Functional-neuroanatomy of High-level Visual Cortex: A Quantitative Multimodal Ap

高级视觉皮层的功能神经解剖学：定量多模式应用

• 批准号: 8721703
• 负责人: Kalanit Grill-Spector
• 金额: $ 38.18万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8721703
• 关键词: Accounting; Address; Affect; Agnosia; Algorithms; Anatomy; Architecture; Autistic Disorder; Brain; Cereals; Characteristics; Computer Simulation; Computing Methodologies; Coupling; Data; Diffusion; Dimensions; Disease; Face; Functional Magnetic Resonance Imaging; Goals; Health; Human; Human Characteristics; Image; Individual; Knowledge; Link; Location; Magnetic Resonance Imaging; Measurement; Methods; Mission; Modeling; Neuroanatomy; Perception; Play; Population; Positioning Attribute; Process; Property; Psychophysics; Research; Resolution; Rest; Role; Shapes; Specificity; Stimulus; Stream; Structure; System; Techniques; Temporal Lobe; Testing; Vision; Visual; Visual Cortex; Visual Perception; Visual system structure; Williams Syndrome; base; clinical application; developmental prosopagnosia; extrastriate visual cortex; in vivo; information processing; innovation; neuromechanism; novel; patient population; public health relevance; relating to nervous system; response; white matter

DESCRIPTION (provided by applicant): Humans recognize and categorize the visual input in about a tenth of a second. However, it is still a mystery how the brain achieves this remarkable ability. The cortical visual recognition system consists of a processing stream starting in V1 and ascending into high-level visual areas associated with recognition in ventral temporal cortex (VTC). The goal of the proposed research is to make important theoretical and empirical progress in our understanding of the neural basis of recognition by examining the interplay between neural implementation, representations, and computations in human VTC. Prior research from our lab used high-resolution functional magnetic resonance imaging (HR-fMRI) to advance understanding of the functional organization of VTC by generating an organizational framework detailing its neuroanatomical and topological characteristics. Leveraging these findings, this proposal uses an innovative approach with cutting edge techniques combining HR-fMRI, macro-anatomical, cytoarchitechtonic and myeloarchitectonic measurements, high spatial and angular resolution diffusion imaging (HARDI), advanced tracking algorithms, and computational modeling to address the following three key questions: (1) Is neural microarchitecture an implementational constraint underlying the topological organization of functional representations in VTC? (2) Does structural and functional connectivity regulate functional representations of VTC? (3) How does the neural implementation relate to computations in VTC? Aim 1 will inform if/how the topology of functional representations in VTC is determined by the underlying cytoarchictecture and myeloarchitecture, which may have evolved to optimize particular computations. Aim 2 will investigate the fine-scale functional and structural connectivity of high-level visual cortex determining how information is segregated and integrated within and across adjacent specialized cortical networks. Aim 3 will develop the first generative and quantitative model of VTC computations with the ability to predict responses to stimuli varying in shape, position, and size, while also determining if there is a perceptually-relevant hierarchical processing of information across VTC. This research has important clinical applications for identifying abnormalities in the functional neuroanatomy of VTC within individual brains, and thus, is relevant for patient populations with anatomical or functional VTC deficits, and for individuals with atypical perception or recognition. Overall, the research will break new ground in understanding the neural bases of visual recognition in humans by elucidating the interplay between neural implementation, representations, and computations in human VTC.

描述（由申请人提供）：人类在大约十分之一的时间内识别和分类视觉输入。但是，大脑如何实现这种非凡的能力仍然是一个谜。皮质视觉识别系统由从V1开始的处理流组成，并升至与腹侧颞皮层识别相关的高级视觉区域（VTC）。拟议的研究的目的是通过检查人类VTC中神经实施，表示和计算之间的相互作用，在我们对识别神经基础的理解中做出重要的理论和经验进步。我们实验室的先前研究使用了高分辨率功能磁共振成像（HR-FMRI），通过生成一个详细详细介绍其神经解剖学和拓扑特征的组织框架来提高对VTC功能组织的了解。为了利用这些发现，该提案采用了一种创新的方法，该方法结合了HR-FMRI，宏观动态，细胞机制和骨髓结构的测量，高空间和角度分辨率扩散成像（HARDI），高级跟踪跟踪算法和计算构建的问题（1）IS ic（1）（1）ic（1）（1）（1）（1） VTC中功能表示形式的拓扑组织？ （2）结构和功能连通性是否调节VTC的功能表示？ （3）神经实施与VTC中的计算有何关系？ AIM 1将告知VTC中功能表示的拓扑是否取决于潜在的细胞制度和骨髓结构，这可能已经演变为优化特定的计算。 AIM 2将研究高级视觉皮层的精细尺度功能和结构连接性，以确定如何在相邻的专业皮质网络内和整合信息。 AIM 3将开发VTC计算的第一个生成和定量模型，能够预测形状，位置和大小变化的刺激响应，同时还确定是否存在VTC各个信息的信息层次处理。这项研究具有重要的临床应用，以鉴定单个大脑内VTC功能性神经解剖学异常，因此与患有解剖学或功能性VTC缺陷的患者人群以及具有非典型感知或识别的患者有关。总体而言，这项研究将通过阐明人类VTC中神经实施，表示和计算之间的相互作用来理解人类视觉识别的神经基础的新基础。