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Comment
. 2015 Jan 27;112(4):942-3.
doi: 10.1073/pnas.1423496112. Epub 2015 Jan 13.

Representing "stuff" in visual cortex

Corey M Ziemba  1 , Jeremy Freeman  2
Affiliations
Comment

Representing "stuff" in visual cortex

Corey M Ziemba et al. Proc Natl Acad Sci U S A. .
No abstract available

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
(A) Lateral view of the macaque brain with early ventral stream areas V1, V2, and V4 highlighted. (B) Schematic diagram of the parameters contained in the Portilla Simoncelli texture model. Spectral statistics reflect the output of V1-like filters. Higher-order statistics reflect correlations of these filter outputs across orientations, spatial frequencies, and local positions. Most V1 neurons are only sensitive to spectral statistics, and many V2 neurons are sensitive to both spectral and higher-order statistics; Okazawa et al. show that some V4 neurons are tuned exclusively for higher-order statistics. (C–E) In early ventral stream areas, physically different images can yield similar responses, and different image transformations can reveal particular encoding properties. (C) Rotating an image changes the power spectra but preserves some higher-order statistics. In V4, as reported by Okazawa et al., differently rotated images can yield similar responses. (D) Spatially translating a texture changes the image pixel-by-pixel but preserves the spectral and higher-order statistics. In V2, such images yield similar responses. (E) Randomizing the phase of an image destroys higher-order statistics but preserves the power spectrum. In V1, images with similar spectral statistics yield similar responses, with or without higher-order statistics.
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