Foreground-background segmentation revealed during natural image viewing

Paolo Papale, Andrea Leo, Luca Cecchetti, Giacomo Handjaras, Kendrick N. Kay, Pietro Pietrini, Emiliano Ricciardi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

One of the major challenges in visual neuroscience is represented by foreground-background segmentation. Data from nonhuman primates show that segmentation leads to two distinct, but associated processes: the enhancement of neural activity during figure processing (i.e., foreground enhancement) and the suppression of background-related activity (i.e., background suppression). To study foreground-background segmentation in ecological conditions, we introduce a novel method based on parametric modulation of low-level image properties followed by application of simple computational image-processing models. By correlating the outcome of this procedure with human fMRI activity, measured during passive viewing of 334 natural images, we produced easily interpretable “correlation images” from visual populations. Results show evidence of foreground enhancement in all tested regions, from V1 to lateral occipital complex (LOC), while background suppression occurs in V4 and LOC only. Correlation images derived from V4 and LOC revealed a preserved spatial resolution of foreground textures, indicating a richer representation of the salient part of natural images, rather than a simplistic model of object shape. Our results indicate that scene segmentation occurs during natural viewing, even when individuals are not required to perform any particular task.

Original languageEnglish (US)
Article numbere0075-18.2018
JournaleNeuro
Volume5
Issue number3
DOIs
StatePublished - May 1 2018

Bibliographical note

Funding Information:
Acknowledgements: This work was supported by Italian Ministry for Education, University and Research Grants PRIN 2015WXAXJF and PRIN 2015AR52F9.

Publisher Copyright:
© 2018 Papale et al.

Keywords

  • Figure-ground
  • Human
  • Natural scenes
  • Visual cortex
  • Visual perception
  • fMRI

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