CRCNS Research Proposal: Coding and Propagation of Uncertainty Information During Perceptual Decisions

就像阿加西·克里斯蒂侦探小说中的马普尔小姐一样，大脑经常面临着从嘈杂和模棱两可的线索中推断世界状态的任务。一个重要的问题是，大脑是否以一种近乎最佳的方式进行这种推理，如果是的话，又是如何进行的。该项目将人类和猴子的视觉决策实验与计算模型和最先进的猴子种群记录相结合，来研究这个问题。该项目将带来对神经编码以及神经元和行为之间关系的新见解。在该任务中，观察者将短暂闪现的定向刺激归类为两类之一。类由方向上固定的、重叠的概率分布来定义。两种常见的不确定性形式在这项任务中发挥了作用。感官观察中的噪声会导致感觉的不确定性，但即使去除了这种噪声，给定的观察也会与任一类别一致；这是模糊性或类别不确定性的一个例子。最优决策策略要求观察者跟踪每一次试验的感觉不确定性，并将这些信息与两个类别的知识适当地结合起来。这个项目的第一部分将决定人类和猴子在这项任务中采取的计算策略是否接近最优。第二部分是关于感觉不确定性是否以及如何在猴子初级视觉皮质逐一试验的基础上被编码，并随后用于猴子的决定。这项研究将检验著名的感官不确定性表征理论框架。在第三部分，将考察感觉不确定性信息从视觉皮质到更高级别的决策区域--前额叶皮质的传播。综上所述，该项目将构成在大脑皮层人口层面上对最佳推理的第一次全面测试。

Like Miss Marple in an Agathie Christie detective novel, the brain is often faced with the task of inferring a state of the world from noisy and ambiguous clues. An important question is whether, and if so how, the brain performs such inference in a near-optimal manner. This project combines visual decision-making experiments in humans and monkeys with computational modeling and state-of-the-art population recordings in monkey to investigate this question. The project will lead to new insights into the neural code and the relation between neurons and behavior.A task is used in which an observer classifies a briefly flashed oriented stimulus into one of two classes. The classes are defined by fixed, overlapping probability distributions over orientation. Two common forms of uncertainty play a role in this task. Noise in the sensory observation causes sensory uncertainty, but even if this noise were taken away, a given observation would be consistent with either class; this is an example of ambiguity or class uncertainty. The optimal decision strategy requires the observer to keep track of sensory uncertainty on every trial and to appropriately combine this information with knowledge of the two classes.The first part of this project will determine whether the computational strategy taken by humans and monkeys during this task is near-optimal. The second part is concerned with whether and how sensory uncertainty is encoded on a trial-by-trial basis in monkey primary visual cortex, and subsequently used in the monkey's decision. This study will put to the test well-known theoretical frameworks for the representation of sensory uncertainty. In the third part, the propagation of sensory uncertainty information from visual cortex to a higher-level decision area, prefrontal cortex, will be examined. Taken together, this project will constitute the first comprehensive test of optimal inference at the level of cortical populations.