Mental Flexibility and Affect Dynamics: Theoretical Integration, Stochastic Modeling, and Experimental Paradigms

This doctoral dissertation investigates the dynamic interplay between affect dynamics and Flexibility, advancing a unified theoretical and methodological framework grounded in stochastic modelling and experimental research. Moving beyond static conceptualizations of emotion and executive functioning, the work adopts a temporal perspective in which both affect and Flexibility are conceived as processes unfolding over time and reciprocally influencing one another. The dissertation is structured into three main parts: a theoretical part, a methodological part, and a final experimental part. Each section progressively builds upon the previous one, moving from conceptual integration to analytical innovation and, ultimately, to empirical validation within controlled laboratory paradigms. The first part develops the theoretical framework. It begins with a conceptual analysis of affect dynamics grounded in neo-constructionist theories of emotion, particularly Russell’s circumplex model and Barrett’s theory of constructed emotion, which conceptualize affect as continuous movement within a two-dimensional valence–arousal space. In parallel, Flexibility is examined as a polyhedral construct encompassing cognitive, behavioral, affective, emotional, and psychological dimensions. Through a comprehensive scientometric analysis and a systematic review, the dissertation demonstrates the historical fragmentation of Flexibility research and the limited integration between Flexibility and affective science. To address this gap, the construct of Mental Flexibility is proposed as an umbrella framework capturing the shared adaptive principle underlying different Flexibility domains and linking them to affective reorganization across time. The second part introduces methodological and analytical innovations. Stochastic modelling approaches are advanced for the study of affect dynamics, with discrete-time and state Markov chains applied to self-report data within idiographic designs, to physiological signals such as heart rate variability, and to affective responses elicited by music. A multilevel hidden Markov model is further developed to integrate self-report and physiological data in daily-life contexts, allowing simultaneous modelling of intra-individual transitions and inter-individual variability. In parallel, new psychometric and experimental tools are developed for Flexibility, including a novel self-report instrument and immersive behavioral materials based on 360-degree videos and volumetric reconstructions designed to elicit ecologically valid affective challenges and real-life scenarios. The third and final part of the dissertation is aimed at jointly investigating affect dynamics and Flexibility within controlled laboratory settings. To this end, we first introduce the Affective Storm, an experimental paradigm specifically designed to induce affective dynamics in the laboratory by engineering structured transitions between emotional states. Using IAPS images and immersive virtual reality environments, self-report and synchronized physiological measures are employed to capture the temporal trajectories of affective change. The concluding experimental study represents the first empirical attempt to integrate Flexibility and affect dynamics within a unified laboratory framework, thereby testing whether individual differences in Flexibility are associated with distinct patterns of affective transition and reorganization. Across theoretical integration, methodological innovation, and experimental validation, this work advances a dynamic model of adaptive functioning in which affective variability and Flexibility are understood as interconnected processes. The exploratory findings could support the hypothesis that intermediate levels of Flexibility may promote richer and more adaptive affective dynamics, whereas both excessive rigidity and excessive variability may constrain emotional reorganization