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Widely applicable MATLAB routines for automated analysis of saccadic reaction times

Saccadic reaction time (SRT) is a widely used dependent variable in eye-tracking studies of human cognition and its disorders. SRTs are also frequently measured in studies with special populations, such as infants and young children, who are limited in their ability to follow verbal instructions and...

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Autores principales: Leppänen, Jukka M., Forssman, Linda, Kaatiala, Jussi, Yrttiaho, Santeri, Wass, Sam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427653/
https://www.ncbi.nlm.nih.gov/pubmed/24788324
http://dx.doi.org/10.3758/s13428-014-0473-z
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author Leppänen, Jukka M.
Forssman, Linda
Kaatiala, Jussi
Yrttiaho, Santeri
Wass, Sam
author_facet Leppänen, Jukka M.
Forssman, Linda
Kaatiala, Jussi
Yrttiaho, Santeri
Wass, Sam
author_sort Leppänen, Jukka M.
collection PubMed
description Saccadic reaction time (SRT) is a widely used dependent variable in eye-tracking studies of human cognition and its disorders. SRTs are also frequently measured in studies with special populations, such as infants and young children, who are limited in their ability to follow verbal instructions and remain in a stable position over time. In this article, we describe a library of MATLAB routines (Mathworks, Natick, MA) that are designed to (1) enable completely automated implementation of SRT analysis for multiple data sets and (2) cope with the unique challenges of analyzing SRTs from eye-tracking data collected from poorly cooperating participants. The library includes preprocessing and SRT analysis routines. The preprocessing routines (i.e., moving median filter and interpolation) are designed to remove technical artifacts and missing samples from raw eye-tracking data. The SRTs are detected by a simple algorithm that identifies the last point of gaze in the area of interest, but, critically, the extracted SRTs are further subjected to a number of postanalysis verification checks to exclude values contaminated by artifacts. Example analyses of data from 5- to 11-month-old infants demonstrated that SRTs extracted with the proposed routines were in high agreement with SRTs obtained manually from video records, robust against potential sources of artifact, and exhibited moderate to high test–retest stability. We propose that the present library has wide utility in standardizing and automating SRT-based cognitive testing in various populations. The MATLAB routines are open source and can be downloaded from http://www.uta.fi/med/icl/methods.html. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.3758/s13428-014-0473-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-44276532015-05-14 Widely applicable MATLAB routines for automated analysis of saccadic reaction times Leppänen, Jukka M. Forssman, Linda Kaatiala, Jussi Yrttiaho, Santeri Wass, Sam Behav Res Methods Article Saccadic reaction time (SRT) is a widely used dependent variable in eye-tracking studies of human cognition and its disorders. SRTs are also frequently measured in studies with special populations, such as infants and young children, who are limited in their ability to follow verbal instructions and remain in a stable position over time. In this article, we describe a library of MATLAB routines (Mathworks, Natick, MA) that are designed to (1) enable completely automated implementation of SRT analysis for multiple data sets and (2) cope with the unique challenges of analyzing SRTs from eye-tracking data collected from poorly cooperating participants. The library includes preprocessing and SRT analysis routines. The preprocessing routines (i.e., moving median filter and interpolation) are designed to remove technical artifacts and missing samples from raw eye-tracking data. The SRTs are detected by a simple algorithm that identifies the last point of gaze in the area of interest, but, critically, the extracted SRTs are further subjected to a number of postanalysis verification checks to exclude values contaminated by artifacts. Example analyses of data from 5- to 11-month-old infants demonstrated that SRTs extracted with the proposed routines were in high agreement with SRTs obtained manually from video records, robust against potential sources of artifact, and exhibited moderate to high test–retest stability. We propose that the present library has wide utility in standardizing and automating SRT-based cognitive testing in various populations. The MATLAB routines are open source and can be downloaded from http://www.uta.fi/med/icl/methods.html. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.3758/s13428-014-0473-z) contains supplementary material, which is available to authorized users. Springer US 2014-05-02 2015 /pmc/articles/PMC4427653/ /pubmed/24788324 http://dx.doi.org/10.3758/s13428-014-0473-z Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Leppänen, Jukka M.
Forssman, Linda
Kaatiala, Jussi
Yrttiaho, Santeri
Wass, Sam
Widely applicable MATLAB routines for automated analysis of saccadic reaction times
title Widely applicable MATLAB routines for automated analysis of saccadic reaction times
title_full Widely applicable MATLAB routines for automated analysis of saccadic reaction times
title_fullStr Widely applicable MATLAB routines for automated analysis of saccadic reaction times
title_full_unstemmed Widely applicable MATLAB routines for automated analysis of saccadic reaction times
title_short Widely applicable MATLAB routines for automated analysis of saccadic reaction times
title_sort widely applicable matlab routines for automated analysis of saccadic reaction times
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427653/
https://www.ncbi.nlm.nih.gov/pubmed/24788324
http://dx.doi.org/10.3758/s13428-014-0473-z
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