NDLI: An integrated model of fixational eye movements and microsaccades

Content Provider	PubMed Central
Author	Engbert, Ralf Mergenthaler, Konstantin Sinn, Petra Pikovsky, Arkady
Abstract	When we fixate a stationary target, our eyes generate miniature (or fixational) eye movements involuntarily. These fixational eye movements are classified as slow components (physiological drift, tremor) and microsaccades, which represent rapid, small-amplitude movements. Here we propose an integrated mathematical model for the generation of slow fixational eye movements and microsaccades. The model is based on the concept of self-avoiding random walks in a potential, a process driven by a self-generated activation field. The self-avoiding walk generates persistent movements on a short timescale, whereas, on a longer timescale, the potential produces antipersistent motions that keep the eye close to an intended fixation position. We introduce microsaccades as fast movements triggered by critical activation values. As a consequence, both slow movements and microsaccades follow the same law of motion; i.e., movements are driven by the self-generated activation field. Thus, the model contributes a unified explanation of why it has been a long-standing problem to separate slow movements and microsaccades with respect to their motion-generating principles. We conclude that the concept of a self-avoiding random walk captures fundamental properties of fixational eye movements and provides a coherent theoretical framework for two physiologically distinct movement types.
Related Links	http://dx.doi.org/10.1073/pnas.1102730108
Starting Page	765
File Format	PDF
ISSN	10916490
e-ISSN	10916490
Journal	Proceedings of the National Academy of Sciences of the United States of America
Issue Number	39
Volume Number	108
Language	English
Publisher	National Academy of Sciences
Publisher Date	2011-09-27
Access Restriction	Open
Rights Holder	National Academy of Sciences
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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