Literature DB >> 26765944

Disentangling Representations of Object Shape and Object Category in Human Visual Cortex: The Animate-Inanimate Distinction.

Daria Proklova1, Daniel Kaiser1, Marius V Peelen1.   

Abstract

Objects belonging to different categories evoke reliably different fMRI activity patterns in human occipitotemporal cortex, with the most prominent distinction being that between animate and inanimate objects. An unresolved question is whether these categorical distinctions reflect category-associated visual properties of objects or whether they genuinely reflect object category. Here, we addressed this question by measuring fMRI responses to animate and inanimate objects that were closely matched for shape and low-level visual features. Univariate contrasts revealed animate- and inanimate-preferring regions in ventral and lateral temporal cortex even for individually matched object pairs (e.g., snake-rope). Using representational similarity analysis, we mapped out brain regions in which the pairwise dissimilarity of multivoxel activity patterns (neural dissimilarity) was predicted by the objects' pairwise visual dissimilarity and/or their categorical dissimilarity. Visual dissimilarity was measured as the time it took participants to find a unique target among identical distractors in three visual search experiments, where we separately quantified overall dissimilarity, outline dissimilarity, and texture dissimilarity. All three visual dissimilarity structures predicted neural dissimilarity in regions of visual cortex. Interestingly, these analyses revealed several clusters in which categorical dissimilarity predicted neural dissimilarity after regressing out visual dissimilarity. Together, these results suggest that the animate-inanimate organization of human visual cortex is not fully explained by differences in the characteristic shape or texture properties of animals and inanimate objects. Instead, representations of visual object properties and object category may coexist in more anterior parts of the visual system.

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Year:  2016        PMID: 26765944     DOI: 10.1162/jocn_a_00924

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  32 in total

1.  A data-driven approach to stimulus selection reveals an image-based representation of objects in high-level visual areas.

Authors:  David D Coggan; Afrodite Giannakopoulou; Sanah Ali; Burcu Goz; David M Watson; Tom Hartley; Daniel H Baker; Timothy J Andrews
Journal:  Hum Brain Mapp       Date:  2019-07-23       Impact factor: 5.038

2.  Sensorimotor-independent development of hands and tools selectivity in the visual cortex.

Authors:  Ella Striem-Amit; Gilles Vannuscorps; Alfonso Caramazza
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-17       Impact factor: 11.205

3.  Animacy and real-world size shape object representations in the human medial temporal lobes.

Authors:  Anna Blumenthal; Bobby Stojanoski; Chris B Martin; Rhodri Cusack; Stefan Köhler
Journal:  Hum Brain Mapp       Date:  2018-06-26       Impact factor: 5.038

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

Authors:  Bria Long; Chen-Ping Yu; Talia Konkle
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-31       Impact factor: 11.205

5.  A compositional neural code in high-level visual cortex can explain jumbled word reading.

Authors:  Aakash Agrawal; Kvs Hari; S P Arun
Journal:  Elife       Date:  2020-05-05       Impact factor: 8.140

6.  The Neural Representations of Movement across Semantic Categories.

Authors:  Valentina Borghesani; Marianna Riello; Benno Gesierich; Valentina Brentari; Alessia Monti; Maria Luisa Gorno-Tempini
Journal:  J Cogn Neurosci       Date:  2019-03-18       Impact factor: 3.225

7.  Posterior parietal influences on visual network specialization during development: An fMRI study of functional connectivity in children ages 9 to 12.

Authors:  Jonathan F O'Rawe; Anna S Huang; Daniel N Klein; Hoi-Chung Leung
Journal:  Neuropsychologia       Date:  2019-03-05       Impact factor: 3.139

8.  The Ventral Visual Pathway Represents Animal Appearance over Animacy, Unlike Human Behavior and Deep Neural Networks.

Authors:  Stefania Bracci; J Brendan Ritchie; Ioannis Kalfas; Hans P Op de Beeck
Journal:  J Neurosci       Date:  2019-06-13       Impact factor: 6.167

9.  Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images.

Authors:  Marcie L King; Iris I A Groen; Adam Steel; Dwight J Kravitz; Chris I Baker
Journal:  Neuroimage       Date:  2019-05-01       Impact factor: 6.556

10.  Ultra-high-resolution fMRI of Human Ventral Temporal Cortex Reveals Differential Representation of Categories and Domains.

Authors:  Eshed Margalit; Keith W Jamison; Kevin S Weiner; Luca Vizioli; Ru-Yuan Zhang; Kendrick N Kay; Kalanit Grill-Spector
Journal:  J Neurosci       Date:  2020-02-24       Impact factor: 6.167

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