Active inference unifies intentional and conflict-resolution imperatives of motor control
Fig 7
First simulation: reaching a fixed target in space.
(A) Schematic representation of the agent having direct vision of his own arm, which initially rests on a table surface and could only move by rotating the elbow around the vertical axis. (B) Task specification. The agent has to reach a target location (green star) by rotating the arm so to reach the configuration shown in grey, at θT, corresponding to having the hand at the target location [xT, yT] = g(θT). (C-G) Dynamics of the model variables during the task. The vertical bars mark the time at which the target location is disclosed. (C) Joint angle of the real (black) and inferred (red) arm configurations, expressed in radians; the green line represents the arm configuration θT for which the hand is on the target. (D) Real (black) and inferred (red) velocity of the elbow joint angle velocity. (E) Action, represented in our model as an angular acceleration. (F) The three prediction errors considered in the model: model dynamics error (green) and the two sensory errors, proprioceptive (magenta) and visual (blue). Please note that in this plot, the prediction error units correspond to different dimensions and cannot be directly compared. (G) Contributions of proprioceptive (magenta) and visual (blue) errors in determining the action, more specifically the two vector components in the r.h.s. of Eq G4 in Fig 6. See the main text for explanation.