Abstract
A central hypothesis concerning sensory processing is that the neuronal circuits are specifically adapted to represent natural stimuli efficiently. Here we show a novel effect in cortical coding of natural images. Using spike-triggered average or spike-triggered covariance analyses, we first identified the visual features selectively represented by each cortical neuron from its responses to natural images. We then measured the neuronal sensitivity to these features when they were present in either natural images or random stimuli. We found that in the responses of complex cells, but not of simple cells, the sensitivity was markedly higher for natural images than for random stimuli. Such elevated sensitivity leads to increased detectability of the visual features and thus an improved cortical representation of natural scenes. Interestingly, this effect is due not to the spatial power spectra of natural images, but to their phase regularities. These results point to a distinct visual-coding strategy that is mediated by contextual modulation of cortical responses tuned to the spatial-phase structure of natural scenes.
Highlights
An essential goal in studying the visual system is to understand how it processes natural scenes, which exhibit distinct statistical properties [1,2,3,4,5,6,7]
In this study, we use the term ‘‘preferred feature’’ solely to facilitate the discussion of our findings on cortical feature sensitivity; we do not imply that these features are necessarily optimal for driving the cortical neuron, as the neuronal responses are known to be modulated by various contextual stimuli, including those in the nonclassical receptive field (RF) [22]
The main finding of this study is a new response property of complex cells pertaining to the coding of natural stimuli
Summary
An essential goal in studying the visual system is to understand how it processes natural scenes, which exhibit distinct statistical properties [1,2,3,4,5,6,7]. In the primary visual cortex (V1), response properties of both simple [14,15,16] and complex [17,18] cells can be ‘‘derived’’ from the statistics of natural scenes and the principle of efficient coding. These studies underscore the importance of understanding neuronal response properties with respect to natural-scene statistics. In this study, we use the term ‘‘preferred feature’’ solely to facilitate the discussion of our findings on cortical feature sensitivity; we do not imply that these features are necessarily optimal for driving the cortical neuron, as the neuronal responses are known to be modulated by various contextual stimuli, including those in the nonclassical RF [22]
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