Simple go/no-go task modelled under AI.

(a) Structure of the task (see main text) (b)-(d) The state-action heatmap showing inferences on the agent’s state over a rare ‘Go!’ trial. Large updates are required at t = 2, after the animal receives the ‘go’ cue which forces it to update its action plans and state inferences. This update is proposed to cause a large, time specific input into LC, which causes a sudden phasic burst of LC activity. The lower part of the Fig shows the full modelling of the go/no-go task, with components as described in Fig 1.