Bridging emotion theory and neurobiology through dynamic systems modeling

TLDR

Dynamic systems modeling offers a common language linking emotion theory and neurobiology by describing how higher‑order wholes emerge from lower‑order constituents through bidirectional causal processes. The study applies dynamic‑systems principles to emotion–cognition, developing a psychological model that delineates trigger, self‑amplification, and self‑stabilization phases of emotion‑appraisal states and links them to neural processes. The model describes neural structures and functions of appraisal and emotion, modeling their integration through nested feedback, neuromodulation, vertical integration, action‑monitoring, synaptic plasticity, functional integration, and temporal synchronization.

Abstract

Efforts to bridge emotion theory with neurobiology can be facilitated by dynamic systems (DS) modeling. DS principles stipulate higher-order wholes emerging from lower-order constituents through bidirectional causal processes – offering a common language for psychological and neurobiological models. After identifying some limitations of mainstream emotion theory, I apply DS principles to emotion–cognition relations. I then present a psychological model based on this reconceptualization, identifying trigger, self-amplification, and self-stabilization phases of emotion-appraisal states, leading to consolidating traits. The article goes on to describe neural structures and functions involved in appraisal and emotion, as well as DS mechanisms of integration by which they interact. These mechanisms include nested feedback interactions, global effects of neuromodulation, vertical integration, action-monitoring, and synaptic plasticity, and they are modeled in terms of both functional integration and temporal synchronization. I end by elaborating the psychological model of emotion–appraisal states with reference to neural processes.