Computational EEG modelling of decision making under ambiguity reveals spatio-temporal dynamics of outcome evaluation

Publication date: 15 March 2017
Source:Behavioural Brain Research, Volume 321
Author(s): Lee Jollans, Robert Whelan, Louise Venables, Oliver H. Turnbull, Matteo Cella, Simon Dymond
Complex human cognition, such as decision-making under ambiguity, is reflected in dynamic spatio-temporal activity in the brain. Here, we combined event-related potentials with computational modelling of the time course of decision-making and outcome evaluation during the Iowa Gambling Task. Measures of choice probability generated using the Prospect Valence Learning Delta (PVL-Delta) model, in addition to objective trial outcomes (outcome magnitude and valence), were applied as regressors in a general linear model of the EEG signal. The resulting three-dimensional spatio-temporal characterization of task-related neural dynamics demonstrated that outcome valence, outcome magnitude, and PVL-Delta choice probability were expressed in distinctly separate event related potentials. Our findings showed that the P3 component was associated with an experience-based measure of outcome expectancy.



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