The primary visual cortex creates a bottom-up saliency map
This proposal links physiology with psychophysics, thereby making testable predictions some of which are subsequently conrmed experimentally and accounted for behavioral data such as how task diculties can be inuenced by image features and their spatial congurations.
A bottom up visual saliency map in the primary visual cortex, theory and its experimental tests
The theoretical proposal that the primary visual cortex (V1) creates a saliency map of the visual space, such that the receptive field location of the most responsive V1 neuron to a scene is most likely selected for attentional processing is presented.
Testing the hypothesis that V 1 creates a bottom-up saliency map
- Psychology, Biology
This chapter is adapted from Zhaoping L. May KA (2007) Psychophysical tests of the hypothesis of a bottom-up saliency map in primary visual cortex, which shows that a unique vertical bar among horizontal bars is said to be salient and pops out perceptually.
Saliency, attention, and visual search: an information theoretic approach.
- PsychologyJournal of vision
It is demonstrated that a variety of visual search behaviors appear as emergent properties of the model and therefore basic principles of coding and information transmission are demonstrated.
Perceptual learning of pop-out and the primary visual cortex
Abstract I propose that perceptual learning of tasks to detect targets among uniform background items involves changing intra-cortical interactions in the primary visual cortex (V1). This is the case…
Learning visual saliency
- Computer Science2011 45th Annual Conference on Information Sciences and Systems
This work studies the feature integration problem and proposes two improved strategies: first, a weighted linear combination of features using the constraint linear regression algorithm, and second, an AdaBoost based algorithm to approach the feature selection, thresholding, weight assignment, and nonlinear integration in a single principled framework.
Neural Mechanisms of Saliency, Attention, and Orienting
- Psychology, Biology
Evidence for mechanisms in the primate brain that integrate bottom-up saliency with internal goals for flexible orienting towards behaviorally relevant stimuli is reviewed and novel issues and insights are raised that challenge current views about the neural basis of saliency, attention, and orienting.
Stimulus Saliency Modulates Pre-Attentive Processing Speed in Human Visual Cortex
- PsychologyPloS one
By linking the Posterior Contralateral Negativity (PCN) component to reaction time (RT) performance, this work tested one specific prediction of such salience summation models: expedited shifts of focal-attention to targets with low, as compared to high, target-distracter similarity.
Superior colliculus neurons encode a visual saliency map during free viewing of natural dynamic video
- Biology, PsychologyNature communications
A strong test of the saliency hypothesis is conducted by comparing the output of a well-established computational saliency model with the activation of neurons in the primate superior colliculus (SC), a midbrain structure associated with attention and gaze, while monkeys watched video of natural scenes.
SHOWING 1-10 OF 48 REFERENCES
Saliency And Figure-Ground Effects
We have proposed that a saliency map is an outcome of pre-attentive computation by the primary visual cortex (V1). This awards higher responses, or saliencies, to boundaries between homogeneous input…
Extraction of perceptually salient contours by striate cortical networks
- BiologyVision Research
Pre-attentive segmentation in the primary visual cortex.
- BiologySpatial vision
It is proposed that contextual influences serve pre-attentive visual segmentation by causing relatively higher neural responses to important or conspicuous image locations, making them more salient for perceptual pop-out.
Shifts in selective visual attention: towards the underlying neural circuitry.
- BiologyHuman neurobiology
This study addresses the question of how simple networks of neuron-like elements can account for a variety of phenomena associated with this shift of selective visual attention and suggests a possible role for the extensive back-projection from the visual cortex to the LGN.
Computational modelling of visual attention
- Psychology, BiologyNature Reviews Neuroscience
Five important trends have emerged from recent work on computational models of focal visual attention that emphasize the bottom-up, image-based control of attentional deployment, providing a framework for a computational and neurobiological understanding of visual attention.
Contextual influences in V1 as a basis for pop out and asymmetry in visual search.
- Biology, PsychologyProceedings of the National Academy of Sciences of the United States of America
A model used to show how simple, bottom-up, neural mechanisms in primary visual cortex can qualitatively explain the preattentive component of complex psychophysical phenomena of visual search for a target among distracters suggests that contextual influences in V1 play a significant role.
Influence of scene-based properties on visual search.
- Psychology, BiologyScience
This work has shown that visual search also has access to another level of representation, one that describes properties in the corresponding three-dimensional scene that are three dimensionality and the direction of lighting, but not viewing direction.
Primary Cortical Dynamics for Visual Grouping
It is proposed that the primary visual cortex (V1) contributes to both kinds of groupings with a single mechanism of cortical interac-tions/dynamics mediated by the horizontal connections, and that the dynamics enhance the saliencies of those features in the contours or near the region boundaries.
Visual segmentation by contextual influences via intra-cortical interactions in the primary visual cortex.
It is proposed that contextual influences are used for pre-attentive visual segmentation, and this model is the first that performs texture or region segmentation in exactly the same neural circuit that solves the dual problem of the enhancement of contours.