Literature DB >> 23798444

Trade-off between curvature tuning and position invariance in visual area V4.

Tatyana O Sharpee1, Minjoon Kouh, John H Reynolds.   

Abstract

Humans can rapidly recognize a multitude of objects despite differences in their appearance. The neural mechanisms that endow high-level sensory neurons with both selectivity to complex stimulus features and "tolerance" or invariance to identity-preserving transformations, such as spatial translation, remain poorly understood. Previous studies have demonstrated that both tolerance and selectivity to conjunctions of features are increased at successive stages of the ventral visual stream that mediates visual recognition. Within a given area, such as visual area V4 or the inferotemporal cortex, tolerance has been found to be inversely related to the sparseness of neural responses, which in turn was positively correlated with conjunction selectivity. However, the direct relationship between tolerance and conjunction selectivity has been difficult to establish, with different studies reporting either an inverse or no significant relationship. To resolve this, we measured V4 responses to natural scenes, and using recently developed statistical techniques, we estimated both the relevant stimulus features and the range of translation invariance for each neuron. Focusing the analysis on tuning to curvature, a tractable example of conjunction selectivity, we found that neurons that were tuned to more curved contours had smaller ranges of position invariance and produced sparser responses to natural stimuli. These trade-offs provide empirical support for recent theories of how the visual system estimates 3D shapes from shading and texture flows, as well as the tiling hypothesis of the visual space for different curvature values.

Entities:  

Keywords:  Gabor model; feature selectivity; natural stimuli; object recognition; vision

Mesh:

Year:  2013        PMID: 23798444      PMCID: PMC3710868          DOI: 10.1073/pnas.1217479110

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


  45 in total

1.  Shape representation in area V4: position-specific tuning for boundary conformation.

Authors:  A Pasupathy; C E Connor
Journal:  J Neurophysiol       Date:  2001-11       Impact factor: 2.714

2.  Computation of pattern invariance in brain-like structures.

Authors:  S Ullman; S Soloviev
Journal:  Neural Netw       Date:  1999-10

3.  Genealogy of the "grandmother cell".

Authors:  Charles G Gross
Journal:  Neuroscientist       Date:  2002-10       Impact factor: 7.519

4.  Analyzing neural responses to natural signals: maximally informative dimensions.

Authors:  Tatyana Sharpee; Nicole C Rust; William Bialek
Journal:  Neural Comput       Date:  2004-02       Impact factor: 2.026

5.  Geometrical computations explain projection patterns of long-range horizontal connections in visual cortex.

Authors:  Ohad Ben-Shahar; Steven Zucker
Journal:  Neural Comput       Date:  2004-03       Impact factor: 2.026

6.  Characterizing responses of translation-invariant neurons to natural stimuli: maximally informative invariant dimensions.

Authors:  Michael Eickenberg; Ryan J Rowekamp; Minjoon Kouh; Tatyana O Sharpee
Journal:  Neural Comput       Date:  2012-06-26       Impact factor: 2.026

7.  Estimating linear-nonlinear models using Renyi divergences.

Authors:  Minjoon Kouh; Tatyana O Sharpee
Journal:  Network       Date:  2009       Impact factor: 1.273

Review 8.  Neural representations for object perception: structure, category, and adaptive coding.

Authors:  Zoe Kourtzi; Charles E Connor
Journal:  Annu Rev Neurosci       Date:  2011       Impact factor: 12.449

9.  Receptive fields and functional architecture of monkey striate cortex.

Authors:  D H Hubel; T N Wiesel
Journal:  J Physiol       Date:  1968-03       Impact factor: 5.182

10.  Central V4 receptive fields are scaled by the V1 cortical magnification and correspond to a constant-sized sampling of the V1 surface.

Authors:  Brad C Motter
Journal:  J Neurosci       Date:  2009-05-06       Impact factor: 6.167

View more
  18 in total

1.  Multimap formation in visual cortex.

Authors:  Rishabh Jain; Rachel Millin; Bartlett W Mel
Journal:  J Vis       Date:  2015       Impact factor: 2.240

2.  'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification.

Authors:  Dean A Pospisil; Anitha Pasupathy; Wyeth Bair
Journal:  Elife       Date:  2018-12-20       Impact factor: 8.140

3.  Curvature-processing network in macaque visual cortex.

Authors:  Xiaomin Yue; Irene S Pourladian; Roger B H Tootell; Leslie G Ungerleider
Journal:  Proc Natl Acad Sci U S A       Date:  2014-08-04       Impact factor: 11.205

4.  Coding of shape features in the macaque anterior intraparietal area.

Authors:  Maria C Romero; Pierpaolo Pani; Peter Janssen
Journal:  J Neurosci       Date:  2014-03-12       Impact factor: 6.167

5.  Performance-optimized hierarchical models predict neural responses in higher visual cortex.

Authors:  Daniel L K Yamins; Ha Hong; Charles F Cadieu; Ethan A Solomon; Darren Seibert; James J DiCarlo
Journal:  Proc Natl Acad Sci U S A       Date:  2014-05-08       Impact factor: 11.205

6.  Function determines structure in complex neural networks.

Authors:  Tatyana O Sharpee
Journal:  Proc Natl Acad Sci U S A       Date:  2014-05-29       Impact factor: 11.205

Review 7.  Using goal-driven deep learning models to understand sensory cortex.

Authors:  Daniel L K Yamins; James J DiCarlo
Journal:  Nat Neurosci       Date:  2016-03       Impact factor: 24.884

8.  Emergence of transformation-tolerant representations of visual objects in rat lateral extrastriate cortex.

Authors:  Sina Tafazoli; Houman Safaai; Gioia De Franceschi; Federica Bianca Rosselli; Walter Vanzella; Margherita Riggi; Federica Buffolo; Stefano Panzeri; Davide Zoccolan
Journal:  Elife       Date:  2017-04-11       Impact factor: 8.140

9.  Neural Quadratic Discriminant Analysis: Nonlinear Decoding with V1-Like Computation.

Authors:  Marino Pagan; Eero P Simoncelli; Nicole C Rust
Journal:  Neural Comput       Date:  2016-09-14       Impact factor: 2.026

Review 10.  Integration of objects and space in perception and memory.

Authors:  Charles E Connor; James J Knierim
Journal:  Nat Neurosci       Date:  2017-10-26       Impact factor: 24.884

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.