The human visual system is organized as a parallel, hierarchical network, and successive stages of visual processing appear to represent increasingly complicated aspects of shape-related and semantic information. However, the way that shape-related and semantic information is represented across much of the visual hierarchy is still poorly understood. The primary goal of this proposal is to understand how information about object shape and semantic category is represented explicitly across mid- and high-level visual areas. To address this important issue we propose to undertake a series of human functional MRI (fMRI) studies, using both synthetic and natural movies. Data will be analyzed by means of a powerful voxel-wise modeling (VM) approach that has been developed in my laboratory over the past several years.
In Aim 1 we propose to measure human brain activity evoked by synthetic naturalistic movies, and to use VM to evaluate and compare several competing theories of shape representation across the entire visual cortex.
In Aim 2 we propose to use VM to evaluate and compare competing theories of semantic representation.
In Aim 3 we propose to use machine learning and and VM to discover new aspects of shape and semantic representation. These experiments will provide fundamental new insights about the representation of visual information across visual cortex.

Public Health Relevance

Disorders of central vision can severely affect quality of life and the design of treatments and devices for improving visual function will depend critically on understanding the organization of visual cortex. We propose to use functional MRI and sophisticated computational data analysis and modeling procedures to evaluate and compare multiple theories of visual function. The results will reveal how visual information is represented across the several dozen distinct functional areas that constitute human visual cortex.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY019684-06
Application #
9040948
Study Section
Mechanisms of Sensory, Perceptual, and Cognitive Processes Study Section (SPC)
Program Officer
Flanders, Martha C
Project Start
2009-07-01
Project End
2019-03-31
Budget Start
2016-04-01
Budget End
2017-03-31
Support Year
6
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
de Heer, Wendy A; Huth, Alexander G; Griffiths, Thomas L et al. (2017) The Hierarchical Cortical Organization of Human Speech Processing. J Neurosci 37:6539-6557
Nishimoto, Shinji; Huth, Alexander G; Bilenko, Natalia Y et al. (2017) Eye movement-invariant representations in the human visual system. J Vis 17:11
Huth, Alexander G; Lee, Tyler; Nishimoto, Shinji et al. (2016) Decoding the Semantic Content of Natural Movies from Human Brain Activity. Front Syst Neurosci 10:81
Huth, Alexander G; de Heer, Wendy A; Griffiths, Thomas L et al. (2016) Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532:453-8
Çukur, Tolga; Huth, Alexander G; Nishimoto, Shinji et al. (2016) Functional Subdomains within Scene-Selective Cortex: Parahippocampal Place Area, Retrosplenial Complex, and Occipital Place Area. J Neurosci 36:10257-10273
Lescroart, Mark D; Stansbury, Dustin E; Gallant, Jack L (2015) Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas. Front Comput Neurosci 9:135
Gao, James S; Huth, Alexander G; Lescroart, Mark D et al. (2015) Pycortex: an interactive surface visualizer for fMRI. Front Neuroinform 9:23
Vu, An T; Gallant, Jack L (2015) Using a novel source-localized phase regressor technique for evaluation of the vascular contribution to semantic category area localization in BOLD fMRI. Front Neurosci 9:411
Naselaris, Thomas; Olman, Cheryl A; Stansbury, Dustin E et al. (2015) A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes. Neuroimage 105:215-28
Çukur, Tolga; Huth, Alexander G; Nishimoto, Shinji et al. (2013) Functional subdomains within human FFA. J Neurosci 33:16748-66

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