How a scientific community is organized can affect whether disagreement drives progress or leads to isolation. Students and postdocs are uniquely placed to build communities that bridge theoretical and methodological divides. Drawing on a student-led society in consciousness science, we show how empowering early-career researchers can turn fragmentation into collaboration.
Cognitive flexibility allows us to adjust behavior when environmental rules change and to recombine prior knowledge in novel situations. However, the computations underlying rule discovery remain unclear: how do rule representations emerge as we interact with the environment? While it is often considered a hallmark of human behavior, converging evidence highlights comparable forms of abstract learning in rodents. Across species, prefrontal activity patterns encode structured representations that support generalization and monitor for rule switches. In this review, we synthesize recent behavioral, neural, and computational work highlighting models that formalize rule inference and creation. We consider how a translational framework linking circuit-level mechanisms to computational principles can help us understand disruptions in cognitive flexibility in disorders such as schizophrenia.
Cognitive maps are essential for navigation, but to what extent are they involved in thinking more broadly? In this opinion article, we examine whether cognitive maps constitute a genuine vehicle for thought and how they relate to the notion of a language of thought. Integrating work from philosophy, psychology, and neuroscience, we suggest that map-like representations offer a distinct, flexible medium for encoding information and exhibit compositionality in both spatial and nonspatial domains. We then consider how dynamic neural mechanisms-replay, theta sequences, and vector computation-may transform map-based representations into sequential routelike formats that interface with cortical systems supporting propositional thinking. Cognitive maps may be complementary to symbolic cognition, jointly enabling flexible human reasoning.
The weight of body parts is largely hidden from conscious experience. People underestimate the weight of their limbs, whereas individuals in clinical populations often experience them as abnormally heavy. We argue that limb weight is a fundamental dimension of internal body representations and a conscious reflection of the functional state of sensorimotor processing.
Understanding human decision-making processes in everyday life is a central, yet rarely addressed, challenge in psychology. Either real-life complexity is reduced by isolating specific aspects of decision-making in highly constrained experimental settings, yielding insights into specific cognitive mechanisms under idealized conditions, or decision-making is studied in real-life contexts, using high-level descriptions of behavior that do not afford fine-grained, process-level insights. Bridging this gap poses a challenge of both measurement and inference. Recent advances in high-resolution tracking technologies provide novel solutions to many measurement challenges but are rarely integrated with formal psychological theory. In this article, we review tracking technologies and statistical tools, proposing a cognitive-computational framework that uses high-resolution spatiotemporal data to investigate the mechanisms of real-life decision-making in a theory-driven manner.
Memory routinely transforms continuous experience into discrete episodes that support flexible retrieval. We propose that these structured representations are established via rapid neural reactivation occurring at the completion of an event. A growing body of evidence across tasks and recording modalities shows that event termination elicits rapid reinstatement of recently encoded neural representations. We review findings revealing that end-of-event reactivation is a robust and functionally meaningful phenomenon, describing when it occurs, how it is measured, and which neural signatures characterize it. We propose that neural reactivation at event offsets offers an efficient neural mechanism for stabilizing newly formed traces against interference, binding relational features into a coherent event index, integrating episodes into pre-existing schemas, and preserving temporal continuity across events.
Differences between musicians and nonmusicians are routinely attributed to training-induced plasticity and transfer, even though pre-existing factors provide equally plausible explanations. We propose repositioning correlational research: not to infer training effects, but to constrain causal accounts, reveal the neurocognitive organization of abilities, guide experimental studies, and integrate with genetically informed designs.
In recent years, several claims have been put forth suggesting that animals of different species address each other using receiver-specific calls that function as individual names. If accurate, this would demonstrate a capacity for symbolic social reference that has rarely been documented in nonhuman communication systems. To evaluate such claims, we propose three minimal criteria for identifying names: individual reference, symbolic representation, and shared meaning. We then review the evidence relevant to these criteria in the species for which name-like calls have been suggested: spectacled parrotlets, common marmosets, African elephants, and bottlenose dolphins. Together, these criteria provide a clear and theoretically grounded framework for exploring the use of name-like calls in nonhuman animals.
People change across daily situations and life transformations, yet maintain a stable sense of self. Explaining this stability requires understanding how identities, traits, values, and memories interact—what changes together, what resists change, and how. We propose that the self is represented as a dynamic causal network of self-aspects linked by beliefs about how they influence one another. Coherence arises when activated self-aspects align with internal beliefs and contextual demands. When disrupted, the network restores coherence through activation shifts that preserve structure or through structural reorganization that reshapes it. This perspective distinguishes the self from associative, categorical, or hierarchical accounts by specifying directional dependencies that constrain change, and highlights how modifying connections among self-aspects promotes coherence and well-being.
Music is pervasive across human history, cultures, and development, yet its evolutionary origins remain unresolved due to the interplay of cultural and biological influences. We argue that identifying uniquely human musicality requires cross-primate comparative research that integrates rhythm and melody processing with exposure, computational principles, and intrinsic reward.
Brain-computer interfaces (BCIs) have achieved transformative success in restoring movement and communication. However, extending these approaches to decoding or recovery of cognitive function, such as attention or memory, poses fundamentally new challenges. Cognitive BCIs will need to contend with distributed and dynamic neural processes that differ sharply from the more localized, stable representations underlying motor and language control, imposing new technical and conceptual demands. Conversely, neuromodulation, long used in neurological and psychiatric therapies, offers a complementary methodological path and initial translational applications through causal modulation of cognitive circuits. Integrating these approaches into adaptive, closed-loop systems could allow cognitive BCIs to restore mental function and bridge systems neuroscience and next-generation neurotherapeutics capable of monitoring and shaping human cognition in real time.
Over the past decade, comparisons between deep neural networks (DNNs) and the human brain have become central to cognitive neuroscience. Early work focused on vision, driven by the success of convolutional neural networks in object recognition, before such comparisons later gained traction in language with the rise of large-scale language models. These comparisons have validated existing hypotheses and generated new ones, challenging views of information processing, connectivity, and computational goals. Despite progress, debates persist over the interpretability and validity of mapping DNNs to brains, underscoring the need for more refined models and methods. Looking ahead, integrating cross-modal insights from vision and language, together with improved modeling and experimental frameworks, promises to advance the mechanistic understanding of cognition.
Many worry that AI use will erode human cognition. We discuss evidence suggesting that offloading cognition to AI can impede skill acquisition and lead to skill decay, but risks depend on how AI is used. We also consider whether our basic cognitive abilities might prove more resilient to this erosion.
Why do some people remain mentally healthy under stress, while others develop symptoms? Recent observational and interventional evidence indicates that positive appraisal style-the tendency to interpret threats in a mildly positive fashion-is a key resilience factor and a promising target for preventive interventions.
Noninvasive methods are making it possible to study neural replay in humans. Although focused on alignment with rodent findings, human research often tacitly assumes that replay is linked to conscious, deliberate thought. This assumption represents a missed opportunity to investigate the links between replay and consciousness, as well as cross-species differences more broadly.
Psychological traits are not uniformly distributed across space; they are geographically clustered. The emerging interdisciplinary field of geographical psychology integrates insights from psychology and the social sciences to understand the causes and consequences of this clustering. By leveraging big data, geospatial analysis, and computational modeling, researchers have identified robust geographical patterns across regions and nations in personality, values, well-being, and prejudice. This review synthesizes key findings on these geographical differences and how they relate to societal-level and individual-level outcomes. Opportunities and challenges for a cognitive science that incorporates a geographical perspective are discussed. Overall, a geographical perspective highlights the dynamic interplay between place and psychology, offering new insights into human behavior and pathways for integrating geography into cognitive science.
Multi-brain neurofeedback offers new possibilities for guiding social interaction by capturing and modulating interpersonal neural dynamics in real time. We propose a hierarchical framework where neurofeedback targets shared sensory dynamics (signal), socio-cognitive processes (functional), or social outcomes (system). We highlight key methodological challenges and potential real-world therapeutic and pedagogical applications.
Developmental voice change exposes a gap in models of self-voice processing: these models explain predictive control and self-voice recognition but not how vocal signals integrate into self-representations. I propose a hierarchical framework in which recursive interactions across sensorimotor predictions, self-voice representations, and higher-order self-representations support the emergence of the vocal self.
Visual search depends on attentional priority, shaped by stimulus salience, current goals, and prior experiences. Although overall search performance declines with age, it remains unclear to what extent this reflects impaired attentional guidance rather than other age-related changes. In this review article, we evaluate how each source of guidance operates across adulthood. Once perceptual factors and general slowing are accounted for, experience-based guidance is largely preserved across timescales, from intertrial priming to lifetime knowledge. Guidance by stable goals and physical salience is also broadly intact. However, specific age-related changes emerge: the influence of past experiences increases under demanding conditions, and goal-directed attention becomes less efficient when priorities must be rapidly reconfigured, pointing to difficulty in resolving conflicts between past and present priorities.
Successful communication requires that members of a language community share a common store of knowledge about words and their meanings. Yet, words show remarkable flexibility, adapting to different situations and extending their meanings in novel and creative ways. The FUSE (Flexible Use of Semantic and Episodic knowledge) model offers a unified account of stability and flexibility in word meaning. Word meanings are constructed dynamically by integrating relatively stable, stored lexical-semantic knowledge with context-specific semantic predictions and idiosyncratic semantic associations that are retrieved from episodic memory. When words are ambiguous or used in unfamiliar or creative ways, contextual predictions and episodic memories become especially important, compensating for the limitations of stored lexical knowledge.
