Memory and Cognition Research

At Yuval Nir Lab, I used data science tools to study the brain. My thesis project focused on analyzing eye movement data through advanced signal processing, statistics, and machine learning techniques. This work aims to develop a novel no-report paradigm for studying memory and cognition.

Abstract

Human memory is typically studied by direct questioning, and the recollection of events is investigated through verbal reports. Using the MEGA (Memory Episode Gaze Anticipation) paradigm, we show that monitoring anticipatory gaze using eye tracking can quantify memory retrieval without verbal report. Upon repeated viewing of movie clips, eye gaze patterns anticipating salient events can quantify their memory traces seconds before these events appear on the screen. Machine learning-based classification can identify whether a given viewing is associated with memory for the event based on single-trial data of gaze features.

Published Research

This research has been published in Communications Psychology (Nature Portfolio):

Anticipatory eye gaze as a marker of memory

Preprint available on bioRxiv: Seeing the Future: Anticipatory Eye Gaze as a Marker of Memory