Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation. (February 2014)

• Record Type: Journal Article
• Authors: Araújo, Duarte; Diniz, Ana; Passos, Pedro; Davids, Keith
• Is Part Of: Adaptive behavior. Volume 22:Number 1(2014)
• Page Start: 21
• Page End: 30
• Publication Date: 2014-02
• Subjects: Social coordination -- bifurcations -- decision making; Animal behavior -- Periodicals; Animals -- Adaptation -- Periodicals; Adaptability (Psychology) -- Periodicals; Adaptation, Psychological -- Periodicals; Artificial intelligence -- Periodicals; 591.5
• DOI: 10.1177/1059712313497370
• Languages: English
• ISSNs: 1741-2633

Abstract

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V ( x )=− k 1 x + k 2 ax 2 /2− bx 4 /4+ x 6 /6, where k 1 and k 2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise ε t, leading to the motion equation dx / dt = − dV / dx + Q 0.5 ε t, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.