Cognitive Neurodynamics

, Volume 6, Issue 1, pp 107–113 | Cite as

A novel symbolization scheme for multichannel recordings with emphasis on phase information and its application to differentiate EEG activity from different mental tasks

  • Stavros I. DimitriadisEmail author
  • Nikolaos A. Laskaris
  • Vasso Tsirka
  • Sofia Erimaki
  • Michael Vourkas
  • Sifis Micheloyannis
  • Spiros Fotopoulos
Brief Communication


Symbolic dynamics is a powerful tool for studying complex dynamical systems. So far many techniques of this kind have been proposed as a means to analyze brain dynamics, but most of them are restricted to single-sensor measurements. Analyzing the dynamics in a channel-wise fashion is an invalid approach for multisite encephalographic recordings, since it ignores any pattern of coordinated activity that might emerge from the coherent activation of distinct brain areas. We suggest, here, the use of neural-gas algorithm (Martinez et al. in IEEE Trans Neural Netw 4:558–569, 1993) for encoding brain activity spatiotemporal dynamics in the form of a symbolic timeseries. A codebook of k prototypes, best representing the instantaneous multichannel data, is first designed. Each pattern of activity is then assigned to the most similar code vector. The symbolic timeseries derived in this way is mapped to a network, the topology of which encapsulates the most important phase transitions of the underlying dynamical system. Finally, global efficiency is used to characterize the obtained topology. We demonstrate the approach by applying it to EEG-data recorded from subjects while performing mental calculations. By working in a contrastive-fashion, and focusing in the phase aspects of the signals, we show that the underlying dynamics differ significantly in their symbolic representations.


Symbolic dynamics Multichannel EEG Transitions Math tasks 

Supplementary material

11571_2011_9186_MOESM1_ESM.doc (132 kb)
Supplementary material 1 (DOC 132 kb)


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Stavros I. Dimitriadis
    • 1
    • 2
    Email author
  • Nikolaos A. Laskaris
    • 2
  • Vasso Tsirka
    • 3
  • Sofia Erimaki
    • 3
  • Michael Vourkas
    • 4
  • Sifis Micheloyannis
    • 3
  • Spiros Fotopoulos
    • 1
  1. 1.Electronics Laboratory, Department of PhysicsUniversity of PatrasPatrasGreece
  2. 2.Artificial Intelligence and Information Analysis Laboratory, Department of InformaticsAristotle UniversityThessalonikiGreece
  3. 3.Medical Division (Laboratory L.Widén)University of CreteIraklion, CreteGreece
  4. 4.Technical High School of Crete, EstavromenosIraklion, CreteGreece

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