The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Nonlinear multivariate analysis of neurophysiological signals
Open accessAbstract
Multivariate time series analysis is extensively used in neurophysiology with the aim of studying the relationship between simultaneously recorded signals. Recently, advances on information theory and nonlinear dynamical systems theory have allowed the study of various types of synchronization from time series. In this work, we first describe the multivariate linear methods most commonly used in neurophysiology and show that they can be extended to assess the existence of nonlinear interdependence between signals. We then review the concepts of entropy and mutual information followed by a detailed description of nonlinear methods based on the concepts of phase synchronization, generalized synchronization and event synchronization. In all cases, we show how to apply these methods to study different kinds of neurophysiological data. Finally, we illustrate the use of multivariate surrogate data test for the assessment of the strength (strong or weak) and the type (linear or nonlinear) of interdependence between neurophysiological signals.
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Cited by
Network modelling methods for FMRI
Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, C. F., Nichols, T. E., Ramsey, J. D., & Woolrich, M. W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.063 · Cited by 1,878
Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?
Hindriks, R., Adhikari, M. H., Murayama, Y., Ganzetti, M., Mantini, D., Logothetis, N. K., & Deco, G. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.055 · Cited by 632
Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG
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Psychological entropy: a framework for understanding uncertainty-related anxiety
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The organization of physiological brain networks
Stam, C. J., & van Straaten, E. C. W. (2012) · Clinical Neurophysiology · doi:10.1016/j.clinph.2012.01.011 · Cited by 567
Metadata
- Authors
- Pereda, E., Quiroga, R. Q., & Bhattacharya, J.
- Venue
- Progress in Neurobiology
- Publisher
- Elsevier BV
- Published
- 2005-09
- Volume
- 77
- Issue
- 1-2
- Pages
- 1-37
- ISSN
- 0301-0082 (ISSN-L)
- OpenAlex
- W1987387046
- Cited by
- 1,076
- References
- 12
- FWCI
- 16.44
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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