The Evolutionary Theory of Behavior Dynamics: Complexity, Darwinism, and the Emergence of High-Level Phenotypes Open Access

Popa, Andrei (2013)

Permanent URL: https://etd.library.emory.edu/concern/etds/9880vr10s?locale=en
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Abstract

McDowell (2004) instantiated low-level Darwinian processes in a computational theory of behavior dynamics. The theory causes a population of behaviors to evolve through time under the selection pressure of the environment. It has been tested under a variety of conditions and the emergent outcomes were repeatedly shown to be qualitatively and quantitatively indistinguishable from those displayed by live organisms (McDowell, in press). As empirical evidence accumulates and our understanding of the theory matures, the analogy between biological and behavioral evolution becomes more compelling. Expanding the exploration of this analogy becomes both necessary and fascinating. The main purpose of this project was to explore the effects of mutation and the environment's value and conduciveness on various dimensions of behavioral variability, in continuous choice environments. Secondly, qualitative predictions made by the Evolutionary Theory about the effects of changeover delays (COD) on behavior variability were verified against the behavior of college students in equivalent environments. The continuous choice behavior of college students was correctly predicted on eight out of eight behavioral dimensions. Thirdly, low-level characteristics of students' continuous choice behavior were compared with traditional measures of impulsivity and sustained attention, in an effort to investigate the potential equivalence between mutation and a property of the nervous system that produces impulsivity-like symptoms. The results were inconclusive, likely due to a lack of extreme impulsivity scores in the human sample. The findings presented in this paper provided significant additional evidence for the selectionist account as a valid mechanism of behavior change. In addition, the knowledge generated by the Evolutionary Theory provided important insights about clinically-relevant phenomena, such as disordered variability (or impulsivity) and raise the possibility of using the theory as a platform for simulating the emergence of specific high-level phenotypes. These implications appear even more fascinating considering that a connection with mental health was not explicitly sought, nor can it be traced to the inner-workings of the theory. This challenges our current understanding of mental illness and provides a new way of thinking about the evolution of behavioral repertoires and their emergent high-level characteristics.

Table of Contents

Table of Contents

Introduction 1

Complexity, emergence, and evolution 5

The Evolutionary Theory of Behavior Dynamics 8

The present project: motivation and specific aims 10

Changeover Delay in live (COD) and virtual (HDCOD) organisms 12

Specific Aims 14

Phase 1 15

Methods 16

Subjects and procedure 16

Independent variables 19

The Hamming Distance changeover delay (HDCOD) 19

Experimental design 21

Results 23

Measures 23

Traditional descriptors of continuous-choice 23

Changeover profiles (COMAX) 23

Topographic variability (ΔPHENOTYPE) 24

Inter-Bout Time (IBT) 25

Bout frequency, bout length, and sustained behavior 26

Description of results: general format 26

Sensitivity (a), COMAX, and ΔPHENOTYPE 27

Target behaviors and obtained reinforcers 32 Bout frequency and length 35

Sustained behavior and IBT 37

Discussion 41

General effects of mutation 41

Mutation and ADHD 42

Effects of "good" environments 43

Effects of "bad" environments 44

Different low-level mechanics, similar high-level outcomes 45

Summary and implications.. 48

Phase 2 50

Methods 50

Results 53

Behavioral characteristics of continuous-choice behavior of college students 54

Effects of changeover delays on the behavior of virtual organisms (HDCOD) and college students (COD) 56

Discussion 59

Phase 3 60

Methods 61

Results 63

Continuous-choice behavior and impulsivity/inattention 64

Relations between various measures of impulsivity/inattention 66

Discussion 70

General discussion 73

References 81

Tables 99

Figures 108

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