The role of cortical feedback in visual face processing

皮层反馈在视觉面部处理中的作用

• 批准号: 8354364
• 负责人: Elias Issa
• 金额: $ 9万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8354364
• 关键词: Anterior; Area; Brain; Commit; Computer Simulation; Conflict (Psychology); Coupling; Data; Detection; Disease; Engineering; Face; Face Processing; Feedback; Goals; Human; Image; Interdisciplinary Study; Laboratories; Macaca; Maps; Measures; Mentors; Modeling; Nature; Noise; Pathway interactions; Pattern; Perception; Phase; Play; Population; Positioning Attribute; Prevalence; Primates; Process; Process Measure; Property; Prosthesis; Recurrence; Research Infrastructure; Resolution; Retina; Role; Sensory; Series; Signal Transduction; Site; Social Behavior; Social Functioning; Source; Specific qualifier value; Specificity; System; Techniques; Testing; Time; Training; Vision; Visual; Work; base; design; face mask; improved; inferotemporal cortex; innovation; insight; interest; neural circuit; next generation; novel; optogenetics; reconstruction; relating to nervous system; research study; response; tool

DESCRIPTION (provided by applicant): Face recognition is an important part of everyday human social behavior, yet the neural circuits underlying face processing are only beginning to be understood. In particular, it remains unclear how feedback recurrently modifies face representations at the neural level despite evidence that face processing is a dynamic process. Here, I will study the role of feedback in the face patch system in primate inferotemporal cortex (IT). In the mentored phase of the project (Aim 1), I will probe the dynamics of neural responses across the face pathway under challenging image conditions (noise, occlusion) designed to maximally engage recurrent processing. Preliminary data that I have collected show that neural responses in the middle face patch evolve over time to resolve ambiguous information in a manner that correlates with activity in the anterior patches. The next logical step, which is goal of the second half of the mentored phase (Aim 2), is to measure how the anterior face patches causally influence activity in the middle face patch, and pharmacological inactivation of anterior regions will be used to systematically map the locus of feedback. In the independent phase of the project (Aim 3), I will use newly developed optogenetic silencing tools to test how rapidly and precisely projections arising from within the feedback locus can modulate middle face patch activity. An innovative feature of this project is the use of a novel stereo microfocal x-ray syste for registering the precise spatial position of all feedback sources and targets allowing for reconstruction of large scale (Aim 2) and fine scale (Aim 3) maps of source-target interactions. This endeavor will eventually yield an engineer's version of a neural circuit diagram and constrain computational models proposing different roles (gain control, resonance, and prediction) for feedback. The proposed work will be initiated in the laboratory of Jim DiCarlo at MIT. Dr. DiCarlo is a committed mentor that leads a highly collaborative, interdisciplinary research group. During the mentored phase of the project (K99; Aims 1 and 2), I will acquire training in techniques for population neural recording, pharmacological inactivation, and optogenetics providing an experimental platform for transition to an independent position in the second phase (R00; Aim 3) of the project. PUBLIC HEALTH RELEVANCE: How the collective action of distributed neural systems leads to our rich percept of the visual world is not well understood, and disorders of the circuits involved in perception, especially those involved in face recognition, can impair normal social function. Understanding the neural circuitry underlying face processing will provide valuable insights into how humans see, will improve next generation brain prosthetics for restoring visual function, and will inspire artificial vision systems.

描述（由申请人提供）：人脸识别是人类日常社会行为的重要组成部分，然而人们对人脸处理背后的神经回路的了解才刚刚开始。特别是，尽管有证据表明面部处理是一个动态过程，但仍不清楚反馈如何在神经水平上周期性地修改面部表征。在这里，我将研究反馈在灵长类动物颞下皮层（IT）的面部补丁系统中的作用。在项目的指导阶段（目标1），我将探索在具有挑战性的图像条件下（噪声，遮挡），旨在最大限度地参与循环处理的面部通路的神经反应动力学。我收集的初步数据表明，面部中间区域的神经反应随着时间的推移而演变，以一种与前区域活动相关的方式来解决模糊信息。下一个合乎逻辑的步骤，也是指导阶段后半段的目标（目标2），是测量前部面部斑块如何对中间面部斑块的活动产生因果影响，并且前部区域的药理失活将用于系统地绘制反馈位点。在项目的独立阶段（目标3），我将使用新开发的光遗传沉默工具来测试反馈位点内产生的投影如何快速准确地调节中间面部斑块活动。该项目的一个创新特点是使用了一种新型的立体微焦x射线系统，用于记录所有反馈源和目标的精确空间位置，从而可以重建源-目标相互作用的大比尺（目标2）和精细比尺（目标3）地图。这一努力最终将产生工程师版本的神经电路图，并约束为反馈提出不同角色（增益控制、共振和预测）的计算模型。这项提议的工作将在麻省理工学院吉姆·迪卡洛的实验室开始。DiCarlo博士是一位忠诚的导师，领导着一个高度协作的跨学科研究小组。在项目指导阶段（K99； Aims 1和2），我将接受群体神经记录、药物失活和光遗传学技术的培训，为项目二期（R00; Aim 3）过渡到独立位置提供实验平台。