Wiley Interdisciplinary Reviews-Cognitive Science最新文献

Inner speech decoding is the process of identifying silently generated speech from neural signals. In recent years, this candidate technology has gained momentum as a possible way to support communication in severely impaired populations. Specifically, this approach promises hope for people with a variety of physical or neurological disabilities who need alternative means of verbal expression. This review covers recording modalities that range from the noninvasive EEG to the high-density electrocorticography and discusses how linear discriminant analysis, deep convolutional networks, and hybrid fusion of EEG with fMRI are integrated into machine learning strategies to infer covert speech. This review synthesizes evidence to suggest that small vocabularies, under controlled conditions, can yield relatively reasonable accuracy while further refining the decoding outcome via context-based approaches. The impact of sensor quality, training data size, and domain adaptation is illustrated by focusing on public datasets of imagined or articulated speech. Throughout the article, the methodological standards emerging across laboratories will be discussed, emphasizing that effective inner speech recognition involves high-quality preprocessing, subject calibration, and informed modeling choices balanced against computational power for interpretability. In addition to technical advancements, this review also examines the ethical, societal, and regulatory challenges surrounding inner speech decoding, including brain data privacy, neural rights, informed consent, and user trust. Addressing these interdisciplinary issues is critical for the responsible development and real-world adoption of such technologies. This article is categorized under: Neuroscience > Computation Computer Science and Robotics > Machine Learning.

Climate change (CC) is a global phenomenon characterized by long-term shifts in temperatures and weather patterns. Aside from natural causes, we have been facing a full-blown climate crisis primarily driven by human activity, leading to increasingly frequent and extreme weather events that put a strain on people's mental capacities. Addressing CC necessitates a temporal perspective as both causes and potential solutions extend beyond the present. However, despite being a significant challenge for humanity, CC is often considered temporally distant, leading to abstract thinking and reduced urgency for action. Considering the diverse dimensions that concur to define CC, this review will explore the link between CC and time cognition, building on insights from cognitive sciences. Upon considering the tangible effects of the anthropogenic CC (Changing Place), we argue that change in the social construction of time is inherent to CC and drifts to the point of affecting psychological well-being (Changing Time). Moreover, considering that time is central to cognition and interlinked with several cognitive functions, we will consider the literature investigating the impact of CC-related eco-anxiety on cognitive abilities within the framework of time cognition. Furthermore, we assess how eco-anxiety and time cognition interact, potentially serving as markers of mental well-being (Changing Thoughts). By framing CC within the realm of time cognition, we offer an interdisciplinary perspective on cognition and well-being, advocating for the integration of cognitive science into climate adaptation and mitigation efforts to foster more effective, psychologically sustainable long-term climate strategies (Changing Future). This article is categorized under: Neuroscience > Cognition.

This primer summarizes the contemporary debate in moral psychology about whether disgust plays a role in moral judgment, and what that role might be. The importance of the debate is explained, then several approaches to studying the issue are reviewed. First, I review experimental studies that induce incidental disgust. Then, I examine other approaches to studying this question, including correlational studies of disgust sensitivity, studies of whether disgust responds to moral content, and research on whether moral transgressions can evoke disgust. I then cast this debate in the philosophical framework of thesis-antithesis-synthesis, and present several possible ways of synthesizing conflicting findings and resolving the debate.

While predictive coding offers a powerful framework for investigating schizophrenia, its therapeutic applications remain nascent. To facilitate a "therapy turn" in the field, this review establishes a model-oriented, operationalist, and comprehensive understanding of schizophrenia. We examine predictive coding models across key domains-embodiment, co-occurrence of over- and under-weighting priors, subjective time processing, language production and comprehension, self-other differentiation, and social interaction. Each model is linked to corresponding clinical impairments and manifestations in schizophrenia. Finally, we propose a roadmap for future research, outlining the rationale and methods for leveraging this framework to develop novel interventions. This article is categorized under: Psychology > Prediction Psychology > Brain Function and Dysfunction.

There are few cognitive functions more essential than decision making, as better decisions improve our chances of survival. Cost-benefit decisions as they apply to most scenarios in the developed world can range from relatively mundane to reasonably important; however, particularly risky choices such as speeding on our way to work or consuming suspicious foods can pose a genuine risk of significant harm or illness. How is it that our brains learn and evaluate these risks and rewards to arrive at decisions? Additionally, what drives some of us to continue despite, or avoid because of, potential adverse consequences? This review explores neural mechanisms underlying cost-benefit decision making, focusing on paradigms used in human and particularly rodent studies to model decision making under the risk of explicit punishments, such as pain, discomfort, or loss. The review focuses on several key brain regions (the prefrontal cortex, basolateral amygdala, and striatum), and their roles in the assessment of rewards, punishments (or risk thereof), and motivated behaviors. It also discusses pertinent literature on the role of dopamine arising from the ventral tegmental area, as a neuromodulator critical for learning and reinforcement in the context of risky decision making. This article is categorized under: Neuroscience > Behavior Economics > Individual Decision-Making Psychology > Reasoning and Decision Making.

From birth, our visual system is sensitive to movement. Motion, as defined by any change in spatial position over time, is part of our daily lives and can refer to various visual information from elements of nature (like a tree swaying in the wind), objects (like a moving car), animals (like a running dog) or people (like two people dancing). Atypical motion processing, in particular for social and biological movement cues, could lead to difficulties in social interaction and communication, like those observed in Autism Spectrum Disorder (ASD). Extensive research has focused on coherent and biological motion processing in ASD, showing difficulties for both motion categories. Motion-related differences also emerge in several social contexts like emotion processing, joint attention, language acquisition, and body relationship with the environment. However, it remains unclear whether high-level difficulties stem from low-level processing issues or are specific to interpreting social cues. It appears that critical steps between low-level local cues processing and high-level biological/social contexts have not been studied. Adopting an approach encompassing a motion gradient from low to high levels could help identify when motion-related difficulties arise in ASD and which specific types or attributes of motion are most affected. This would offer a more comprehensive and integrated perspective on motion processing in ASD. This article is categorized under: Neuroscience > Cognition.

As longevity increases, cognitive decline in older adults has become a growing concern. Consequently, an increasing interest in the potential of digital tools (e.g., serious games (SG) and virtual reality (VR)) for early screening of Mild Cognitive Impairment (MCI) is emerging. Traditional cognitive assessments like the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are widely used but have limitations related to cultural bias and manual scoring, while their digital adaptations, such as MOCA-CC, maintain diagnostic accuracy while offering remote administration and automated scoring. Innovative tools, such as the Virtual Super Market (VSM) test and Panoramix Suite, instead, assess cognitive domains like memory, attention, and executive function while promoting engagement and preserving ecological validity, making assessments more reflective of real-world tasks. Several studies show that these tools exhibit strong diagnostic performance, with sensitivity and specificity often exceeding 80%. However, although digital tools offer advantages in accessibility and user engagement, challenges remain concerning technological literacy, data privacy, and long-term validation. Future research should focus on validating these tools across diverse populations and exploring hybrid models that combine traditional and digital assessments, as digital tools show promise in transforming cognitive screening and enabling earlier interventions for cognitive decline. This article is categorized under: Psychology > Development and Aging Neuroscience > Cognition.

Contractualist moral theories view morality as a matter of mutually beneficial agreements among rational agents. Compared to its rivals in moral philosophy-consequentialism, deontology, and virtue ethics-contractualism has only recently started to attract attention in empirical work on the cognitive science of morality. Is it fruitful to adopt a contractualist lens to better understand how moral cognition works? After introducing the main contractualist theories in contemporary moral philosophy, I present five reasons to take inspiration from this family of normative theories to develop descriptive accounts of morality. Then, I review how the contractualist framework has been used to contribute to our understanding of moral cognition at three interrelated levels of analysis: Morality's evolutionary logic, its cognitive organization, and the specific cognitive processes and forms of reasoning involved in moral judgment and decision making. First, several evolutionary accounts of morality argue that its evolutionary logic must be understood in contractualist terms. Second, resource-rational contractualism proposes that the subcomponents of moral cognition-including well-studied rule- and outcome-based mechanisms, and much less studied agreement-based processes-are organized to efficiently approximate the outcome of explicit negotiation under resource constraints. Third, recent empirical developments suggest that three characteristically contractualist forms of reasoning-virtual bargaining, we-reasoning, and universalization-can be involved in producing moral judgments and decisions in a variety of contexts. Beyond the traditional distinction between rules and consequences, these various research programs open a third way for the cognitive science of morality, one based on agreement. This article is categorized under: Psychology > Reasoning and Decision Making Economics > Interactive Decision-Making Philosophy > Value.

How do theories of the functions of parts of the brain change? I argue that computational hypotheses help explain the nature of theorizing in cognitive neurobiology. I will focus on the orbitofrontal cortex (OFC), a frontal region of the brain implicated in an array of cognitive functions. Different theories of OFC state different principles of OFC function and use different concepts to construct those principles. There are also differences in the patterns of use of evidence across different theories. I briefly survey several extant proposals for understanding theory change in science generally and cognitive neuroscience specifically, including paradigm shifts, tool innovation, mechanism discovery, conceptual innovation, exploratory experimentation, and changes in measurement techniques. While these extant approaches fall short at describing the nature of theory change illustrated by the case of OFC, they are compatible with my proposal that these theoretical changes and differences in the use of evidence result from different computational hypotheses about the region.

Category learning gives rise to category formation, which is a crucial ability in human cognition. Category learning is also one of the required learning abilities in language development. Understanding the evolution of category learning thus can shed light on the evolution of human cognition and language. The current paper emphasizes its foundational role in language evolution by reviewing behavioral and neurological studies on category learning across species. In doing so, we first review studies on the critical role of category learning in learning sounds, words, and grammatical patterns of language. Next, from a comparative perspective, we review studies on category learning conducted on different species of nonhuman animals, including invertebrates and vertebrates, suggesting that category learning displays evolutionary continuity. Then, from a neurological perspective, we focus on the prefrontal cortex and the basal ganglia. Reviewing the involvement of these structures in vertebrates and the proposed homologous brain structure to the basal ganglia in invertebrates in category learning, as well as in language processing in humans, suggests that the neural basis of category learning likely has an ancient origin dating back to invertebrates. With evidence from both behavioral and neurological levels in both nonhuman animals and humans, we conclude that category learning lays a crucial cognitive foundation for language evolution.