Tracking the Time-Varying Cortical Connectivity Patterns by Adaptive Multivariate Estimators
Abstract
The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Algorithms have been developed for estimating functional connectivity from electrophysiological source signals derived from EEG or MEG, including directed transfer function, adaptive directed transfer function, direct directed transfer function, and partial directed coherence.
“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 [101]
Cites
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989 · see citing works
Investigating Causal Relations by Econometric Models and Cross-Spectral Methods
Granger, C. W. J. (2010) · Essays in Econometrics · doi:10.1017/cbo9780511753978.002 · Cited by 4,762 · see citing works
Wittenmark, B. (1993) · Automatica · doi:10.1016/0005-1098(93)90162-m · Cited by 3,067 · see citing works
Adaptive filter theory (2nd ed.)
Haykin, S. (1991) · Prentice-Hall, Inc eBooks · Cited by 1,905 · see citing works
Partial directed coherence: a new concept in neural structure determination
Baccalá, L. A., & Sameshima, K. (2001) · Biological Cybernetics · doi:10.1007/pl00007990 · Cited by 1,791 · see citing works
Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine
Regan, D. M. (1989) · Medical Entomology and Zoology · Cited by 1,303 · see citing works
A new method of the description of the information flow in the brain structures
Kaminski, M. J., & Blinowska, K. J. (1991) · Biological Cybernetics · doi:10.1007/bf00198091 · Cited by 1,047 · see citing works
Kamiński, M., Ding, M., Truccolo, W., & Bressler, S. L. (2001) · Biological Cybernetics · doi:10.1007/s004220000235 · Cited by 990 · see citing works
The elusive concept of brain connectivity
Horwitz, B. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00112-5 · Cited by 779 · see citing works
Stam, C. J., & van Dijk, B. W. (2002) · Physica D Nonlinear Phenomena · doi:10.1016/s0167-2789(01)00386-4 · Cited by 634 · see citing works
Ding, M., Bressler, S. L., Yang, W., & Liang, H. (2000) · Biological Cybernetics · doi:10.1007/s004229900137 · Cited by 582 · see citing works
Babiloni, F., Cincotti, F., Babiloni, C., Carducci, F., Mattia, D., Astolfi, L., Basilisco, A., Rossini, P. M., Ding, L., Ni, Y., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.09.036 · Cited by 412 · see citing works
Self-citationHesse, W., Möller, E., Arnold, M., & Schack, B. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00366-7 · Cited by 382 · see citing works
Self-citationComparison of different cortical connectivity estimators for high‐resolution EEG recordings
Astolfi, L., Cincotti, F., Mattia, D., Marciani, M. G., Baccalá, L. A., Fallani, F. D. V., Salinari, S., Ursino, M., Zavaglia, M., Ding, L., et al. (2006) · Human Brain Mapping · doi:10.1002/hbm.20263 · Cited by 357 · see citing works
Self-citationEvaluation of different measures of functional connectivity using a neural mass model
Olivier David, A., Cosmelli, D. J., & Friston, K. J. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.10.006 · Cited by 339 · see citing works
Determination of EEG Activity Propagation: Pair-Wise Versus Multichannel Estimate
Kuś, R., Kamiński, M., & Blinowska, K. J. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.827929 · Cited by 328 · see citing works
Estimating the errors on measured entropy and mutual information
Roulston, M. S. (1999) · Physica D Nonlinear Phenomena · doi:10.1016/s0167-2789(98)00269-3 · Cited by 286 · see citing works
Matthias Winterhalder, A., Schelter, B. O., Hesse, W., Schwab, K., Leistritz, L., Klan, D., Bauer, R., Timmer, J., & Witte, H. (2005) · Signal Processing · doi:10.1016/j.sigpro.2005.07.011 · Cited by 184 · see citing works
Self-citationMöller, E., Schack, B., Arnold, M., & Witte, H. (2001) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(00)00350-2 · Cited by 139 · see citing works
Self-citationThe Electroencephalogram and the Adaptive Autoregressive Model: Theory and Applications
Schlögl, A. (2000) · Cited by 137 · see citing works
Sub-second “temporal attention” modulates alpha rhythms. A high-resolution EEG study
Babiloni, C., Miniussi, C., Babiloni, F., Carducci, F., Cincotti, F., Percio, C. D., Sirello, G., Fracassi, C., Nobre, A. C., & Rossini, P. M. (2004) · Cognitive Brain Research · doi:10.1016/j.cogbrainres.2003.12.010 · Cited by 130 · see citing works
Self-citationLaura Astolfi, A., Febo Cincotti, A., Donatella Mattia, A., Babiloni, C., Carducci, F., Basilisco, A., Rossini, P. M., Salinari, S., Ding, L., Ni, Y., et al. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2004.10.012 · Cited by 128 · see citing works
Self-citationHuman Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine
Galloway, N. R. (1990) · British Journal of Ophthalmology · doi:10.1136/bjo.74.4.255-a · Cited by 114 · see citing works
Laura Astolfi, A., Febo Cincotti, A., Donatella Mattia, A., Salinari, S., Babiloni, C., Basilisco, A., Rossini, P. M., Ding, L., Ni, Y., He, B., et al. (2004) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2004.10.006 · Cited by 101 · see citing works
Self-citationMultimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle
Babiloni, F., Mattia, D., Babiloni, C., Astolfi, L., Salinari, S., Basilisco, A., Rossini, P. M., Marciani, M. G., & Cincotti, F. (2004) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2004.10.007 · Cited by 91 · see citing works
Self-citationBabiloni, F., Babiloni, C., Locche, L., Febo Cincotti, A., Rossini, P. M., & Carducci, F. (2000) · Medical & Biological Engineering & Computing · doi:10.1007/bf02345746 · Cited by 84 · see citing works
Self-citationUrbano, A., Babiloni, C., Onorati, P., & Babiloni, F. (1998) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/s0013-4694(97)00150-8 · Cited by 78 · see citing works
Self-citationLaura Astolfi, A., Febo Cincotti, A., Babiloni, C., Carducci, F., Basilisco, A., Rossini, P. M., Salinari, S., Donatella Mattia, A., Cerutti, S., BenDayan, D., et al. (2005) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2005.845371 · Cited by 76 · see citing works
Self-citationBabiloni, C., Babiloni, F., Carducci, F., Cappa, S. F., Cincotti, F., Percio, C. D., Miniussi, C., Moretti, D. V., Rossi, S., Sosta, K., et al. (2003) · Clinical Neurophysiology · doi:10.1016/s1388-2457(03)00286-4 · Cited by 69 · see citing works
Self-citationProperties of MEG tomographic maps obtained with spatial filtering
Groß, J., Timmermann, L., Kujala, J., Salmelin, R. H., & Schnitzler, A. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00101-0 · Cited by 67 · see citing works
Urbano, A., Babiloni, C., Onorati, P., Carducci, F., Ambrosini, A., Fattorini, L., & Babiloni, F. (1998) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.1998.00072.x · Cited by 67 · see citing works
Self-citationDynamic Topographic Spectral Analysis of Cognitive Processes
Schack, B. (1999) · Springer series in synergetics · doi:10.1007/978-3-642-60007-4_13 · Cited by 16 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Electrophysiological source imaging: A noninvasive window to brain dynamics
He, B., Sohrabpour, A., Brown, E., & Liu, Z. (2018) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-062117-120853 · Cited by 297 · see citing works
Electrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities
He, B., Yang, L., Wilke, C., & Yuan, H. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2139210 · Cited by 300 · see citing works
Coito, A., Michel, C. M., van Mierlo, P., Vulliemoz, S., & Plomp, G. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2619665 · Cited by 75 · see citing works
Laminar dynamics of high amplitude beta bursts in human motor cortex
Bonaiuto, J. J., Little, S., Neymotin, S. A., Jones, S. R., Barnes, G. R., & Bestmann, S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118479 · Cited by 76 · see citing works
- Authors
- Astolfi, L., Cincotti, F., Mattia, D., De Vico Fallani, F., Tocci, A., Colosimo, A., Salinari, S., Marciani, M. G., Hesse, W., Witte, H., Ursino, M., Zavaglia, M., & Babiloni, F.
- Affiliations
- Fondazione Santa Lucia (IT)
- Sapienza University of Rome (IT)
- University of Rome Tor Vergata (IT)
- Friedrich Schiller University Jena (DE)
- University of Bologna (IT)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2008-03
- Volume
- 55
- Issue
- 3
- Pages
- 902-913
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2151051991
- Cited by
- 179
- References
- 32
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 1 · 2023: 5 · 2022: 9 · 2021: 13 · 2020: 11 · 2019: 9 · 2018: 16 · 2017: 9 · 2016: 15 · 2015: 14 · 2014: 15 · 2013: 9 · 2012: 8
- FWCI
- 6.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- directed transfer function, partial directed coherence, Granger causality, EEG, motor tasks, cortical networks, signal-to-noise ratio, number of trials
- MeSH terms
- Adult, Algorithms, Brain Mapping, Electroencephalography, Evoked Potentials, Female, Humans, Male, Motor Cortex, Movement, Nerve Net, Neural Pathways, Pattern Recognition, Automated, 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 ›
Are you an author, or do you see a problem with this page? Request a review
