Resilience mechanisms to counteract aging and the onset of neurological and neurodegenerative diseases are becoming an increasingly central issue due to the aging of the population. Several mechanisms have been hypothesized, and in the context of cognitive resilience, the construct of cognitive reserve has attracted considerable interest. However, it is becoming increasingly clear that there are several possible mechanisms of resilience (e.g., motor, affective, behavioral, etc.) which interact with each other, influencing inter-individual variability in healthy and pathological aging trajectories. However, to date, central-peripheral processes have not yet been explicitly incorporated as a resilience mechanism in models of cognitive and affective aging. This perspective article therefore aims to propose a new resilience mechanism, the "Neuroautonomic Adaptive Resilience" (NAR) that implicate a flexible and efficient integration of the central and the autonomic nervous system, allowing individuals to adapt effectively to stressors throughout their lives. This perspective proposes its theoretical framework, its operationalization, and its integration with existing concepts in the field of cognitive and affective neuroscience of aging.
Musical expertise is often associated with enhanced cognitive abilities, underpinned by neural mechanisms unique to musicians. Research has provided evidence of associations between musical training and functional aspects of cognition. However, the neural changes associated with musical expertise, particularly in relation to working memory, remain poorly understood. To address this gap, we conducted an activation likelihood estimation (ALE) meta-analysis to examine differences in functional neural activity between musicians and non-musicians during working memory tasks. Meta-analytic connectivity modeling (MACM) was conducted to explore broader networks of co-activation associated with regions of interest identified during the initial ALE meta-analysis. Nine functional magnetic resonance imaging (fMRI) studies, including 228 participants (113 musicians and 115 non-musicians), were included in the final analysis. Musicians exhibited hyperactivations in the right medial frontal gyrus and hypoactivations across the right middle occipital gyrus, the right precentral gyrus, the left inferior parietal lobule, the right claustrum, and the left cerebellum during working memory tasks. MACM revealed distributed networks of co-activation with links to various cognitive functions across regions of interest uncovered by the ALE analysis. Based on these findings, we propose that distinct functional networks and enhanced neural efficiency in musicians may support working memory performance across the lifespan. This article is categorized under: Neuroscience > Cognition Psychology > Development and Aging Cognitive Biology > Cognitive Development.
Collective memory in humans refers to individual memories that become shared within a community and contribute to social identity, coordination, and cultural continuity. Extensive research shows that collective memory emerges through language-mediated interaction, social influence, and distributed cognitive mechanisms, supporting cooperation, decision-making, and cultural transmission. While these processes are well documented in humans, it remains unclear whether, and in what sense, collective memory exists in nonhuman animals. Here we propose a systematic comparative framework for understanding collective memory across species. We first outline the cognitive foundations of collective memory in humans, highlighting the roles of episodic, semantic, autobiographical, and procedural memory, together with mechanisms such as memory conformity, social contagion, memory convergence, transactive memory systems, and ritualized practices. We then examine whether nonhuman animals possess functional precursors of these mechanisms. Across taxa, animals exhibit episodic-like and semantic-like memory, social learning, conformity, distributed information systems, and ritualized behaviors that allow groups to store, transmit, and update knowledge beyond individual capacities. These processes support stable traditions, coordinated action, and adaptive responses. Although nonhuman animals show no evidence of autonoetic consciousness or human-like autobiographical memory, we argue that collective memory should be understood as a graded, non-dichotomous phenomenon grounded in distributed cognition.
Research on memory and the physical environment has expanded across neuroscience, environmental psychology, and spatial cognition. Yet the literature remains conceptually diverse. A central reason is that the term environment is used to refer to different kinds of phenomena across traditions. In some studies, environment is treated as a broad category, such as natural versus urban. In others, it is defined through spatial and perceptual features, such as landmarks or space geometry. It is also understood as a contextual or event-related structure that becomes bound to experience and later supports retrieval. These approaches are often discussed separately, even when they address overlapping questions about memory. This review organizes the field into three broad traditions: category-based, feature-based, and context-based accounts. We show how each tradition foregrounds different environmental properties, memory systems, and mechanisms. Category-based work most often links environment to attention and working memory, feature-based work to navigation and spatial representation, and context-based work to episodic encoding and retrieval. By placing these traditions side by side, the review clarifies how the environment has been conceptualized in memory research and how different assumptions about environment shape the questions asked, the methods used, and the kinds of memory effects that become visible. The review further proposes that environment can be understood as contributing to memory in at least three roles: as structure, as navigational scaffold, and as cue. Together, these distinctions provide a structured account of a diverse field and identify directions for future work on the relationship between environment and memory.
Cognitive neuroscience has made remarkable advances by conducting rigorously controlled experiments inside the laboratory. However, the generalizability and real-world relevance of these findings remain limited, in part due to fundamental, often unexamined, assumptions about how cognition operates across species and contexts. In this viewpoint, we critically evaluate three commonly held assumptions underlying current cognitive neuroscience practices: (1) laboratory animals serve as accurate representatives of their wild conspecifics; (2) animal models effectively mirror human cognitive processes; and (3) digital twins provide faithful, functionally equivalent representations of their real-world analogs. We argue that these assumptions, if left unexamined, risk narrowing our understanding of cognition by excluding the behavioral flexibility, environmental variability, and agency that natural settings afford. We advocate for an expanded notion of ecological validity to include the naturalness of both subjects and environments, and we highlight methodological shifts, such as the use of enriched experimental contexts, mobile neuroimaging, and immersive virtual environments. By reassessing these foundational assumptions, we advocate for an approach to cognitive neuroscience that better reflects the complexity of real-world behavior, species-specific cognition, and the environments, physical or virtual, in which cognition is embedded.
In this paper, we introduce the reader to the field of cognitive network science, that is, the application of network science methods to study human cognition and knowledge structures. Cognitive networks are representations of associative knowledge between concepts in a cognitive system apt at acquiring, storing, processing and producing language, that is, the mental lexicon. In a cognitive network, nodes represent concepts with links expressing relations, such as semantic, syntactic, phonological and visual connections, for example, "canine" and "dog" (nodes) linked by "being synonyms" (link). Hence, cognitive networks represent associative knowledge in mathematical, measurable and quantifiable ways. Can such structure be used to gain insights over cognitive phenomena? We explore this research question by reviewing recent, pioneering key applications and limitations of cognitive networks across visual, auditory, and semantic language processing tasks, either in healthy or clinical populations. We also review applications of cognitive networks modeling language acquisition, reconstructing text content and assessing creativity or personality traits in individuals. Our paper also gently introduces the reader to mathematical notations, definitions and measures about single-layer and multiplex networks as well as hypergraphs. Last but not least, across phonological, semantic and syntactic networks, we guide the reader through relevant psychological frameworks, datasets and software packages that might all aid current and future cognitive network scientists. This article is categorized under: Psychology > Memory Psychology > Theory and Methods Linguistics > Cognitive
Perceptual-motor coupling, fundamental to human cognition and behavior, plays a crucial role in dynamic interactive contexts ranging from basic motor control to complex action understanding. Recent evidence reveals how kinematic invariants-consistent patterns in human movement-serve as a common language between perception and action, enabling both movement execution and understanding. Through the lens of striking skills-a paradigmatic example that uniquely integrates multiple aspects of perceptual-motor interaction-this review synthesizes evidence for three distinct yet interacting levels of coupling. Level 1 coupling involves fundamental interactions between perceptual and motor processes through dual-stream visual processing, where kinematic invariants are initially extracted and processed. Level 2 encompasses sophisticated control mechanisms that maintain these invariant patterns during action execution through continuous sensorimotor integration. Level 3 coupling transforms these movement patterns into meaningful representations through the action observation network, enabling action understanding and prediction. Evidence indicates these levels operate simultaneously during real-world performance, with kinematic invariants being processed and utilized differently at each level while maintaining continuous interaction between levels. By synthesizing key theories such as the dual-stream model, model-based and online control, and common coding theory in relation to movement invariants, we provide an integrative understanding of perceptual-motor coupling applicable across various domains of human behavior. This multilevel perspective offers insights into the fundamental relationship between perception and action in human cognition, with implications spanning from everyday actions to specialized skills in sports. This article is categorized under: Psychology > Motor Skill and Performance Neuroscience > Behavior Philosophy > Action.
The self and its disorders in schizophrenia have been studied extensively over recent decades. Much of this literature is grounded in a bipartite understanding of the self, distinguishing the pre-reflective, minimal self from the reflective, narrative self. However, few studies have systematically examined the links between disturbances at these two levels of self. This integrative review addresses this gap by analyzing both theoretical and empirical contributions. Three theoretical models are described. The Structural model posits that minimal self-disorders hierarchically give rise to narrative self-disturbances and the schizophrenia phenotype, with a primarily pathogenic focus. The Dialectical model emphasizes reciprocal interactions between minimal and narrative self-disturbances, generating the schizophrenia phenotype with both pathogenic and salutogenic implications. The Contextual model highlights social, territorial, and biological dimensions of the self and its disorders in context. Empirical studies specifically addressing the mechanistic links between minimal and narrative self-disturbances remain scarce and preliminary. Overall, the literature appears preliminary and occasionally speculative, yet it suggests several promising avenues for future research and clinically relevant applications. This article is categorized under: Philosophy > Consciousness Psychology > Theory and Methods.
The "inverted U" relationship between movement and cognition throughout the human lifespan highlights the intricate interplay between physical activity and cognitive function. This relationship posits that an optimal level of physical activity maximizes cognitive function, while insufficient activity can lead to suboptimal cognitive outcomes. This phenomenon is observed from fetal development to old age, emphasizing the importance of maintaining a balance in physical activity for overall well-being. During fetal development, maternal physical activity positively influences fetal brain growth, laying the foundation for future cognitive and physical functioning. As the child develops, regular physical activity supports improvements in key cognitive functions such as attention, memory, and executive function abilities essential for learning and academic success. In adulthood, maintaining an active lifestyle continues to play a central role in preserving cognitive abilities and reducing the risk of neurodegenerative diseases such as Alzheimer's. The inverted U model suggests that optimal cognitive functioning is achieved at moderate levels of physical activity, while too little activity can be detrimental. In older adulthood, regular physical activity is vital for maintaining cognitive function, slowing cognitive decline, and improving quality of life. In summary, understanding the balance between physical activity and cognition across the lifespan is essential for promoting cognitive resilience and sustained well-being. This article is categorized under: Cognitive Biology > Cognitive Development Psychology > Development and Aging Psychology > Learning.
Insomnia has become the most prevalent sleep disorder in the world. The hyperarousal model is one of the main theories to explain the pathogenesis of insomnia disorder, and neuroimaging studies have provided important evidence to support this model. Although the findings vary, the overall results indicate that insomnia patients experience a condition of hyperarousal. We reviewed and summarized the related evidence from previous functional and structural neuroimaging studies of hyperarousal, which mainly showed enhanced local activity and interregional functional connectivity, increased metabolism, structural changes in gray matter, and altered white matter connectivity. Future research should further focus on cortical hyperarousal in different insomnia subtypes, unify the treatment criteria based on a sleep-staging interpretation, strictly control for the effects of age and gender, and advance the application of neuroimaging in the diagnosis and prognostic evaluation of insomnia. This article is categorized under:
The public perception of clinical psychology has been heavily influenced by neuroscientific methods over the past several decades. However, we have seldom stopped to consider to what extent neuroscience can contribute to our understanding of how human psychology-including our experience of our psychological self-operates. This article reviews the progress and weaknesses of an extant psychopharmacological approach to psychological disorders. A psychological model is developed, which positions current neuroscientific research as describing symptoms, rather than causes, of mental disorders. This model relates closely to network theories of psychological disorders, with a strong emphasis on the Pattern Theory of the Self, where disruptions to the psychological self are a central etiological factor in mental disorders. In doing so, this article argues that the philosophical underpinnings of clinical psychological and neuroscientific research should be reconsidered if we intend to develop effective interventions for mental disorders. This article is contextualized in the author's experience of psychological and neuroscientific training, as well as subsequent research experience as a neuroscientist. This article is categorized under: Psychology > Theory and Methods Philosophy > Foundations of Cognitive Science Neuroscience > Clinical.
Many researchers in cognitive science and linguistics now recognize that iconicity – perceived resemblance between the form and meaning of a signal (e.g., a word, sign, or gesture) – is an essential property of language, playing vital roles in its processing, learning, and historical development. Iconicity is also fundamental to the human ability to create meaningful new signals without reliance on convention. This “iconic turn” raises a critical question for the study of language origins: Do great apes use iconic gestures? Apes are well documented to use a flexible and wide-ranging repertoire of gestures, and many appear to be iconic representations of actions, including directive touches, visual directives, and pantomimed actions. However, the most widely accepted theories – ontogenetic ritualization and biological inheritance through phylogenetic ritualization – argue that this apparent form-meaning resemblance is not psychologically real to the apes using the gestures. They argue instead that effective actions are channeled into gestures through repeated use, either through an individual’s experience or over generations of evolution. Yet, it is increasingly recognized that these theories cannot account for the variability and contextual tuning of ape gestures. Alternatively, reasoning from cognitive theories of human gesture and iconicity as rooted in sensorimotor simulation and mental imagery, apes may use a range of gestures that appear homologous to the iconic gestures of humans, even if comparatively restricted in imaginative scope and anchored heavily in a here-and-now context. This fundamental capacity for iconic gesturing may have been a critical precursor to the evolution of language.
Chanting is an ancient and globally widespread ritualistic practice involving rhythmic vocalization or repetition of words, phrases, or sounds. While previous reviews have considered the neurophysiological impact of meditation and spirituality, chanting has received limited systematic investigation. This review aimed to identify and synthesize neural correlates of chanting, examine methodological variability, and determine consistent neural patterns across chanting studies and styles. PsycINFO and PubMed databases were systematically searched for neuroimaging studies including chanting, mantra, and repetitive prayer. Articles published through October 8, 2024, were included, yielding 899 initial articles. After applying exclusion criteria, 24 studies were included. Study quality was assessed using the adapted Effective Public Health Practice Project (EPHPP) criteria. Findings demonstrate that chanting activates brain regions involved in attention and emotional regulation, including the prefrontal cortex, insula, and cingulate gyrus. Deactivation of default mode network (DMN) areas, particularly the posterior cingulate cortex and hippocampus, was also observed, suggesting reduced self-referential thought. Electroencephalography (EEG) studies revealed increased theta activity, indicating enhanced relaxation during chanting. Although heterogeneity in sample sizes, imaging modalities, participant characteristics, and control conditions preclude a formal meta-analysis, the findings lay a foundation for advancing research into the neural mechanisms of chanting. Chanting engages neural networks associated with attention and emotional regulation. The consistent pattern of prefrontal activation and DMN deactivation suggests mechanisms similar to other contemplative practices.
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.
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.
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.
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.
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.
