The Role of V4 During Natural Vision
Event details
| Date | 16.11.2012 |
| Hour | 11:00 › 12:00 |
| Speaker | Dr. Julien Mairal INRIA Grenoble |
| Location | |
| Category | Conferences - Seminars |
The functional organization of area V4 in the mammalian ventral visual pathway is far from being well understood. V4 is believed to play an important role in the recognition of shapes and objects and in visual attention, but its complexity makes it hard to analyze. Individual cells in V4 have been shown to exhibit a large diversity of preferences to visual stimuli characteristics, including orientation, curvature, motion, color and texture. Such observations were for a large part obtained from electrophysiological and imaging studies, when a subject (monkey or human) is shown a sequence of artificial stimuli during data acquisition. In our study, we intend to go beyond such an approach and analyze a population of V4 neurons in naturalistic conditions. More precisely, we record responses from V4 neurons to grayscale still natural images---that is, discarding color and motion content. We propose a new computational model for V4 that does not rely on any pre-defined image features but only on invariance and sparse coding principles. Our approach is the first to achieve comparable prediction performance for V4 as for V1 cells on responses to natural images. Our model is also interpretable using sparse principal component analysis. In the neuron population observed and based on our computational model, we discover as our main finding two groups of neurons: those selective to texture versus those selective to contours. This supports the thesis that one primary role of V4 is to extract objects from background in the visual field. Moreover, our study also confirms the diversity of V4 neurons. Among those selective to contours, some of them are selective to orientation, others to acute curvature features.
This is a joint work with Yuval Benjamini, Ben Willmore, Michael Oliver, Jack Gallant and Bin Yu. All of this work was performed at UC Berkeley.
This is a joint work with Yuval Benjamini, Ben Willmore, Michael Oliver, Jack Gallant and Bin Yu. All of this work was performed at UC Berkeley.
Practical information
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- Free