There is no evidence that meaning maps capture semantic information relevant to gaze guidance: Reply to Henderson, Hayes, Peacock, and Rehrig (2021)
Marek A Pedziwiatr,
Thomas SA Wallis,
The concerns raised by Henderson, Hayes, Peacock, and Rehrig (2021) are based on misconceptions of our work. We show that Meaning Maps (MMs) do not predict gaze guidance better than a state-of-the-art saliency model that is based on semantically-neutral, high-level features. We argue that there is therefore no evidence to date that MMs index anything beyond these features. Furthermore, we show that although alterations in meaning cause changes in gaze guidance, MMs fail to capture these alterations. We agree that semantic information is important in the guidance of eye-movements, but the contribution of MMs for understanding its role remains elusive.
My research interests include eye movements, saliency prediction, benchmarking, representation learning and statistics.
Professor for Computational Neuroscience and Machine Learning & Director of the Tübingen AI Center
Matthias Bethge is Professor for Computational Neuroscience and Machine Learning at the University of Tübingen and director of the Tübingen AI Center, a joint center between Tübingen University and MPI for Intelligent Systems that is part of the German AI strategy.