Seeing requires pooling information over space and time. The nervous system must appropriately integrate and segregate inputs in order to correctly interpret visual scenes. The proposal seeks to build experimental and computational infrastructure to characterize how the human visual system pools information from simple space-time stimuli using multiple imaging modalities, and to relate these measurements to visual perception. A key component of the proposal is to combine measurements from functional MRI with scalp and intracranial electrodes. The different instruments for measuring human brain function have very different sensitivities. Spatial summation measurements and temporal summation measurements will be conducted to derive models of cortical space-time receptive fields. We will test hypotheses about how these receptive fields are organized throughout the visual pathways, characterizing differences between central and peripheral cortical representations and between early and late visual areas. The organization of spatial summation across the visual pathways is better understood than the organization of temporal summation. Spatial summation will therefore be emphasized in model development and validation;temporal summation will be emphasized in later stages. In the mentored phase of the award, one set of studies will be conducted to establish the basic computational infrastructure. Methods will be developed to use measurements in one modality to predict data in another modality. This work will involve modeling spatial summation across the many visual field maps using fMRI, and then using these models to predict the pattern of activity across electrode arrays in response to simple visual stimuli. For a second set of studies, these models will be used as constraints to resolve temporal responses with EEG at the spatial resolution of fMRI. Findings from both sets of studies will be validated with measurements of intracranial electrodes in a clinical subject population. Computational models will be developed to integrate visualization and analysis across the modalities. In the independent phase of the award, temporal summation will be studied with fMRI and the results compared against those from EEG. Measurements of temporal summation will characterize the temporal integration period of different brain areas. Concurrent EEG and psychophysical experiments will be conducted to identify the neural activity patterns associated with perception of various stimulus classes. Together the pattern of results will provide an account of how temporal processing across the visual hierarchy shapes perception. The mentored phase will take place at Stanford University, mostly in the Center for Neurobiological Imaging. The studies will build on the candidate's expertise in functional MRI experiments, computational modeling, and psychophysics. Training in conducting and analyzing EEG experiments and relating the results to MRI data will be a significant part of the training in the mentored phase. The candidate will seek an independent faculty position during the second year of the mentored phase.
The study will characterize how visual inputs are integrated over space and time throughout the cortical visual pathways. These measures will enable a better understanding of the relative contribution of low-level and high-level factors in neurodevelopmental disorders, such as amblyopia. Certain types of amblyopes, for example, have significant temporal deficits - a failure to properly integrate visual information over short intervals. This failure has a profound impact on the ability to see. Obtaining models of how the typically developing visual system integrates information will be of value in understanding and measuring deviations from these responses in neurodevelopmental disorders.
|Hermes, D; Miller, K J; Wandell, B A et al. (2015) Stimulus Dependence of Gamma Oscillations in Human Visual Cortex. Cereb Cortex 25:2951-9|
|Horiguchi, Hiroshi; Wandell, Brian A; Winawer, Jonathan (2014) A Predominantly Visual Subdivision of The Right Temporo-Parietal Junction (vTPJ). Cereb Cortex :|