Evaluating Effective Connectivity of Trust in Human-Automation Interaction: A Dynamic Causal Modeling (DCM) Study
HUMAN FACTORS, 64(6), 1051–1069.
author keywords: trust in automation; neuroergonomics; dynamic causal modeling; electroencephalography
MeSH headings : Automation; Bayes Theorem; Brain; Brain Mapping / methods; Humans; Magnetic Resonance Imaging / methods; Reproducibility of Results; Trust
TL;DR:
It is indicated that trust and distrust can be two distinctive neural processes in human–automation interaction—distrust being a more complex network than trust, possibly due to the increased cognitive load.
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Objective Using dynamic causal modeling (DCM), we examined how credibility and reliability affected the way brain regions exert causal influence over each other—effective connectivity (EC)—in the context of trust in automation.