Online research in philosophy

Considered in relation to the component brain systems of appraisal-emotion interactions, dynamical systems theory blurs the divisions that seem obvious in a psychological analysis, such as between arousal, emotion, and appraisal. At the same time, the component brain mechanisms can themselves be seen to be incomplete as units of analysis, making sense only in the context of the whole organism.

I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar equivalencies between organic dynamic systems and other cognitive functions. This type of research could help us discover how (and/or if) it is possible to use Dynamic Systems Theory to more accurately model the cognitive functions that are now being modeled by subroutines in Symbolic AI computer models. If such a reduction of subroutines to basins of attraction is possible, it could free AI from the limitations that prompted Fodor to say that it was impossible to model certain higher level cognitive functions.

Lewis proposes a “reconceptualization” of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for more than 30 years. This commentary summarizes some of these themes and points to areas of particularly active research in this area.

Fully interpreted, Lewis's dynamic systems modeling of emotion encompasses psychological-adaptation thinking and individual and group differences in normal and abnormal behavior. It weakens the categorical perspective in evolutionary psychology and the clinical sciences; and suggests continuity between “normal” or “abnormal” behavior in whatever way this is self and culturally constituted, although culture/linguistic factors and selfhood are neglected. Application of a dynamic systems model could improve formulation of clinical problems.

Self-organizing dynamic systems (DS) modeling is appropriate to conceptualizing the relationship between emotion and cognition-appraisal. Indeed, DS modeling can be applied to encompass and integrate additional phenomena at levels lower than emotional interpretations (genes), at the same level (motives), and at higher levels (social, cognitive, and moral emotions). Also, communication is a phenomenon involved in dynamic system interactions at all levels.

Lewis neglects cross-cultural data in his dynamic systems model of emotion, probably because appraisal theory disregards behavior and because anthropologists have not engaged discussions of neural plasticity in the brain sciences. Considering cultural variation in emotion-related behavior, such as grieving, indigenous descriptions of emotions, and alternative developmental regimens, such as sport, opens up avenues to test dynamic systems models.

Dynamic systems theory (DS) provides tools for exploring how simpler elements can interact to produce complex psychological configurations. It may, as Lewis demonstrates, provide means for explicating relationships between two reductionist approaches to overlapping sets of phenomena. The result is a description of psychological phenomena at a level that begins to achieve the richness we would hope to achieve in examining psychological life as it is experienced and explored in psychoanalysis.

Lewis proposes a solution for bridging the gap between cognitive-psychological and neurobiological theories of emotion in terms of dynamic systems modeling. However, an important brain network is absent in his account: the neuroendocrine system. In this commentary, the dynamic features of the cross-talk between the hypothalamic-pituitary-adrenal (HPA) and gonadal (HPG) axes are discussed within a triple-balance model of emotion.

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. Key Words: appraisal; bidirectional causality; cognition; dynamic systems; emotion; neurobiology; part–whole relations; self-organization.