My academic interests focus on how people come to construct meaning in their lives from their experiences, and how their life journeys change them over time.
Here, I look at fact, fiction, and fantasy to explore how the human brain processes information and shapes it around social influence and emotional experience, regardless of its reliability.
Why does a film we know to be fiction still move our attitudes, and why does a documented, fact-checked report often move them less? This proposal treats that question as a modeling problem rather than a paradox. I review the state of knowledge on human belief updating as approximate, noisy Bayesian inference, including predictive-coding and reward-based accounts of how the brain forms and revises beliefs at the neural level, evidence that belief formation can be directly manipulated (via dopaminergic and prefrontal mechanisms), and the neural signature of resisting belief change for identity-linked convictions. I connect this to the neuroscience of narrative transportation and the meta-analytic evidence that fictional, entertainment-first narratives shift attitudes, beliefs, intentions, and behaviors about as durably as purpose-built educational messages, and nearly as strongly as matched non-narrative information. I propose a computational account in which a person’s posterior belief is a noisy, precision-weighted combination of prior belief and incoming signal, where the precision assigned to a narrative signal is boosted by emotional arousal and transportation even as it is discounted by the signal’s known fictional status. I then translate that abstract precision term into the concrete audio-video production techniques, editing rhythm, music and sound design, character concreteness, and threat framing, that filmmakers already use to shape it. The model’s output is a probability of belief change, recovered from a synthetic-population, Monte Carlo approach used to calibrate agent-based opinion models against published effect sizes. I close with concrete research questions, a synthetic-data measurement plan, and a path toward empirical validation.
This simulation shows the difference in belief intensity and persistence comparing a strong emotional experience that is fictional with factual information with low emotional content.
