Population Dynamics in the Oculomotor System

项目总结 感觉运动转换是由运动前大脑网络介导的，其中单个神经元代表 与感觉、认知和运动相关的信息。在上丘(SC)，有一个中枢，用于 产生视觉引导的眼球跳动，许多神经元在所有三个阶段都是活跃的，发出 感觉和运动事件期间短暂的、高频的尖峰爆发，并表现出持续的、较低的 两次爆炸之间的射速活动。对多个信息维度的混合选择性体现了 一种潜在有效的神经系统信息表示模式，但它也引发了至关重要的 问：是什么特征区分了这两次爆发，解码者如何准确地知道何时启动？ 一种运动，如果它的输入在不需要运动的时候是活动的(例如，响应于感觉 刺激)？在低频活动中编码了哪些信息，在此过程中是如何调制的 不同的认知需求？我们认为，这些问题的答案不在于个人的行为。 而不是在活跃的神经元群体和时间动力学中。特定目标1测试 通过量化区分感觉和运动的特征来启动运动的各种神经机制 整个南卡罗来纳州的人口都发生了汽车爆裂。具体目标2侧重于干预的低频活动 在这两次爆发之间。我们将使用动力学系统的方法来描述神经轨迹是如何 在感觉运动转换过程中的进化，以及对于不同认知负荷的任务它是如何不同的。一种能力 根据任务要求区分神经轨迹表明了一种潜在的机制，通过它 不同维度的信息可以被多路传输到同一群神经元中。

PROJECT SUMMARY Sensorimotor transformations are mediated by premotor brain networks where individual neurons represent sensory, cognitive, and movement-related information. In the superior colliculus (SC), a central hub for producing visually-guided saccadic eye movements, many neurons are active during all three stages, emitting transient, high-frequency bursts of spikes during the sensory and motor events and exhibiting persistent, lower firing rate activity in-between the bursts. The mixed-selectivity to multiple dimensions of information exemplifies a potentially efficient mode of information representation by the nervous system, but it also raises crucial questions: What features differentiate the two bursts, and how does a decoder know precisely when to initiate a movement if its inputs are active at times when a movement is not desired (e.g., in response to sensory stimulation)? What information is encoded in the low-frequency activity, and how is it modulated during different cognitive demands? We reason that the answers to these questions lie not in the activity of individual neurons but rather across the population of active neurons and in the temporal dynamics. Specific Aim 1 tests various neural mechanisms of movement initiation by quantifying features that differentiate the sensory and motor bursts across the SC population. Specific Aim 2 focuses on the low-frequency activity that intervenes between the two bursts. We will use a dynamical systems approach to characterize how the neural trajectory evolves during sensorimotor transformation and how it differs for tasks with different cognitive loads. The ability to discriminate neural trajectories according to task demands indicates a potential mechanism by which different dimensions of information can be multiplexed into the same population of neurons.