Experimental comparison of connectivity measures with simulated EEG signals.
Directional connectivity measures exist with different theoretical backgrounds, i.e., information theoretic, parametric-modeling based or phase related. In this paper, we perform the first comparison in this extend of a set of conventional and directed connectivity measures [cross-correlation, coher...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 50; no. 7; pp. 683 - 689 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jul2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104468663&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104468663 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jul2012 vid: 50 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104468663 NLM22614134 2011597983 10.1007/s11517-012-0911-y NLM22614134 104468663 ppf: 683 ppct: 6 formats: fmt: @attributes: type: P tig: atl: Experimental comparison of connectivity measures with simulated EEG signals. aug: au: Silfverhuth MJ Hintsala H Kortelainen J Seppänen T Silfverhuth, Minna J Hintsala, Heidi Kortelainen, Jukka Seppänen, Tapio affil: Department of Computer Science and Engineering, University of Oulu, Oulu, Finland sug: subj: Electroencephalography Methods Models, Biological Neural Pathways Physiology Brain Mapping Methods Human Signal Processing, Computer Assisted Sensitivity and Specificity ab: Directional connectivity measures exist with different theoretical backgrounds, i.e., information theoretic, parametric-modeling based or phase related. In this paper, we perform the first comparison in this extend of a set of conventional and directed connectivity measures [cross-correlation, coherence, phase slope index (PSI), directed transfer function (DTF), partial-directed coherence (PDC) and transfer entropy (TE)] with eight-node simulation data based on real resting closed eye electroencephalogram (EEG) source signal. The ability of the measures to differentiate the direct causal connections from the non-causal connections was evaluated with the simulated data. Also, the effects of signal-to-noise ratio (SNR) and decimation were explored. All the measures were able to distinguish the direct causal interactions from the non-causal relations. PDC detected less non-causal connections compared to the other measures. Low SNR was tolerated better with DTF and PDC than with the other measures. Decimation affected most the results of TE, DTF and PDC. In conclusion, parametric-modeling-based measures (DTF, PDC) had the highest sensitivity of connections and tolerance to SNR in simulations based on resting closed eye EEG. However, decimation of data has to be carefully considered with these measures. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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