Estimating the distribution of neural connections in the saccadic system using a biologically plausible learning rule — Preliminary results

Abstract

Saccades are rapid movements that reposition the eye in space. Several neural structures involved in saccadic control have been characterized, providing a unique opportunity for systems-level investigations of the premotor neural circuitry. This study focuses on the role of the superior colliculus (SC) in the planning and control of saccadic eye movements in monkeys. Saccade-related neural activity in the SC is highly distributed, with saccade displacement commands coded in a topologically-organized motor map. Downstream from the SC, this spatiotemporal code is transformed into the temporal code necessary to drive the oculomotor neurons. Researchers have postulated that this transformation is implemented in the projection weights between the SC and the brainstem saccadic burst generator. Here, an empirical neural network study is used to predict the topological variation of these projection weights. Estimates of the spatiotemporal neural activity in the SC were used as the open-loop inputs to the model. The projection weights from the SC to excitatory burst neurons (EBNs) in the brainstem were trained using a biologically plausible evolutionary learning rule (the chemotaxis algorithm), while well-known features of the downstream neural structures were fixed. The objective function was defined as the squared error between the model output and actual eye position trajectories for several magnitudes of horizontal saccades (integrated over time). Simulation results predict the excitatory connections from the SC to EBNs increase in strength or density with collicular location (from rostral to caudal).