Eye-tracking data support in MNE-Python

Eye-tracking devices are widely used in neuroscience research. Studies of visual perception and attention in particular are increasingly integrating eye-tracking and EEG/MEG devices, in order to gain a better understanding of these processes and their neural correlates. However, the Python community has yet to coalesce around a well-supported package for analyzing eye-tracking signals. This project proposes to integrate support for reading, visualizing, and analyzing eye-tracking signals in MNE-Python. By incorporating the ability to analyze eye-tracking data into MNE-Python, researchers would be able to analyze both neural and eye movement data within the same software environment, making MNE-Python more versatile and useful for a wider range of research questions. Finally, MNE-Python has a large community of developers and users, making it likely that eye-tracking integration will prove useful for many in the scientific Python community. This project will focus on building a robust I/O routine for eye-tracking data and developing functions for preprocessing, visualization, and analytical routines that are commonly required in eye-tracking research. This includes the ability to interpolate eye-position data during blinks, produce heatmap plots of eye-position across trials, and estimate the deconvolved pupil response.