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与利用 准确的感知对生存至关重要，但可用的感官信息往往 穷困的。观察者在做出决定时，似乎知道自己的不确定性 它不仅反映了感性的决策，也反映了这些决策的准确性。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？这项提案试图回答这个问题，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，这一建议将综合结果 从人类和非人类灵长类动物到结合感觉不确定性的特征和 它的神经基础。这项建议包括三个具体的研究和培训目标。首先，我们 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(目标1)。我们提出了一种观点，即刺激的特征 是由视觉神经元的反应平均值编码的，而刺激不确定性是由 响应增益中的方差。我们将在早期视觉中进行电生理记录 同时以不同程度的不确定性呈现刺激以进一步发展和测试这一点 理论。这一目标将提供计算神经科学和设计的强大培训 用理论驱动的方法进行实验。第二，我们将确定下游电路如何 解码感知的刺激不确定性(目标2)，通过记录来自训练为 判断噪声感官刺激的知觉可靠性。要实现这一目标，就需要录音 同时来自多个区域的大量神经元群体，因此将在 尖端的、大规模的电生理技术。最后，我们将把洞察力 从非人灵长类动物的神经生理学实验中收集到的关于人类行为的 激发知觉自信的新方法(目标3)。这一方法将包括培训 以及应用基于价值的决策的概念来严格隔离信心 行为来自潜在的回报偏好的影响，如风险态度。这些 实验将是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，这项提案的结果将有助于 揭示感觉回路在表征和利用不确定性引导视觉方面的作用 感知力。

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.