Towards detecting connectivity in EEG: A comparative study of parameters of effective connectivity measures on simulated data

Hanieh Bakhshayesh, Tyler S. Grummett, Azin S. Janani, Sean P. Fitzgibbon, Kenneth J. Pope

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We compare the performance of many effective connectivity measures in detecting statistically significant causal connections between time series drawn from linear and nonlinear coupled systems. Fifteen measures are compared, drawn from two families (information theoretic, and frequency- and time-based multivariate autoregressive models), including common and uncommon measures. Measures were tested on simulated data from three systems: three coupled Hénon maps; a multivariate autoregressive (MVAR) model with and without EEG as an exogenous input; and simulated EEG. Comparisons focus on the effective of parameter choices, e.g. maximum model order or maximum number of lags, for different lengths of data. Performance varies with dataset, and no measure was outstanding for all datasets. Strong performance is obtained where the measure’s model and data source match (eg MVAR model, or frequency domain measures with narrowband data). When there is no match, information theoretic measures and Copula Granger causality generally perform best.

Original languageEnglish
Title of host publication2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages297-301
Number of pages5
ISBN (Electronic)9781538624715
DOIs
Publication statusPublished - 24 Jan 2019
Event2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Kuching, Malaysia
Duration: 3 Dec 20186 Dec 2018

Publication series

Name2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings

Conference

Conference2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018
CountryMalaysia
CityKuching
Period3/12/186/12/18

Keywords

  • Comparison
  • connectivity
  • EEG
  • Parameters

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    Bakhshayesh, H., Grummett, T. S., Janani, A. S., Fitzgibbon, S. P., & Pope, K. J. (2019). Towards detecting connectivity in EEG: A comparative study of parameters of effective connectivity measures on simulated data. In 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings (pp. 297-301). [8626645] (2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECBES.2018.8626645