Direct or indirect? Graphical models for neural oscillators.
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Summary
Multivariate times series techniques are presented and investigated by means of simulated as well as physiological time series to distinguish direct and indirect interrelations in multivariate systems.
- Type
- article
- Published
- 2006-01-01
- Cited by
- 73
- References
- 21
- OpenAlex
- https://openalex.org/W16046108
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15793446
Keywords
Coal, Electricity generation, Nuclear power, Thermal power station, Environmental science
References
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- Quantitative analysis of tremor time series.
- A framework for the analysis of mixed time series/point process data--theory and application to the study of physiological tremor, single motor unit discharges and electromyograms.
- Graphical interaction models for multivariate time series1
- Central motor loop oscillations in parkinsonian resting tremor revealed magnetoencephalography
- Cross-spectral Analysis of tremor Time Series
- Partial directed coherence: a new concept in neural structure determination
- Time Series: Theory and Methods
- Dynamic synchronisation of central oscillators in essential tremor.
- Fourier Analysis of Time Series: An Introduction
- Time Series: Data Analysis and Theory.
- Investigating causal relations by econometric models and cross-spectral methods
- Tremor-correlated cortical activity in essential tremor
- Time and Frequency Domain Analysis of Spike Train and Time Series Data
Cited by
- Alpha Band Cortico-Muscular Coherence Occurs in Healthy Individuals during Mechanically-Induced Tremor
- Sensitivity analysis of (renormalized) partial directed coherence for the study of corticomuscular causality
- Modelling and analysis of cortico-hippocampal interactions and dynamics during sleep and anaesthesia
- Multivariate analysis of dynamical processes
- Fourier Bayesian Information Criterion for network structure and causality estimation
- Single trial classification of magnetoencephalographic recordings using Granger causality.
- A nonlinear causality measure in the frequency domain: nonlinear partial directed coherence with applications to EEG.
- Detection of Information Flow in Major International Financial Markets by Interactivity Network Analysis
- Bayesian learning of graphical vector autoregressions with unequal lag-lengths
- Dynamics of Circadian Thalamocortical Flow of Information during a Peripheral Neuropathic Pain Condition
- Multiple frequency functional connectivity in the hand somatosensory network: an EEG study.
- Measuring Connectivity in Linear Multivariate Processes: Definitions, Interpretation, and Practical Analysis
- Simulation of multivariate non-gaussian autoregressive time series with given autocovariance and marginals
- Study on connectivity between coherent central rhythm and electromyographic activities
- Network inference in the presence of latent confounders: the role of instantaneous causalities.
- Time-variant estimation of directed influences during Parkinsonian tremor.
- Distances of Time Series Components by Means of Symbolic Dynamics
- Reliability of multivariate causality measures for neural data.
- A new method using coherence to obtain the model order in the evaluation of partial directed coherence
- Choice of multivariate autoregressive model order affecting real network functional connectivity estimate.
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