Measuring statistical learning by eye-tracking. (15th August 2022)
- Record Type:
- Journal Article
- Title:
- Measuring statistical learning by eye-tracking. (15th August 2022)
- Main Title:
- Measuring statistical learning by eye-tracking
- Authors:
- Ergul, Ayca
Zolnai, Tamás
Dávid, Dominika Réka
Pesthy, Orsolya
Nemeth, Marton
Kiss, Mariann
Nagy, Márton
Nemeth, Dezso - Abstract:
- Abstract: Statistical learning—the skill to pick up probability-based regularities of the environment—plays a crucial role in adapting to the environment and learning perceptual, motor, and language skills in healthy and clinical populations. Here, we developed a new method to measure statistical learning without any manual responses. We used the Alternating Serial Reaction Time (ASRT) task, adapted to eye-tracker, which, besides measuring reaction times (RTs), enabled us to track learning-dependent anticipatory eye movements. We found robust, interference-resistant learning on RT; moreover, learning-dependent anticipatory eye movements were even more sensitive measures of statistical learning on this task. Our method provides a way to apply the widely used ASRT task to operationalize statistical learning in clinical populations where the use of manual tasks is hindered, such as in Parkinson's disease. Furthermore, it also enables future basic research to use a more sensitive version of this task to measure predictive processing.
- Is Part Of:
- Experimental results. Volume 3(2022)
- Journal:
- Experimental results
- Issue:
- Volume 3(2022)
- Issue Display:
- Volume 3, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 3
- Issue:
- 2022
- Issue Sort Value:
- 2022-0003-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-15
- Subjects:
- statistical learning -- eye-tracking -- Alternating Serial Reaction Time task -- procedural learning
Science -- Experiments -- Periodicals
Science -- Methodology -- Periodicals
507.24 - Journal URLs:
- https://www.cambridge.org/core/journals/experimental-results/latest-issue ↗
- DOI:
- 10.1017/exp.2022.8 ↗
- Languages:
- English
- ISSNs:
- 2516-712X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23024.xml