Motion-corrected eye tracking (MoCET) improves gaze accuracy during visual fMRI experiments

Dataset Description: MoCET Study – Head Motion Parameters and Eye Tracking Data This dataset contains the head motion parameters and eye tracking data used in the Motion-Corrected Eye Tracking (MoCET) study, which investigates the impact of head motion on gaze accuracy in fMRI experiments and proposes a method for drift correction. Contents: Head motion parameters (*.tsv): Six-degree-of-freedom (6 DoF) motion estimates derived from fMRI preprocessing, including translations (X, Y, Z) and rotations (pitch, yaw, roll). ex) sub-003_ses-07R_task-mcHERDING_run-1_desc-confounds_timeseries.tsv Pupil data (*.csv): Raw pupil coordinates recorded at high temporal resolution. ex) sub-003_ses-07R_task-mcHERDING_run-1_recording-eyetracking_physio_log.csv Eye tracking (*.txt): Data file (_dat) logs the time interval between video frames and is used to match video frames to actual time. History file (_his) logs the TTL signal from the MRI scanner and is used to match eye tracking data to fMRI data sub-003_ses-07R_task-mcHERDING_run-1_recording-eyetracking_physio_dat.txt sub-003_ses-07R_task-mcHERDING_run-1_recording-eyetracking_physio_his.txt Usage: This dataset can serve as a benchmark for evaluating eye tracking drift correction methods and is particularly useful for: Investigating head motion-induced gaze errors in fMRI experiments. Validating motion correction techniques for high-precision eye tracking. Developing and testing new algorithms for eye tracking in neuroimaging research. Restrictions: Neuroimaging and gameplay data are not included due to privacy and storage constraints. This dataset is intended for research purposes only.