Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2018 Sep 18;115(38):E9015-E9024. doi: 10.1073/pnas.1719616115. Epub 2018 Aug 31.

Mid-level visual features underlie the high-level categorical organization of the ventral stream.

Author information

1
Department of Psychology, Harvard University, Cambridge, MA 02138; brialorelle@gmail.com.
2
Department of Psychology, Stanford University, Stanford, CA 94305.
3
Department of Psychology, Harvard University, Cambridge, MA 02138.
4
Phiar Technologies, Inc., Palo Alto, CA 94303.

Abstract

Human object-selective cortex shows a large-scale organization characterized by the high-level properties of both animacy and object size. To what extent are these neural responses explained by primitive perceptual features that distinguish animals from objects and big objects from small objects? To address this question, we used a texture synthesis algorithm to create a class of stimuli-texforms-which preserve some mid-level texture and form information from objects while rendering them unrecognizable. We found that unrecognizable texforms were sufficient to elicit the large-scale organizations of object-selective cortex along the entire ventral pathway. Further, the structure in the neural patterns elicited by texforms was well predicted by curvature features and by intermediate layers of a deep convolutional neural network, supporting the mid-level nature of the representations. These results provide clear evidence that a substantial portion of ventral stream organization can be accounted for by coarse texture and form information without requiring explicit recognition of intact objects.

KEYWORDS:

deep neural networks; fMRI; mid-level features; object recognition; ventral stream organization

PMID:
30171168
PMCID:
PMC6156638
[Available on 2019-03-18]
DOI:
10.1073/pnas.1719616115
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center