Evidence map›Paper›PMID 29992408›Full record

ArticleBehavior research methods2019

Preprocessing pupil size data: Guidelines and code.

Mariska E Kret, Elio E Sjak-Shie

Abstract read
In one paragraph

Article in Behavior research methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 173 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
173citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

173 citing papers in PubMed, 1 synthesis or guideline pooled it.

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113 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Mariska E KretCognitive Psychology Department, Leiden University, Wassenaarseweg 52, 2333 AK, Leiden, The Netherlands. m.e.kret@fsw.leidenuniv.nl.
Elio E Sjak-ShieLeiden Institute of Psychology, Leiden University, Leiden, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pupillometry has been one of the most widely used response systems in psychophysiology. Changes in pupil size can reflect diverse cognitive and emotional states, ranging from arousal, interest and effort to social decisions, but they are also widely used in clinical practice to assess patients' brain functioning. As a result, research involving pupil size measurements has been reported in practically all psychology, psychiatry, and psychophysiological research journals, and now it has found its way into the primatology literature as well as into more practical applications, such as using pupil size as a measure of fatigue or a safety index during driving. The different systems used for recording pupil size are almost as variable as its applications, and all yield, as with many measurement techniques, a substantial amount of noise in addition to the real pupillometry data. Before analyzing pupil size, it is therefore of crucial importance first to detect this noise and deal with it appropriately, even prior to (if need be) resampling and baseline-correcting the data. In this article we first provide a short review of the literature on pupil size measurements, then we highlight the most important sources of noise and show how these can be detected. Finally, we provide step-by-step guidelines that will help those interested in pupil size to preprocess their data correctly. These guidelines are accompanied by an open source MATLAB script (available at https://github.com/ElioS-S/pupil-size ). Given that pupil diameter is easily measured by standard eyetracking technologies and can provide fundamental insights into cognitive and emotional processes, it is hoped that this article will further motivate scholars from different disciplines to study pupil size.

Indexed as

ArousalEmotionsGuidelines as TopicNoisePupilInstructionsManualOpen source codePsychophysiologyPupil size

Identifiers

PMID29992408
PMCPMC6538573

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.