Uncovering the Functional Organization and Cell Type Composition of Cortical Face Areas
揭示面部皮质区域的功能组织和细胞类型组成
基本信息
- 批准号:10227904
- 负责人:
- 金额:$ 24.66万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-01 至 2022-06-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAreaBiological ModelsBrainCalciumCallithrixCallithrix jacchus jacchusCellsCharacteristicsCodeComputer ModelsDevelopmentDimensionsDiseaseDisease modelElectrophysiology (science)FaceFace ProcessingFill-ItFoundationsFragile X SyndromeFunctional ImagingFunctional Magnetic Resonance ImagingFutureGoalsHeadHumanImageImaging TechniquesImmunohistochemistryImpairmentIn SituKnowledgeLeadLifeLocationMacacaMapsMental disordersMissionModelingMolecularMonkeysMusNeuronsOutcomePersonal SatisfactionPhotic StimulationPopulationPrimatesProsopagnosiaPublic HealthResearchResolutionSocial PerceptionSpecificitySportsSyndromeSystemTechnologyTestingTissuesTransgenic OrganismsUnited States National Institutes of HealthVisionVisualVisual CortexVisual system structureWilliams SyndromeWorkautism spectrum disorderbasecell typedevelopmental prosopagnosiadisabilityexperimental studyimprovedinformation processinginnovationinsightlissencephalyneuromechanismnovel strategiesobject recognitionoperationoptical imagingrelating to nervous systemsocialtranscriptomicstwo-photonvisual information
项目摘要
PROJECT SUMMARY
There is a fundamental gap in our understanding of how cortical circuit operations aid in high-level visual
information-processing like face recognition. The existence of this conceptual gap constitutes an important
problem because, until it is filled, it will neither be possible to explain face recognition and the computations face-
selective networks implement, nor understand the reasons for face-recognition impairments in disorders like
developmental prosopagnosia (face blindness). The long-term goal is to understand the neural mechanisms of
face recognition and build an artificial face-recognition system implementing neural computations and thus
explain face recognition mechanistically. The overall objective of this proposal presents a major step towards
this goal: the establishment of a new approach and a new model system that permits imaging of large neural
populations with single-cell resolution and cell-type differentiation within face-selective areas and surrounding
regions. These technological advances are expected to lead to the understanding of the functional organization
of face areas and how it impacts population codes for faces. The central hypotheses that will be tested, are that
face areas are composed of multiple columns with different functional specializations, and that facial codes are
highly cell type specific. The rationale for this proposal is that, after completion of the proposed research, the
central gap in the understanding of how cortical circuit operations enable high-level vision will have been
narrowed through the establishment of a new model system with unprecedented power to uncover the functional
organization and circuit mechanisms of population codes of object recognition. The hypothesis will be tested by
pursuing two specific aims: 1) Uncover the Spatial Organization of Face-Specializations of the Marmoset Brain;
and 2) Determine the Cell-Type Specificity of Face Representations in Face-Selective areas. Two-photon
calcium imaging during visual stimulation, combined with tissue clearing and cell type identification through
immunohistochemistry will identify the functional organization of face areas and their surroundings with single-
cell resolution. The approach is innovative because it presents a new and substantive departure from the status
quo and because it addresses an NEI-relevant problem, the neural mechanisms of social perception, in a new
way. The proposed research is significant, because it will provide a critical step forward towards a mechanistic
understanding of the neural computations performed inside face areas, allow for the development of highly
improved artificial face-processing systems, and advance our understanding of the functional organization of
face areas in a new dimension and from the level of single cells to the level of face areas. The outcomes will lay
the foundation for the determination of the molecular organization of high-level visual circuits and the
development of transgenic disease models. The project, therefore, is of direct relevance for the understanding
of prosopagnosia, as well as altered social information processing in syndromes like autism spectrum disorders,
fragile X, and Williams syndrome.
项目摘要
我们对皮层回路的运作如何帮助高水平视觉的理解存在着根本性的差距。
像人脸识别这样的信息处理。这种概念上的差距构成了一个重要的
问题,因为,直到它被填满,它既不可能解释人脸识别和计算脸-
选择性网络实现,也不理解面部识别障碍的原因,
发育性面容失认症(脸盲)。长期的目标是了解神经机制,
人脸识别,并建立一个实现神经计算的人工人脸识别系统,
机械地解释面部识别。该提案的总体目标是朝着以下目标迈出一大步:
这一目标:建立一种新的方法和一个新的模型系统,允许成像的大神经
在面选择性区域和周围区域内具有单细胞分辨率和细胞类型分化的群体
地区这些技术进步有望导致对职能组织的理解
以及它如何影响面部的人口代码。将要检验的中心假设是,
面部区域由具有不同功能专业化的多个列组成,并且面部代码是
高度细胞类型特异性。提出这项建议的理由是,在拟议的研究完成后,
在理解皮层回路运作如何实现高水平视觉方面的核心空白将是
缩小通过建立一个新的模式系统,以前所未有的权力,以揭示功能
物体识别的总体编码的组织和电路机制。该假设将通过以下方式进行检验:
追求两个特定的目标:1)揭示绒猴大脑面部特化的空间组织;
以及2)确定面部选择区域中面部表示的细胞类型特异性。双光子
在视觉刺激期间的钙成像,结合组织清除和细胞类型识别,
免疫组织化学将识别面部区域及其周围的功能组织,
细胞分辨率这一办法是创新的,因为它提出了一种新的、实质性的做法,
因为它解决了一个NEI相关的问题,社会感知的神经机制,在一个新的
路上了拟议的研究是重要的,因为它将提供一个关键的一步,
对面部区域内部执行的神经计算的理解,允许高度的
改进人工面部处理系统,并推进我们对面部功能组织的理解。
面区域在一个新的维度,并从单细胞水平的面区域的水平。结果将取决于
确定高级视觉电路的分子组织的基础,
转基因疾病模型的开发。因此,该项目直接关系到理解
面孔失认症,以及自闭症谱系障碍等综合征中改变的社会信息处理,
脆性X染色体和威廉姆斯综合征。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Winrich Freiwald其他文献
Winrich Freiwald的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Winrich Freiwald', 18)}}的其他基金
Revealing the mechanisms of primate face recognition with synthetic stimulus sets optimized to compare computational models
通过优化比较计算模型的合成刺激集揭示灵长类动物面部识别的机制
- 批准号:
10524626 - 财政年份:2022
- 资助金额:
$ 24.66万 - 项目类别:
Genetic dissection of cortical projection neurons in social brain circuits
社会脑回路中皮质投射神经元的基因解剖
- 批准号:
10452678 - 财政年份:2021
- 资助金额:
$ 24.66万 - 项目类别:
Genetic dissection of cortical projection neurons in social brain circuits
社会脑回路中皮质投射神经元的基因解剖
- 批准号:
10303553 - 财政年份:2021
- 资助金额:
$ 24.66万 - 项目类别:
Defining the Neural Circuits of Attention Control: A New Hypothesis
定义注意力控制的神经回路:一个新假设
- 批准号:
10356859 - 财政年份:2020
- 资助金额:
$ 24.66万 - 项目类别:
Defining the Neural Circuits of Attention Control: A New Hypothesis
定义注意力控制的神经回路:一个新假设
- 批准号:
10576288 - 财政年份:2020
- 资助金额:
$ 24.66万 - 项目类别:
Motor Compositionality in the Control of Facial Movements
控制面部运动的运动组合性
- 批准号:
10599085 - 财政年份:2019
- 资助金额:
$ 24.66万 - 项目类别:
Motor Compositionality in the Control of Facial Movements
控制面部运动的运动组合性
- 批准号:
10374011 - 财政年份:2019
- 资助金额:
$ 24.66万 - 项目类别:
CRCNS: US-Japan Research Proposal: The Computational Principles of a Neural Face Processing System
CRCNS:美日研究提案:神经人脸处理系统的计算原理
- 批准号:
9765324 - 财政年份:2018
- 资助金额:
$ 24.66万 - 项目类别:
CRCNS: US-Japan Research Proposal: The Computational Principles of a Neural Face Processing System
CRCNS:美日研究提案:神经人脸处理系统的计算原理
- 批准号:
10016303 - 财政年份:2018
- 资助金额:
$ 24.66万 - 项目类别:
相似国自然基金
层出镰刀菌氮代谢调控因子AreA 介导伏马菌素 FB1 生物合成的作用机理
- 批准号:2021JJ40433
- 批准年份:2021
- 资助金额:0.0 万元
- 项目类别:省市级项目
寄主诱导梢腐病菌AreA和CYP51基因沉默增强甘蔗抗病性机制解析
- 批准号:32001603
- 批准年份:2020
- 资助金额:24.0 万元
- 项目类别:青年科学基金项目
AREA国际经济模型的移植.改进和应用
- 批准号:18870435
- 批准年份:1988
- 资助金额:2.0 万元
- 项目类别:面上项目
相似海外基金
Onboarding Rural Area Mathematics and Physical Science Scholars
农村地区数学和物理科学学者的入职
- 批准号:
2322614 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Standard Grant
Point-scanning confocal with area detector
点扫描共焦与区域检测器
- 批准号:
534092360 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Major Research Instrumentation
TRACK-UK: Synthesized Census and Small Area Statistics for Transport and Energy
TRACK-UK:交通和能源综合人口普查和小区域统计
- 批准号:
ES/Z50290X/1 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Research Grant
Wide-area low-cost sustainable ocean temperature and velocity structure extraction using distributed fibre optic sensing within legacy seafloor cables
使用传统海底电缆中的分布式光纤传感进行广域低成本可持续海洋温度和速度结构提取
- 批准号:
NE/Y003365/1 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Research Grant
Collaborative Research: Scalable Manufacturing of Large-Area Thin Films of Metal-Organic Frameworks for Separations Applications
合作研究:用于分离应用的大面积金属有机框架薄膜的可扩展制造
- 批准号:
2326714 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Standard Grant
Collaborative Research: Scalable Manufacturing of Large-Area Thin Films of Metal-Organic Frameworks for Separations Applications
合作研究:用于分离应用的大面积金属有机框架薄膜的可扩展制造
- 批准号:
2326713 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Standard Grant
Unlicensed Low-Power Wide Area Networks for Location-based Services
用于基于位置的服务的免许可低功耗广域网
- 批准号:
24K20765 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area
RAPID:协作研究:2024 年 3 月 26 日 DC-马里兰-弗吉尼亚地区 Francis Scott Key 大桥倒塌事故后果的多方面数据收集
- 批准号:
2427233 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Standard Grant
RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area
RAPID:协作研究:2024 年 3 月 26 日 DC-马里兰-弗吉尼亚地区 Francis Scott Key 大桥倒塌事故后果的多方面数据收集
- 批准号:
2427232 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Standard Grant
RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area
RAPID:协作研究:2024 年 3 月 26 日 DC-马里兰-弗吉尼亚地区 Francis Scott Key 大桥倒塌事故后果的多方面数据收集
- 批准号:
2427231 - 财政年份:2024
- 资助金额:
$ 24.66万 - 项目类别:
Standard Grant