A Biologically Plausible Computational Theory for Value Integration and Action Selection in Decisions with Competing Alternatives
Fig 3
Characteristic examples of the simulated model activity in single- and two- target trials with the corresponding reaching movements, for a “rapid reaching choice” experiment.
Each trial started with either a single black target or two gray potential targets presented simultaneously in both visual fields. In the single-target trials, the actual target location was known prior to reach onset (upper row). In the two-target trials, reaching movements were initiated without knowing the actual location of the target (bottom row). Each of the two potential targets had an equal probability to turn black (i.e., cued target). When the hand crossed a pre-defined threshold (black discontinuous line in the bottom right panel), the actual target was cued for action. The left and the middle columns depict the activity in the spatial sensory input field and the motor plan formation field for the single- (top row) and two- (bottom row) target trials. Notice that when both potential targets were presented, the activity in the motor plan formation field was weaker, compared to activity generated in a single-target trials where the actual location of the target was known in advance. The populations of neurons related to the two potential targets remained active and competed against each other until the actual target was cued, and the activity of the non-cued target vanished. On trials when only a single target is presented, the reaches were made directly to the target. However, when two potential targets are presented in the field, the model generates spatial averaging reaching movements—i.e., initial reaching movement towards an intermediate position between the two targets followed by a corrective movement to the cued target. “Movement time” (or response time) indicates the time that the framework initiated the reaching movement.