Current Biology
Volume 31, Issue 1, 11 January 2021, Pages 51-65.e5
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Article
Early Emergence of Solid Shape Coding in Natural and Deep Network Vision

https://doi.org/10.1016/j.cub.2020.09.076Get rights and content
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Highlights

  • Brain coding of solid shape emerges at the beginning, not end, of object processing

  • Early-stage area V4 processes flat and solid shape in parallel in distinct modules

  • Artificial deep visual networks (AlexNet) also encode solid shape in early layers

Summary

Area V4 is the first object-specific processing stage in the ventral visual pathway, just as area MT is the first motion-specific processing stage in the dorsal pathway. For almost 50 years, coding of object shape in V4 has been studied and conceived in terms of flat pattern processing, given its early position in the transformation of 2D visual images. Here, however, in awake monkey recording experiments, we found that roughly half of V4 neurons are more tuned and responsive to solid, 3D shape-in-depth, as conveyed by shading, specularity, reflection, refraction, or disparity cues in images. Using 2-photon functional microscopy, we found that flat- and solid-preferring neurons were segregated into separate modules across the surface of area V4. These findings should impact early shape-processing theories and models, which have focused on 2D pattern processing. In fact, our analyses of early object processing in AlexNet, a standard visual deep network, revealed a similar distribution of sensitivities to flat and solid shape in layer 3. Early processing of solid shape, in parallel with flat shape, could represent a computational advantage discovered by both primate brain evolution and deep-network training.

Keywords

vision
primate
cortex
3D
V4
shape
object
ventral pathway
neural coding
deep network

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