decisions from interference, and scaffold motivation in the absence of accessible reward signals. We propose that these computational considerations have important implications for algorithmic architectures supporting decision making, including separate algorithms for goal selection and implementation, and for monitoring ongoing goals versus alternative sources of reward. Finally, we discuss how a variety of mechanisms supporting goal commitment and abandonment could relate to dimensions affected in mental health.

Communication errors are typically viewed as detrimental, yet they can benefit collective foraging in social insects. Temnothorax ants provide a powerful model for studying how such errors arise during tandem running and how they might improve group performance under certain environmental conditions.

A fundamental question regarding the human mind is how we derive knowledge from others' episodic memories, to learn about things we did not experience directly. This learning is vital for understanding the world around us and guides our actions and decisions. We propose a novel framework to investigate how people learn from others' episodic memories, hypothesizing that in such learning, people take an evaluative stance to avoid acquiring misleading information. Information evaluated as more veridical will be more likely to be learned from. We review the cues used to evaluate others' memories. These cues may be conveyed and interpreted automatically (e.g., various aspects of prosody), or more deliberatively (e.g., description of recollective content, overt metacognitive claims of certainty or specificity).