Evaluating fMRI-Based Estimation of Eye Gaze During Naturalistic Viewing.

ABSTRACT: The collection of eye gaze information during functional magnetic resonance imaging (fMRI) is important for monitoring variations in attention and task compliance, particularly for naturalistic viewing paradigms (e.g., movies). However, the complexity and setup requirements of current in-scanner eye tracking solutions can preclude many researchers from accessing such information. Predictive eye estimation regression (PEER) is a previously developed support vector regression-based method for retrospectively estimating eye gaze from the fMRI signal in the eye's orbit using a 1.5-min calibration scan. Here, we provide confirmatory validation of the PEER method's ability to infer eye gaze on a TR-by-TR basis during movie viewing, using simultaneously acquired eye tracking data in five individu

SUBMITTER: Son J 

PROVIDER: S-EPMC7132907 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature