Why Do We Need Computational Models of Psychological Change and Recovery, and How Should They Be Designed and Tested?

Abstract

Traditional research methodologies typically assume that humans operate on the basis of an "open loop" stimulus-process-response rather than the "closed loop" control of internal state. They also average behavioral data across repeated measures rather than assess it continuously, and they draw inferences about the working of an individual from statistical group effects. As such, we propose that they are limited in their capacity to accurately identify and test for the mechanisms of change within psychological therapies. As a solution, we explain the advantages of using a closed loop functional architecture, based on an extended homeostatic model of the brain, to construct working computational models of individual clients that can be tested against real-world data. Specifically, we describe tests of a perceptual control theory (PCT) account of psychological change that combines the components of negative feedback control, hierarchies, conflict, reorganization, and awareness into a working model of psychological function, and dysfunction. In brief, psychopathology is proposed to be the loss of control experienced due to chronic, unresolved conflict between important personal goals. The mechanism of change across disorders and different psychological therapies is proposed to be the capacity for the therapist to help the client shift and sustain their awareness on the higher level goals that are driving goal conflict, for sufficiently long enough to permit a trial-and-error learning process, known as reorganization, to "stumble" upon a solution that regains control. We report on data from studies that have modeled these components both separately and in combination, and we describe the parallels with human data, such as the pattern of early gains and sudden gains within psychological therapy. We conclude with a description of our current research program that involves the following stages: (1) construct a model of the conflicting goals that are held by people with specific phobias; (2) optimize a model for each individual using their dynamic movement data from a virtual reality exposure task (VRET); (3) construct and optimize a learning parameter (reorganization) within each model using a subsequent VRET; (3) validate the model of each individual against a third VRET. The application of this methodology to robotics, attachment dynamics in childhood, and neuroimaging is discussed.

Disentangling Trait-Like Between-Individual vs. State-Like Within-Individual Effects in Studying the Mechanisms of Change in CBT

“…These preliminary findings on the implementation of machine leaning approaches to identifying predictors of state-like effects stress the importance of thoughtful selection of relevant predictors in future trial designs, as well as consideration of a variety of machine leaning-related analytical approaches. It is also worth noting that computational models of psychological change and recovery that attempt to directly emulate the psychological mechanisms occurring within each individual client may contribute to progress in psychotherapy research toward precision medicine ( 68 ).…”

A Thematic Analysis of Multiple Pathways Between Nature Engagement Activities and Well-Being

“…Importantly, this model is analytical rather than formal, and the aim of future research will be to formalize these components within a PCT architecture and construct individualized models that can be tested for their fit with real world data within natural environments. This methodology is challenging, but it provides a particularly robust test of a psychological theory (Mansell and Huddy, 2020 ). The functional specification of a model will also facilitate the research and translational impact within new technology, such as smartphones and augmented or virtual reality, which is a burgeoning area in nature engagement research (Wooller et al, 2018 ; MacIntyre et al, 2020 ; Yin et al, 2020 ).…”

“…it also provides a framework for computational modeling of psychological pathways (Mansell and Huddy, 2020). Notably, PCT has influenced the development of theories used within the nature engagement field such as choice theory (Glasser, 1981) and wild system theory (Jordan, 2008).…”

“…When this occurs, attention needs to be directed and sustained above the systems in conflict so that an intrinsic, trial-and-error learning process, known as reorganization, can adjust neural strengths and connections until the conflict is resolved. Thus, PCT provides a biologically grounded framework for human decision making, conflict resolution, well-being enhancement and maintenance (Carey et al, 2014 ); it also provides a framework for computational modeling of psychological pathways (Mansell and Huddy, 2020 ). Notably, PCT has influenced the development of theories used within the nature engagement field such as choice theory (Glasser, 1981 ) and wild system theory (Jordan, 2008 ).…”

What Research Evidence Is Valid for Psychotherapy Research?

“…To analyze such complex interplay of multiple factors we need the type of advanced psychotherapy process research that we will describe later. Recently, researchers leaning on complexity theory have used computational models to, for example, formalize ideographic theories of functional analysis for panic disorder and to test a perceptual control theory account of psychological change ( 21 , 22 ).…”