Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly
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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-12-01
|
| Series: | Developmental Cognitive Neuroscience |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S187892931930297X |
| _version_ | 1819237789747642368 |
|---|---|
| author | Roy S. Hessels Ignace T.C. Hooge |
| author_facet | Roy S. Hessels Ignace T.C. Hooge |
| author_sort | Roy S. Hessels |
| collection | DOAJ |
| description | 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. Keywords: Eye tracking, Data quality, Development, Data analysis, Longitudinal |
| first_indexed | 2024-12-23T13:25:55Z |
| format | Article |
| id | doaj.art-6fbcce8a3c8a4c18be450279852dfec6 |
| institution | Directory Open Access Journal |
| issn | 1878-9293 |
| language | English |
| last_indexed | 2024-12-23T13:25:55Z |
| publishDate | 2019-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Developmental Cognitive Neuroscience |
| spelling | doaj.art-6fbcce8a3c8a4c18be450279852dfec62022-12-21T17:45:18ZengElsevierDevelopmental Cognitive Neuroscience1878-92932019-12-0140Eye tracking in developmental cognitive neuroscience – The good, the bad and the uglyRoy S. Hessels0Ignace T.C. Hooge1Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands; Developmental Psychology, Utrecht University, Utrecht, The Netherlands; Corresponding author at: Heidelberglaan 1, 3584CS Utrecht, The Netherlands.Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The NetherlandsEye 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. Keywords: Eye tracking, Data quality, Development, Data analysis, Longitudinalhttp://www.sciencedirect.com/science/article/pii/S187892931930297X |
| spellingShingle | Roy S. Hessels Ignace T.C. Hooge Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly Developmental Cognitive Neuroscience |
| title | Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly |
| title_full | Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly |
| title_fullStr | Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly |
| title_full_unstemmed | Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly |
| title_short | Eye tracking in developmental cognitive neuroscience – The good, the bad and the ugly |
| title_sort | eye tracking in developmental cognitive neuroscience the good the bad and the ugly |
| url | http://www.sciencedirect.com/science/article/pii/S187892931930297X |
| work_keys_str_mv | AT royshessels eyetrackingindevelopmentalcognitiveneurosciencethegoodthebadandtheugly AT ignacetchooge eyetrackingindevelopmentalcognitiveneurosciencethegoodthebadandtheugly |