Abstract
Complex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems, we investigate the Markov order of sequences of microsaccadic eye movements from human observers. We calculate the integrated likelihood of a given sequence for various orders of the Markov process and use this in a Bayesian framework for statistical inference on the Markov order. Our analysis shows that data from most participants are best explained by a first-order Markov process. This is compatible with recent findings of a statistical coupling of subsequent microsaccade orientations. Our method might prove to be useful for a broad class of biological systems.
Highlights
Many biological systems produce discrete sequences of events that can be used to characterize the underlying generating processes, e.g., neural spike trains [1] or saccadic eye movements [2]
In our work we assumed that the sequences of microsaccades directions are realizations of a stationary stochastic process that we described as a Markov process with unknown order
Symbol sequences obtained from experimental observations of complex biological dynamics can be modeled by a stochastic process
Summary
Many biological systems produce discrete sequences of events that can be used to characterize the underlying generating processes, e.g., neural spike trains [1] or saccadic eye movements [2]. Using a coarse-grained description of the data as symbol sequences [3], we can analyze their statistical properties in terms of a Markov process [4]. A critical parameter in such a model is the order of the Markov process which captures the time span of the statistical dependence within the sequence of symbols. Our eyes are never motionless and continually produce small irregular movements. Two components of these miniature or fixational eye movements (FEM) are microsaccades (rapid small-amplitude movements) and physiological drift (a slower, random component of the motion) [5,6,7,8]. For an illustration of characteristic microsaccade properties, see Figure 1a
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
