Representation and utilization of sensory uncertainty in the primate visual system

项目摘要 感觉不确定性在灵长类视觉系统中的表征和利用 准确的感知对生存至关重要，但可用的感官信息往往是不可能的。 贫困。观察者在做出决定时，似乎知道自己的不确定性， 感知决策以及反映这些决策的准确性。这意味着 处理感觉信息的神经回路也代表了这种不确定性。 信息.这是怎么回事？本建议旨在回答这一问题，并调查其 对感知和行为的影响。通过结合理论神经科学， 电生理记录和知觉实验，这项建议将整合结果 从人类和非人类灵长类动物，以联合收割机结合感官不确定性的表征， 它的神经基础。这项建议包括三个具体的研究和培训目标。一是 将利用理论和生理学来开发和测试一种新的计算理论， 感觉神经元编码刺激的不确定性（Aim 1）。我们提出一种观点，即刺激特征 是由视觉神经元的反应平均值编码的，但刺激的不确定性是由 响应增益的方差。我们将进行早期视觉的电生理记录， 皮层，同时呈现具有不同不确定性水平的刺激，以进一步开发和测试这一点。 理论这一目标将提供强有力的培训，在计算神经科学和设计 用理论驱动的方法进行实验。其次，我们将确定下游电路如何 解码刺激感知的不确定性（目标2），通过记录来自动物的神经元训练， 判断嘈杂的感官刺激的感知可靠性。实现这一目标将需要记录 同时从多个区域的大型神经元群体中提取，因此将提供以下训练： 尖端的大规模电生理技术最后，我们将连接的见解 从非人类灵长类动物的神经生理学实验中收集到的人类行为， 一种新的方法来引发感知信心（目标3）。这一方法将涉及以下方面的培训： 并应用基于价值的决策概念，严格隔离信心 行为受到潜在的奖励偏好、风险态度等的影响。这些 实验将是至关重要的，作为探索可能的破坏的潜在基础。 神经精神障碍中的不确定性编码总的来说，这项建议的结果将有助于 揭示了感觉回路在表征和利用不确定性来引导视觉的作用。 perception.

Project Summary Representation and utilization of sensory uncertainty in the primate visual system Accurate perception is vital for survival, but available sensory information can often be impoverished. Observers act with seeming knowledge of their own uncertainty when making perceptual decisions as well as reflecting on the accuracy of those decisions. This implies that neural circuits which process sensory information also represent the uncertainty of this information. How does this work? This proposal seeks to answer this question and investigate its implications for perception and behavior. By combining theoretical neuroscience, electrophysiological recordings, and perceptual experiments, this proposal will integrate results from human and nonhuman primates to combine the characterization of sensory uncertainty and its neuronal basis. This proposal comprises three specific research and training aims. First, we will leverage theory and physiology to develop and test a novel computational theory of how sensory neurons encode stimulus uncertainty (Aim 1). We propose a view that stimulus features are encoded by the response mean of visual neurons, but stimulus uncertainty is encoded by variance in the response gain. We will conduct electrophysiological recordings in the early visual cortex while presenting stimuli with varying levels of uncertainty to further develop and test this theory. This aim will provide strong training in computational neuroscience and the design of experiments with a theory-driven approach. Second, we will identify how downstream circuits decode stimulus uncertainty for perception (Aim 2), by recording neurons from animals trained to judge the perceptual reliability of noisy sensory stimuli. Achieving this aim will require recording from large neuronal populations across multiple areas simultaneously, so will provide training in cutting-edge, large-scale electrophysiological techniques. Finally, we will connect the insights gleaned from neurophysiological experiments in nonhuman primates to human behavior through a novel approach to eliciting perceptual confidence (Aim 3). This approach will involve training in and application of concepts from value-based decision-making to rigorously isolate confidence behavior from the potential influence of reward preferences, such as risk attitude. These experiments will be vital as a potential foundation for exploring the possible disruption of uncertainty encoding in neuropsychiatric disorders. Overall, results from this proposal will help to reveal the role of sensory circuits in representing and utilizing uncertainty to guide visual perception.