The mind's golden cage and cognition in the wild

How attention and working memory work together in the pursuit of goals: The development of the sampling-remembering trade-off

Most work in the last 50 years on visual working memory and attention has used a classic psychophysical setup: participants are instructed to attend to, or remember, a set of items. This setup sidesteps the role of cognitive control; effort is maximal, tasks are simple, and strategies are limited. While this approach has yielded important insights, it provides no clear path toward an integrative theory (Kristjánsson & Draschkow, 2021) and, like studying a town's walkability by having its college students run the 50-yard dash, it runs the danger of focusing on edge cases. Here, in this theoretical opinion article, we argue for an approach where dynamic relationships between the agent and the environment are understood functionally, in light of an agent's goals. This means a shift in emphasis from the performance of the mechanisms underlying a narrow task ("remember these items!") to their control in pursuit of a naturalistic goal ("make a sandwich!", Land & Hayhoe, 2001). Here, we highlight the sampling-remembering trade-off between exploiting goal-relevant information in the environment versus maintaining it in working memory. We present a dynamic feedback model of this trade-off - where the individual weighs the subjective costs of accessing external information versus those of maintaining it in memory - using insights from existing cognitive control models based on economic principles (Kool & Botvinick, 2018). This trade-off is particularly interesting in children, as the optimal use of internal resources is even more crucial when limited. Our model makes some specific predictions for future research: 1) an individual child strikes a preferred balance between the effort to attend to goal-relevant information in the environment versus the effort to maintain it in working memory, 2) in order to maintain this balance as underlying memory and cognitive control mechanisms improve with age, the child will have to increasingly shift toward remembering, and 3) older children will show greater adaptability to changing task demands.

Inspired by struggle: A personal journey to global precision brain health

Dr. Agustin Ibanez joins iScience editor Maryam Fard to discuss his personal journey in brain health research. He advocates for integrating diversity in neurodegeneration studies, crucial for understanding conditions like dementia. He founded ReDLat and BrainLat, advancing research across Latin America and empowering underrepresented voices. This inspiring discussion showcases his commitment to fostering interdisciplinary approaches to drive global brain health progress. Dr. Ibanez is also the Guest Editor of iScience's Special Issue: "Transdisciplinary approaches to arts and health: Integrating creative practice in clinical and public health contexts."

Levelling up the study of animal gameplay

Play in humans and other animals is widespread and intuitive to recognise. Creative, unstructured play is difficult to quantify, but games direct play towards a specific goal and have defined rules, mechanics and rewards. To date, games have been under-utilised in human and animal behavioural neuroscience. This review evaluates evidence that animals can play human games, including game-theory contests, tangible games, and video games. Animals can be trained to play various human games with cognitive capacities such as role adoption, rule-following and performance monitoring. Animals can make irrational gameplay decisions that jeopardise rewards and have salient emotional responses to winning and losing. Games can advance the field of behavioural neuroscience in several ways. Cognitive tasks can become more engaging and ecologically relevant by adding game elements, known as gamification. Games can be used to induce and measure more naturalistic emotional responses to the process of overcoming (progression/regression) and end state (winning/losing) of cognitive challenges. There is also scope to target specific cognitive skill deficiencies in captive animals using games. However, a recent rapid increase in computerised testing environments raises an important ethical question about the boundary between games and reality for animals.

Allostatic Interoceptive Overload Across Psychiatric and Neurological Conditions

Emerging theories emphasize the crucial role of allostasis (anticipatory and adaptive regulation of the body's biological processes) and interoception (integration, anticipation, and regulation of internal bodily states) in adjusting physiological responses to environmental and bodily demands. In this review, we explore the disruptions in integrated allostatic interoceptive mechanisms in psychiatric and neurological disorders, including anxiety, depression, Alzheimer's disease, and frontotemporal dementia. We assess the biological mechanisms associated with allostatic interoception, including whole-body cascades, brain structure and function of the allostatic interoceptive network, heart-brain interactions, respiratory-brain interactions, the gut-brain-microbiota axis, peripheral biological processes (inflammatory, immune), and epigenetic pathways. These processes span psychiatric and neurological conditions and call for developing dimensional and transnosological frameworks. We synthesize new pathways to understand how allostatic interoceptive processes modulate interactions between environmental demands and biological functions in brain disorders. We discuss current limitations of the framework and future transdisciplinary developments. This review opens a new research agenda for understanding how allostatic interoception involves brain predictive coding in psychiatry and neurology, allowing for better clinical application and the development of new therapeutic interventions.

Ecological brain: reframing the study of human behaviour and cognition

The last decade has seen substantial advances in the capacity to record behaviour and neural activity in humans in real-world settings, to simulate real-world situations in laboratory settings and to apply sophisticated analyses to large-scale data. Along with these developments, a growing number of groups has begun to advocate for real-world neuroscience and cognitive science. Here, we review the arguments and the available methods for real-world research and outline an overarching framework that embeds key ideas proposed in the literature integrating them into a cyclic process of 'bringing the lab to the real world' (recording behavioural and neural activity in real-world settings) and 'bringing the real-world to the lab' (manipulating the environments in which behaviours occur in the laboratory) that combines exploratory and confirmatory research and is interdisciplinary (including those sciences concerned with the natural, built or virtual environment). We highlight the benefits brought by this framework emphasizing the greater potential for novel discovery, theory development and human-centred applications to the environment.

Neuroimaging Meta-Analyses Reveal Convergence of Interoception, Emotion, and Social Cognition Across Neurodegenerative Diseases

BACKGROUND

Simultaneous interoceptive, emotional, and social cognition deficits are observed across neurodegenerative diseases. Indirect evidence suggests shared neurobiological bases underlying these impairments, termed the allostatic-interoceptive network (AIN). However, no study has yet explored the convergence of these deficits in neurodegenerative diseases or examined how structural and functional changes contribute to cross-domain impairments.

METHODS

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) activated likelihood estimate meta-analysis encompassed studies that met the following inclusion criteria: interoception, emotion, or social cognition tasks; neurodegenerative diseases (behavioral variant frontotemporal dementia, primary progressive aphasias, Alzheimer's disease, Parkinson's disease, multiple sclerosis); and neuroimaging (structural: magnetic resonance imaging voxel-based morphometry; functional: magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography).

RESULTS

Of 20,593 studies, 170 met inclusion criteria (58 interoception, 65 emotion, and 47 social cognition) involving 7032 participants (4963 patients and 2069 healthy control participants). In all participants combined, conjunction analyses revealed AIN involvement of the insula, amygdala, orbitofrontal cortex, anterior cingulate, striatum, thalamus, and hippocampus across domains. In behavioral variant frontotemporal dementia, this conjunction was replicated across domains, with further involvement of the temporal pole, temporal fusiform cortex, and angular gyrus. A convergence of interoception and emotion in the striatum, thalamus, and hippocampus in Parkinson's disease and the posterior insula in primary progressive aphasias was also observed. In Alzheimer's disease and multiple sclerosis, disruptions in the AIN were observed during interoception, but no convergence with emotion was identified.

CONCLUSIONS

Neurodegeneration induces dysfunctional AIN across atrophy, connectivity, and metabolism, more accentuated in behavioral variant frontotemporal dementia. Findings bolster the predictive coding theories of large-scale AIN, calling for more synergistic approaches to understanding interoception, emotion, and social cognition impairments in neurodegeneration.

The resolution of proactive interference in a novel visual working memory task: A behavioral and pupillometric study

Proactive interference (PI) occurs when previously learned information impairs memory for more recently learned information. Most PI studies have employed verbal stimuli, while the role of PI in visual working memory (VWM) has had relatively little attention. In the verbal domain, Johansson and colleagues (2018) found that pupil diameter - a real-time neurophysiological index of cognitive effort - reflects the accumulation and resolution of PI. Here we use a novel, naturalistic paradigm to test the behavioral and pupillary correlates of PI resolution for what-was-where item-location bindings in VWM. Importantly, in our paradigm, trials (PI vs. no-PI condition) are mixed in a block, and participants are naïve to the condition until they are tested. This design sidesteps concerns about differences in encoding strategies or generalized effort differences between conditions. Across three experiments (N = 122 total) we assessed PI's effect on VWM and whether PI resolution during memory retrieval is associated with greater cognitive effort (as indexed by the phasic, task-evoked pupil response). We found strong support for PI's detrimental effect on VWM (even with our spatially distributed stimuli), but no consistent link between interference resolution and effort during memory retrieval (this, even though the pupil was a reliable indicator that higher-performing individuals tried harder during memory encoding). We speculate that when explicit strategies are minimized, and PI resolution relies primarily on implicit processing, the effect may not be sufficient to trigger a robust pupillometric response.

Biomarkers of neurodegeneration across the Global South

Research on neurodegenerative diseases has predominantly focused on high-income countries in the Global North. This Series paper describes the state of biomarker evidence for neurodegeneration in the Global South, including Latin America, Africa, and countries in south, east, and southeast Asia. Latin America shows growth in fluid biomarker and neuroimaging research, with notable advancements in genetics. Research in Africa focuses on genetics and cognition but there is a paucity of data on fluid and neuroimaging biomarkers. South and east Asia, particularly India and China, has achieved substantial progress in plasma, neuroimaging, and genetic studies. However, all three regions face several challenges in the form of a lack of harmonisation, insufficient funding, and few comparative studies both within the Global South, and between the Global North and Global South. Other barriers include scarce infrastructure, lack of knowledge centralisation, genetic and cultural diversity, sociocultural stigmas, and restricted access to tools such as PET scans. However, the diverse ethnic, genetic, economic, and cultural backgrounds in the Global South present unique opportunities for bidirectional learning, underscoring the need for global collaboration to enhance the understanding of dementia and brain health.

Rewilding psychology

Some commentators have recently argued that scientific psychology is overly reliant on artificial laboratory-based activities and that it undervalues field-based investigations. However, it remains unclear how a field-based programme of psychological research might be organized in a scalable way. We examine and compare two existing field-based approaches: Roger Barker's behaviour settings programme and Edwin Hutchins's distributed cognition programme. Both programmes prioritize observational work, and both reject the individual as the unit of analysis in favour of a community-scale unit. However, whereas the behaviour settings programme is concerned with structural properties of community life, distributed cognition is concerned more narrowly with the functional analysis of expert team performance. We discuss how these programmes can inform a future community-scale approach to studying psychology in the wild. We conclude that the two programmes are proof of concept of the possibility of a scientific psychology that rejects methodological individualism. This article is part of the theme issue 'People, places, things and communities: expanding behaviour settings theory in the twenty-first century'.

Multisensory integration of speech and gestures in a naturalistic paradigm

Speech comprehension is crucial for human social interaction, relying on the integration of auditory and visual cues across various levels of representation. While research has extensively studied multisensory integration (MSI) using idealised, well-controlled stimuli, there is a need to understand this process in response to complex, naturalistic stimuli encountered in everyday life. This study investigated behavioural and neural MSI in neurotypical adults experiencing audio-visual speech within a naturalistic, social context. Our novel paradigm incorporated a broader social situational context, complete words, and speech-supporting iconic gestures, allowing for context-based pragmatics and semantic priors. We investigated MSI in the presence of unimodal (auditory or visual) or complementary, bimodal speech signals. During audio-visual speech trials, compared to unimodal trials, participants more accurately recognised spoken words and showed a more pronounced suppression of alpha power-an indicator of heightened integration load. Importantly, on the neural level, these effects surpassed mere summation of unimodal responses, suggesting non-linear MSI mechanisms. Overall, our findings demonstrate that typically developing adults integrate audio-visual speech and gesture information to facilitate speech comprehension in noisy environments, highlighting the importance of studying MSI in ecologically valid contexts.

Gaming expertise induces meso‑scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling

Video games are a valuable tool for studying the effects of training and neural plasticity on the brain. However, the underlying mechanisms related to plasticity-associated brain structural changes and their impact on brain dynamics are unknown. Here, we used a semi-empirical whole-brain model to study structural neural plasticity mechanisms linked to video game expertise. We hypothesized that video game expertise is associated with neural plasticity-mediated changes in structural connectivity that manifest at the meso‑scale level, resulting in a more segregated functional network topology. To test this hypothesis, we combined structural connectivity data of StarCraft II video game players (VGPs, n = 31) and non-players (NVGPs, n = 31), with generic fMRI data from the Human Connectome Project and computational models, to generate simulated fMRI recordings. Graph theory analysis on simulated data was performed during both resting-state conditions and external stimulation. VGPs' simulated functional connectivity was characterized by a meso‑scale integration, with increased local connectivity in frontal, parietal, and occipital brain regions. The same analyses at the level of structural connectivity showed no differences between VGPs and NVGPs. Regions that increased their connectivity strength in VGPs are known to be involved in cognitive processes crucial for task performance such as attention, reasoning, and inference. In-silico stimulation suggested that differences in FC between VGPs and NVGPs emerge in noisy contexts, specifically when the noisy level of stimulation is increased. This indicates that the connectomes of VGPs may facilitate the filtering of noise from stimuli. These structural alterations drive the meso‑scale functional changes observed in individuals with gaming expertise. Overall, our work sheds light on the mechanisms underlying structural neural plasticity triggered by video game experiences.

Emerging Theories of Allostatic-Interoceptive Overload in Neurodegeneration

Recent integrative multilevel models offer novel insights into the etiology and course of neurodegenerative conditions. The predictive coding of allostatic-interoception theory posits that the brain adapts to environmental demands by modulating internal bodily signals through the allostatic-interoceptive system. Specifically, a domain-general allostatic-interoceptive network exerts adaptive physiological control by fine-tuning initial top-down predictions and bottom-up peripheral signaling. In this context, adequate adaptation implies the minimization of prediction errors thereby optimizing energy expenditure. Abnormalities in top-down interoceptive predictions or peripheral signaling can trigger allostatic overload states, ultimately leading to dysregulated interoceptive and bodily systems (endocrine, immunological, circulatory, etc.). In this context, environmental stress, social determinants of health, and harmful exposomes (i.e., the cumulative life-course exposition to different environmental stressors) may interact with physiological and genetic factors, dysregulating allostatic interoception and precipitating neurodegenerative processes. We review the allostatic-interoceptive overload framework across different neurodegenerative diseases, particularly in the behavioral variant frontotemporal dementia (bvFTD). We describe how concepts of allostasis and interoception could be integrated with principles of predictive coding to explain how the brain optimizes adaptive responses, while maintaining physiological stability through feedback loops with multiple organismic systems. Then, we introduce the model of allostatic-interoceptive overload of bvFTD and discuss its implications for the understanding of pathophysiological and neurocognitive abnormalities in multiple neurodegenerative conditions.

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.

Walking the talk for dementia: A unique immersive, embodied, and multi-experiential initiative

Coping with dementia requires an integrated approach encompassing personal, health, research, and community domains. Here we describe "Walking the Talk for Dementia," an immersive initiative aimed at empowering people with dementia, enhancing dementia understanding, and inspiring collaborations. This initiative involved 300 participants from 25 nationalities, including people with dementia, care partners, clinicians, policymakers, researchers, and advocates for a 4-day, 40 km walk through the Camino de Santiago de Compostela, Spain. A 2-day symposium after the journey provided novel transdisciplinary and horizontal structures, deconstructing traditional hierarchies. The innovation of this initiative lies in its ability to merge a physical experience with knowledge exchange for diversifying individuals' understanding of dementia. It showcases the transformative potential of an immersive, embodied, and multi-experiential approach to address the complexities of dementia collaboratively. The initiative offers a scalable model to enhance understanding, decrease stigma, and promote more comprehensive and empathetic dementia care and research.

Testing the hormesis hypothesis on motor behavior under stress

While much research has focused on the deleterious effects of stress on goal-directed behavior in recent decades, current views increasingly discuss growth under stress, often assuming dose-dependent effects of stress in a curvilinear association. This is based on the concept of hormesis, which postulates a strengthening effect of stress at low-to-moderate doses. Leveraging this approach, hormetic curves indicate under which stress dose an individual is able to maintain or even increase goal-directed behavior. The present study aimed to test the hormetic effect of low-to-moderate stress on tactical movement performance in the context of police operational scenarios in virtual reality. In teams of three to four, 37 riot police officers had to search a building for a potentially aggressive perpetrator in three scenarios with escalating stress potential (i.e., increasing weapon violence and number of civilians). Tactical movement performance as behavioral response was quantified by the sample entropy of each officer's velocity derived from positional data. To account for inter-individuality in response to the scenarios, we assessed self-reported stress, anxiety, mental effort, and vagally mediated heart rate variability. Specifically, we tested the quadratic associations between tactical movement performance and stress parameters, respectively. Random-intercept-random-slope regressions revealed neither significant linear nor quadratic associations between any of the stress parameters and performance. While we did not find evidence for hormesis in the present study, it stimulates theoretical discussions about the definition of "baseline" functioning and how the understanding of hormesis can move from psychological to behavioral adaptations to stressors.

Intrinsic timescales and predictive allostatic interoception in brain health and disease

The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.

The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds

The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21-89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.

Gaming expertise induces meso-scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling Gaming expertise, neuroplasticity and functional dynamics

Video games are a valuable tool for studying the effects of training and neural plasticity on the brain. However, the underlaying mechanisms related to plasticity-induced brain structural changes and their impact in brain dynamics are unknown. Here, we used a semi-empirical whole-brain model to study structural neural plasticity mechanisms linked to video game expertise. We hypothesized that video game expertise is associated with neural plasticity-mediated changes in structural connectivity that manifest at the meso-scale level, resulting in a more segregated functional network topology. To test this hypothesis, we combined structural connectivity data of StarCraft II video game players (VGPs, n = 31) and non-players (NVGPs, n = 31), with generic fMRI data from the Human Connectome Project and computational models, with the aim of generating simulated fMRI recordings. Graph theory analysis on simulated data was performed during both resting-state conditions and external stimulation. VGPs' simulated functional connectivity was characterized by a meso-scale integration, with increased local connectivity in frontal, parietal and occipital brain regions. The same analyses at the level of structural connectivity showed no differences between VGPs and NVGPs. Regions that increased their connectivity strength in VGPs are known to be involved in cognitive processes crucial for task performance such as attention, reasoning, and inference. In-silico stimulation suggested that differences in FC between VGPs and NVGPs emerge in noisy contexts, specifically when the noisy level of stimulation is increased. This indicates that the connectomes of VGPs may facilitate the filtering of noise from stimuli. These structural alterations drive the meso-scale functional changes observed in individuals with gaming expertise. Overall, our work sheds light into the mechanisms underlying structural neural plasticity triggered by video game experiences.

Navigating the multiple dimensions of the creativity-mental disorder link: a Convergence Mental Health perspective

BACKGROUND

This paper discusses a paradox in mental health. It manifests as a relationship between adverse "bad" effects (suffering, clinical costs, loss of productivity) in individuals and populations and advantageous "good" aspects of mental disorders. These beneficial aspects (scientific, artistic and political accomplishments) emanate at the societal level through the frequently unprecedented creativity of people suffering from mental disorders and their relatives. Such gains can contribute to societal innovation and problem-solving. Especially in times of accelerated social-ecological change, approaches are needed that facilitate best-possible mental health care but also recognize creative ideas conducive to beneficial clinical and social-ecological innovations as soon as possible.

DISCUSSION

This paper emphasizes the need to account for creativity as a crucial component in evolving mental health systems and societies. It highlights the need for wide-ranging approaches and discusses how research targeting multiple facets (e.g., brain level, cognitive neuroscience, psychiatry, neurology, socio-cultural, economic and other factors) might further our understanding of the creativity-mental disorder link and its importance for innovating mental health systems and societies.

CONCLUSION

Our discussion clarifies that considerable research will be needed to obtain a better understanding of how creativity associated with mental disorders may help to create more sustainable societies on a fast-changing planet through innovative ideas. Given the current-state-of-the-art of research and healthcare management, our discussion is currently speculative. However, it provides a basis for how pros and cons might be studied in the future through transdisciplinary research and collaborations across sectors of society.

Brain capital, ecological development and sustainable environments

The importance of improving brain and mental health and developing sustainable environments is increasingly recognised. Understanding the syndemic interactions between these processes can help address contemporary societal challenges and foster global innovation. Here, we propose a green brain capital model that integrates environmental drivers of brain health and green skills necessary for long-term sustainability and discuss the role of interdisciplinary approaches in promoting individual and collective behavioural changes. We draw on existing literature and research to highlight the connections between brain health, environmental factors and green skills. Environmental factors and exposome can have long-lasting adverse effects on brain health, particularly in vulnerable populations. Investing in green brain capital can prepare societies to address global crises. Green skills, including creativity, ecological intelligence and digital literacy, are critical for promoting sustainable environments. Access to nature improves brain and mental health, and interdisciplinary fields such as neurourbanism can inform urban planning to benefit citizens' well-being. Building brain capital and environmental sustainability interactions requires increasing future generations' awareness, education and training. A comprehensive approach to green brain capital can enable greater societal scaling, synergistically protecting brain health and environmental sustainability.

Frontotemporal dementia presentation in patients with heterozygous p.H157Y variant of TREM2

BACKGROUND

The triggering receptor expressed on myeloid cell 2 (TREM2) is a major regulator of neuroinflammatory processes in neurodegeneration. To date, the p.H157Y variant of TREM2 has been reported only in patients with Alzheimer's disease. Here, we report three patients with frontotemporal dementia (FTD) from three unrelated families with heterozygous p.H157Y variant of TREM2: two patients from Colombian families (study 1) and a third Mexican origin case from the USA (study 2).

METHODS

To determine if the p.H157Y variant might be associated with a specific FTD presentation, we compared in each study the cases with age-matched, sex-matched and education-matched groups-a healthy control group (HC) and a group with FTD with neither TREM2 mutations nor family antecedents (Ng-FTD and Ng-FTD-MND).

RESULTS

The two Colombian cases presented with early behavioural changes, greater impairments in general cognition and executive function compared with both HC and Ng-FTD groups. These patients also exhibited brain atrophy in areas characteristic of FTD. Furthermore, TREM2 cases showed increased atrophy compared with Ng-FTD in frontal, temporal, parietal, precuneus, basal ganglia, parahippocampal/hippocampal and cerebellar regions. The Mexican case presented with FTD and motor neuron disease (MND), showing grey matter reduction in basal ganglia and thalamus, and extensive TDP-43 type B pathology.

CONCLUSION

In all TREM2 cases, multiple atrophy peaks overlapped with the maximum peaks of TREM2 gene expression in crucial brain regions including frontal, temporal, thalamic and basal ganglia areas. These results provide the first report of an FTD presentation potentially associated with the p.H157Y variant with exacerbated neurocognitive impairments.

Intellectual cyborgs and the future of science

Unlike classical artificial intelligence (AI), generative AI has the potential to transform scientists into intellectual cyborgs. Leveraging embodied cognition and extended mind theories can help us understand this scientific revolution. Despite ethical concerns, generative AI can enhance research efficiency and accessibility. However, this requires unprecedented proactive regulation and responsible development.

Multimodal, Idiographic Ambulatory Sensing Will Transform our Understanding of Emotion

Emotions are inherently complex - situated inside the brain while being influenced by conditions inside the body and outside in the world - resulting in substantial variation in experience. Most studies, however, are not designed to sufficiently sample this variation. In this paper, we discuss what could be discovered if emotion were systematically studied within persons 'in the wild', using biologically-triggered experience sampling: a multimodal and deeply idiographic approach to ambulatory sensing that links body and mind across contexts and over time. We outline the rationale for this approach, discuss challenges to its implementation and widespread adoption, and set out opportunities for innovation afforded by emerging technologies. Implementing these innovations will enrich method and theory at the frontier of affective science, propelling the contextually situated study of emotion into the future.

Factors associated with healthy aging in Latin American populations

Latin American populations may present patterns of sociodemographic, ethnic and cultural diversity that can defy current universal models of healthy aging. The potential combination of risk factors that influence aging across populations in Latin American and Caribbean (LAC) countries is unknown. Compared to other regions where classical factors such as age and sex drive healthy aging, higher disparity-related factors and between-country variability could influence healthy aging in LAC countries. We investigated the combined impact of social determinants of health (SDH), lifestyle factors, cardiometabolic factors, mental health symptoms and demographics (age, sex) on healthy aging (cognition and functional ability) across LAC countries with different levels of socioeconomic development using cross-sectional and longitudinal machine learning models (n = 44,394 participants). Risk factors associated with social and health disparities, including SDH (β > 0.3), mental health (β > 0.6) and cardiometabolic risks (β > 0.22), significantly influenced healthy aging more than age and sex (with null or smaller effects: β < 0.2). These heterogeneous patterns were more pronounced in low-income to middle-income LAC countries compared to high-income LAC countries (cross-sectional comparisons), and in an upper-income to middle-income LAC country, Costa Rica, compared to China, a non-upper-income to middle-income LAC country (longitudinal comparisons). These inequity-associated and region-specific patterns inform national risk assessments of healthy aging in LAC countries and regionally tailored public health interventions.

Beyond simple laboratory studies: Developing sophisticated models to study rich behavior

Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions. In this article, we argue that psychology and neuroscience should increasingly adopt innovative experimental designs, measurement methods, analysis techniques and sophisticated computational models to probe rich, ecologically valid forms of behavior, including social behavior. We discuss the challenges of studying rich forms of behavior as well as the novel opportunities offered by state-of-the-art methodologies and new sensing technologies, and we highlight the importance of developing sophisticated formal models. We exemplify our arguments by reviewing some recent streams of research in psychology, neuroscience and other fields (e.g., sports analytics, ethology and robotics) that have addressed rich forms of behavior in a model-based manner. We hope that these "success cases" will encourage psychologists and neuroscientists to extend their toolbox of techniques with sophisticated behavioral models - and to use them to study rich forms of behavior as well as the cognitive and neural processes that they engage.

Moving beyond the lab: investigating empathy through the Empirical 5E approach

Empathy is a complex and multifaceted phenomenon that plays a crucial role in human social interactions. Recent developments in social neuroscience have provided valuable insights into the neural underpinnings and bodily mechanisms underlying empathy. This methodology often prioritizes precision, replicability, internal validity, and confound control. However, fully understanding the complexity of empathy seems unattainable by solely relying on artificial and controlled laboratory settings, while overlooking a comprehensive view of empathy through an ecological experimental approach. In this article, we propose articulating an integrative theoretical and methodological framework based on the 5E approach (the "E"s stand for embodied, embedded, enacted, emotional, and extended perspectives of empathy), highlighting the relevance of studying empathy as an active interaction between embodied agents, embedded in a shared real-world environment. In addition, we illustrate how a novel multimodal approach including mobile brain and body imaging (MoBi) combined with phenomenological methods, and the implementation of interactive paradigms in a natural context, are adequate procedures to study empathy from the 5E approach. In doing so, we present the Empirical 5E approach (E5E) as an integrative scientific framework to bridge brain/body and phenomenological attributes in an interbody interactive setting. Progressing toward an E5E approach can be crucial to understanding empathy in accordance with the complexity of how it is experienced in the real world.

Social and non-social working memory in neurodegeneration

Although social functioning relies on working memory, whether a social-specific mechanism exists remains unclear. This undermines the characterization of neurodegenerative conditions with both working memory and social deficits. We assessed working memory domain-specificity across behavioral, electrophysiological, and neuroimaging dimensions in 245 participants. A novel working memory task involving social and non-social stimuli with three load levels was assessed across controls and different neurodegenerative conditions with recognized impairments in: working memory and social cognition (behavioral-variant frontotemporal dementia); general cognition (Alzheimer's disease); and unspecific patterns (Parkinson's disease). We also examined resting-state theta oscillations and functional connectivity correlates of working memory domain-specificity. Results in controls and all groups together evidenced increased working memory demands for social stimuli associated with frontocinguloparietal theta oscillations and salience network connectivity. Canonical frontal theta oscillations and executive-default mode network anticorrelation indexed non-social stimuli. Behavioral-variant frontotemporal dementia presented generalized working memory deficits related to posterior theta oscillations, with social stimuli linked to salience network connectivity. In Alzheimer's disease, generalized working memory impairments were related to temporoparietal theta oscillations, with non-social stimuli linked to the executive network. Parkinson's disease showed spared working memory performance and canonical brain correlates. Findings support a social-specific working memory and related disease-selective pathophysiological mechanisms.

Heterogeneous factors influence social cognition across diverse settings in brain health and age-related diseases

Aging may diminish social cognition, which is crucial for interaction with others, and significant changes in this capacity can indicate pathological processes like dementia. However, the extent to which non-specific factors explain variability in social cognition performance, especially among older adults and in global settings, remains unknown. A computational approach assessed combined heterogeneous contributors to social cognition in a diverse sample of 1063 older adults from 9 countries. Support vector regressions predicted the performance in emotion recognition, mentalizing, and a total social cognition score from a combination of disparate factors, including clinical diagnosis (healthy controls, subjective cognitive complaints, mild cognitive impairment, Alzheimer's disease, behavioral variant frontotemporal dementia), demographics (sex, age, education, and country income as a proxy of socioeconomic status), cognition (cognitive and executive functions), structural brain reserve, and in-scanner motion artifacts. Cognitive and executive functions and educational level consistently emerged among the top predictors of social cognition across models. Such non-specific factors showed more substantial influence than diagnosis (dementia or cognitive decline) and brain reserve. Notably, age did not make a significant contribution when considering all predictors. While fMRI brain networks did not show predictive value, head movements significantly contributed to emotion recognition. Models explained between 28-44% of the variance in social cognition performance. Results challenge traditional interpretations of age-related decline, patient-control differences, and brain signatures of social cognition, emphasizing the role of heterogeneous factors. Findings advance our understanding of social cognition in brain health and disease, with implications for predictive models, assessments, and interventions.

Can prosocial values improve brain health?

Prosocial values play a critical role in promoting care and concern for the well-being of others and prioritizing the common good of society. Evidence from population-based reports, cognitive neuroscience, and clinical studies suggests that these values depend on social cognition processes, such as empathy, deontological moral cognition, moral emotions, and social cooperation. Additionally, indirect evidence suggests that various forms of prosocial behaviors are associated with positive health outcomes at the behavioral, cardiovascular, immune, stress-related, and inflammatory pathways. However, it is unclear whether prosociality can positively influence brain health outcomes. In this perspective, we propose that prosocial values are not only influenced by brain conditions but could also potentially play a role in protecting brain health. We review studies from various fields that support this claim, including recent reports of prosociality-based interventions impacting brain health. We then explore potential multilevel mechanisms, based on the reduction of allostatic overload at behavioral, cardiovascular, immune, stress-related, and inflammatory levels. Finally, we propose potential prosociality-based interventions for improving brain health in at-risk populations, such as psychiatric and neurological patients, and individuals exposed to poverty or violence. Our perspective suggests that prosocial values may play a role in promoting and maintaining healthy brains.

Source space connectomics of neurodegeneration: One-metric approach does not fit all

Brain functional connectivity in dementia has been assessed with dissimilar EEG connectivity metrics and estimation procedures, thereby increasing results' heterogeneity. In this scenario, joint analyses integrating information from different metrics may allow for a more comprehensive characterization of brain functional interactions in different dementia subtypes. To test this hypothesis, resting-state electroencephalogram (rsEEG) was recorded in individuals with Alzheimer's Disease (AD), behavioral variant frontotemporal dementia (bvFTD), and healthy controls (HCs). Whole-brain functional connectivity was estimated in the EEG source space using 101 different types of functional connectivity, capturing linear and nonlinear interactions in both time and frequency-domains. Multivariate machine learning and progressive feature elimination was run to discriminate AD from HCs, and bvFTD from HCs, based on joint analyses of i) EEG frequency bands, ii) complementary frequency-domain metrics (e.g., instantaneous, lagged, and total connectivity), and iii) time-domain metrics with different linearity assumption (e.g., Pearson correlation coefficient and mutual information). <10% of all possible connections were responsible for the differences between patients and controls, and atypical connectivity was never captured by >1/4 of all possible connectivity measures. Joint analyses revealed patterns of hypoconnectivity (patientsHCs) in both groups was mainly identified in frontotemporal regions. These atypicalities were differently captured by frequency- and time-domain connectivity metrics, in a bandwidth-specific fashion. The multi-metric representation of source space whole-brain functional connectivity evidenced the inadequacy of single-metric approaches, and resulted in a valid alternative for the selection problem in EEG connectivity. These joint analyses reveal patterns of brain functional interdependence that are overlooked with single metrics approaches, contributing to a more reliable and interpretable description of atypical functional connectivity in neurodegeneration.

Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples

BACKGROUND

Dementia's diagnostic protocols are mostly based on standardised neuroimaging data collected in the Global North from homogeneous samples. In other non-stereotypical samples (participants with diverse admixture, genetics, demographics, MRI signals, or cultural origins), classifications of disease are difficult due to demographic and region-specific sample heterogeneities, lower quality scanners, and non-harmonised pipelines.

METHODS

We implemented a fully automatic computer-vision classifier using deep learning neural networks. A DenseNet was applied on raw (unpreprocessed) data from 3000 participants (behavioural variant frontotemporal dementia-bvFTD, Alzheimer's disease-AD, and healthy controls; both male and female as self-reported by participants). We tested our results in demographically matched and unmatched samples to discard possible biases and performed multiple out-of-sample validations.

FINDINGS

Robust classification results across all groups were achieved from standardised 3T neuroimaging data from the Global North, which also generalised to standardised 3T neuroimaging data from Latin America. Moreover, DenseNet also generalised to non-standardised, routine 1.5T clinical images from Latin America. These generalisations were robust in samples with heterogenous MRI recordings and were not confounded by demographics (i.e., were robust in both matched and unmatched samples, and when incorporating demographic variables in a multifeatured model). Model interpretability analysis using occlusion sensitivity evidenced core pathophysiological regions for each disease (mainly the hippocampus in AD, and the insula in bvFTD) demonstrating biological specificity and plausibility.

INTERPRETATION

The generalisable approach outlined here could be used in the future to aid clinician decision-making in diverse samples.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer's Disease

Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain dynamics are temporally irreversible and thus establish a preferred direction in time (i.e., arrow of time). However, little is known about how the time-reversal symmetry of spontaneous brain activity is affected by Alzheimer's disease (AD). We hypothesized that the level of irreversibility would be compromised in AD, signaling a fundamental shift in the collective properties of brain activity toward equilibrium dynamics. We investigated the irreversibility from resting-state fMRI and EEG data in male and female human patients with AD and elderly healthy control subjects (HCs). We quantified the level of irreversibility and, thus, proximity to nonequilibrium dynamics by comparing forward and backward time series through time-shifted correlations. AD was associated with a breakdown of temporal irreversibility at the global, local, and network levels, and at multiple oscillatory frequency bands. At the local level, temporoparietal and frontal regions were affected by AD. The limbic, frontoparietal, default mode, and salience networks were the most compromised at the network level. The temporal reversibility was associated with cognitive decline in AD and gray matter volume in HCs. The irreversibility of brain dynamics provided higher accuracy and more distinctive information than classical neurocognitive measures when differentiating AD from control subjects. Findings were validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between the entropy generation rate of brain dynamics and the clinical presentation of AD, opening new avenues for dementia characterization at different levels.SIGNIFICANCE STATEMENT By assessing the irreversibility of large-scale dynamics across multiple brain signals, we provide a precise signature capable of distinguishing Alzheimer's disease (AD) at the global, local, and network levels and different oscillatory regimes. Irreversibility of limbic, frontoparietal, default-mode, and salience networks was the most compromised by AD compared with more sensory-motor networks. Moreover, the time-irreversibility properties associated with cognitive decline and atrophy outperformed and complemented classical neurocognitive markers of AD in predictive classification performance. Findings were generalized and replicated with an out-of-sample validation procedure. We provide novel multilevel evidence of reduced irreversibility in AD brain dynamics that has the potential to open new avenues for understating neurodegeneration in terms of the temporal asymmetry of brain dynamics.

Genuine high-order interactions in brain networks and neurodegeneration

Brain functional networks have been traditionally studied considering only interactions between pairs of regions, neglecting the richer information encoded in higher orders of interactions. In consequence, most of the connectivity studies in neurodegeneration and dementia use standard pairwise metrics. Here, we developed a genuine high-order functional connectivity (HOFC) approach that captures interactions between 3 or more regions across spatiotemporal scales, delivering a more biologically plausible characterization of the pathophysiology of neurodegeneration. We applied HOFC to multimodal (electroencephalography [EEG], and functional magnetic resonance imaging [fMRI]) data from patients diagnosed with behavioral variant of frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and healthy controls. HOFC revealed large effect sizes, which, in comparison to standard pairwise metrics, provided a more accurate and parsimonious characterization of neurodegeneration. The multimodal characterization of neurodegeneration revealed hypo and hyperconnectivity on medium to large-scale brain networks, with a larger contribution of the former. Regions as the amygdala, the insula, and frontal gyrus were associated with both effects, suggesting potential compensatory processes in hub regions. fMRI revealed hypoconnectivity in AD between regions of the default mode, salience, visual, and auditory networks, while in bvFTD between regions of the default mode, salience, and somatomotor networks. EEG revealed hypoconnectivity in the γ band between frontal, limbic, and sensory regions in AD, and in the δ band between frontal, temporal, parietal and posterior areas in bvFTD, suggesting additional pathophysiological processes that fMRI alone can not capture. Classification accuracy was comparable with standard biomarkers and robust against confounders such as sample size, age, education, and motor artifacts (from fMRI and EEG). We conclude that high-order interactions provide a detailed, EEG- and fMRI compatible, biologically plausible, and psychopathological-specific characterization of different neurodegenerative conditions.

Multi-feature computational framework for combined signatures of dementia in underrepresented settings

Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.