Literature DB >> 21569854

Transformation from image-based to perceptual representation of materials along the human ventral visual pathway.

Chihiro Hiramatsu1, Naokazu Goda, Hidehiko Komatsu.   

Abstract

Every object in the world has its own surface quality that is a reflection of the material from which the object is made. We can easily identify and categorize materials (wood, metal, fabric etc.) at a glance, and this ability enables us to decide how to interact appropriately with these objects. Little is known, however, about how materials are represented in the brain, or how that representation is related to material perception or the physical properties of material surface. By combining multivoxel pattern analysis of functional magnetic resonance imaging data with perceptual and image-based physical measures of material properties, we found that the way visual information about materials is coded gradually changes from an image-based representation in early visual areas to a perceptual representation in the ventral higher-order visual areas. We suggest that meaningful information about multimodal aspects of real-world materials reside in the ventral cortex around the fusiform gyrus, where it can be utilized for categorization of materials.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21569854     DOI: 10.1016/j.neuroimage.2011.04.056

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  34 in total

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2.  Image statistics underlying natural texture selectivity of neurons in macaque V4.

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3.  Material surface properties modulate vection strength.

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4.  Accuracy and speed of material categorization in real-world images.

Authors:  Lavanya Sharan; Ruth Rosenholtz; Edward H Adelson
Journal:  J Vis       Date:  2014-08-13       Impact factor: 2.240

5.  Representation of the material properties of objects in the visual cortex of nonhuman primates.

Authors:  Naokazu Goda; Atsumichi Tachibana; Gouki Okazawa; Hidehiko Komatsu
Journal:  J Neurosci       Date:  2014-02-12       Impact factor: 6.167

6.  Manifold decoding for neural representations of face viewpoint and gaze direction using magnetoencephalographic data.

Authors:  Po-Chih Kuo; Yong-Sheng Chen; Li-Fen Chen
Journal:  Hum Brain Mapp       Date:  2018-02-11       Impact factor: 5.038

7.  Feature-coding transitions to conjunction-coding with progression through human visual cortex.

Authors:  Rosemary A Cowell; Krystal R Leger; John T Serences
Journal:  J Neurophysiol       Date:  2017-09-20       Impact factor: 2.714

8.  Visual segmentation of complex naturalistic structures in an infant eye-tracking search task.

Authors:  Karola Schlegelmilch; Annie E Wertz
Journal:  PLoS One       Date:  2022-04-01       Impact factor: 3.240

9.  Correspondence between Monkey Visual Cortices and Layers of a Saliency Map Model Based on a Deep Convolutional Neural Network for Representations of Natural Images.

Authors:  Nobuhiko Wagatsuma; Akinori Hidaka; Hiroshi Tamura
Journal:  eNeuro       Date:  2021-02-09

Review 10.  Long-term memory search across the visual brain.

Authors:  Milan Fedurco
Journal:  Neural Plast       Date:  2012-07-19       Impact factor: 3.599

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