Abstract
Visual object recognition in humans and nonhuman primates is achieved by the ventral visual pathway (ventral occipital-temporal cortex, VOTC), which shows a well-documented object domain structure. An on-going question is what type of information is processed in the higher-order VOTC that underlies such observations, with recent evidence suggesting effects of certain visual features. Combining computational vision models, fMRI experiment using a parametric-modulation approach, and natural image statistics of common objects, we depicted the neural distribution of a comprehensive set of visual features in the VOTC, identifying voxel sensitivities with specific feature sets across geometry/shape, Fourier power, and color. The visual feature combination pattern in the VOTC is significantly explained by their relationships to different types of response-action computation (fight-or-flight, navigation, and manipulation), as derived from behavioral ratings and natural image statistics. These results offer a comprehensive visual feature map in the VOTC and a plausible theoretical explanation as a mapping onto different types of downstream response-action systems.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (31671128, 31925020, 31700999, 31700943, and 31500882), the Changjiang Scholar Professorship Award (T2016031), and Fundamental Research Funds for the Central Universities (2017EYT35). We thank Shiguang Shan for discussions about computational vision models, and Joshua B. Julian for generously sharing codes for the right-angle and curvature computations.
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Fan, S., Wang, X., Wang, X. et al. Topography of Visual Features in the Human Ventral Visual Pathway. Neurosci. Bull. 37, 1454–1468 (2021). https://doi.org/10.1007/s12264-021-00734-4
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DOI: https://doi.org/10.1007/s12264-021-00734-4