Stimulus-driven attentional capture by a static discontinuity between perceptual groups.

J Exp Psychol Hum Percept Perform

Department of Psychology, University of Albany, State University of New York, USA.

Published: April 2010

After C. L. Folk, R. W. Remington, and J. C. Johnston (1992) proposed their contingent-orienting hypothesis, there has been an ongoing debate over whether purely stimulus-driven attentional capture can occur for visual events that are salient by virtue of a distinctive static property (as opposed to a dynamic property such as abrupt onset). The present study identified 3 methodological criteria for establishing that attentional capture is stimulus driven and not contingent on top-down attentional control settings. In 5 experiments, attentional capture occurred for a static discontinuity at the boundary between one group of homogeneous items (red Xs) abutted next to a group of homogeneous items that were featurally different (green Xs) within a single row. Experiment 1 intentionally violated one of the criteria for demonstrating stimulus-driven capture so as to establish that contingent attentional capture can occur for this novel type of static cue. In the remaining 4 experiments, even with all 3 criteria for stimulus-driven capture partially or completely satisfied, the static discontinuity captured attention. These attentional capture effects are the first to be obtained when all 3 criteria for establishing that they are purely stimulus driven have been satisfied.

Download full-text PDF

Source
http://dx.doi.org/10.1037/a0015871DOI Listing

Publication Analysis

Top Keywords

attentional capture
24
static discontinuity
12
stimulus-driven attentional
8
capture
8
capture occur
8
criteria establishing
8
stimulus driven
8
group homogeneous
8
homogeneous items
8
stimulus-driven capture
8

Similar Publications

The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition and classification. A generative adversarial network named TRPC-GAN with texture recovery and physical constraints is proposed to mitigate this impact. This network not only effectively removes haze but also better preserves the texture information of the original remote sensing image, thereby enhancing the visual quality of the dehazed image.

View Article and Find Full Text PDF

EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer.

Sci Rep

December 2024

School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, 434100, Hubei, China.

Emotions play a crucial role in human thoughts, cognitive processes, and decision-making. EEG has become a widely utilized tool in emotion recognition due to its high temporal resolution, real-time monitoring capabilities, portability, and cost-effectiveness. In this paper, we propose a novel end-to-end emotion recognition method from EEG signals, called MSDCGTNet, which is based on the Multi-Scale Dynamic 1D CNN and the Gated Transformer.

View Article and Find Full Text PDF

Background: There is an under-reporting of anaesthesia-related safety events. Incident-capturing systems (ICSs) are essential for patient safety monitoring, identifying risks and ongoing opportunities for improvement. After a literature review and assessment of our current ICSs, we concluded that our institution lacked a reliable anaesthesia-specific ICS system, leading to under-reporting of anaesthesia-related safety events.

View Article and Find Full Text PDF

Social media generates vast amounts of spatio-temporal sequential data. However, current methods often ignore the complex spatio-temporal correlations within these data. This oversight makes it difficult to fully capture the dynamic features of the data.

View Article and Find Full Text PDF

This paper presents a deep learning model based on an active learning strategy. The model achieves accurate identification of vegetation types in the study area by utilizing multispectral data obtained from preprocessing of unmanned aerial vehicle (UAV) remote sensing equipment. This approach offers advantages such as high data accuracy, mobility, and easy data collection.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!