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The Virtual Personalities Neural Network Model: Neurobiological Underpinnings

  • Stephen J. Read (a1), Ashley D. Brown (a1), Peter Wang (a1) and Lynn C. Miller (a1)

Abstract

The Virtual Personalities Model is a motive-based neural network model that provides both a psychological model and a computational implementation that explicates the dynamics and often large within-person variability in behavior that arises over time. At the same time the same model can produce—across many virtual personalities—between-subject variability in behavior that when factor analyzed yields familiar personality structure (e.g., the Big Five). First, we describe our personality model and its implementation as a neural network model. Second, we focus on detailing the neurobiological underpinnings of this model. Third, we examine the learning mechanisms, and their biological substrates, as ways that the model gets “wired up,” discussing Pavlovian and Instrumental conditioning, Pavlovian to Instrumental transfer, and habits. Finally, we describe the dynamics of how initial differences in propensities (e.g., dopamine functioning), wiring differences due to experience, and other factors could operate together to develop and change personality over time, and how this might be empirically examined. Thus, our goal is to contribute to the rising chorus of voices seeking a more precise neurobiologically based science of the complex dynamics underlying personality.

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Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial- NoDerivatives licence (http://creativecommons.org/licenses/by-ncnd/4.0/), which permits noncommercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.

Corresponding author

Author for correspondence: Stephen J. Read, E-mail: read@usc.edu

References

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