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Journal of Classification

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18-11-2020

Clustering Brain Signals: a Robust Approach Using Functional Data Ranking

Authors: Tianbo Chen, Ying Sun, Carolina Euan, Hernando Ombao

Published in: Journal of Classification | Issue 3/2021

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Abstract

In this paper, we analyze electroencephalograms (EEGs) which are recordings of brain electrical activity. We develop new clustering methods for identifying synchronized brain regions, where the EEGs show similar oscillations or waveforms according to their spectral densities. We treat the estimated spectral densities from many epochs or trials as functional data and develop clustering algorithms based on functional data ranking. The two proposed clustering algorithms use different dissimilarity measures: distance of the functional medians and the area of the central region. The performance of the proposed algorithms is examined by simulation studies. We show that, when contaminations are present, the proposed methods for clustering spectral densities are more robust than the mean-based methods. The developed methods are applied to two stages of resting state EEG data from a male college student, corresponding to early exploration of functional connectivity in the human brain.

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Caiado, J., Crato, N., & Peña, D. (2006). A periodogram-based metric for time series classification. Computational Statistics & Data Analysis, 50(10), 2668–2684.MathSciNetCrossRef

Euan, C., Ombao, H., & Ortega, J. (2018). The hierarchical spectral merger algorithm: a new time series clustering procedure. Journal of Classification.

Euán, C., Ombao, H., & Ortega, J. (2018). Spectral synchronicity in brain signals. Statistics in medicine, 37(19), 2855–2873.MathSciNetCrossRef

Fingelkurts, A.A., Fingelkurts, A.A., & Kähkönen, S. (2005). Functional connectivity in the brain—is it an elusive concept? Neuroscience & Biobehavioral Reviews, 28(8), 827–836.CrossRef

Freyermuth, J.M., Ombao, H., & von Sachs, R. (2010). Tree-structured wavelet estimation in a mixed effects model for spectra of replicated time series. Journal of the American Statistical Association, 105(490), 634–646.MathSciNetCrossRef

Gao, X., Shahbaba, B., Fortin, N., & Ombao, H. (2018). Evolutionary state-space model and its application to time-frequency analysis of local field potentials. arXiv:1610.07271.

Hasenstab, K., Sugar, C., Telesca, D., Jeste, S., & Şentürk, D. (2016). Robust functional clustering of ERP data with application to a study of implicit learning in autism. Biostatistics, 17(3), 484–498.MathSciNetCrossRef

Kakizawa, Y., Shumway, R.H., & Taniguchi, M. (1998). Discrimination and clustering for multivariate time series. Journal of the American Statistical Association, 93(441), 328–340.MathSciNetCrossRef

Krafty, R.T. (2016). Discriminant analysis of time series in the presence of within-group spectral variability. Journal of Time Series Analysis, 37(4), 435–450. https://doi.org/10.1111/jtsa.12166.MathSciNetCrossRef

López-Pintado, S., & Romo, J. (2009). On the concept of depth for functional data. Journal of the American Statistical Association, 104(486), 718–734.MathSciNetCrossRef

Maharaj, E.A., & D’Urso, P. (2012). Wavelets-based clustering of multivariate time series. Fuzzy Sets and Systems, 193, 33–61.MathSciNetCrossRef

Montero, P., Vilar, J.A., & et al. (2014). Tsclust: an r package for time series clustering. Journal of Statistical Software, 62(1), 1–43.CrossRef

Ngo, D., Sun, Y., Genton, M.G., Wu, J., Srinivasan, R., Cramer, S.C., & Ombao, H. (2015). An exploratory data analysis of electroencephalograms using the functional boxplots approach. Frontiers in Neuroscience, p. 9.

Nguyen, X.V., Epps, J., & Bailey, J. (2009). Information theoretic measures for clusterings comparison: is a correction for chance necessary? p. 135.

Ombao, H., Raz, J.A., Strawderman, R.L., & Sachs, R.V. (2001). A simple generalised crossvalidation method of span selection for periodogram smoothing. Biometrika, 88(4), 1186–1192.MathSciNetCrossRef

Orhan, U., Hekim, M., & Ozer, M. (2011). EEG Signals classification using the k-means clustering and a multilayer perceptron neural network model. Expert Systems with Applications, 38(10), 13475–13481.CrossRef

Panuccio, A., Bicego, M., & Murino, V. (2002). A hidden Markov model-based approach to sequential data clustering. In Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR), pages 734–743. Springer.

Purdon, P.L., Pierce, E.T., Mukamel, E.A., Prerau, M.J., Walsh, J.L., Wong, K.F.K., Salazar-Gomez, A.F., Harrell, P.G., Sampson, A.L., Cimenser, A., Ching, S., Kopell, N.T., e Tavares-Stoeckela, C., Habeeb, K., Merhar, R., & Brown, E.N. (2013). Electroencephalogram signatures of loss and recovery of consciousness from propofol. Proceedings of the National Academy of Sciences, 110(12), E1142–E1151.CrossRef

Rutkowski, T.M., Mandic, D.P., Cichocki, A., & Przybyszewski, A.W. (2010). EMD approach to multichannel eeg data—the amplitude and phase components clustering analysis. Journal of Circuits Systems, and Computers, 19(01), 215–229.CrossRef

Shumway, R.H., & Stoffer, D.S. (2016). Time series analysis and its applications: with R examples. Springer Science & Business Media.

Sun, Y. (2011). Functional boxplots. Journal of Computational and Graphical Statistics.

Sun, Y., & Genton, M.G. (2012). Adjusted functional boxplots for spatio-temporal data visualization and outlier detection. Environmetrics, 23(1), 54–64.MathSciNetCrossRef

Vilar, J.A., & Pértega, S. (2004). Discriminant and cluster analysis for Gaussian stationary processes: local linear fitting approach. Journal of Nonparametric Statistics, 16(3-4), 443–462.MathSciNetCrossRef

Viqueira, M., Zapirain, B.G., & Zorrilla, A.M. (2013). Ocular movement and cardiac rhythm control using EEG techniques. In Medical Imaging in Clinical Practice. InTech.

Wahba, G. (1980). Automatic smoothing of the log periodogram. Journal of the American Statistical Association, 75(369), 122–132.CrossRef

Wu, J., Srinivasan, R., Kaur, A., & Cramer, S.C. (2014). Resting-state cortical connectivity predicts motor skill acquisition. NeuroImage, 91, 84–90.CrossRef

Title: Clustering Brain Signals: a Robust Approach Using Functional Data Ranking
Authors: Tianbo Chen
Ying Sun
Carolina Euan
Hernando Ombao
Publication date: 18-11-2020
Publisher: Springer US
Published in: Journal of Classification / Issue 3/2021
Print ISSN: 0176-4268
Electronic ISSN: 1432-1343
DOI: https://doi.org/10.1007/s00357-020-09382-1

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