Topic: urgency

Finding the right amount of deliberation, between insufficient and excessive, is a hard decision-making problem that depends on the value we place on our time. Average reward, putatively encoded by tonic dopamine, serves in existing reinforcement learning (RL) theory as the stationary opportunity cost of time. This cost often varies with context, however, which changes over time. Current RL approaches thus do not efficiently handle task non-stationarity. Yet, the brain's representation of and computation with time's value, including its impact on the neural dynamics of deliberation, must accou

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