Decoding and Reconstructing Color from Responses in Human Visual Cortex. Brouwer, Heeger. JNeuro 2009

  1. Tried to decode color from FMRI with “conventional pattern classification, a forward model of idealized color tuning, an d ” PCA
    1. The conventional classifier was able to match training data to colors, but the forward model was able to extrapolate to new colors
  2. Color was decoded accurately from:
    1. V1, V2, V3, V4, and V01
    2. But not L01, L02, V3A/B or MT+
  3. In V4 and V01, 1st 2 principcal components “revealed progression through perceptual color space” (closeness defined a special way)
    1. This similarity didn’t manifest itself anywhere else, even though classification may have been accurate, and classification was actually most accurate in V1, where this similarity effect didn’t manifest itself.
    2. “This dissociation implies a transformation from the color representation in V1 to reflect color space in V4 and V01.”
  4. There is color sensitivity throughout visual cortex
  5. Classification of visual information through fMRI has been done previously on object categories, hand gestures, and visual features
  6. <mostly skipping notes on materials and methods>
  7. Stimulus was a slowly drifting series of concentric rings<, actually a little unclear about this, the description of the colors, and motion are not clear to me>
  8. Classification was done through an 8-way (8 colors originally presented) classifier, not some means of regression
  9. “The first two principal components of the simulated cone-opponency responses revealed results similar to those observed in V1.”
  10. “The forward model assumed that each voxel contained a large number of color-selective neurons, each tuned to a different hue.” <There are more details>
  11. The cone-opponency model, however was worse at recreating a space that pushed all the colors apart, their forward model was successful at that, however
  12. Forward model not only allowed for decoding, but also reconstructing stimulus colors from test data
  13. <Skipping to discussion, running out of time>
  14. Mean voxel responses themselves did not reliably distinguish color
  15. Here saturation didnt vary, only hue varied
  16. “Obviously, the lack of progression in the early visual areas (in particular V1) should not be taken as an indication that these areas are colorblind…  An alternative model of color selectivity, based on cone-opponent tuning rather than hue tuning, reproduced many features of the non-circular and self-intersecting color space derived from teh V1 PCA scores”
  17. “…spatially distributed representations of color in V4 supported ‘interpolation’ to decode a stimulus color based on the responses to perceptually similar colors.”
  18. “Nonetheless, our results support the hypothesis that V4 and VO1 play a special role in color vision and the perception of
    unique hues…”

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