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Updated: May 19, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
Published on: December 15, 2023
Distinct attention networks for feature enhancement and suppression in vision
David A Bridwell1, Ramesh Srinivasan
1Department of Cognitive Sciences, University of California, Irvine, CA, USA. dbridwell@mrn.org
Abstract:
Attention biases sensory processing toward neurons containing information about behaviorally relevant events. These attentional biases apparently reflect the combined influence of feature enhancement and suppression. We examined the separate influence of enhancement and suppression in visual processing by determining whether responses to an unattended flicker were modulated when the flicker features matched target features at the attended location, competed with those features, or were neutral. We found that suppression primarily modulated parietal networks with a preferred frequency in the lower alpha band (f2=8 Hz), and enhancement primarily influenced parietal networks with a preferred frequency in the upper alpha band (f2=12 Hz). These responses were coupled with perception, with large responses to the unattended flicker leading to subsequently detected targets when the target features matched the flicker features (i.e., during enhancement). Our results suggest that enhancement and suppression are two distinct processes that work together to shape visual perception.
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