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Open Access 01-09-2018 | Original Paper

A Time-Varying Connectivity Analysis from Distributed EEG Sources: A Simulation Study

Authors: Eshwar G. Ghumare, Maarten Schrooten, Rik Vandenberghe, Patrick Dupont

Published in: Brain Topography | Issue 5/2018

Abstract

Time-varying connectivity analysis based on sources reconstructed using inverse modeling of electroencephalographic (EEG) data is important to understand the dynamic behaviour of the brain. We simulated cortical data from a visual spatial attention network with a time-varying connectivity structure, and then simulated the propagation to the scalp to obtain EEG data. Distributed EEG source modeling using sLORETA was applied. We compared different dipole (representing a source) selection strategies based on their time series in a region of interest. Next, we estimated multivariate autoregressive (MVAR) parameters using classical Kalman filter and general linear Kalman filter approaches followed by the calculation of partial directed coherence (PDC). MVAR parameters and PDC values for the selected sources were compared with the ground-truth. We found that the best strategy to extract the time series of a region of interest was to select a dipole with time series showing the highest correlation with the average time series in the region of interest. Dipole selection based on power or based on the largest singular value offer comparable alternatives. Among the different Kalman filter approaches, the use of a general linear Kalman filter was preferred to estimate PDC based connectivity except when only a small number of trials are available. In the latter case, the classical Kalman filter can be an alternative.

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Ahrens H, Argin F, Klinkenbusch L (2012) A comparison of minimum norm and MUSIC for a combined MEG/EEG sensor array. Adv Radio Sci 10:99–104. https://doi.org/10.5194/ars-10-99-2012 CrossRef

Arnold M, Milner X, Witte H, Bauer R, Braun C (1998) Adaptive AR modeling of nonstationary time series by means of Kalman filtering. IEEE Trans Biomed Eng 45(5):553–562. https://doi.org/10.1109/10.668741 CrossRefPubMed

Astolfi L, Cincotti F, Mattia D, Marciani MG, Baccalá LA, De Vico Fallani F, Salinari S, Ursino M, Zavaglia M, Babiloni F (2006) Assessing cortical functional connectivity by partial directed coherence: simulations and application to real data. IEEE Trans Biomed Eng 53(9):1802–1812. https://doi.org/10.1109/TBME.2006.873692 CrossRefPubMed

Astolfi L, Cincotti F, Mattia D, De Vico Fallani F, Tocci A, Colosimo A, Salinari S, Marciani M, Hesse W, Witte H, Ursino M, Zavaglia M, Babiloni F (2008) Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators. IEEE Trans Biomed Eng 55(3):902–913. https://doi.org/10.1109/TBME.2007.905419 CrossRefPubMed

Babiloni F, Babiloni C, Carducci F, Romani G, Rossini P, Angelone L, Cincotti F (2003) Multimodal integration of high-resolution EEG and functional magnetic resonance imaging data: a simulation study. NeuroImage 19(1):1–15. https://doi.org/10.1016/S1053-8119(03)00052-1 CrossRefPubMed

Babiloni F, Babiloni C, Carducci F, Romani GL, Rossini PM, Angelone LM, Cincotti F (2004) Multimodal integration of EEG and MEG data: a simulation study with variable signal-to-noise ratio and number of sensors. Hum Brain Mapp 22(1):52–62. https://doi.org/10.1002/hbm.20011 CrossRefPubMed

Baccalá LA, Sameshima K (2001) Partial directed coherence: a new concept in neural structure determination. Biol Cybern 84(6):463–474. https://doi.org/10.1007/PL00007990 CrossRefPubMed

Becker H, Albera L, Comon P, Gribonval R, Wendling F, Merlet I (2016) Localization of distributed EEG sources in the context of epilepsy: a simulation study. IRBM 37(5–6):242–253. https://doi.org/10.1016/j.irbm.2016.04.001 CrossRef

Blackman RB, Tukey JW (1959) The measurement of power spectra: from the point of view of communications engineering. Dover Books on Engineering and Engineering Physics, Dover

Bradley A, Yao J, Dewald J, Richter C-P (2016) Evaluation of electroencephalography source localization algorithms with multiple cortical sources. PLoS ONE 11(1):e0147266. https://doi.org/10.1371/journal.pone.0147266 CrossRefPubMedPubMedCentral

Campbell K, Kumar A, Hofman W (1980) Human and automatic validation of a phase-locked loop spindle detection system. Electroencephalogr Clin Neurophysiol 48(5):602–605CrossRefPubMed

Coito A, Michel CM, van Mierlo P, Vulliemoz S, Plomp G (2016) Directed functional brain connectivity based on EEG source imaging: methodology and application to temporal lobe epilepsy. IEEE Trans Biomed Eng 63(12):2619–2628. https://doi.org/10.1109/TBME.2016.2619665 CrossRefPubMed

Corbetta M, Patel G, Shulman GL (2008) The reorienting system of the human brain: from environment to theory of mind. Neuron 58(3):306–324. https://doi.org/10.1016/j.neuron.2008.04.017 CrossRefPubMedPubMedCentral

Dougherty RF, Koch VM, Brewer Aa, Fischer B, Modersitzki J, Wandell B a (2003) Visual field representations and locations of visual areas V1/2/3 in human visual cortex. J Vision 3(10):1. https://doi.org/10.1167/3.10.1 CrossRef

Dümpelmann M, Ball T, Schulze-Bonhage A (2012) sLORETA allows reliable distributed source reconstruction based on subdural strip and grid recordings. Hum Brain Mapp 33(5):1172–1188. https://doi.org/10.1002/hbm.21276 CrossRefPubMed

Eftaxias K, Sanei S (2013) Diffusion adaptive filtering for modelling brain responses to motor tasks. In: 2013 18th International conference on digital signal processing (DSP) vol 1. IEEE, pp 1–5. https://doi.org/10.1109/ICDSP.2013.6622799

Farahibozorg S-R, Henson RN, Hauk O (2017) Adaptive cortical parcellations for source reconstructed EEG/MEG connectomes. NeuroImage 44:1–43. https://doi.org/10.1016/j.neuroimage.2017.09.009 CrossRef

Freiwald WA, Valdes P, Bosch J, Biscay R, Jimenez JC, Rodriguez LM, Rodriguez V, Kreiter AK, Singer W (1999) Testing non-linearity and directedness of interactions between neural groups in the macaque inferotemporal cortex. J Neurosci Methods 94(1):105–19CrossRefPubMed

Gao L, Sommerlade L, Coffman B, Zhang T, Stephen JM, Li D, Wang J, Grebogi C, Schelter B (2015) Granger causal time-dependent source connectivity in the somatosensory network. Sci Rep 5(1):10399. https://doi.org/10.1038/srep10399 CrossRefPubMedPubMedCentral

Ghumare E, Schrooten M, Vandenberghe R, Dupont P (2015) Comparison of different Kalman filter approaches in deriving time varying connectivity from EEG data. In: 2015 37th Annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 2199–2202. https://doi.org/10.1109/EMBC.2015.7318827

Gillebert CR, Mantini D, Peeters R, Dupont P, Vandenberghe R (2013) Cytoarchitectonic mapping of attentional selection and reorienting in parietal cortex. NeuroImage 67:257–272. https://doi.org/10.1016/j.neuroimage.2012.11.026 CrossRefPubMed

Gramfort A, Papadopoulo T, Olivi E, Clerc M (2010) OpenMEEG: opensource software for quasistatic bioelectromagnetics. BioMed Eng Online 9(1):45. https://doi.org/10.1186/1475-925X-9-45 CrossRefPubMedPubMedCentral

Hassan M, Wendling F (2015) Tracking dynamics of functional brain networks using dense EEG. IRBM 36(6):324–328. https://doi.org/10.1016/j.irbm.2015.09.004 CrossRef

Hassan M, Dufor O, Merlet I, Berrou C, Wendling F (2014) EEG source connectivity analysis: from dense array recordings to brain networks. PLoS ONE 9(8):e105041. https://doi.org/10.1371/journal.pone.0105041 CrossRefPubMedPubMedCentral

Hassan M, Merlet I, Mheich A, Kabbara A, Biraben A, Nica A, Wendling F (2017) Identification of interictal epileptic networks from dense-EEG. Brain Topogr 30(1):60–76. https://doi.org/10.1007/s10548-016-0517-z CrossRefPubMed

Haufe S, Ewald A (2016) A Simulation framework for benchmarking EEG-based brain connectivity estimation methodologies. Brain Topogr. https://doi.org/10.1007/s10548-016-0498-y

Hauk O, Wakeman DG, Henson R (2011) Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics. NeuroImage 54(3):1966–1974. https://doi.org/10.1016/j.neuroimage.2010.09.053 CrossRefPubMedPubMedCentral

Jeffs B, Leahy R, Singh M (1987) An evaluation of methods for neuromagnetic image reconstruction. IEEE Trans Bio-med Eng 34(9):713–723CrossRef

Lai Y, Van Drongelen W, Ding L, Hecox KE, Towle VL, Frim DM, He B (2005) Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings. Clin Neurophysiol 116(2):456–465. https://doi.org/10.1016/j.clinph.2004.08.017 CrossRefPubMed

Leistritz L, Pester B, Doering A, Schiecke K, Babiloni F, Astolfi L, Witte H (2013) Time-variant partial directed coherence for analysing connectivity: a methodological study. Philos Trans R Soc A 371(1997):20110616. https://doi.org/10.1098/rsta.2011.0616 CrossRef

Leistritz L, Schiecke K, Astolfi L, Witte H (2016) Time-variant modeling of brain processes. Proc IEEE 104(2):262–281. https://doi.org/10.1109/JPROC.2015.2497144 CrossRef

Lie OV, van Mierlo P (2017) Seizure-onset mapping based on time-variant multivariate functional connectivity analysis of high-dimensional intracranial EEG: a Kalman filter approach. Brain Topogr 30(1):46–59. https://doi.org/10.1007/s10548-016-0527-x CrossRefPubMed

Liu B-W, Mao J-W, Shi Y-J, Lu Q-C, Liang P-J, Zhang P-M (2016) Analyzing epileptic network dynamics via time-variant partial directed coherence. In: 2016 IEEE International conference on bioinformatics and biomedicine (BIBM). IEEE, pp 368–374 https://doi.org/10.1109/BIBM.2016.7822547

Lopes da Silva F (2013) EEG and MEG: relevance to neuroscience. Neuron 80(5):1112–1128. https://doi.org/10.1016/j.neuron.2013.10.017 CrossRefPubMed

Mahjoory K, Nikulin VV, Botrel L, Linkenkaer-Hansen K, Fato MM, Haufe S (2016) Consistency of EEG source localization and connectivity estimates. Neuroimage 152:590–601. https://doi.org/10.1016/j.neuroimage.2017.02.076 CrossRef

Makeig S (2002) Dynamic brain sources of visual evoked responses. Science 295(5555):690–694. https://doi.org/10.1126/science.1066168 CrossRefPubMed

Mao J-W, Ye X-L, Li Y-H, Liang P-J, Xu J-W, Zhang P-M (2016) Dynamic network connectivity analysis to identify epileptogenic zones based on stereo-electroencephalography. Front Computat Neurosci 10:113. https://doi.org/10.3389/fncom.2016.00113 CrossRef

van Mierlo P, Papadopoulou M, Carrette E, Boon P, Vandenberghe S, Vonck K, Marinazzo D (2013) Functional brain connectivity from EEG in epilepsy: seizure prediction and epileptogenic focus localization. Prog Neurobiol 121:19–35. https://doi.org/10.1016/j.pneurobio.2014.06.004 CrossRef

Milde T, Leistritz L, Astolfi L, Miltner WH, Weiss T, Babiloni F, Witte H (2010) A new Kalman filter approach for the estimation of high-dimensional time-variant multivariate AR models and its application in analysis of laser-evoked brain potentials. NeuroImage 50(3):960–969. https://doi.org/10.1016/j.neuroimage.2009.12.110 CrossRefPubMed

Omidvarnia A, Azemi G, Boashash B, O’Toole JM, Colditz PB, Vanhatalo S (2014) Measuring time-varying information flow in scalp EEG signals: orthogonalized partial directed coherence. IEEE Trans Biomed Eng 61(3):680–693. https://doi.org/10.1109/TBME.2013.2286394 CrossRefPubMed

Oostendorp TF, Delbeke J, Stegeman DF (2000) The conductivity of the human skull: results of in vivo and in vitro measurements. IEEE Trans Biomed Eng 47(11):1487–1492. https://doi.org/10.1109/TBME.2000.880100 CrossRefPubMed

Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 24(Suppl D):5–12PubMed

Plomp G, Hervais-Adelman A, Astolfi L, Michel CM (2016) Early recurrence and ongoing parietal driving during elementary visual processing. Sci Rep 5(1):18733. https://doi.org/10.1038/srep18733 CrossRef

Porcaro C, Zappasodi F, Rossini PM, Tecchio F (2009) Choice of multivariate autoregressive model order affecting real network functional connectivity estimate. Clin Neurophysiol 120(2):436–448. https://doi.org/10.1016/j.clinph.2008.11.011 CrossRefPubMed

Qin Y, Xu P, Yao D (2010) A comparative study of different references for EEG default mode network: the use of the infinity reference. Clin Neurophysiol 121(12):1981–1991. https://doi.org/10.1016/j.clinph.2010.03.056 CrossRefPubMed

Rueda-Delgado L, Solesio-Jofre E, Mantini D, Dupont P, Daffertshofer A, Swinnen S (2017) Coordinative task difficulty and behavioural errors are associated with increased long-range beta band synchronization. NeuroImage 146(October):883–893. https://doi.org/10.1016/j.neuroimage.2016.10.030 CrossRefPubMed

Sameshima K, Takahashi DY, Baccalá L a (2015) On the statistical performance of Granger-causal connectivity estimators. Brain Inform 2(2):119–133. https://doi.org/10.1007/s40708-015-0015-1 CrossRefPubMedPubMedCentral

Schlögl A (2002) Time series analysis-a toolbox for the use with Matlab. Technische Universität Graz, Graz. URL http://www.dpmitu-grazacat/schloegl/matlab/tsa

Schlögl A, Supp G (2006) Analyzing event-related EEG data with multivariate autoregressive parameters. Prog Brain Res 159:135–147. https://doi.org/10.1016/S0079-6123(06)59009-0 CrossRefPubMed

Schneider T, Neumaier A (2001) Algorithm 808: ARfit–a matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models. ACM Trans Math Softw 27(1):58–65. https://doi.org/10.1145/382043.382316 CrossRef

Siebenhühner F, Lobier M, Wang S H, Palva S, Palva J M (2016) Measuring large-scale synchronization with human MEG and EEG: challenges and solutions. In: Multimodal oscillation-based connectivity theory. Springer , Cham, pp 1–18 https://doi.org/10.1007/978-3-319-32265-0_1

Sohrabpour A, Ye S, Worrell GA, Zhang W, He B (2016) Noninvasive electromagnetic source imaging and granger causality analysis: an electrophysiological connectome (eConnectome) approach. IEEE Trans Biomed Eng 63(12):2474–2487. https://doi.org/10.1109/TBME.2016.2616474 CrossRefPubMedPubMedCentral

Stenroos M, Hauk O (2013) Minimum-norm cortical source estimation in layered head models is robust against skull conductivity error. NeuroImage 81:265–272. https://doi.org/10.1016/j.neuroimage.2013.04.086 CrossRefPubMedPubMedCentral

Simpson GV, Weber DL, Dale CL, Pantazis D, Bressler SL, Leahy RM, Luks TL (2011) Dynamic activation of frontal, parietal, and sensory regions underlying anticipatory visual spatial attention. J Neurosci 31(39):13880–13889. https://doi.org/10.1523/JNEUROSCI.1519-10.2011 CrossRefPubMedPubMedCentral

Tang D, Hu L, Li H, Zhang Q, Chen A (2013) The neural dynamics of conflict adaptation within a look-to-do transition. PLoS ONE 8(2):e57912. https://doi.org/10.1371/journal.pone.0057912 CrossRefPubMedPubMedCentral

Vossel S, Geng JJ, Fink GR (2014) Dorsal and ventral attention systems. The Neuroscientist 20(2):150–159. https://doi.org/10.1177/1073858413494269 CrossRefPubMedPubMedCentral

Wagner M, Fuchs M, Kastner J (2003) Evaluation of sLORETA in the presence of noise and multiple sources. Brain Topogr 16(4):277–280. https://doi.org/10.1023/B:BRAT.0000032865.58382.62 CrossRef

Wang Y, Ting C-M, Ombao H (2016) Modeling effective connectivity in high-dimensional cortical source signals. IEEE J Sel Top Sign Process 10(7):1315–1325. https://doi.org/10.1109/JSTSP.2016.2600023 CrossRef

Wilke C, Ding Lei, He Bin (2008) Estimation of time-varying connectivity patterns through the use of an adaptive directed transfer function. IEEE Trans Biomed Eng 55(11):2557–2564. https://doi.org/10.1109/TBME.2008.919885 CrossRefPubMedPubMedCentral

Title: A Time-Varying Connectivity Analysis from Distributed EEG Sources: A Simulation Study
Authors: Eshwar G. Ghumare
Maarten Schrooten
Rik Vandenberghe
Patrick Dupont
Publication date: 01-09-2018
Publisher: Springer US
Published in: Brain Topography / Issue 5/2018
Print ISSN: 0896-0267
Electronic ISSN: 1573-6792
DOI: https://doi.org/10.1007/s10548-018-0621-3

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A Time-Varying Connectivity Analysis from Distributed EEG Sources: A Simulation Study

Abstract

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