Cognition of Time and Thinking Beyond.

A common research protocol in cognitive neuroscience is to train subjects to perform deliberately designed experiments while recording brain activity, with the aim of understanding the brain mechanisms underlying cognition. However, how the results of this protocol of research can be applied in technology is seldom discussed. Here, I review the studies on time processing of the brain as examples of this research protocol, as well as two main application areas of neuroscience (neuroengineering and brain-inspired artificial intelligence). Time processing is a fundamental dimension of cognition, and time is also an indispensable dimension of any real-world signal to be processed in technology. Therefore, one may expect that the studies of time processing in cognition profoundly influence brain-related technology. Surprisingly, I found that the results from cognitive studies on timing processing are hardly helpful in solving practical problems. This awkward situation may be due to the lack of generalizability of the results of cognitive studies, which are under well-controlled laboratory conditions, to real-life situations. This lack of generalizability may be rooted in the fundamental unknowability of the world (including cognition). Overall, this paper questions and criticizes the usefulness and prospect of the abovementioned research protocol of cognitive neuroscience. I then give three suggestions for future research. First, to improve the generalizability of research, it is better to study brain activity under real-life conditions instead of in well-controlled laboratory experiments. Second, to overcome the unknowability of the world, we can engineer an easily accessible surrogate of the object under investigation, so that we can predict the behavior of the object under investigation by experimenting on the surrogate. Third, the paper calls for technology-oriented research, with the aim of technology creation instead of knowledge discovery.

Differently different?: A commentary on the emerging social cognitive neuroscience of female autism.

Autism is a neurodevelopmental condition, behaviourally identified, which is generally characterised by social communication differences, and restrictive and repetitive patterns of behaviour and interests. It has long been claimed that it is more common in males. This observed preponderance of males in autistic populations has served as a focussing framework in all spheres of autism-related issues, from recognition and diagnosis through to theoretical models and research agendas. One related issue is the near total absence of females in key research areas. For example, this paper reports a review of over 120 brain-imaging studies of social brain processes in autism that reveals that nearly 70% only included male participants or minimal numbers (just one or two) of females. Authors of such studies very rarely report that their cohorts are virtually female-free and discuss their findings as though applicable to all autistic individuals. The absence of females can be linked to exclusionary consequences of autism diagnostic procedures, which have mainly been developed on male-only cohorts. There is clear evidence that disproportionately large numbers of females do not meet diagnostic criteria and are then excluded from ongoing autism research. Another issue is a long-standing assumption that the female autism phenotype is broadly equivalent to that of the male autism phenotype. Thus, models derived from male-based studies could be applicable to females. However, it is now emerging that certain patterns of social behaviour may be very different in females. This includes a specific type of social behaviour called camouflaging or masking, linked to attempts to disguise autistic characteristics. With respect to research in the field of sex/gender cognitive neuroscience, there is emerging evidence of female differences in patterns of connectivity and/or activation in the social brain that are at odds with those reported in previous, male-only studies. Decades of research have excluded or overlooked females on the autistic spectrum, resulting in the construction of inaccurate and misleading cognitive neuroscience models, and missed opportunities to explore the brain bases of this highly complex condition. A note of warning needs to be sounded about inferences drawn from past research, but if future research addresses this problem of male bias, then a deeper understanding of autism as a whole, as well as in previously overlooked females, will start to emerge.

Autism is a neurodevelopmental condition, behaviourally identified, which is generally characterised by social communication differences, and restrictive and repetitive patterns of behaviour and interests. It has long been claimed that it is more common in males, with oft-quoted ratios of 4M: 1F. This has been reflected in the development of diagnostic criteria for autism and, consequently, of measures of eligibility for autism research programmes, with females being (as is now emerging) disproportionately excluded.As outlined in this review, this issue has been particularly problematic in brain-based studies of autism. Many studies have only tested male autistic participants, or minimal numbers of autistic females. By default, sex differences were not examined. But the impression given by such research reports has commonly been that the findings would be applicable to all autistic individuals.Recent psychological and clinical research has shown that there are a significant number of autistic females who have been missed by traditional diagnostic practices. Their inclusion has increased their eligibility for autism research studies. With respect to brain research, it has become possible to devise studies with matched numbers of autistic females and males, and to replicate studies that have previously only tested males. Newly emerging findings from such studies are demonstrating that the 'robust' autism-related differences previously observed in autistic male-only cohorts do not fully generalise to autistic females.It will be necessary to exercise caution in drawing inferences from previous male-biased studies of the autistic brain. However, the identification and inclusion of previously excluded female autistic participants hopefully offers more accurate insights into this highly complex and heterogeneous condition.

Bridging cognitive neuroscience and education: Insights from EEG recording during mathematical proof evaluation.

BACKGROUND: Much of modern mathematics education prioritizes symbolic formalism even at the expense of non-symbolic intuition, we contextualize our study in the ongoing debates on the balance between symbolic and non-symbolic reasoning. We explore the dissociation of oscillatory dynamics between algebraic (symbolic) and geometric (non-symbolic) processing in advanced mathematical reasoning during a naturalistic design. METHOD: Employing mobile EEG technology, we investigated students' beta and gamma wave patterns over frontal and parietal regions while they engaged with mathematical demonstrations in symbolic and non-symbolic formats within a tutor-student framework. We used extended, naturalistic stimuli to approximate an authentic educational setting. CONCLUSION: Our findings reveal nuanced distinctions in neural processing, particularly in terms of gamma waves and activity in parietal regions. Furthermore, no clear overall format preference emerged from the neuroscientific perspective despite students rating symbolic demonstrations higher for understanding and familiarity.

Getting closer to social interactions using electroencephalography in developmental cognitive neuroscience.

The field of developmental cognitive neuroscience is advancing rapidly, with large-scale, population-wide, longitudinal studies emerging as a key means of unraveling the complexity of the developing brain and cognitive processes in children. While numerous neuroscientific techniques like functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) have proved advantageous in such investigations, this perspective proposes a renewed focus on electroencephalography (EEG), leveraging underexplored possibilities of EEG. In addition to its temporal precision, low costs, and ease of application, EEG distinguishes itself with its ability to capture neural activity linked to social interactions in increasingly ecologically valid settings. Specifically, EEG can be measured during social interactions in the lab, hyperscanning can be used to study brain activity in two (or more) people simultaneously, and mobile EEG can be used to measure brain activity in real-life settings. This perspective paper summarizes research in these three areas, making a persuasive argument for the renewed inclusion of EEG into the toolkit of developmental cognitive and social neuroscientists.

Overcoming boundaries: Interdisciplinary challenges and opportunities in cognitive neuroscience.

Cognitive neuroscience has considerable untapped potential to translate our understanding of brain function into applications that maintain, restore, or enhance human cognition. Complex, real-world phenomena encountered in daily life, professional contexts, and in the arts, can also be a rich source of information for better understanding cognition, which in turn can lead to advances in knowledge and health outcomes. Interdisciplinary work is needed for these bi-directional benefits to be realized. Our cognitive neuroscience team has been collaborating on several interdisciplinary projects: hardware and software development for brain stimulation, measuring human operator state in safety-critical robotics environments, and exploring emotional regulation in actors who perform traumatic narratives. Our approach is to study research questions of mutual interest in the contexts of domain-specific applications, using (and sometimes improving) the experimental tools and techniques of cognitive neuroscience. These interdisciplinary attempts are described as case studies in the present work to illustrate non-trivial challenges that come from working across traditional disciplinary boundaries. We reflect on how obstacles to interdisciplinary work can be overcome, with the goals of enriching our understanding of human cognition and amplifying the positive effects cognitive neuroscientists have on society and innovation.

Model Virtues in Computational Cognitive Neuroscience.

There is an abundance of computational models in cognitive neuroscience. A framework for what is desirable in a model, what justifies the introduction of a new one, or what makes one better than another is lacking, however. In this article, we examine key qualities ("virtues") that are desirable in computational models, and how these are interrelated. To keep the scope of the article manageable, we focus on the field of cognitive control, where we identified six "model virtues": empirical accuracy, empirical scope, functional analysis, causal detail, biological plausibility, and psychological plausibility. We first illustrate their use in published work on Stroop modeling and then discuss what expert modelers in the field of cognitive control said about them in a series of qualitative interviews. We found that virtues are interrelated and that their value depends on the modeler's goals, in ways that are not typically acknowledged in the literature. We recommend that researchers make the reasons for their modeling choices more explicit in published work. Our work is meant as a first step. Although our focus here is on cognitive control, we hope that our findings will spark discussion of virtues in other fields as well.

A new era in cognitive neuroscience: the tidal wave of artificial intelligence (AI).

Translating artificial intelligence techniques into the realm of cognitive neuroscience holds promise for significant breakthroughs in our ability to probe the intrinsic mechanisms of the brain. The recent unprecedented development of robust AI models is changing how and what we understand about the brain. In this Editorial, we invite contributions for a BMC Neuroscience Collection on "AI and Cognitive Neuroscience".

Stanislas Dehaene.

Stanislas Dehaene is a cognitive neuroscientist elucidating the biological mechanisms that give rise to human perception and cognition. In a conversation with Neuron, he talks about his ongoing interest in consciousness research, the role of theory in neuroscience, and his current work on education and the science of learning.

Models need mechanisms, but not labels.

The target article proposes a model involving the important but not well-investigated topics of curiosity and creativity. The model, however, falls short of providing convincing explanations of the basic mechanisms underlying these phenomena. We outline the importance of mechanistic thinking in dealing with the concepts outlined in this article specifically and within psychology and cognitive neuroscience in general.

The SocialVidStim: a video database of positive and negative social evaluation stimuli for use in social cognitive neuroscience paradigms.

This paper describes the SocialVidStim-a database of video stimuli available to the scientific community depicting positive and negative social evaluative and neutral statements. The SocialVidStim comprises 53 diverse individuals reflecting the demographic makeup of the USA, ranging from 9 to 41 years old, saying 20-60 positive and 20-60 negative social evaluative statements (e.g. 'You are a very trustworthy/annoying person'), and 20-60 neutral statements (e.g. 'The sky is blue'), totaling 5793 videos post-production. The SocialVidStim are designed for use in behavioral and functional magetic resonance imaging paradigms, across developmental stages, in diverse populations. This study describes stimuli development and reports initial validity and reliability data on a subset videos (N = 1890) depicting individuals aged 18-41 years. Raters perceive videos as expected: positive videos elicit positively valenced ratings, negative videos elicit negatively valenced ratings and neutral videos are rated as neutral. Test-retest reliability data demonstrate intraclass correlations in the good-to-excellent range for negative and positive videos and the moderate range for neutral videos. We also report small effects on valence and arousal that should be considered during stimuli selection, including match between rater and actor sex and actor believability. The SocialVidStim is a resource for researchers and we offer suggestions for using the SocialVidStim in future research.

Fractals in Neuropsychology and Cognitive Neuroscience.

The fractal dimension of cognition refers to the idea that the cognitive processes of the human brain exhibit fractal properties. This means that certain patterns of cognitive activity, such as visual perception, memory, language, or problem-solving, can be described using the mathematical concept of fractal dimension.The idea that cognition is fractal has been proposed by some researchers as a way to understand the complex, self-similar nature of the human brain. However, it's a relatively new idea and is still under investigation, so it's not yet clear to what extent cognitive processes exhibit fractal properties or what implications this might have for our understanding of the brain and clinical practice. Indeed, the mission of the "fractal neuroscience" field is to define the characteristics of fractality in human cognition in order to differently characterize the emergence of brain disorders.

Efectos del tratamiento con andrógenos sobre la neurocognición en adolescentes transgénero de mujer a hombre / Androgen treatment effects on neurocognition in female-to-male transgender adolescents

Introducción Se ha planteado la hipótesis de que la neurocognición en personas transgénero durante el tratamiento hormonal cruzado podría aproximarse a la del género subjetivo. Sin embargo, la investigación sobre este tema ha producido resultados inconsistentes y, hasta donde sabemos, ningún estudio ha investigado los cambios neurocognitivos en adolescentes transgénero de mujer a hombre (FM) tratados con andrógenos. Sujetos y métodos Quince adolescentes transgénero FM (14-17 años) se sometieron a pruebas neuropsicológicas para examinar los efectos de los andrógenos en sus habilidades visuoespaciales, memoria verbal, velocidad de procesamiento y funciones ejecutivas. Utilizamos un diseño longitudinal en el que se evaluó a 10 participantes dos veces, antes y después de recibir, durante 12 meses, tratamiento con testosterona. Este grupo también se comparó con cinco adolescentes transgénero FM sin tratamiento con andrógenos. Resultados Los participantes evaluados antes y después de 12 meses de tratamiento con andrógenos mejoraron significativamente en velocidad de procesamiento en una tarea visuoespacial (prueba de la figura compleja de Rey-Osterrieth) y en una tarea visual (Stroop), en una tarea de memoria verbal (test de aprendizaje verbal España-Complutense) y en interferencia (Stroop), y exhibieron un menor control de la impulsividad (test de percepción de diferencias revisado). Los adolescentes que recibieron tratamiento con andrógenos mostraron un peor control de la impulsividad cognitiva que los adolescentes que no recibieron tratamiento con andrógenos. Conclusiones Los resultados indican que los andrógenos influyen en la memoria verbal, la interferencia cognitiva, el control de la impulsividad y la velocidad de procesamiento. (AU)

INTRODUCTION It has been hypothesized that cognitive and memory-related brain function in transgender during cross-sex hormonal treatment might be activated towards that of the subjective gender. However, research on this topic has produced inconsistent results, and to the best of our knowledge no studies have investigated neurocognitive changes in androgen-treated female-to-male (FM) transgender adolescents. SUBJECTS AND METHODS A total of 15 FM transgender adolescents (14-17 years) underwent neuropsychological testing in order to examine the effects of androgen on visuo-spacial abilities, verbal memory language, processing speed and executive functions. We used a longitudinal design in which 10 participants were tested twice, before and after receiving 12 months of testosterone treatment. This group was also compared with 5 FM transgender adolescents off-androgen treatment. RESULTS Participants tested before and after 12 months of androgen treatment improved significantly on processing speed in a visuo-spatial (Rey-Osterrieth complex figure test) and in a visuo-oral task (Stroop), their performance on a verbal memory task (TAVEC) and on interference (Stroop) and they exhibited lower impulsivity control (CARAS-R). On-androgen treatment adolescents exhibited worse cognitive impulsivity control than off-androgen treatment adolescents. CONCLUSIONS The results indicate that androgen has an influence on immediate verbal memory, cognitive interference, impulsivity control and processing speed. (AU)

Deep social neuroscience: the promise and peril of using artificial neural networks to study the social brain.

This review offers an accessible primer to social neuroscientists interested in neural networks. It begins by providing an overview of key concepts in deep learning. It then discusses three ways neural networks can be useful to social neuroscientists: (i) building statistical models to predict behavior from brain activity; (ii) quantifying naturalistic stimuli and social interactions; and (iii) generating cognitive models of social brain function. These applications have the potential to enhance the clinical value of neuroimaging and improve the generalizability of social neuroscience research. We also discuss the significant practical challenges, theoretical limitations and ethical issues faced by deep learning. If the field can successfully navigate these hazards, we believe that artificial neural networks may prove indispensable for the next stage of the field's development: deep social neuroscience.

A synergetic turn in cognitive neuroscience of brain diseases.

Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.

The involvement of the human prefrontal cortex in the emergence of visual awareness.

Exploring the neural mechanisms of awareness is a fundamental task of cognitive neuroscience. There is an ongoing dispute regarding the role of the prefrontal cortex (PFC) in the emergence of awareness, which is partially raised by the confound between report- and awareness-related activity. To address this problem, we designed a visual awareness task that can minimize report-related motor confounding. Our results show that saccadic latency is significantly shorter in the aware trials than in the unaware trials. Local field potential (LFP) data from six patients consistently show early (200-300ms) awareness-related activity in the PFC, including event-related potential and high-gamma activity. Moreover, the awareness state can be reliably decoded by the neural activity in the PFC since the early stage, and the neural pattern is dynamically changed rather than being stable during the representation of awareness. Furthermore, the enhancement of dynamic functional connectivity, through the phase modulation at low frequency, between the PFC and other brain regions in the early stage of the awareness trials may explain the mechanism of conscious access. These results indicate that the PFC is critically involved in the emergence of awareness.

Normative Processing Needs Multiple Levels of Explanation: From Algorithm to Implementation.

Norms are the rules about what is allowed or forbidden by social groups. A key debate for norm psychology is whether these rules arise from mechanisms that are domain-specific and genetically inherited or domain-general and deployed for many other nonnorm processes. Here we argue for the importance of assessing and testing domain-specific and domain-general processes at multiple levels of explanation, from algorithmic (psychological) to implementational (neural). We also critically discuss findings from cognitive neuroscience supporting that social and nonsocial learning processes, essential for accounts of cultural evolution, can be dissociated at these two levels. This multilevel framework can generate new hypotheses and empirical tests of cultural evolution accounts of norm processing against purely domain-specific nativist alternatives.

Searching for the Metaverse: Neuroscience of Physical and Digital Communities.

What distinguishes real-world communities from their online counterparts? Social and cognitive neuroscience research on social networks and collective intentionality will be used in the article to answer this question. Physical communities are born in places. And places engage "we-mode" neurobiological and cognitive processes as behavioral synchrony, shared attention, deliberate attunement, interbrain synchronization, and so on, which create coherent social networks of very different individuals who are supported by a "wisdom of crowd." Digital technologies remove physical boundaries, giving people more freedom to choose their activities and groups. At the same time, however, the lack of physical co-presence of community members significantly reduces their possibility of activating "we-mode" cognitive processes and social motivation. Because of this, unlike physical communities that allow interaction between people from varied origins and stories, digital communities are always made up of people who have the same interests and knowledge (communities of practice). This new situation disrupts the "wisdom of crowd," making the community more radical and less accurate (polarization effect), allowing influential users to wield disproportionate influence over the group's beliefs, and producing inequalities in the distribution of social capital. However, a new emergent technology-the Metaverse-has the potential to reverse this trend. Several studies have revealed that virtual and augmented reality-the major technologies underlying the Metaverse-can engage the same neurobiological and cognitive "we-mode" processes as real-world environments. If the many flaws in this technology are fixed, it might encourage people to engage in more meaningful and constructive interactions in online communities.

The cognitive neuroscience of self-awareness: Current framework, clinical implications, and future research directions.

Self-awareness, the ability to take oneself as the object of awareness, has been an enigma for our species, with different answers to this question being provided by religion, philosophy, and, more recently, science. The current review aims to discuss the neurocognitive mechanisms underlying self-awareness. The multidimensional nature of self-awareness will be explored, suggesting how it can be thought of as an emergent property observed in different cognitive complexity levels, within a predictive coding approach. A presentation of alterations of self-awareness in neuropsychiatric conditions will ground a discussion on alternative frameworks to understand this phenomenon, in health and psychopathology, with future research directions being indicated to fill current gaps in the literature. This article is categorized under: Philosophy > Consciousness Psychology > Brain Function and Dysfunction Neuroscience > Cognition.

Exploring a formal approach to selecting studies for replication: A feasibility study in social neuroscience.

Replication of published results is crucial for ensuring the robustness and self-correction of research, yet replications are scarce in many fields. Replicating researchers will therefore often have to decide which of several relevant candidates to target for replication. Formal strategies for efficient study selection have been proposed, but none have been explored for practical feasibility - a prerequisite for validation. Here we move one step closer to efficient replication study selection by exploring the feasibility of a particular selection strategy that estimates replication value as a function of citation impact and sample size (Isager, van 't Veer, & Lakens, 2021). We tested our strategy on a sample of fMRI studies in social neuroscience. We first report our efforts to generate a representative candidate set of replication targets. We then explore the feasibility and reliability of estimating replication value for the targets in our set, resulting in a dataset of 1358 studies ranked on their value of prioritising them for replication. In addition, we carefully examine possible measures, test auxiliary assumptions, and identify boundary conditions of measuring value and uncertainty. We end our report by discussing how future validation studies might be designed. Our study demonstrates the importance of investigating how to implement study selection strategies in practice. Our sample and study design can be extended to explore the feasibility of other formal study selection strategies that have been proposed.