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. 2017 Dec 12;8:2064. doi: 10.1038/s41467-017-01912-7

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — Decoding shape-invariant color and color-invariant shape from color patches. a SVM models were trained to classify hues independent of shape. The population response of a set of randomly-selected units was used as the input to each model. Half of the trials were used for training and the remaining half for cross-validation. Shape-invariant hue could be significantly better decoded by AMC and ALC populations than by CLC (for 50 units, p < 0.01 for both comparisons, 2000 iterations of bootstrapping). Furthermore, ALC showed better overall decoding than AMC (p = 0.013). Dashed line indicates chance level (1/8 = 12.5%). Results are averages across 2000 iterations of random sampling. Errorbars represent s.d. b similar to (a), but only quantifies decoding accuracy for two hue categories: red and yellow. Decoding based on AMC is better than ALC, but not significant (p = 0.185). c similar to (a), but for a combined population of anterior color-patch neurons. d similar to (a), but for hue-invariant shape decoding. CLC is significantly better than ALC and AMC (for 50 units, p < 0.01 between CLC and ALC, p = 0.028 between CLC and AMC). Furthermore, neurons outside color patches showed better performance than color-patch neurons, but only significantly better than ALC and AMC (For 25 units, p < 0.01 between outside and ALC, p = 0.019 between outside and AMC and p = 0.186 between outside and CLC). Dashed line indicates chance level (1/82 = 1.2%)