eyeris-package: eyeris: Flexible, Extensible, & Reproducible Pupillometry...
In eyeris: Flexible, Extensible, & Reproducible Pupillometry Preprocessing
eyeris-package R Documentation
eyeris: Flexible, Extensible, & Reproducible Pupillometry Preprocessing
Description
Pupillometry offers a non-invasive window into the mind and has been used extensively as a psychophysiological readout of arousal signals linked with cognitive processes like attention, stress, and emotional states [Clewett et al. (2020) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41467-020-17851-9")}; Kret & Sjak-Shie (2018) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/s13428-018-1075-y")}; Strauch (2024) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.tins.2024.06.002")}]. Yet, despite decades of pupillometry research, many established packages and workflows to date unfortunately lack design patterns based on Findability, Accessibility, Interoperability, and Reusability (FAIR) principles [see Wilkinson et al. (2016) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2016.18")}]. 'eyeris', on the other hand, follows a design philosophy that provides users with an intuitive, modular, performant, and extensible pupillometry data preprocessing framework out-of-the-box. 'eyeris' introduces a Brain Imaging Data Structure (BIDS)-like organization for derivative (i.e., preprocessed) pupillometry data as well as an intuitive workflow for inspecting preprocessed pupil epochs using interactive output report files [Esteban et al. (2019) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41592-018-0235-4")}; Gorgolewski et al. (2016) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2016.44")}].
Author(s)
Maintainer: Shawn Schwartz stschwartz@stanford.edu (ORCID) [copyright holder]
Other contributors:
Stanford Wu Tsai Human Performance Alliance [funder]
Stanford Ric Weiland Graduate Fellowship [funder]
Stanford Center for Mind, Brain, Computation and Technology [funder]
NIH National Institute on Aging R01-AG065255 [funder]
NIH National Institute on Aging R01-AG079345 [funder]
National Science Foundation Graduate Research Fellowship DGE-2146755 [funder]
McKnight Brain Research Foundation Clinical Translational Research Scholarship in Cognitive Aging and Age-Related Memory Loss [funder]
American Brain Foundation [funder]
American Academy of Neurology [funder]
Mingjian He (ORCID) [contributor]
Haopei Yang (ORCID) [contributor]
Alice Xue (ORCID) [contributor]
Gustavo Santiago-Reyes (ORCID) [contributor]
See Also
Useful links:
eyeris documentation built on June 13, 2025, 5:09 p.m.
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| eyeris-package | R Documentation |
eyeris: Flexible, Extensible, & Reproducible Pupillometry Preprocessing
Description
Pupillometry offers a non-invasive window into the mind and has been used extensively as a psychophysiological readout of arousal signals linked with cognitive processes like attention, stress, and emotional states [Clewett et al. (2020) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41467-020-17851-9")}; Kret & Sjak-Shie (2018) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/s13428-018-1075-y")}; Strauch (2024) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.tins.2024.06.002")}]. Yet, despite decades of pupillometry research, many established packages and workflows to date unfortunately lack design patterns based on Findability, Accessibility, Interoperability, and Reusability (FAIR) principles [see Wilkinson et al. (2016) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2016.18")}]. 'eyeris', on the other hand, follows a design philosophy that provides users with an intuitive, modular, performant, and extensible pupillometry data preprocessing framework out-of-the-box. 'eyeris' introduces a Brain Imaging Data Structure (BIDS)-like organization for derivative (i.e., preprocessed) pupillometry data as well as an intuitive workflow for inspecting preprocessed pupil epochs using interactive output report files [Esteban et al. (2019) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41592-018-0235-4")}; Gorgolewski et al. (2016) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2016.44")}].
Author(s)
Maintainer: Shawn Schwartz stschwartz@stanford.edu (ORCID) [copyright holder]
Other contributors:
Stanford Wu Tsai Human Performance Alliance [funder]
Stanford Ric Weiland Graduate Fellowship [funder]
Stanford Center for Mind, Brain, Computation and Technology [funder]
NIH National Institute on Aging R01-AG065255 [funder]
NIH National Institute on Aging R01-AG079345 [funder]
National Science Foundation Graduate Research Fellowship DGE-2146755 [funder]
McKnight Brain Research Foundation Clinical Translational Research Scholarship in Cognitive Aging and Age-Related Memory Loss [funder]
American Brain Foundation [funder]
American Academy of Neurology [funder]
Mingjian He (ORCID) [contributor]
Haopei Yang (ORCID) [contributor]
Alice Xue (ORCID) [contributor]
Gustavo Santiago-Reyes (ORCID) [contributor]
See Also
Useful links:
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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