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A Dual Task Procedure Combined with Rapid Serial Visual Presentation to Test Attentional Blink for Nontargets
Published on: December 5, 2014
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Temporal cues derived from statistical patterns can overcome resource limitations in the attentional blink
Troy A W Visser1, Jeneva L Ohan, James T Enns
1School of Psychology (M304), University of Western Australia, 35 Stirling Hwy, Crawley, Western Australia, 6009, Australia, troy.visser@uwa.edu.au.
Attention, Perception & Psychophysics
|March 28, 2015
Summary
Humans can use statistical patterns to predict visual targets and reduce the attentional blink (AB). This study shows that predicting the second target (T2) timing improves accuracy and processing efficiency in the AB task.
Area of Science:
- Cognitive Psychology
- Neuroscience
- Visual Perception
Background:
- Humans are adept at identifying statistical patterns in visual stimuli.
- The attentional blink (AB) impairs accuracy for a second target (T2) at brief intertarget intervals.
- Previous research explored pattern detection but not its application to mitigating the AB.
Purpose of the Study:
- To investigate if statistical patterns in intertarget lags can predict T2 arrival.
- To determine if predicting T2 onset can ameliorate the attentional blink (AB).
- To examine how differential lag distributions influence attentional resource allocation.
Main Methods:
- Comparison of AB performance under aging versus nonaging lag distributions.
- Aging distribution: increased T2 likelihood with time if not yet occurred.
- Nonaging distribution: equal lag frequencies.
- Utilized accuracy measures (Experiments 1-2) and response time (Experiment 3).
Main Results:
- The aging distribution significantly improved T2 accuracy at longer lags compared to the nonaging condition.
- The nonaging distribution demonstrated faster T2 discrimination at shorter lags.
- Participants successfully used statistical patterns to anticipate T2 onset.
Conclusions:
- Statistical learning of intertarget lag distributions aids in predicting target timing.
- Predictive abilities can be leveraged to overcome attentional limitations like the AB.
- This demonstrates flexible deployment of attentional resources based on learned statistical regularities.
