The Neural Control of Disconjugate Saccades

为了在三维空间中准确地观察远近目标，有关相对深度的信息从视觉皮层发送到脑干的运动控制中心，脑干的运动控制中心反过来产生适当的运动命令来移动眼睛。然而，令人惊讶的是，视觉皮层提供的深度信息是如何被用来精确地瞄准每只眼睛的视觉目标的，这是非常有争议的。因此，这个项目的目标是了解大脑如何控制眼球运动来准确地观察远近物体。我们之前的实验提供了令人信服的证据，证明长期以来被认为是纯共轭前运动驱动来源的脑干跳跃性产生器，实际上提供了暂时适当的趋同信息，以驱动近目标和远目标之间的快速跳跃性眼球运动（即析取的跳跃性）。事实上，大多数神经元动态地编码单个眼睛的运动，它们随时间变化的放电编码产生准确的解耦扫视所需的驱动。

To accurately look between near and far targets in 3-dimensional space, information about relative depth is sent from the visual cortex to the motor control centers in the brainstem, which in turn generate appropriate motor commands to move the eyes. Surprisingly, however, how the depth information supplied by the visual cortex is used to precisely aim each eye on a visual target is highly controversial. Accordingly, the objective of this project is to understand how the brain controls eye movements to accurately look between near and far objects. Our previous experiments provided compelling evidence that the brainstem saccadic generator, which was long considered a source of purely conjugate premotor drive, in fact provides temporally appropriate vergence information to drive rapid saccadic eye movements between near and far targets (i.e., disjunctive saccades). Indeed, the majority neurons dynamically encode the movement of an individual eye, and their time-varying discharges encode the drive required to produce accurate disconjugate saccades. In the present proposal, I will take this work to the next level and identify the source of the vergence-related signal to premotor neurons. I will focus on two candidate regions: 1) the superior colliculus, which receives inputs from disparity sensitive cortical regions such as the frontal eye fields, and 2) the cerebellum (specifically, oculomotor vermis and fastigial nucleus), which contain neurons with important projections to premotor saccadic neurons. The eye command signals encoded in these regions will be quantified in alert behaving monkeys during near-far viewing tasks. System identification techniques developed in our laboratory will be used to describe neuronal responses dynamics. The resultant findings will be used to generate a novel physiologically-relevant model of binocular control. Taken together, our physiological and modeling results will also provide a foundation for understanding the general strategies used by the brain to coordinate the activation of multiple muscles in the control of more complex voluntary movements.