Midbrain Mechanisms of Sensory-Guided Oculomotor Choice

描述（由申请人提供）：本项目的目标是调查上级丘（SC）对选择行为的感知和运动贡献;具体来说， 我们建议在紧急决策任务的背景下这样做，使我们能够以前所未有的有效性将感知和运动表现分离开来。神经科学家已经深入研究了选择行为，在许多任务中，做出感知判断，然后进行运动报告。虽然这种方法非常成功，但也有局限性。最值得注意的是，各种隐性因素，如注意力，预期，动机或任务难度可以相互交易，产生无法通过标准心理物理指标解决的模糊性，即，反应时间和选择准确性。因此，关于选择时机的基本问题仍然知之甚少。做出知觉判断和执行运动动作来报告需要多长时间？受试者在什么时间点接受特定选项？当成功率增加时，是因为刺激被更有效地处理，或者更快，还是因为更多的时间被用于分析？这个项目中的PI最近开发了一个紧急选择任务，通过这个任务，这些问题--以及潜在的神经机制--可以以一种直接、明确的方式进行检查。它产生了一种新的心理物理测量，转速曲线，它表征了一个主题的知觉表现随着时间的推移独立的运动执行。PI还构建了一个计算模型，将神经元反应与受试者的行为联系起来， 详细在所提出的实验中，将从训练的猴子记录SC中的神经元活动。 to perform执行this novel新saccadic-choice扫视-choice选择task任务.将讨论两个问题。首先，参与的SC在知觉处理，这与SC的牢固确立的角色，在扫视执行，仍然不太好的特点。将利用转速曲线的独特性质来确定何时感知信息通知SC活动，以及这如何与任务执行期间受试者的感知的时间演变相关（目标1）。此外，将使用各种空间和时间配置将亚阈值微刺激电流注入SC，以确定人工诱发的活动如何影响感知和运动性能（Aim 2）。第二个问题是，当选择行为受到多感官刺激（即同时呈现视觉和听觉线索）的驱动时，它是如何变化的。的 SC是已知的最有效地响应这种刺激组合，但他们的影响在选择行为尚未进行评估。一个多感觉的任务变体将被用来确定是否多感觉整合改变知觉判断或扫视运动计划的速度（目标3）。这项工作将提供有关感知信息如何动态转化为运动输出的关键见解，将表征神经元水平的多感觉整合如何导致增强的行为表现，并将确定SC如何参与这些过程。

DESCRIPTION (provided by applicant): The goal of this project is to investigate the perceptual andmotor contributions of the superior colliculus (SC) to choice behavior; specifically, we propose to do this in the context of an urgent decision-making task that allows us to dissociate perceptual and motor performance with great, unprecedented effectiveness. Neuroscientists have intensely studied choice behavior with numerous tasks in which a perceptual judgement is made and is followed by a motor report. While highly successful, this approach has limitations. Most notably, various covert factors such as attention, anticipation, motivation or task difficulty can be traded against each other, creating ambiguities that cannot be resolved via standard psychophysical metrics, i.e., reaction time and choice accuracy. Thus, fundamental questions about the timing of choices remain poorly understood. How long does it take to make a perceptual judgement versus executing a motor action to report it? At what point in time is a subject committed to a particular option? When the success rate increases, is it because stimuli are processed more efficiently, or faster, or because more time is dedicated to their analysis? The PIs in this project recently developed an urgent-choice task with which these questions - and the underlying neural mechanisms - can be examined in a direct, unambiguous way. It produces a new psychophysical measure, the tachometric curve, which characterizes a subject's perceptual performance over time independently of motor execution. The PIs have also constructed a computational model that relates neuronal responses to the subjects' behavior with great quantitative detail. In the proposed experiments, neuronal activity in the SC will be recorded from monkeys trained to performthis novel saccadic-choice task. Two problems will be addressed. First, the participation of the SC in perceptual processing, which in contrast to the SC's firmly established role in saccade execution, remains less well characterized. The unique properties of the tachometric curve will be exploited to determine when perceptual information informs the SC activity, and how this correlates with the temporal evolution of the subject's percept during task performance (Aim 1). In addition, subthreshold microstimulation current will be injected into the SC using various spatial and temporal configurations to determine how the artificially evoked activity impacts perceptual and motor performance (Aim2). The second problemis how choice behavior changes when it is driven by multisensory stimuli; that is, by the simultaneous presentation of visual and auditory cues. The SC is known to respond most effectively to such stimulus combinations, but their impact during choice behavior has not been assessed. A multisensory variant of the task will be used to determine whether multisensory integration alters the speed of the perceptual judgements or of the saccadic motor plans (Aim 3). This work will provide critical insight about how perceptual information is dynamically translated into motor output, will characterize how multisensory integration at the neuronal level leads to enhanced behavioral performance, and will determine how the SC participates in these processes..