Microstimulation in a spiking neural network model of the midbrain superior colliculus

Abstract The midbrain superior colliculus (SC) generates a rapid saccadic eye movement to a sensory stimulus by recruiting a population of cells in its topographically organized motor map. Supra-threshold electrical microstimulation in the SC reveals that the site of stimulation produces a normometric saccade vector with little effect of the stimulation parameters. Moreover, electrically evoked saccades (E-saccades) have kinematic properties that strongly resemble natural, visual-evoked saccades (V-saccades). These findings support models in which the saccade vector is determined by a center-of-gravity computation of activated neurons, while its trajectory and kinematics arise from downstream feedback circuits in the brainstem. Recent single-unit recordings, however, have indicated that the SC population also specifies instantaneous kinematics. These results support an alternative model, in which the desired saccade trajectory, including its kinematics, follows from instantaneous summation of movement effects of all SC spike trains. But how to reconcile this model with microstimulation results? Although it is thought that microstimulation activates a large population of SC neurons, the mechanism through which it arises is unknown. We developed a spiking neural network model of the SC, in which microstimulation directly activates a relatively small set of neurons around the electrode tip, which subsequently sets up a large population response through lateral synaptic interactions. We show that through this mechanism the population drives an E-saccade with near-normal kinematics that are largely independent of the stimulation parameters. Only at very low stimulus intensities the network recruits a population with low firing rates, resulting in abnormally slow saccades. Author Summary The midbrain Superior Colliculus (SC) contains a topographically organized map for rapid goal-directed gaze shifts, in which the location of the active population determines size and direction of the eye-movement vector, and the neural firing rates specify the eye-movement kinematics. Electrical microstimulation in this map produces eye movements that correspond to the site of stimulation with normal kinematics. We here explain how intrinsic lateral interactions within the SC network of spiking neurons sets up the population activity profile in response to local microstimulation to explain these results.