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: 8528613
• 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 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8528613
• 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.

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，但人脸处理的神经回路才刚刚开始被理解。特别是，它仍然不清楚反馈如何在神经水平上反复修改面部表征，尽管有证据表明，面部处理是一个动态的过程。在这里，我将研究反馈在灵长类动物下颞叶皮层（IT）的面孔补丁系统中的作用。在该项目的指导阶段（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神经反应的动态。我收集的初步数据显示，随着时间的推移，中面部斑块的神经反应会演变，以与前面部斑块的活动相关的方式来解决模糊信息。下一个合乎逻辑的步骤，这是指导阶段（目标2）的后半部分的目标，是测量前面部贴片如何因果地影响中面部贴片的活动，并且前区域的药理学失活将用于系统地映射反馈的轨迹。在该项目的独立阶段（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射如何快速和精确地调节中面斑块活动。该项目的一个创新特点是使用一种新型的立体微焦点X射线系统，用于记录所有反馈源和目标的精确空间位置，从而重建大尺度（目标2）和细尺度（目标3）源-目标相互作用的地图。这一奋进最终将产生一个工程师版本的神经电路图，并约束计算模型，提出不同的角色（增益控制，共振和预测）的反馈。拟议的工作将在麻省理工学院的Jim DiCarlo实验室启动。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。在该项目的指导阶段（K99;目标1和2），我将获得群体神经记录，药理学失活和光遗传学技术的培训，为在该项目的第二阶段（R 00;目标3）过渡到独立职位提供实验平台。