000128256 001__ 128256
000128256 037__ $$aIKEEART-2012-003
000128256 040__ $$aAristotle University of Thessaloniki
000128256 041__ $$aeng
000128256 100__ $$aDimitriadis, Stavros I.
000128256 245__ $$aA novel symbolization scheme for multichannel recordings with emphasis on phase information and its application to differentiate EEG activity from different mental tasks
000128256 520__ $$aSymbolic 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.
000128256 653__ $$aSymbolic dynamics Multichannel EEG
000128256 653__ $$aTransitions Math tasks
000128256 700__ $$aΔημητριάδης, Σταύρος Ι.
000128256 700__ $$aLaskaris Nikolaos A.
000128256 700__ $$aTsirka, Vasso
000128256 700__ $$aErimaki, Sofia
000128256 700__ $$aVourkas, Michael
000128256 700__ $$aMicheloyannis, Sifis
000128256 700__ $$aFotopoulos, Spiros
000128256 710__ $$aΑριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης$$bΣχολή Θετικών Επιστημών, Τμήμα Πληροφορικής
000128256 773__ $$dSPRINGER$$gvol.6 no.1  p.107-113$$nPublished Version$$o10.1007/s11571-011-9186-5$$tCognitive Neurodynamics$$vPublished$$x18714080
000128256 909CO $$ooai:invenio.lib.auth.gr:128256$$pIKEEART
000128256 980__ $$aIKEE
000128256 980__ $$aIKEEART
000128256 990__ $$aOriginally submitted by stdimitr on Tue, 10 Jan 2012$$d201201101418$$m01$$t1326197931$$y2012
000128256 991__ $$aApproved and Edited by ekarkani on Tue, 10 Jan 2012$$d201201101433$$m01$$t1326198808$$y2012