CAREER: Probabilistic inference in the primate visual system

本课题研究了知觉推理(即推理感觉环境的性质)和知觉内省(即评估推理的质量)过程中感觉和前额叶皮质之间的功能关系。这两项任务的关键是，它们都需要考虑感知的不确定性。当知觉的不确定性很高时(即当感官测量不明确时)，知觉推论往往由先前的经验指导，而对感知指导的决定的信心往往较低。神经回路如何评估感觉信号的可靠性，并将这种评估用于知觉推理和知觉内省，目前还没有很好的理解。这项拟议的研究将在两个方面促进我们的理解。首先，通过同时记录执行知觉推理和内省任务的动物的早期视觉皮质和下游联想皮质的神经活动。其次，通过使用这些经验观察来评估不同大脑区域如何在面对不确定性时协同工作来产生感知和认知的理论建议。将收集的数据和将开发的数据分析工具将提供给神经科学界。该项目还将产生更广泛的影响，为一群来自代表性不足背景的初三和高年级学生提供德克萨斯州奥斯汀大学计算和系统神经科学方面的带薪暑期研究实习机会，并让德克萨斯州中部的初中生和高中生参与神经科学。该项目将以灵长类V1及其前额叶皮质(FEF区)的下游靶标为模型系统，研究概率感知推理的神经实现。该提案采用了非人类灵长类动物的行为任务，在这些任务中，非人类灵长类动物通过眼跳运动来交流刺激方向判断(以及他们对这一决定的信心)。任务范式将知觉推理和知觉自信的神经关联与行动计划的神经关联区分开来。神经群体活动将用多个联合插入的多电极阵列来记录。该方案利用神经编码的功能模型来研究V1和FEF群体活动之间的关系的性质、强度和动态演变。这些实验涉及对刺激特征、感觉不确定性和先验概率的操纵。因此，该项目旨在揭示神经编码的规范原则，这些原则在许多大脑区域和模式中都被实例化。收集的数据将对寻求连接电路结构和功能的大规模分布式计算模型的开发具有价值。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project investigates the functional relation between sensory and prefrontal cortex during perceptual inference (i.e., inferring properties of the sensory environment) and perceptual introspection (i.e., evaluating the quality of this inference). Key to both tasks is that they require consideration of perceptual uncertainty. When perceptual uncertainty is high (i.e., when sensory measurements are ambiguous), perceptual inferences tend to be guided by prior experience, and confidence in perceptually guided decisions tends to be low. How neural circuits assess the reliability of sensory signals and use this assessment for perceptual inference and perceptual introspection is not well understood. The proposed research will advance our understanding in two ways. First, by simultaneously recording neural activity in early visual cortex and down-stream association cortex from animals performing perceptual inference and introspection tasks. Second, by using these empirical observations to evaluate theoretical proposals of how different brain regions work together to produce perception and cognition in the face of uncertainty. The data that will be collected and the data-analysis tools that will be developed will be made available to the neuroscience community. This project will also have a broader impact by providing a select group of junior and senior students from underrepresented backgrounds with a paid summer research internship in computational and systems neuroscience at UT Austin, and by engaging middle- and high-school students of central Texas in neuroscience.This project will study the neural implementation of probabilistic perceptual inference, using primate V1 and its downstream targets in the prefrontal cortex (area FEF) as the model system. The proposal employs behavioral tasks in which non-human primates communicate stimulus orientation judgements (and their confidence in this decision) with saccadic eye movements. The task paradigms distinguish the neural correlates of perceptual inference and perceptual confidence from those of action planning. Neural population activity will be recorded with multiple jointly inserted multi-electrode arrays. The proposal leverages functional models of neural coding to study the nature, strength, and dynamic evolution of the relation between V1 and FEF population activity. The experiments involve manipulations of stimulus features, sensory uncertainty, and prior probability. As such, the project aims to uncover canonical principles of neural coding that are instantiated in many brain regions and modalities. The data collected will be valuable for the development of models of large-scale distributed computation that seek to bridge circuit structure and function.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.