Rethinking Emotion Across the Lifespan: Dynamic, Multilevel, and Real-World Perspectives

Emotions are fundamental to human adaptation, influencing cognition, decision-making, social behavior, learning, health, and well-being throughout life. Over the past two decades, affective science has undergone a substantial conceptual transformation, moving beyond traditional models that viewed emotions as relatively discrete or static phenomena toward dynamic, multilevel, and context-dependent frameworks. Contemporary perspectives increasingly recognize emotions as emergent processes arising from continuous interactions among biological, cognitive, psychological, interpersonal, environmental, and sociocultural systems. Rather than focusing solely on isolated emotional states or individual regulation strategies, current research seeks to understand how emotional experiences fluctuate across time, contexts, and developmental stages.Within this evolving framework, emotion regulation is no longer conceptualized as a single, universal process but as a diverse set of adaptive and maladaptive mechanisms shaped by neurodevelopment, personality, executive functioning, motivation, stress exposure, social relationships, and cultural contexts. Increasing evidence suggests that regulatory processes differ according to the specific emotions involved, such as fear, anger, sadness, or positive affect, and follow distinct developmental trajectories from childhood through older adulthood. Likewise, growing interest has been directed toward concepts such as emotional flexibility, emotional awareness, emotional granularity, emotional complexity, and interpersonal regulation, which provide a richer understanding of adaptive emotional functioning across the lifespan.Developmental and lifespan perspectives have become particularly influential in explaining how emotional processes evolve across different phases of life. Research has demonstrated that emotional competencies emerge through continuous interactions between maturation, learning, and social experience, with important implications for mental health, resilience, and successful adaptation. In later adulthood, contemporary theories increasingly emphasize that aging is characterized not only by cognitive and biological changes but also by shifts in motivational priorities and emotional goals. Older adults often demonstrate preserved or even enhanced emotional well-being through adaptive strategies that prioritize emotionally meaningful experiences, contributing to a more balanced understanding of aging that extends beyond deficit-oriented perspectives.Simultaneously, affective science has increasingly acknowledged that emotions cannot be fully understood outside their interpersonal and sociocultural contexts. Emotional experiences, expression, communication, and regulation are profoundly shaped by family environments, peer relationships, educational settings, workplaces, communities, and cultural norms. From caregiver–child co-regulation during early development to interpersonal emotion regulation in adulthood and social connectedness in later life, emotions are increasingly recognized as inherently relational processes embedded within broader social ecosystems.Parallel advances in affective neuroscience have considerably expanded our understanding of the biological foundations of emotional functioning. Research integrating neuroimaging, electrophysiology, psychophysiology, endocrinology, and computational neuroscience has revealed that emotions emerge from dynamic interactions among distributed neural networks, autonomic responses, hormonal systems, and bodily signals. Rather than being localized to isolated brain regions, emotional processes involve coordinated activity across cortical and subcortical circuits supporting appraisal, attention, memory, prediction, decision-making, and behavioral adaptation. These multilevel approaches have substantially improved our understanding of both typical emotional functioning and emotional dysfunction across clinical and non-clinical populations.At the same time, methodological innovation is transforming how emotions are investigated. Traditional laboratory paradigms and retrospective self-report measures are increasingly complemented by ecologically valid methodologies capable of capturing emotional experiences as they unfold in everyday life. Ecological Momentary Assessment (EMA), Experience Sampling Methods (ESM), passive sensing technologies, wearable devices, smartphone-based assessments, and digital phenotyping now enable continuous measurement of emotional dynamics across real-world contexts. Furthermore, multimodal approaches combining behavioral performance, facial expression, speech analysis, eye tracking, electroencephalography (EEG), functional neuroimaging, electrodermal activity, heart-rate variability, and other physiological signals provide increasingly comprehensive characterizations of emotional functioning.Recent developments in artificial intelligence, machine learning, deep learning, computational psychiatry, and network science are further reshaping affective science. These approaches facilitate automated emotion recognition, prediction of emotional states, identification of latent emotional phenotypes, and modeling of complex interactions among biological, psychological, and environmental variables across large-scale datasets. Such computational advances are opening new opportunities for precision assessment, personalized interventions, and digital mental health applications.Collectively, these conceptual and methodological developments have important translational implications across clinical, educational, occupational, technological, and community settings. Emotion-focused interventions are increasingly adopting lifespan-oriented, transdiagnostic, and personalized approaches designed to enhance emotional resilience, psychological flexibility, adaptive regulation, and overall well-being. Likewise, growing evidence highlights the central role of emotions in learning, academic achievement, workplace performance, healthy aging, interpersonal relationships, and quality of life, emphasizing the need for emotionally informed policies and interventions across diverse populations.Taken together, contemporary affective science is moving toward increasingly integrative models capable of explaining emotional functioning across multiple levels of analysis, developmental stages, and real-world environments. By bridging developmental psychology, affective neuroscience, cognitive science, social psychology, computational modeling, and digital technologies, the field is advancing toward a more comprehensive understanding of how emotions emerge, evolve, and influence human behavior throughout the lifespan.This Research Topic aims to bring together high-quality theoretical, methodological, and empirical contributions that advance our understanding of emotion and emotion regulation across the lifespan. We particularly welcome interdisciplinary research integrating developmental, affective, cognitive, clinical, educational, neuroscientific, social, computational, and technological perspectives. We encourage submissions employing quantitative, qualitative, mixed-methods, longitudinal, experimental, ecological, computational, and intervention designs, including systematic reviews, meta-analyses, theoretical papers, methodological advances, and original empirical research.Topics of interest include, but are not limited to:● Emotion development from infancy to older adulthood● Lifespan trajectories of emotion regulation● Emotional flexibility, granularity, awareness, and complexity● Positive and negative emotions across development● Emotion–cognition interactions● Executive functions and emotional functioning● Social and interpersonal emotion regulation● Family, peer, and educational influences on emotional development● Cultural and cross-cultural perspectives on emotion● Emotion, resilience, and psychological well-being● Healthy emotional aging● Emotion and psychopathology across the lifespan● Emotion in educational, occupational, and community settings● Affective neuroscience of emotion and emotion regulation● Neural, autonomic, hormonal, and psychophysiological mechanisms of emotion● EEG, ERP, fMRI, MEG, fNIRS, and multimodal neuroimaging studies● Ecological Momentary Assessment (EMA) and Experience Sampling Methods (ESM)● Passive sensing, wearable technologies, and digital phenotyping● Multimodal emotion assessment (behavioral, physiological, facial, vocal, and movement data)● Artificial intelligence and machine learning for emotion research● Computational and network models of emotional processes● Longitudinal and dynamic systems approaches● Emotion-centered prevention and intervention programs● Emotion in digital environments, social media, and human–technology interaction● Open science, reproducibility, and methodological innovations in emotion research. Topic editors: Sandra Carvalho, Laura Cristina Cortes Garcia, Diego Pinal, Miguel Rodriguez Valverde Source: https://www.frontiersin.org/research-topics/84293/rethinking-emotion-across-the-lifespan-dynamic-multilevel-and-real-world-perspectives