Perceptual salience affects the contents of working memory during free-recollection of objects from natural scenes

Frontiers in Human Neuroscience
Tiziana Pedale, Valerio Santangelo

Abstract

One of the most important issues in the study of cognition is to understand which are the factors determining internal representation of the external world. Previous literature has started to highlight the impact of low-level sensory features (indexed by saliency-maps) in driving attention selection, hence increasing the probability for objects presented in complex and natural scenes to be successfully encoded into working memory (WM) and then correctly remembered. Here we asked whether the probability of retrieving high-saliency objects modulates the overall contents of WM, by decreasing the probability of retrieving other, lower-saliency objects. We presented pictures of natural scenes for 4 s. After a retention period of 8 s, we asked participants to verbally report as many objects/details as possible of the previous scenes. We then computed how many times the objects located at either the peak of maximal or minimal saliency in the scene (as indexed by a saliency-map; Itti et al., 1998) were recollected by participants. Results showed that maximal-saliency objects were recollected more often and earlier in the stream of successfully reported items than minimal-saliency objects. This indicates that bottom-up sensory salience ...Continue Reading

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Citations

Dec 1, 2015·Frontiers in Human Neuroscience·Elger AbrahamseJean-Philippe van Dijck
Jan 18, 2015·Behavioural Brain Research·Valerio Santangelo
Nov 13, 2018·Frontiers in Systems Neuroscience·Shiva KamkarReza Lashgari
May 10, 2019·Attention, Perception & Psychophysics·Daniel B Dodgson, Jane E Raymond
May 22, 2019·Brain Structure & Function·Tiziana PedaleValerio Santangelo
Jul 19, 2019·Frontiers in Integrative Neuroscience·Nobuhiko GotoAlexandre Schaefer
Oct 8, 2020·Journal of Child Language·Klaus Hofmann, Andreas Baumann
Jun 17, 2021·Psychonomic Bulletin & Review·Susan M Ravizza, Katelyn M Conn

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Software Mentioned

SPSS
Saliency Toolbox

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