Abstract
Attention fluctuates between optimal and suboptimal states. However, whether these fluctuations affect how we learn visual regularities remains untested. Using web-based real-time triggering, we investigated the impact of sustained attentional state on statistical learning using online and offline measures of learning. In three experiments (N = 450), participants performed a continuous performance task (CPT) with shape stimuli. Unbeknownst to participants, we measured response times (RTs) preceding each trial in real time and inserted distinct shape triplets in the trial stream when RTs indicated that a participant was attentive or inattentive. We measured online statistical learning using changes in RTs to regular triplets relative to random triplets encountered in the same attentional states. We measured offline statistical learning with a target detection task in which participants responded to target shapes selected from the regular triplets and with tasks in which participants explicitly re-created the regular triplets or selected regular shapes from foils. Online learning evidence was greater in high vs. low attentional states when combining data from all three experiments, although this was not evident in any experiment alone. On the other hand, we saw no evidence of impacts of attention fluctuations on measures of statistical learning collected offline, after initial exposure in the CPT. These results suggest that attention fluctuations may impact statistical learning while regularities are being extracted online, but that these effects do not persist to subsequent tests of learning about regularities.
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Data and code are available at https://osf.io/46grb/?view_only=53d7f6d3e5374a02a30021444b1ebee0.
Notes
Shape stimuli were presented for 800 ms, and mean RT for frequent-category trials was 379.39 ms (SD = 121.28 ms). Thus, the lack of RT recording during the ITI (800–1,000 ms after stimulus onset) did not likely result in a large number of missed responses. Participants missed (i.e., failed to respond to) 2.96% frequent-category trials on average.
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Acknowledgements
We thank Jiaying Zhao for sharing the task stimuli. We also thank Omid Kardan for his analysis suggestions. This work was supported by National Science Foundation BCS-2043740 (M.D.R.) and resources provided by The University of Chicago Research Computing Center.
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Zhang, Z., Rosenberg, M.D. Assessing the impact of attention fluctuations on statistical learning. Atten Percept Psychophys (2023). https://doi.org/10.3758/s13414-023-02805-2
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DOI: https://doi.org/10.3758/s13414-023-02805-2