Bridging Gaps in Understanding Consciousness Vol. II: Advancing Empirical and Methodological Frontiers

Consciousness research, bridging psychology, neuroscience, psychiatry, philosophy, engineering, computational science, artificial intelligence, and contemplative science, has become an increasingly multidisciplinary field seeking to uncover the mechanisms underlying subjective experience. Volume I of this Research Topic highlighted the richness and conceptual diversity of contemporary consciousness studies here. Despite ongoing advances, translating theoretical models into precise, testable, and empirically supported frameworks remains a major challenge. Contemporary neurophysiological, computational, engineering-based, and behavioral approaches have improved understanding of conscious processes, yet methodological limitations and the persistent gap between theory and measurement continue to hinder cumulative progress. Bridging this gap requires robust operational definitions, innovative empirical paradigms, and cross-disciplinary methodologies capable of linking consciousness to measurable data across multiple levels of analysis. Emerging advances in artificial intelligence and data-driven modeling also offer new opportunities to strengthen methodological rigor and formalize theoretical constructs.This Research Topic aims to build upon the foundation established by Volume I by fostering a new wave of empirical research that tests, refines, and advances scientific approaches to understanding consciousness. The objective is to strengthen the scientific basis of consciousness studies by encouraging data-driven methodologies that yield replicable findings, mechanistic insight, and theoretical clarity. In addition to testing existing frameworks, this volume welcomes bottom-up and emergent approaches that derive insight from empirical structure, computational modelling, and cross-disciplinary analytical methods. Submissions are especially encouraged that develop falsifiable predictions, compare competing theoretical or computational frameworks, apply computational or AI-assisted analytical approaches, or introduce methodological innovations to assess consciousness across cognitive, neural, and computational domains. Particular interest is given to work integrating engineering methodologies, large-scale data analysis, and formal modelling to improve the operationalization and empirical assessment of conscious processes. By integrating empirical investigation with formal and theoretical development, this Volume II seeks to drive the field toward measurable and cumulative scientific progress.To gather further insights into the measurable and mechanistic foundations of consciousness, we welcome empirical, theoretical, computational, and methodological contributions addressing, but not limited to, the following themes:- Empirical testing and refinement of major theories of consciousness- Comparisons of conscious and non-conscious processing- Neural, behavioral, physiological, and computational markers of awareness- Developmental, clinical, and translational studies of consciousness- Cross-species and cross-scale investigations linking molecular, neural, cognitive, and systems-level processes- Network dynamics, information integration, and large-scale brain organization during conscious states- Computational, artificial intelligence, and engineering-based approaches for modeling consciousness, improving data-driven inference, and enhancing the empirical assessment of conscious processes- Methodological and analytical innovations for operationalizing consciousness Topic editors: Poppy L.A. Schoenberg, Tetsuo Kida, Kuk Jin Jang Source: https://www.frontiersin.org/research-topics/79232/bridging-gaps-in-understanding-consciousness-vol-ii-advancing-empirical-and-methodological-frontiers