Abstract

Shape and texture are both important properties of visual objects, but texture is relatively less understood. Here, we characterized neuronal responses to discrete textures in monkey inferotemporal (IT) cortex and asked whether they can explain classic findings in human texture perception. We focused on three classic findings on texture discrimination: 1) it can be easy or hard depending on the constituent elements; 2) it can have asymmetries, and 3) it is reduced for textures with randomly oriented elements. We recorded neuronal activity from monkey inferotemporal (IT) cortex and measured texture perception in humans for a variety of textures. Our main findings are as follows: 1) IT neurons show congruent selectivity for textures across array size; 2) textures that were easy for humans to discriminate also elicited distinct patterns of neuronal activity in monkey IT; 3) texture pairs with asymmetries in humans also exhibited asymmetric variation in firing rate across monkey IT; and 4) neuronal responses to randomly oriented textures were explained by an average of responses to homogeneous textures, which rendered them less discriminable. The reduction in discriminability of monkey IT neurons predicted the reduced discriminability in humans during texture discrimination. Taken together, our results suggest that texture perception in humans is likely based on neuronal representations similar to those in monkey IT.

Highlights

  • TEXTURE IS AN IMPORTANT PROPERTY of objects, but it has received relatively little attention compared with shape

  • We focused on three classic findings on texture discrimination: 1) it can be easy or hard depending on the constituent elements; 2) it can have asymmetries, and 3) it is reduced for textures with randomly oriented elements

  • We recorded single-unit activity from the left inferotemporal cortex of two macaque monkeys while they viewed a variety of discrete textures in a fixation task

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Summary

Introduction

TEXTURE IS AN IMPORTANT PROPERTY of objects, but it has received relatively little attention compared with shape. A second goal of our study was to characterize how IT neurons represent discrete textures This issue remains largely unexplored: previous studies have characterized how IT neurons respond to shapes filled with a variety of textures (Kovacs et al 2003; Köteles et al 2008) but have not elucidated how responses to a texture are related to the local shapes in a texture. This question is difficult to answer using natural textures because they contain local features that cannot be manipulated without disrupting other features or their overall arrangement. Our results show that texture representations in monkey IT neurons predict human texture discrimination

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