Topic: Hierarchical Bayesian Modelling

Jointly fitting models to behavioural and neurophysiological decision-related signals, in principle, enables greater scope for model complexity and richer inferences than can be achieved using behavioural data alone. In recent work, constraining the starting points of evidence-accumulating decision variables to match motor preparation levels reflected in mu/beta EEG activity facilitated the identification of evidence-independent “urgency” contributions to the decision process and drift-rate and non-decision time modulations by speed pressure, which were misestimated by standard models of behav