The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment
Abstract
In this article we consider the application of parametric spectral analysis to multichannel event-related potentials (ERPs) during cognitive experiments. We show that with proper data preprocessing, Adaptive MultiVariate AutoRegressive (AMVAR) modeling is an effective technique for dealing with nonstationary ERP time series. We propose a bootstrap procedure to assess the variability in the estimated spectral quantities. Finally, we apply AMVAR spectral analysis to a visuomotor integration task, revealing rapidly changing cortical dynamics during different stages of task processing.
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“Algorithms have been developed for estimating functional connectivity from electrophysiological source signals derived from EEG (or MEG), including directed transfer function (DTF) algorithm (98), the adaptive DTF (ADTF) (99–101), direct DTF (dDTF) (102), and partial directed coherence (PDC) (103).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [99]
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Self-citationRecursive Multichannel Maximum Entropy Spectral Estimation
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The brainweb: phase synchronization and large-scale integration
Varela, F., Lachaux, J.-P., Rodriguez, E., & Martinerie, J. (2001) · Nature Reviews Neuroscience · doi:10.1038/35067550 · Cited by 4,761
Michel, C. M., & Koenig, T. W. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.062 · Cited by 1,418
The pulvinar regulates information transmission between cortical areas based on attention demands
Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., & Kastner, S. (2012) · Science · doi:10.1126/science.1223082 · Cited by 1,016
Nonlinear multivariate analysis of neurophysiological signals
Pereda, E., Quiroga, R. Q., & Bhattacharya, J. (2005) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2005.10.003 · Cited by 1,066
Brovelli, A., Ding, M., Ledberg, A., Chen, Y., Nakamura, R., & Bressler, S. L. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308538101 · Cited by 1,073
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Metadata
- Authors
- Ding, M., Bressler, S. L., Yang, W., & Liang, H.
- Affiliations
- Florida Atlantic University (US)
- Venue
- Biological Cybernetics
- Published
- 2000-06-21
- Volume
- 83
- Issue
- 1
- Pages
- 35-45
- ISSN
- 0340-1200 (ISSN-L)
- 1432-0770
- OpenAlex
- W2074501647
- Cited by
- 582
- References
- 16
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 12 · 2023: 19 · 2022: 24 · 2021: 20 · 2020: 25 · 2019: 36 · 2018: 32 · 2017: 22 · 2016: 32 · 2015: 31 · 2014: 37 · 2013: 36 · 2012: 33
- FWCI
- 5.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Biological Cybernetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r03mh058190-02)
- National Institute of Mental Health (MH-58190-02)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- event-related potentials, parametric spectral estimation, non-stationary time series, data preprocessing, model validation, cortical dynamics
- MeSH terms
- Animals, Cerebral Cortex, Cognition, Evoked Potentials, Macaca, Models, Neurological, Pattern Recognition, Visual, Psychomotor Performance, Reproducibility of Results, Multivariate Analysis
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