A runnable neural network model of the structure and dynamics of human personality embedded in a virtual environment

We present a single-agent neural network model, based on the biologically plausible neural network framework Emergent (O'Reilly et al., 2020), that operationalizes our theory of how individual differences in the neural systems underlying motivation interact with situational characteristics to give rise to within-subject personality dynamics (Read et al., 2010). We first manipulate key parameters of our neural network model to create "individuals" varying in their underlying motivational structure and dynamics. We then simulate the interaction of these individuals with varying situational configurations in virtual environments created with the video game engine Unity to provide a complex model explaining multifarious factors including: A) how situational configurations produce high within-subject variability in behavior; B) how certain situational configurations give rise to some personality factors more than others; C) the degree to which one’s personality structure as opposed to one’s environment plays a role in producing behaviors; and D) how physiological factors influence the presentation of the Big Five personality factors through behaviors.