Imports plain-text ASC data files from EyeLink eye trackers 
    into (relatively) tidy data frames for analysis and visualization.

Import gaze data from  edf files generated by 
  the SR Research <https://www.sr-research.com/> EyeLink eye tracker. Gaze data,
  both recorded events and samples, is imported per trial. The package allows to extract
  events of interest, such as saccades, blinks, etc. as well as
  recorded variables and custom events (areas of interest, triggers) into separate tables.
  The package requires EDF API library that can be obtained at <https://www.sr-research.com/support/>.

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) <doi:10.1038/s41467-020-17851-9>; Kret & Sjak-Shie (2018) <doi:10.3758/s13428-018-1075-y>; Strauch (2024) <doi:10.1016/j.tins.2024.06.002>]. Yet, despite decades of pupillometry research, many established packages and workflows to date lack design patterns based on Findability, Accessibility, Interoperability, and Reusability (FAIR) principles [see Wilkinson et al. (2016) <doi:10.1038/sdata.2016.18>]. 'eyeris' provides a modular, performant, and extensible preprocessing framework for pupillometry data with BIDS-like organization and interactive output reports [Esteban et al. (2019) <doi:10.1038/s41592-018-0235-4>; Gorgolewski et al. (2016) <doi:10.1038/sdata.2016.44>]. Development was supported, in part, by the Stanford Wu Tsai Human Performance Alliance, Stanford Ric Weiland Graduate Fellowship, Stanford Center for Mind, Brain, Computation and Technology, NIH National Institute on Aging Grants (R01-AG065255, R01-AG079345), NSF GRFP (DGE-2146755), McKnight Brain Research Foundation Clinical Translational Research Scholarship in Cognitive Aging and Age-Related Memory Loss, American Brain Foundation, and the American Academy of Neurology.

Enables the automation of actions across the pipeline, including 
  initial steps of transforming binocular data and gap repair to event-based 
  processing such as fixations, saccades, and entry/duration in Areas of 
  Interest (AOIs). It also offers visualisation of eye movement and AOI 
  entries. These tools take relatively raw (trial, time, x, and y form) data 
  and can be used to return fixations, saccades, and AOI entries and time spent
  in AOIs. As the tools rely on this basic data format, the functions can work 
  with data from any eye tracking device. Implements fixation and saccade 
  detection using methods proposed by Salvucci and Goldberg (2000) 
  <doi:10.1145/355017.355028>.