Methods in cognitive pupillometry: Design, preprocessing, and statistical analysis
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Abstract
Cognitive pupillometry is the measurement of pupil size to investigate cognitive processes such as attention, mental effort, working memory, and many others. Currently, there is no commonly agreed-upon methodology for conducting cognitive-pupillometry experiments, and approaches vary widely between research groups and even between different experiments from the same group. This lack of consensus makes it difficult to know which factors to consider when conducting a cognitive-pupillometry experiment. Here we provide a comprehensive, hands-on guide to methods in cognitive pupillometry, with a focus on trial-based experiments in which the measure of interest is the task-evoked pupil response to a stimulus. We cover all methodological aspects of cognitive pupillometry: experimental design, preprocessing of pupil-size data, and statistical techniques to deal with multiple comparisons when testing pupil-size data. In addition, we provide code and toolboxes (in Python) for preprocessing and statistical analysis, and we illustrate all aspects of the proposed workflow through an example experiment and example scripts.
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Because no specific time window was preregistered for the pupil expectancy hypothesis, cross-validation was used to extract samples from the whole response time window.
“We did not preregister a specific time window to assess our hypotheses regarding the effect of expectancy on pupil sizes; thus, we use cross-validation to extract samples from the whole response time window as recommended by Mathôt and Vilotijević [39].”
From Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework (2026) · cites this paper as [39]
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Self-citationEmphasis on peripheral vision is accompanied by pupil dilation
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Noradrenaline tracks emotional modulation of attention in human amygdala
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First steps into the pupillometry multiverse of developmental science
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Impact of Stimulation Duration in taVNS—Exploring Multiple Physiological and Cognitive Outcomes
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Self-citationEffort drives saccade selectionPreprint
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Self-citationEmphasis on peripheral vision is accompanied by pupil dilation
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The next frontier: Moving human fear conditioning research online
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Early roots of information-seeking: Infants predict and generalize the value of informationPreprint
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A Primer on Design and Data Analysis for Cognitive Pupillometry
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Effort Drives Saccade SelectionPreprint
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Self-citationPhasic alertness generates urgency and amplifies competition between evidence accumulatorsPreprint
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Population-Level Activity Dissociates Preparatory Overt from Covert Attention
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Pupil Diameter during Counting Tasks as Potential Baseline for Virtual Reality Experiments
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Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learning
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Main Sequence of Human Luminance-evoked Pupil Dynamics
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Eye Movements as Indicators of Deception: A Machine Learning Approach
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Pupil size tracks attentional breadth in the Navon task
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Immediate and sustained effects of verbal labels for newly-learned categories
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Phasic Alertness Impairs Cognitive Control by Amplifying Competition between Evidence Accumulators
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Rhythmic Interaction Influences Synchrony Perception in VR
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- Authors
- Mathôt, S., & Vilotijević, A.
- Affiliations
- University of Groningen (NL)
- Corresponding author
- Mathôt, Sebastiaan
- Venue
- Behavior Research Methods
- Published
- 2022-08-26
- Volume
- 55
- Issue
- 6
- Pages
- 3055-3077
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- PMC
- PMC10556184
- OpenAlex
- W4293794846
- Cited by
- 235
- References
- 107
- Citations by year
- 2026: 65 · 2025: 95 · 2024: 46 · 2023: 22 · 2022: 5 · 2021: 1 · 2013: 1
- FWCI
- 20.78
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Behavior Research Methods (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Vidi.191.045)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Keywords
- pupil size, experimental design, multiple comparisons, statistical analysis, attention, cognitive effort, working memory, Python library
- MeSH terms
- Attention, Cognition, Humans, Memory, Short-Term, Pupil, Research Design
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