Population Neuroscience: An Arranged Marriage

Due to needs surrounding rigor and reproducibility, subgroup specific disease knowledge, and questions of external validity, data harmonization is an essential tool in population neuroscience of Alzheimer’s disease and related dementias (ADRD). Systematic harmonization of data elements is necessary to pool information from heterogeneous samples, and such pooling allows more expansive evaluations of health disparities, more precise effect estimates, and more opportunities to discover effective prevention or treatment strategies. The key goal of this Tutorial in Population Neuroimaging Curriculum, Instruction, and Pedagogy article is to guide researchers in creating a customized population neuroscience of ADRD harmonization training plan to fit their needs or those of their mentees. We provide brief guidance for retrospective data harmonization of multiple data types in this area, including: (1) clinical and demographic, (2) neuropsychological, and (3) neuroimaging data. Core competencies and skills are reviewed, and resources are provided to fill gaps in training as well as data needs. We close with an example study in which harmonization is a critical tool. While several aspects of this tutorial focus specifically on ADRD, the concepts and resources are likely to benefit population neuroscientists working in a range of research areas.

Aging populations in low‐ and middle‐income countries (LMICs) are growing more rapidly than those in high income countries (HICs). Thus, globally, the burden of Alzheimer’s disease and related dementias (ADRD) profoundly impacts LMICs, with greater burden and risk for late‐life women than men. LMICs are unable to meet diagnostic challenges with underfunded healthcare infrastructure, low numbers of clinicians with training and expertise in ADRD, and a lack of culturally and linguistically sensitive screening assessments. Emerging social and societal factors that are important risk and protective factors for later life ADRD and are differentially experienced by gender/sex are relatively understudied, yet essential in LMICs. Typical samples in neuroscience studies have been small and highly selected. They have been biased toward Western, Educated, Industrialized, Rich, and Democratic (WEIRD) samples and do not apply well to target populations in LMICs. In addition, levels‐of‐analysis across social/societal and biological determinants of disease are not typically integrated, and social/societal factors such as sociocultural (e.g., culture, religion, gender norms, access to education, discrimination, social aspects of pandemics, disability), political (e.g., governments and policies; migrants and displaced persons; war and conflict; reproductive health, justice, and agency), environmental (e.g., climate change and pollution), and economic factors (e.g., poverty), and their co‐occurrence, have been minimally considered for their role and impact on ADRD. To better understand gender/sex differences in ADRD in LMICs, we review how these social and societal factors may be important to ADRD using an integrated Population Neuroscience and Syndemics framework. Population neuroscience considers the brain in context using multiple levels of analyses, a life course perspective, and tools to enhance internal and external validity, while Syndemics suggest that diseases and social conditions may cluster and interact in populations with syndemic risk factors—sociocultural, political, economic, and environmental factors which promote stress pathways. We lay out a model in which syndemic risk and protective factors contribute to or protect from stress and biological aging and ultimately ADRD risk, both directly and indirectly through physical and mental health conditions. We close with recommendations for future aging and ADRD research based on this integrated Population Neuroscience‐Syndemics of ADRD framework.

Healthy pregnancy and prevention of psychosis.

Developmental population neuroscience: emerging from ICHBD

Age-related hearing loss (ARHL) has emerged as a significant and potentially modifiable risk factor for neurodegenerative disorders, including Alzheimer's disease. A growing body of evidence links ARHL to structural and functional changes in the brain, with implications for cognitive decline and dementia onset. However, both ARHL and dementia are multifactorial conditions shaped not only by biological mechanisms but also by broader social determinants of health. Inequities in access to hearing care, underrepresentation of marginalised populations in research, and variability in intervention outcomes emphasise the need for a more inclusive and integrated approach to prevention. This review synthesises current evidence on the neurocognitive consequences of ARHL, the potential mechanistic pathways linking hearing loss to dementia, and the role of inequity. It includes a novel perspective by highlighting the need for cross-cultural, population neuroscience approaches incorporating exposome and equity frameworks that capture phenotypic variability across diverse populations. This review outlines key priorities for advancing neurocognitive and translational research on hearing loss, neurodegeneration, and global health equity. Addressing these gaps is essential to developing equitable strategies for dementia prevention and optimising cognitive health across the lifespan.

The call to synergize brain health with mental health has major ramifications for research and policy. Mental health has been recognized as a universal human right, but no such declaration exists for brain health. Here, I defend the right to lifelong brain health as a derived, intermediary, and generative right. It is derived from the right to physical health because it is reducible to facts about the health of the body. This grounds brain health in the right to physical health, a long-standing right with hard legal status, while avoiding "rights inflation." It is intermediary because it bridges the gap between physical and mental health, since the brain is an organ that is central to both physical and mental health. It is generative because it provides impetus to downstream actions including the creation of health-based "neurorights" and bolstering the right to a healthy environment to protect collective cognitive health. Thus, the right to lifelong brain health would guarantee the right of citizens to live and grow in a brain health-promoting environment. A rights-based approach to brain health also has important consequences for research. It would help to move research away from the disease paradigm that focuses on individual risk and responsibility to the study of deeper contributions to brain health and disease through a population neuroscience approach to public brain health. Until the right to brain health is recognized alongside mental health, their synergy will remain incomplete, and brain health promotion will lack unity.

<正>在“人类大科学计划”的时代背景下,脑科学成为21世纪生命科学制高点~([1]).人类面向解析自身科学认知的这一最后疆域,对多学科交叉融合创新提出了重大需求,清晰地认识到学科发展挑战和机遇~([2]).人脑科学研究聚焦解读“人脑如何产生心理行为?”这一核心科学问题,面临“管中窥豹”的“现象科学”困境,需要深入研究影响人类脑智改变的多样性因素~([3]).

The social brain hypothesis proposes that the complexity of human brains has coevolved with increasing complexity of social interactions in primate societies. The present study explored the possible relationships between brain morphology and the richness of more intimate ‘inner’ and wider ‘outer’ social circles by integrating Bayesian hierarchical modeling with a large cohort sample from the UK Biobank resource (n = 10 000). In this way, we examined population volume effects in 36 regions of the ‘social brain’, ranging from lower sensory to higher associative cortices. We observed strong volume effects in the visual sensory network for the group of individuals with satisfying friendships. Further, the limbic network displayed several brain regions with substantial volume variations in individuals with a lack of social support. Our population neuroscience approach thus showed that distinct networks of the social brain show different patterns of volume variations linked to the examined social indices.

Task-based functional magnetic resonance imaging (tb-fMRI) reveals individual differences in the neural basis of cognitive functions by linking specific tasks to neural responses. However, scaling tb-fMRI to population-level studies is challenging due to its cognitive demands, variations in task design across studies, and the limited scope of tasks in large datasets. To address this, we propose DeepTaskGen, a deep-learning approach that generates non-acquired task-based contrast maps from resting-state fMRI (rs-fMRI) data. Our approach enables generating synthetic task images for non-acquired tasks within the study protocol. We validate this approach using the Human Connectome Project lifespan data, then generate 47 contrast maps from 7 different cognitive tasks for over 20,000 individuals from UK Biobank. DeepTaskGen outperforms several benchmarks in generating synthetic task-contrast maps, exhibiting superior reconstruction performance while retaining inter-individual variation essential for biomarker development. Notably, we further showed that synthetic task contrast maps achieved similar or greater performance compared to actual task contrast maps and resting-state connectomes for predicting a wide range of demographic, cognitive, and clinical variables. This approach will facilitate the study of individual differences and the generation of task-related biomarkers by enabling the generation of arbitrary functional cognitive tasks from readily available rs-fMRI data.