Abstract
Cortical dynamics can be recorded in various ways. Theoretical works suggest that analyzing the dynamics of recorded activities might reveal the workings of the underlying neural system. Here we describe the extraction of an activity pattern language that characterizes the dynamics of high-resolution EEG data recorded. We show that the language can be formulated in terms of probabilistic continuation rules which predict reasonably well the dynamics of activity patterns in the data.
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Andras, P. (2006). The Language of Cortical Dynamics. In: R. Berthold, M., Glen, R.C., Fischer, I. (eds) Computational Life Sciences II. CompLife 2006. Lecture Notes in Computer Science(), vol 4216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875741_24
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DOI: https://doi.org/10.1007/11875741_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45767-1
Online ISBN: 978-3-540-45768-8
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