Literature DB >> 21593417

Simple line drawings suffice for functional MRI decoding of natural scene categories.

Dirk B Walther1, Barry Chai, Eamon Caddigan, Diane M Beck, Li Fei-Fei.   

Abstract

Humans are remarkably efficient at categorizing natural scenes. In fact, scene categories can be decoded from functional MRI (fMRI) data throughout the ventral visual cortex, including the primary visual cortex, the parahippocampal place area (PPA), and the retrosplenial cortex (RSC). Here we ask whether, and where, we can still decode scene category if we reduce the scenes to mere lines. We collected fMRI data while participants viewed photographs and line drawings of beaches, city streets, forests, highways, mountains, and offices. Despite the marked difference in scene statistics, we were able to decode scene category from fMRI data for line drawings just as well as from activity for color photographs, in primary visual cortex through PPA and RSC. Even more remarkably, in PPA and RSC, error patterns for decoding from line drawings were very similar to those from color photographs. These data suggest that, in these regions, the information used to distinguish scene category is similar for line drawings and photographs. To determine the relative contributions of local and global structure to the human ability to categorize scenes, we selectively removed long or short contours from the line drawings. In a category-matching task, participants performed significantly worse when long contours were removed than when short contours were removed. We conclude that global scene structure, which is preserved in line drawings, plays an integral part in representing scene categories.

Entities:  

Mesh:

Year:  2011        PMID: 21593417      PMCID: PMC3111263          DOI: 10.1073/pnas.1015666108

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  24 in total

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2.  Rapid natural scene categorization in the near absence of attention.

Authors:  Fei Fei Li; Rufin VanRullen; Christof Koch; Pietro Perona
Journal:  Proc Natl Acad Sci U S A       Date:  2002-06-20       Impact factor: 11.205

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Journal:  Vision Res       Date:  1994-04       Impact factor: 1.886

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Journal:  Eur J Neurosci       Date:  1993-05-01       Impact factor: 3.386

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Authors:  I Biederman; R J Mezzanotte; J C Rabinowitz
Journal:  Cogn Psychol       Date:  1982-04       Impact factor: 3.468

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Journal:  J Exp Psychol Hum Learn       Date:  1980-03

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10.  Cortical analysis of visual context.

Authors:  Moshe Bar; Elissa Aminoff
Journal:  Neuron       Date:  2003-04-24       Impact factor: 17.173

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  58 in total

1.  Deconstructing visual scenes in cortex: gradients of object and spatial layout information.

Authors:  Assaf Harel; Dwight J Kravitz; Chris I Baker
Journal:  Cereb Cortex       Date:  2012-04-03       Impact factor: 5.357

2.  Is that a bathtub in your kitchen?

Authors:  Marius V Peelen; Sabine Kastner
Journal:  Nat Neurosci       Date:  2011-09-27       Impact factor: 24.884

3.  Data-driven functional clustering reveals dominance of face, place, and body selectivity in the ventral visual pathway.

Authors:  Edward Vul; Danial Lashkari; Po-Jang Hsieh; Polina Golland; Nancy Kanwisher
Journal:  J Neurophysiol       Date:  2012-06-27       Impact factor: 2.714

4.  Modality-Independent Coding of Scene Categories in Prefrontal Cortex.

Authors:  Yaelan Jung; Bart Larsen; Dirk B Walther
Journal:  J Neurosci       Date:  2018-06-01       Impact factor: 6.167

Review 5.  Contributions of low- and high-level properties to neural processing of visual scenes in the human brain.

Authors:  Iris I A Groen; Edward H Silson; Chris I Baker
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-01-02       Impact factor: 6.237

6.  Relating Visual Production and Recognition of Objects in Human Visual Cortex.

Authors:  Judith E Fan; Jeffrey D Wammes; Jordan B Gunn; Daniel L K Yamins; Kenneth A Norman; Nicholas B Turk-Browne
Journal:  J Neurosci       Date:  2019-12-23       Impact factor: 6.167

Review 7.  Low-level properties of natural images predict topographic patterns of neural response in the ventral visual pathway.

Authors:  Timothy J Andrews; David M Watson; Grace E Rice; Tom Hartley
Journal:  J Vis       Date:  2015       Impact factor: 2.240

8.  A Double Dissociation in Sensitivity to Verb and Noun Semantics Across Cortical Networks.

Authors:  Giulia V Elli; Connor Lane; Marina Bedny
Journal:  Cereb Cortex       Date:  2019-12-17       Impact factor: 5.357

9.  Coding of navigational affordances in the human visual system.

Authors:  Michael F Bonner; Russell A Epstein
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-17       Impact factor: 11.205

10.  Conjoint representation of texture ensemble and location in the parahippocampal place area.

Authors:  Jeongho Park; Soojin Park
Journal:  J Neurophysiol       Date:  2017-01-25       Impact factor: 2.714

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