Neural structure of a sensory decoder for motor control

This research investigates the neural mechanisms underlying the transformation of sensory input into motor output, focusing on smooth pursuit eye movements. The study challenges the traditional "signal-dependent noise" model by demonstrating that target size significantly alters the relationship between behavioral variance and mean, contradicting established psychophysical laws. A novel circuit model incorporating multiple parallel pathways and noise in the gain control pathway is proposed to account for these findings. The model successfully reproduces behavioral and neural response statistics, highlighting the importance of considering parallel processing and pathway-specific noise in sensory decoding.

Seth W. Egger, Stephen G. Lisberger