Literature DB >> 28416597

Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding.

Carlos R Ponce1, Stephen G Lomber2, Margaret S Livingstone3.   

Abstract

In the macaque monkey brain, posterior inferior temporal (PIT) cortex cells contribute to visual object recognition. They receive concurrent inputs from visual areas V4, V3, and V2. We asked how these different anatomical pathways shape PIT response properties by deactivating them while monitoring PIT activity in two male macaques. We found that cooling of V4 or V2|3 did not lead to consistent changes in population excitatory drive; however, population pattern analyses showed that V4-based pathways were more important than V2|3-based pathways. We did not find any image features that predicted decoding accuracy differences between both interventions. Using the HMAX hierarchical model of visual recognition, we found that different groups of simulated "PIT" units with different input histories (lacking "V2|3" or "V4" input) allowed for comparable levels of object-decoding performance and that removing a large fraction of "PIT" activity resulted in similar drops in performance as in the cooling experiments. We conclude that distinct input pathways to PIT relay similar types of shape information, with V1-dependent V4 cells providing more quantitatively useful information for overall encoding than cells in V2 projecting directly to PIT.SIGNIFICANCE STATEMENT Convolutional neural networks are the best models of the visual system, but most emphasize input transformations across a serial hierarchy akin to the primary "ventral stream" (V1 → V2 → V4 → IT). However, the ventral stream also comprises parallel "bypass" pathways: V1 also connects to V4, and V2 to IT. To explore the advantages of mixing long and short pathways in the macaque brain, we used cortical cooling to silence inputs to posterior IT and compared the findings with an HMAX model with parallel pathways.
Copyright © 2017 the authors 0270-6474/17/375019-16$15.00/0.

Entities:  

Keywords:  V2; V4; convolutional networks; cooling; electrophysiology; inferotemporal cortex

Mesh:

Year:  2017        PMID: 28416597      PMCID: PMC5426187          DOI: 10.1523/JNEUROSCI.2674-16.2017

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  46 in total

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Authors:  H G KUYPERS; M K SZWARCBART; M MISHKIN; H E ROSVOLD
Journal:  Exp Neurol       Date:  1965-02       Impact factor: 5.330

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Authors:  Andres Carrasco; Trecia A Brown; Melanie A Kok; Nicole Chabot; Andrej Kral; Stephen G Lomber
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3.  Performance-optimized hierarchical models predict neural responses in higher visual cortex.

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Journal:  Proc Natl Acad Sci U S A       Date:  2014-05-08       Impact factor: 11.205

4.  Visual effects of lesions of cortical area V2 in macaques.

Authors:  W H Merigan; T A Nealey; J H Maunsell
Journal:  J Neurosci       Date:  1993-07       Impact factor: 6.167

5.  Laminar origin of direct projection from cortex area V1 to V4 in the rhesus monkey.

Authors:  M Yukie; E Iwai
Journal:  Brain Res       Date:  1985-11-04       Impact factor: 3.252

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7.  Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons.

Authors:  Carlo Baldassi; Alireza Alemi-Neissi; Marino Pagan; James J Dicarlo; Riccardo Zecchina; Davide Zoccolan
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8.  Weight consistency specifies regularities of macaque cortical networks.

Authors:  N T Markov; P Misery; A Falchier; C Lamy; J Vezoli; R Quilodran; M A Gariel; P Giroud; M Ercsey-Ravasz; L J Pilaz; C Huissoud; P Barone; C Dehay; Z Toroczkai; D C Van Essen; H Kennedy; K Knoblauch
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9.  A weighted and directed interareal connectivity matrix for macaque cerebral cortex.

Authors:  N T Markov; M M Ercsey-Ravasz; A R Ribeiro Gomes; C Lamy; L Magrou; J Vezoli; P Misery; A Falchier; R Quilodran; M A Gariel; J Sallet; R Gamanut; C Huissoud; S Clavagnier; P Giroud; D Sappey-Marinier; P Barone; C Dehay; Z Toroczkai; K Knoblauch; D C Van Essen; H Kennedy
Journal:  Cereb Cortex       Date:  2012-09-25       Impact factor: 5.357

10.  Color selectivity of neurons in the posterior inferior temporal cortex of the macaque monkey.

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Journal:  Cereb Cortex       Date:  2009-10-30       Impact factor: 5.357

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