Eye tracking in developmental cognitive neuroscience - The good, the bad and the ugly.

Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101541838 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-9307 (Electronic) Linking ISSN: 18789293 NLM ISO Abbreviation: Dev Cogn Neurosci Subsets: MEDLINE

Original Publication: Amsterdam : Elsevier

Child Development/*physiology ; Cognitive Neuroscience/*methods; Adolescent ; Child ; Child, Preschool ; Data Analysis ; Eye Movements ; Female ; Humans ; Infant ; Infant, Newborn ; Male ; Prospective Studies

Eye tracking is a popular research tool in developmental cognitive neuroscience for studying the development of perceptual and cognitive processes. However, eye tracking in the context of development is also challenging. In this paper, we ask how knowledge on eye-tracking data quality can be used to improve eye-tracking recordings and analyses in longitudinal research so that valid conclusions about child development may be drawn. We answer this question by adopting the data-quality perspective and surveying the eye-tracking setup, training protocols, and data analysis of the YOUth study (investigating neurocognitive development of 6000 children). We first show how our eye-tracking setup has been optimized for recording high-quality eye-tracking data. Second, we show that eye-tracking data quality can be operator-dependent even after a thorough training protocol. Finally, we report distributions of eye-tracking data quality measures for four age groups (5 months, 10 months, 3 years, and 9 years), based on 1531 recordings. We end with advice for (prospective) developmental eye-tracking researchers and generalizations to other methodologies.
(Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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Keywords: Data analysis; Data quality; Development; Eye tracking; Longitudinal

Date Created: 20191009 Date Completed: 20200313 Latest Revision: 20240328

20240329

PMC6974897

10.1016/j.dcn.2019.100710

31593909