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.

Deep learning has enabled major advances across most areas of artificial intelligence research. This remarkable progress extends beyond mere engineering achievements and holds significant relevance for the philosophy of cognitive science. Deep neural networks have made significant strides in overcoming the limitations of older connectionist models that once occupied the center stage of philosophical debates about cognition. This development is directly relevant to long-standing theoretical debates in the philosophy of cognitive science. Furthermore, ongoing methodological challenges related to the comparative evaluation of deep neural networks stand to benefit greatly from interdisciplinary collaboration with philosophy and cognitive science. The time is ripe for philosophers to explore foundational issues related to deep learning and cognition; this perspective paper surveys key areas where their contributions can be especially fruitful. This article is categorized under: Philosophy > Artificial Intelligence Computer Science and Robotics > Machine Learning.

Humans and other animals possess the remarkable ability to effectively navigate a shared perceptual environment by discerning which objects and spaces are perceived by others and which remain private to themselves. Traditionally, this capacity has been encapsulated under the umbrella of joint attention or joint action. In this comprehensive review, we advocate for a broader and more mechanistic understanding of this phenomenon, termed co-perception. Co-perception encompasses the sensitivity to the perceptual engagement of others and the capability to differentiate between objects perceived privately and those perceived commonly with others. It represents a distinct concept from mere simultaneous individual perception. Moreover, discerning between private and common objects doesn't necessitate intricate mind-reading abilities or mutual coordination. The act of perceiving objects as either private or common provides a comprehensive account for social scenarios where individuals simply share the same context or may even engage in competition. This conceptual framework encourages a re-examination of classical paradigms that demonstrate social influences on perception. Furthermore, it suggests that the impacts of shared experiences extend beyond affective responses, also influencing perceptual processes. This article is categorized under: Psychology > Attention Philosophy > Foundations of Cognitive Science Philosophy > Psychological Capacities.

Despite its importance in different occupational and everyday contexts, vigilance, typically defined as the capacity to sustain attention over time, is remarkably limited. What explains these limits? Two theories have been proposed. The Overload Theory states that being vigilant consumes limited information-processing resources; when depleted, task performance degrades. The Underload Theory states that motivation to perform vigilance tasks declines over time, thereby prompting attentional shifts and hindering performance. We highlight some conceptual and empirical problems for both theories and propose an alternative: the Strategic Allocation Theory. For the Strategic Allocation Theory, performance on vigilance tasks optimizes as a function of intrinsic and extrinsic motivations, including metacognitive factors such as the expected value of effort and the expected value of planning. Limited capacities must be deployed across task sets to maximize expected reward. The observed limits of vigilance reflect changes in the perceived value of, among other things, sustaining attention to a task rather than attending to something else. Drawing from recent computational theories of cognitive control and meta-reasoning, we argue that the Strategic Allocation Theory explains more phenomena related to vigilance behavior than other theories, including self-report data. Finally, we outline some of the testable predictions the theory makes across several experimental paradigms. This article is categorized under: Philosophy > Foundations of Cognitive Science Psychology > Attention.

This primer describes research on the development of motor behavior. We focus on infancy when basic action systems are acquired-posture, locomotion, manual actions, and facial actions-and we adopt a developmental systems perspective to understand the causes and consequences of developmental change. Experience facilitates improvements in motor behavior and infants accumulate immense amounts of varied everyday experience with all the basic action systems. At every point in development, perception guides behavior by providing feedback about the results of just prior movements and information about what to do next. Across development, new motor behaviors provide new inputs for perception. Thus, motor development opens up new opportunities for acquiring knowledge and acting on the world, instigating cascades of developmental changes in perceptual, cognitive, and social domains. This article is categorized under: Cognitive Biology > Cognitive Development Psychology > Motor Skill and Performance Neuroscience > Development.

The study of consciousness is considered by many one of the most difficult contemporary scientific endeavors and confronts several methodological and theoretical challenges. A central issue that makes the study of consciousness so challenging is that, while the rest of science is concerned with problems that can be verified from a "third person" view (i.e., objectively), the study of consciousness deals with the phenomenon of subjective experience, only accessible from a "first person" view. In the present article, we review early (starting during the late 19th century) and later efforts on measuring consciousness and its absence, focusing on the two main approaches used by researchers within the field: objective (i.e., performance based) and subjective (i.e., report based) measures of awareness. In addition, we compare the advantages and disadvantages of both types of awareness measures, evaluate them according to different methodological considerations, and discuss, among other issues, the possibility of comparing them by transforming them to a common sensitivity measure (d'). Finally, we explore several new approaches-such as Bayesian models to support the absence of awareness or new machine-learning based decoding models-as well as future challenges-such as measuring the qualia, the qualitative contents of awareness-in consciousness research.

Anxiety disorder is a complex disease with the influence of environmental and genetic factors and multimolecular participation, and it is also one of the most common mental disorders. The causes of disorders are not clear but may include a variety of social, psychological, and biological factors. Therefore, neither genetics, neurobiology, nor neuroimaging can independently explain the pathological mechanism. By searching the Web of Science databases, Derwent Innovation Patent database, ClinicalTrials.gov database, and Cortellis database, we analyze the current situation of papers, patents, clinical trials, and drugs of anxiety disorder. Second, the existing literature was reviewed to summarize the neurophysiological mechanism, brain imaging, gene, anti-anxiety drugs, and other aspects of anxiety disorders. This article reviews the research status of anxiety disorders. The heterogeneity of the disease, lack of treatment effectiveness, and gaps in translational medicine still present barriers to further advancement. Thus, in-depth explorations of the underlying biological mechanisms of anxiety disorders, the detection and intervention of biological targets, and further developments based on existing intervention strategies will drive future research on anxiety disorders. This article is categorized under: Neuroscience > Clinical.

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.

This scoping review examines the use of eye movement tracking in personality research across various domains, including job interviews, education and training, human-robot interaction, and user interface design. Eye-tracking has proven effective in capturing behavioral cues linked to personality traits such as emotional responses, leadership potential, and learning preferences. To map existing research and identify prevailing use case scenarios, a systematic search was conducted in the ACM and IEEE digital libraries. From an initial pool of 170 studies, 21 met the inclusion criteria and were subjected to full-text analysis. The purpose of this review is to provide a structured overview of current research trends, methodological approaches, and application contexts. Its contribution lies in synthesizing key insights and highlighting opportunities for future research, particularly in the use of eye-tracking for advancing personalized technologies and behavior-based analytics in fields such as education, marketing, and psychological analysis.

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.

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.

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.

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.

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.

According to an influential research program in cognitive science, philosophy, and linguistics, there is a deep, special connection between generics and pernicious aspects of social cognition, such as stereotyping. Specifically, generics are thought to exacerbate our propensity to essentialize, lead us to overgeneralize based on scarce evidence and to other epistemically dubious patterns of inference. Recently, however, several studies have put empirical and theoretical pressure on some of the main tenets of this research program. The goal of this paper is to bring these results together in a comprehensive narrative and systematically evaluate their impact on the hypothesis that generics have a uniquely problematic effect on our social and cognitive capacities.

Analyzing looking times is among the most important behavioral approaches to studying problems such as infant cognition, perception, or language development. However, process-based approaches to the dynamics of infants' looking times are lacking. Here, we propose a new dynamical framework for modeling infant gaze behavior with full account of the microstructure (i.e., saccades and fixations). Our process-based model is illustrated by reproducing inter-individual differences in a developmental study of noun comprehension (Garrison et al. 2020). In our modeling framework, numerical values of model parameters map onto specific cognitive processes (e.g., attention or working memory) involved in gaze control. Because of the general architecture of the mathematical model and our robust procedures in model inference via Bayesian data assimilation, our framework may find applications in other fields of developmental and cognitive sciences.

This article focuses on familiarity, the form of memory allowing humans to recognize stimuli that have been encountered before. We aim to emphasize its complex nature which includes representational and phenomenological dimensions. The former implies that its neural correlates depend on the type and complexity of the cue stimulus, as different classes of stimuli are represented in distributed ventral visual and medial temporal regions. The second dimension relates to the subjective feeling of familiarity, which results from a fluency signal that is attributed to past encounters with the stimulus. We review mnemonic and non-mnemonic sources of fluency that can induce a sense of familiarity, as well as cases where fluency is not attributed to memory, among which the phenomenological experience of déjà-vu. Across these two dimensions, we highlight key questions to be answered by future studies to improve our understanding of the underpinnings of this form of memory and contribute to building an integrative neurocognitive model of familiarity. Essential to this aim is the clarification of the computational, cognitive, and neural mechanisms involved, namely global matching, fluency attribution, and sharpening. Furthermore, future research is needed to unravel the relationships between these mechanisms. We argue that to achieve these goals, researchers must use appropriate behavioral paradigms and clearly define which dimension of familiarity they investigate.

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.

Mind-wandering (MW) refers to the shift of attention away from an ongoing task and/or external environment towards mental contents (e.g., memories, prospective thoughts) unrelated to the task. Physiological measures (e.g., pupil size, EEG, and fMRI) have often been acquired as objective markers for MW states, which has greatly helped their study as well as triangulation with other measures. Pupillometry in particular has been used as a covert biomarker of MW because it is reliably modulated by several distinct processes spanning arousal, emotion, and attention, and it signals attentional lapses. Yet, coupling MW and the measurement of pupil size has led to seemingly contrasting results. We argue that, common to the studies reviewed here, one reason is resolving to the measurement of tonic pupil size, which reflects low-frequency, slow changes in one's physiological state, and thus implicitly assumes that MW is a static, long-lasting process. We then additionally focus on three major axes of variability in the reviewed studies: (i) the definition and measurement of MW; (ii) the impact of contextual aspects, such as task demands and individual arousal levels; (iii) the identification and tracking of MW in combination with pupillary measures. We provide an overview of these differences and put forward recommendations for using physiological measures-including, but not limited to, pupil size-in MW research effectively. In conclusion, pupillometry can be a very informative tool for MW research, provided that it is used with the due methodological caution.

Research on analogy-making agrees that mapping allows one to find structural similarities when comparing two situations. However, whether retrieval of past events from memory is guided by surface or structural similarities remains subject to empirical debate. The current contribution is aimed at dissolving this controversy by reviewing experimental evidence showing that the determinants of analogical retrieval primarily depend on the encoding of the situations, which is itself modulated by prior categories available to the participants. Based on this review, a conceptual model is introduced (ADAPTER, As Deep As Possible Target Encoding and Retrieval), in which available categories determine the level of abstraction characterizing encoding as well as the type of retrieval that can be implemented. The model also incorporates the impact of encoding contexts and characteristics of the target descriptions on the likelihood of a relational encoding, which in turn influence the determinants of retrieval. This framework elucidates prior findings within a unified account and provides avenues for advancing the debate on the determinants of analogical retrieval by generating empirical predictions. The model also provides novel insights into the developmental trajectory of structurally based retrievals and suggests promising educational interventions aimed at promoting spontaneous transfer.

Working memory is thought to be the psychological capacity that enables us to maintain or manipulate information no longer in our environment for goal-directed action. Recent work argues that working memory is not a so-called natural kind and in turn cannot explain the cognitive processes attributed to it. This paper first clarifies the scope of this earlier critique and argues for a pluralist account of working memory. Under this account, working memory is variously realized by many mechanisms that contribute to the maintenance and manipulation of information across tasks. This view in effect updates one of the earliest pluralist formulations of working memory. Juxtaposing this view against deflationary descriptions allows us to delineate two gradients that help us chart various accounts of working memory and identify their respective theoretical commitments. In turn, we can isolate those accounts that fail to accord with the evidence supporting a pluralist view, and we can begin to rehabilitate working memory as a pluralist, and ultimately more informative, construct.

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.

Emotional disorders inflict an enormous burden on society. Research on brain abnormalities implicated in emotional disorders has witnessed great progress over the past decades. Using cross-sectional and longitudinal designs, resting state functional magnetic resonance imaging (rs-fMRI) and its analytic approaches have been applied to characterize the local properties of patients with emotional disorders. Additionally, brain activity alterations of emotional disorders have shown frequency-specific. Despite the gains in understanding the roles of brain abnormalities in emotional disorders, the limitation of the small sample size needs to be highlighted. Lastly, we proposed that evidence from the positive psychology research stream presents it as a viable discipline, whose suggestions could be developed in future emotional disorders research. Such interdisciplinary research may produce novel treatments and intervention options. This article is categorized under: Psychology > Brain Function and Dysfunction.

The last two decades have seen major advances in cognitive control research. In this paper, I provide an overview of this research. I next make a case that it might benefit from more reflection on its theoretical foundation. I end by suggesting that action theory might be of use with this.

Perception involves the processing of content or information about the world. In what form is this content represented? I argue that perception is widely compositional. The perceptual system represents many stimulus features (including shape, orientation, and motion) in terms of combinations of other features (such as shape parts, slant and tilt, common and residual motion vectors). But compositionality can take a variety of forms. The ways in which perceptual representations compose are markedly different from the ways in which sentences or thoughts are thought to be composed. I suggest that the thesis that perception is compositional is not itself a concrete hypothesis with specific predictions; rather it affords a productive framework for developing and evaluating specific empirical hypotheses about the form and content of perceptual representations. The question is not just whether perception is compositional, but how. Answering this latter question can provide fundamental insights into perception. This article is categorized under: Philosophy > Representation Philosophy > Foundations of Cognitive Science Psychology > Perception and Psychophysics.

Conceptualization underlying language use is an unconscious and automatic process that interacts with the general human cognitive faculty. The main purpose of Mental Spaces Theory (MST), as one of the major frameworks in Cognitive Linguistics, is to shed light on this process and model it in cognitively motivated ways. This overview pursues two objectives: First, to introduce the basics of the theory, as it was originally proposed by Gilles Fauconnier, and second, to show how MST accounts for networks of mental spaces accommodating semantic contents and how it represents the many roles of cognizers in the construal process. The first part of this overview discusses the background of MST and summarizes its major contributions to the field. The second part follows up on how the theory has been evolving toward investigations of attested linguistic/multimodal data. Illustrating how multiple viewpoints are stacked up in modeling the construal of multimodal artifacts as well as linguistic ones, this overview demonstrates the full interpretive potential of the concept of a "mental space" in the processing of multilayered meaning construction.

Perceptual learning is commonly understood as conferring some benefit to the learner, such as allowing for the extraction of more information from the environment. However, perceptual learning can be biased in several different ways, some of which do not appear to provide such a benefit. Here we outline a systematic framework for thinking about bias in perceptual learning and discuss how several cases fit into this framework. We argue these biases are compatible with an understanding in which perceptual learning is beneficial, but that its benefits are tied to both a person's narrow interests and the training environment or domain, and so if there are changes to either of these, then benefits can turn into liabilities, though these are often temporary. This article is categorized under: Psychology > Learning Philosophy > Value Linguistics > Language Acquisition.

Central to how signed languages such as American Sign Language (ASL) express the viewpoint of a signer is the space surrounding the signer's body, and primarily that in front of the signer. Perspective-taking, in its most basic form, is physical and perceptual in nature, where signers might map a scene experienced in the past onto their present surrounding space as they engage in narrative discourse. But beyond this, signers also express conceptual viewpoint in terms of how they view, subjectively, more abstract ideas, for example expressing a particular stance toward someone's actions, and space frequently plays a role here too. The expression of viewpoint affects linguistic structure in a variety of ways, for example, when the perspective shifts from one story character to another, referring to various entities must be tracked, for which ASL has particular linguistic mechanisms that signers employ. At an abstract level, ASL has certain constructions that reflect viewpoint, one example of which is topic-comment constructions, where a topic phrase is subjectively chosen (often paradigmatically) as a means of framing a state of affairs, which is one kind of conceptual viewpoint, whereas the comment that follows is a construction containing, pragmatically, the signer's belief or stance regarding that state of affairs. Through a cognitive linguistics lens, we can see how aspects of viewpoint in ASL involve instances of conceptual blends, relying on metaphor and metonymy, body partitioning, and image schemas.

This review article examines the extant literature on animism and anthropomorphism in infants and young children. A substantial body of work indicates that both infants and young children have a broad concept of what constitutes a sentient agent and react to inanimate objects as they do to people in the same context. The literature has also revealed a developmental pattern in which anthropomorphism decreases with age, but social robots appear to be an exception to this pattern. Additionally, the review shows that children attribute psychological properties to social robots less so than people but still anthropomorphize them. Importantly, some research suggests that anthropomorphism of social robots is dependent upon their morphology and human-like behaviors. The extent to which children anthropomorphize robots is dependent on their exposure to them and the presence of human-like features. Based on the existing literature, we conclude that in infancy, a large range of inanimate objects (e.g., boxes, geometric figures) that display animate motion patterns trigger the same behaviors observed in child-adult interactions, suggesting some implicit form of anthropomorphism. The review concludes that additional research is needed to understand what infants and children judge as social agents and how the perception of inanimate agents changes over the lifespan. As exposure to robots and virtual assistants increases, future research must focus on better understanding the full impact that regular interactions with such partners will have on children's anthropomorphizing. This article is categorized under: Psychology > Learning Cognitive Biology > Cognitive Development Computer Science and Robotics > Robotics.

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.