Visual-motor transformations for smooth pursuit eye movements
When a small, smoothly moving object appears, primates are able to generate a smooth eye movement having a velocity nearly equal to the velocity of the target. The basic anatomical circuit for pursuit is known -- from retina to motoneuron. We are trying to understand how visual inputs related to moving targets are converted by the brain to commands for motor action. In the past 5 years, we have discovered that pursuit is a complex voluntary motor behavior that comprises many components. These include: the representation of target motion with respect to the eye, primarily in extrastriate area MT (Lisberger & Movshon 1999; Osborne et al 2004); pooling of the population response in MT to acquire good estimates of the direction and speed of target motion (Churchland & Lisberger 2001; Gardner et al 2004); an on-line volume control that regulates how strongly visual inputs are transmitted to the motor system (Tanaka & Lisberger 2001); the ability to choose targets based on a spatial window of motor attention under the control of orienting, saccadic eye movements (Gardner & Lisberger 2002); learning based on the recent history of target motions (Chou & Lisberger 2004; Medina & Lisberger 2005); and cerebellar compensation for the physical properties of the eye and orbit.
Our work is currently focusing on two main concepts.
1) We are using theoretical approaches to exploit the variation in natural pursuit behavior and neural responses. Our goal is to correlate the variation in neural and motor behavior as a way of understanding how different groups of neurons contribute to pursuit behavior. Recent unpublished results have revealed that the variation in pursuit behavior can be understood in terms of errors in estimates of the direction, speed, and time of onset of target motion. The coordinate system of the variations implies pursuit operates at the precision to sensory coding, and that motor noise may arise primarily from sensory representations. By relating variations in sensory representation to variations in motor behavior, we will understand how neurons pool the sensory population response to generate eye movements.
2) We are using a combination of precise measurements of eye movement, electrical stimulation, and neural recordings to evaluate the neural basis for modulation of the strength of visual transmission to the motor system. We have evidence that the neural mechanism of this "gain" modulation is related to learning, target choice, and motor attention. Our goal is to identify the neural loci and mechanisms of gain modulation, learning, and target choice.