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Jeremy Freeman, Luke E. Hallum, Michael S. Landy, David J. Heeger, Eero P. Simoncelli; Linking statistical texture models to population coding in the ventral stream. Journal of Vision 2010;10(7):26. doi: 10.1167/10.7.26.
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© ARVO (1962-2015); The Authors (2016-present)
How does the ventral visual pathway encode natural images? Directly characterizing neuronal selectivity has proven difficult: it is hard to find stimuli that drive an individual cell in the extrastriate ventral stream, and even having done so, it is hard to find a low-dimensional parameter space governing its selectivity. An alternative approach is to examine the selectivity of neural populations for images that differ statistically (e.g. in Rust & DiCarlo, 2008). We develop a model of extrastriate populations that compute correlations among the outputs of V1-like simple and complex cells at nearby orientations, frequencies, and positions (Portilla & Simoncelli, 2001). These correlations represent the complex structure of visual textures: images synthesized to match the correlations of an original texture image appear texturally similar. We use such synthetic textures as experimental stimuli. Using fMRI and classification analysis, we show that population responses in extrastriate areas are more variable across different textures than across multiple samples of the same texture, suggesting that neural representations in ventral areas reflect the image statistics that distinguish natural textures. We also use psychophysics to explore how the representation of these image statistics varies over the visual field. In extrastriate areas, receptive field sizes grow with eccentricity. Consistent with recent work by Balas et al. (2009), we model this by computing correlational statistics averaged over regions corresponding to extrastriate receptive fields. This model synthesizes metameric images that are physically different but appear identical because they are matched for local statistics. Together, these results show how physiological and psychophysical measurements can be used to link image statistics to population representations in the ventral stream.
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