Link to software 
Eye tracker: here (96,264 KB)
GUI: here (273 KB)
Our software is based on the open-source GazeParser C and Python libraries 5  that can be controlled via Python. Our system incorporates a number of additions:
- A GUI to quickly start the tracker and setup a recording file
- Modified acquisition settings (pupil threshold, corneal reflection threshold, etc.) on the fly with GUI sliders.
- Extensive calibration features, including a user-guided calibration procedure for minimally-cooperative subjects such as animals or infants.
- Ability to re-use a calibration, facilitating psychophysical studies for cooperative and minimally cooperative subjects (i.e., restarting acquisition after a break or separate session).
- Quadratic transformation of the eye-to-screen mapping for more uniform accuracy across the screen.
- Scene monitor for monitor gaze position on the presented scene.
- Recording of the external stimulus events with the eye timestamps.
- Free recording of eye position in the absence of a stimulus using a click of a button.
 Farivar R & Michaud-Landry D (2016) Construction and Operation of a High-Speed, High-Precision Eye Tracker for Tight Stimulus Synchronization and Real-Time Gaze Monitoring in Human and Animal Subjects. Front. Syst. Neurosci. 10:73. doi: 10.3389/fnsys.2016.00073
 Sogo, H. (2013). GazeParser: an open-source and multiplatform library for low-cost eye tracking and analysis. Behav. Res. Methods 45, 684–695. doi: 10.3758/s13428-012-0286-x
Stimuli used in an fMRI study on the representation of depth-cues in the visual system. These stimuli were created by Hassan Akhavein.
Objects were defined by isolated depth-cues (shading, texture and structure from motion)
Examples of Objects Defined by shading and Textures
Examples of control stimuli
Control Stimuli that preserve the mean depth of the object,
generated from depth-map of the object using steerable