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Abstract

Processing of visual information entails the extraction of features from retinal images that mediate visual perception. In the human ventral cortex, retinotopic and higher visual areas (e.g. Lateral Occipital Complex-LOC) have been implicated in the analysis of simple and more complex features respectively. To test how processing of complex natural images progresses across the human ventral cortex, we used images of scenes and added visual noise that matched the signal in spatial-frequency power spectrum. The resulting images were rescaled to ensure constant mean luminance and r.m.s. contrast across all noise levels. We localized individually in each observer the retinotopic regions and the LOC and measured event-related BOLD response in these regions during a scene discrimination task performed at 4 noise levels. Behavioral accuracy increased with increasing signal-to-noise ratio (SNR). We found that log BOLD signal change from fixation baseline vs. log SNR is well-described by a straight line for all visual areas. The regression slope increased monotonically from lower to higher visual areas along the ventral stream. For example, changes by a factor of 8 in SNR produced little or no change to the BOLD response in V1/V2, but resulted in progressively larger increases in V4v, posterior, and anterior sub-regions of the LOC. These findings suggest that the use of visual noise can reveal the progression in complexity of the natural-image features that are processed across the human visual areas.