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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-citation
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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