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Behavioural brain research v.321, 2017년, pp.28 - 35   SCI SCIE
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Computational EEG modelling of decision making under ambiguity reveals spatio-temporal dynamics of outcome evaluation

Jollans, Lee (School of Psychology, Trinity College Dublin, Dublin 2, Ireland ); Whelan, Robert ( School of Psychology, Trinity College Dublin, Dublin 2, Ireland ); Venables, Louise ( Department of Psychology, Swansea University, Singleton Campus, Swansea SA2 8PP, United Kingdom ); Turnbull, Oliver H. ( School of Psychology, Bangor University, Bangor, Gwynedd LL57 2DG, United Kingdom ); Cella, Matteo ( Department of Psychology, Swansea University, Singleton Campus, Swansea SA2 8PP, United Kingdom ); Dymond, Simon ( Department of Psychology, Swansea University, Singleton Campus, Swansea SA2 8PP, United Kingdom );
  • 초록  

    Abstract 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. Highlights Complex human cognition is reflected in dynamic spatio-temporal activity. We combined event-related potentials with computational modelling. A general linear model created a three-dimensional map of neural dynamics.


  • 주제어

    Computational models .   Decision making .   EEG .   Iowa gambling task.  

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