# Functional-neuroanatomy of high-level visual cortex: a quantitative multimodal approach > **NIH NIH R01** · STANFORD UNIVERSITY · 2024 · $102,650 ## Abstract Project Summary/Abstract Perception of ecologically relevant visual stimuli such as faces and bodies is achieved through two processing streams extending from early visual cortex (EVC) to lateral occipito-temporal cortex (LOTC) and ventral temporal cortex (VTC), respectively. However, if and how the underlying microstructure and white matter connections constrain the functional organization and support neural computations in these visual streams remains poorly understood. Leveraging advancements achieved in the prior funding period, we propose a unique multimodal approach, combining functional magnetic resonance imaging (fMRI), quantitative MRI (qMRI), diffusion MRI (dMRI), anatomical quantification, and innovative computational modeling to elucidate how structural factors constrain the functional organization of LOTC and VTC. The research has three main aims. Aim 1 will test a quantitative model of functional- anatomical correspondence in high-level visual cortex. Using fMRI, analysis of micro- and macro-structure, the research will quantify the correspondence between macroanatomical landmarks, cytoarchitecture, and functional regions in LOTC and VTC. Aim 2 will determine how white matter connections regulate the functional organization of high-level visual cortex. Using dMRI and fMRI this aim will test (i) if different white matter connections from EVC to downstream regions contribute to the segregation of functional regions within and across visual streams, and (ii) if the eccentricity of the origin of these white matter connections impacts the visual field coverage of downstream regions. Aim 3 will develop and test a spatiotemporal population receptive field model of responses in visual cortex. This aim will provide not only an innovative approach using fMRI and computational modeling to predict responses to a large range of stimuli that vary in size, position, timing, and duration, but will also provide a quantitative framework to test the impact of top-down attention on basic visual computations. Overall, the proposed research will significantly advance understanding of high- level vision by filling in longstanding gaps in knowledge. The research will (1) provide a parsimonious model of how the microstructure and connections scaffold the function and computations of both ventral and lateral streams, (2) break new ground in computational models of visual cortex, and (3) generate innovative multimodal in vivo methods to quantify microstructural properties of visual cortex. Together, the research has important implications for clinical conditions that are associated with malfunction of high-level vision including developmental prosopagnosia, autism, and dyslexia. ## Key facts - **NIH application ID:** 10892465 - **Project number:** 3R01EY023915-09S1 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** Kalanit Grill-Spector - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $102,650 - **Award type:** 3 - **Project period:** 2014-06-01 → 2025-01-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10892465 ## Citation > US National Institutes of Health, RePORTER application 10892465, Functional-neuroanatomy of high-level visual cortex: a quantitative multimodal approach (3R01EY023915-09S1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10892465. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*