Visual attention: The past 25 years

By Marisa Carrasco. Vision Research, 2011

2,321 citations recorded by the source corpus.

This review focuses on covert attention and how it alters early vision. I explain why attention is considered a selective process, the constructs of covert attention, spatial endogenous and exogenous attention, and feature-based attention. I explain how in the last 25 years research on attention has characterized the effects of covert attention on spatial filters and how attention influences the selection of stimuli of interest. This review includes the effects of spatial attention on discriminability and appearance in tasks mediated by contrast sensitivity and spatial resolution; the effects of feature-based attention on basic visual processes, and a comparison of the effects of spatial and feature-based attention. The emphasis of this review is on psychophysical studies, but relevant electrophysiological and neuroimaging studies and models regarding how and where neuronal responses are modulated are also discussed.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/02422add22433517f4a89fe10053f46a63c9ec99

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In Cognitive Neuroscience

Citations in the corpus

STNet: Selective Tuning of Convolutional Networks for Object Localization (2017, background): “Visual attention has two modes of execution [4, 14]: Overt attention attempts to compensate for the lack of visual acuity through2017 IEEE International Conference on Computer Vision Workshops”
Figure-ground modulation in awake primate thalamus (2015, background): “Psychophysically, this is an exercise in exogenous (“bottom-up”) attentional capture (25), for the monkeys had no cue and no means of predicting the figure location, which was equally frequent across the four sites.”
What do eyes reveal about the mind?: Algorithmic inference of search targets from fixations (2015, background): “, [84,82,58,13,19]) that suggest neurons to be biased in a top-down manner to render the target more salient.”
A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure (2016, background): “A large body of research suggests that allocation of visual attention is controlled by a set of mutually connected areas, including the Frontal Eye PLOS Computational Biology | DOI:10.1371/journal.pcbi.1004770 February 18, 2016 12 / 18 Fields, Lateral Intraparietal cortex, and sub-cortical structure”
Eye-tracking methodology in mathematics education research: A systematic literature review (2020, background): “However, attention can also be shifted without moving the eyes, which is referred to as covert attention (Carrasco, 2011).”
An Eye-Tracking Study of Tourism Photo Stimuli (2016, background): “Understanding and managing attention is a key determinant of business success (Carrasco 2011; Davenport and Beck 2013), especially as consumers face ever-increasing amounts of information that they cannot possibly process in detail.”
Artificial Neural Networks for Neuroscientists: A Primer (2020, background): “Attention Attention has been extensively studied in neuroscience [Desimone and Duncan, 1995, Carrasco, 2011].”
Attention and choice: a review on eye movements in decision making. (2013, background): “Although early theories of attention emphasized the selection and filtering of perceptual input, it has become clear that attention also influences perception to a great extent, for instance by enhancing contrast sensitivity and spatial resolution (for a review see Carrasco, 2011).”
SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks (2021, background): “These two attention mechanisms correspond exactly to the feature-based attention and the spatial-based attention in the human brain (Carrasco, 2011).”
State-of-the-Art in Visual Attention Modeling (2013, methodology): “Reviews of attention models from psychological, neurobiological, and computational perspectives can be found in [9], [77], [10], [12], [202], [204], [224].”
Foundations of Vision (2018, background): “In comparison, endogenous attention tends to be more adaptive and flexible—observers are able to adopt an attentional template that matches properties of the task-relevant target (Carrasco, 2011).”
Saliency-based Sequential Image Attention with Multiset Prediction (2017, background): “Covert attention precedes eye movements, and is intuitively used to monitor the environment and guide eye movements to salient regions [6, 21].”
A Deep Network Solution for Attention and Aesthetics Aware Photo Cropping (2019, methodology): “We refer readers to two recent surveys [27], [28] for more details of early attention models.”
Visual search: a retrospective. (2011, background): “…pre-cues or simultaneously presented cues improve detection, identiﬁcation, and localization performance while observers are maintaining ﬁxation without making eye movements (Busey & Palmer, 2008; Cameron, Tai, Eckstein, & Carrasco, 2004; Eriksen & Yeh, 1985; for a review, see Carrasco, 2011).”