Assessing direct paths of intracortical causal information flow of oscillatory activity with the isolated effective coherence (iCoh)

Frontiers in Human Neuroscience

Volumn 8, Issue JUNE, 2014, Pages

  Pascual Marqui, Roberto D ^a,b   Biscay, Rolando J ^c   Bosch Bayard, Jorge ^d   Lehmann, Dietrich ^a   Kochi, Kieko ^a   Kinoshita, Toshihiko ^b   Yamada, Naoto ^e   Sadato, Norihiro ^f  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b KANSAI MEDICAL UNIVERSITY   (Japan)

^c UNIVERSIDAD DE VALPARAÍSO   (Chile)

^d CUBAN NEUROSCIENCE CENTER   (Cuba)

^e SHIGA UNIVERSITY OF MEDICAL SCIENCE   (Japan)

^f NATIONAL INSTITUTE FOR PHYSIOLOGICAL SCIENCES   (Japan)

Author keywords

Alpha oscillation connectivity; Causal intracortical connectivity; Isolated effective coherence; LORETA; Resting state electriphysiological connectivity

Indexed keywords

ALPHA RHYTHM; ANTERIOR CINGULATE; ARTICLE; BRAIN ELECTROPHYSIOLOGY; ELECTROENCEPHALOGRAM; EVOKED SOMATOSENSORY RESPONSE; HUMAN; INFERIOR PARIETAL LOBULE; ISOLATED EFFECTIVE COHERENCE; LOW RESOLUTION BRAIN ELECTROMAGNETIC TOMOGRAPHY; MULTIVARIATE ANALYSIS; NERVE CELL NETWORK; NONHUMAN; PARTIAL DIRECTED COHERENCE; POSTERIOR CINGULATE; PRECUNEUS; PREFRONTAL CORTEX; THETA RHYTHM; TIME SERIES ANALYSIS;

EID: 84918583937     PISSN: None     EISSN: 16625161     Source Type: Journal    
DOI: 10.3389/fnhum.2014.00448     Document Type: Article

References (53)

1. Akaike, H. (1968). On the use of a linear model for the identification of feedback systems. Ann. Inst. Stat. Math. 20, 425-439. doi: 10.1007/BF02911655
2. Akaike, H. (1974). A new look at the statistical model identification. Autom. Control IEEE Trans. 19, 716-723. doi: 10.1109/TAC.1974.1100705
3. Baccala, L., Sameshima, K., Ballester, G., Do Valle, A., and Timo-Iaria, C. (1998). Studying the interaction between brain structures via directed coherence and Granger causality. Appl. Signal Process. 5, 40. doi: 10.1007/s005290050005
4. Baccala, L. A., and Sameshima, K. (2001). Partial directed coherence: a new concept in neural structure determination. Biol. Cybern. 84, 463-74. doi: 10.1007/PL00007990
5. Baccalá, L. A., Sameshima, K., and Takahashi, D. (2007). "Generalized partial directed coherence, " in 15th International Conference on Digital Signal Processing IEEE (Wales). 163-166. doi: 10.1109/ICDSP.2007.4288544
6. Baillet, S., Mosher, J. C., and Leahy, R. M. (2001). Electromagnetic brain mapping. Signal Process. Mag. IEEE 18, 14-30. doi: 10.1109/79.962275
7. Blair, R. C., and Karniski, W. (1994). Distribution-Free Statistical Analyses of Surface and Volumetric Maps, Functional Neuroimaging: Technical Foundations, San Diego, CA: Academic Press.
8. Brillinger, D. R. (2001). Time Series: Data Analysis and Theory. Philadelphia, PA: Siam. doi: 10.1137/1.9780898719246
9. Chen, Y., Bressler, S. L., and Ding, M. (2006). Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data. J. Neurosci. Methods 150, 228-237. doi: 10.1016/j.jneumeth.2005.06.011
10. Faes, L., Erla, S., Porta, A., and Nollo, G. (2013). A framework for assessing frequency domain causality in physiological time series with instantaneous effects. Philos. Trans. A Math. Phys. Eng. Sci. 371:20110618. doi: 10.1098/rsta.2011.0618
11. Frei, E., Gamma, A., Pascual-Marqui, R., Lehmann, D., Hell, D., and Vollenweider, F. X. (2001). Localization of MDMA-induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA). Hum. Brain Mapp. 14, 152-165. doi: 10.1002/hbm.1049
12. Fuchs, M., Kastner, J., Wagner, M., Hawes, S., and Ebersole, J. S. (2002). A standardized boundary element method volume conductor model. Clin. Neurophysiol. 113, 702-712. doi: 10.1016/S1388-2457(02)00030-5
13. Geweke, J. F. (1984). Measures of conditional linear dependence and feedback between time series. J. Am. Stat. Assoc. 79, 907-915. doi: 10.1080/01621459.1984.10477110
14. Goldberger, A. L., Amaral, L. A., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., et al. (2000). PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation101, E215-E220. doi: 10.1161/01.CIR.101.23.e215
15. Gomez-Herrero, G., Atienza, M., Egiazarian, K., and Cantero, J. L. (2008). Measuring directional coupling between EEG sources. Neuroimage 43, 497-508. doi: 10.1016/j.neuroimage.2008.07.032
16. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424-438. doi: 10.2307/1912791
17. Helmholtz, H. (1853). Ueber einige Gesetze der Vertheilung elektrischer Ströme in körperlichen Leitern mit Anwendung auf die thierisch-elektrischen Versuche. Ann. Phys. 165, 211-233. doi: 10.1002/andp.18531650603
18. Jao, T., Vertes, P. E., Alexander-Bloch, A. F., Tang, I. N., Yu, Y. C., Chen, J. H., et al. (2013). Volitional eyes opening perturbs brain dynamics and functional connectivity regardless of light input. Neuroimage 69, 21-34. doi: 10.1016/j.neuroimage.2012.12.007
19. Jiménez, J. C., Biscay, R., and Montoto, O. (1995). Modeling the electroencephalogram by means of spatial spline smoothing and temporal autoregression Biol. Cybern. 72, 249-259. doi: 10.1007/BF00201488
20. Jurcak, V., Tsuzuki, D., and Dan, I. (2007). 10/20, 10/10, and 10/5 systems revisited: their validity as relative head-surface-based positioning systems. Neuroimage 34, 1600-1611. doi: 10.1016/j.neuroimage.2006.09.024
21. Kaminski, M., and Blinowska, K. (1991). A new method of the description of the information flow in the brain structures. Biol. Cybern. 65, 203-210. doi: 10.1007/BF00198091
22. Karniski, W., Blair, R. C., and Snider, A. D. (1994). An exact statistical method for comparing topographic maps, with any number of subjects and electrodes. Brain Topogr. 6, 203-210. doi: 10.1007/BF01187710
23. Klimesch, W. (2012). Alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn. Sci. 16, 606-617. doi: 10.1016/j.tics.2012.10.007
24. Knyazev, G. G., Slobodskoj-Plusnin, J. Y., Bocharov, A. V., and Pylkova, L. V. (2011). The default mode network and EEG alpha oscillations: an independent component analysis. Brain Res. 1402, 67-79. doi: 10.1016/j.brainres.2011.05.052
25. Lancaster, J. L., Woldorff, M. G., Parsons, L. M., Liotti, M., Freitas, C. S., Rainey, L., et al. (2000). Automated Talairach atlas labels for functional brain mapping. Hum. Brain Mapp. 10, 120-31. doi: 10.1002/1097-0193(200007)10:3%3C120::AID-HBM30%3E3.0.CO;2-8
26. Lehmann, D., Faber, P. L., Gianotti, L. R., Kochi, K., and Pascual-Marqui, R. D. (2006). Coherence and phase locking in the scalp EEG and between LORETA model sources, and microstates as putative mechanisms of brain temporo-spatial functional organization. J. Physiol. Paris 99, 29-36. doi: 10.1016/j.jphysparis.2005.06.005
27. Lehmann, D., Faber, P. L., Tei, S., Pascual-Marqui, R. D., Milz, P., and Kochi, K. (2012). Reduced functional connectivity between cortical sources in five meditation traditions detected with lagged coherence using EEG tomography. Neuroimage 60, 1574-1586. doi: 10.1016/j.neuroimage.2012.01.042
28. Lütkepohl, H. (2007). New Introduction to Multiple Time Series Analysis. New York, NY: Springer.
29. Marinazzo, D., Liao, W., Chen, H., and Stramaglia, S. (2011). Nonlinear connectivity by Granger causality. Neuroimage 58, 330-338. doi: 10.1016/j.neuroimage.2010.01.099
30. Mazziotta, J., Toga, A., Evans, A., Fox, P., Lancaster, J., Zilles, K., et al. (2001). A probabilistic atlas and reference system for the human brain: international consortium for brain mapping (ICBM). Philos. Trans. R. Soc. Lond. B Biol. Sci. 356, 1293-1322. doi: 10.1098/rstb.2001.0915
31. Mosher, J. C., and Leahy, R. M. (1998). Recursive MUSIC: a framework for EEG and MEG source localization. Biomed. Eng. IEEE Trans. 45, 1342-1354. doi: 10.1109/10.725331
32. Mosher, J. C., Lewis, P. S., and Leahy, R. M. (1992). Multiple dipole modeling and localization from spatio-temporal MEG data. Biomed. Eng. IEEE Trans. 39, 541-557. doi: 10.1109/10.141192
33. Nichols, T. E. (2012). Multiple testing corrections, nonparametric methods, and random field theory. Neuroimage62, 811-815. doi: 10.1016/j.neuroimage.2012.04.014
34. Nichols, T. E., and Holmes, A. P. (2002). Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum. Brain Mapp. 15, 1-25. doi: 10.1002/hbm.1058
35. Nolte, G., Ziehe, A., Nikulin, V. V., Schlogl, A., Kramer, N., Brismar, T., et al. (2008). Robustly estimating the flow direction of information in complex physical systems. Phys. Rev. Lett. 100:234101. doi: 10.1103/PhysRevLett.100.234101
36. Pascual-Marqui, R. (2007). Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. Avilable online at: http://arxiv.org/pdf/0710.3341
37. Pascual-Marqui, R., Biscay, R., Bosch-Bayard, J., Lehmann, D., Kochi, K., Yamada, N., et al. (2014). Isolated effective coherence (iCoh): causal information flow excluding indirect paths. arXiv preprint arXiv:1402.4887.
38. Pascual-Marqui, R. D. (2002). Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp. Clin. Pharmacol. 24(Suppl. D), 5-12.
39. Pascual-Marqui, R. D. (2009). "Theory of the EEG inverse problem, " in Quantitative EEG Analysis: Methods and Clinical Applications, Chapter 5, eds S. Tong and N. V Thakor (Boston, MA: Artech House). 121-140.
40. Pascual-Marqui, R. D., Lehmann, D., Koukkou, M., Kochi, K., Anderer, P., Saletu, B., et al. (2011). Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos. Trans. A Math. Phys. Eng. Sci. 369, 3768-3784. doi: 10.1098/rsta.2011.0081
41. Pascual-Marqui, R. D., Michel, C. M., and Lehmann, D. (1994). Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int. J. Psychophysiol. 18, 49-65. doi: 10.1016/0167-8760(84)90014-X
42. Pearl, J. (2000). Causality: Models, Reasoning and Inference. New York, NY: Cambridge Univ Press.
43. Plomp, G., Quairiaux, C., Michel, C. M., and Astolfi, L. (2014). The physiological plausibility of time-varying Granger-causal modeling: normalization and weighting by spectral power. Neuroimage. 97, 206-216. doi: 10.1016/j.neuroimage.2014.04.016
44. Radhakrishna Rao, C. (1981). A lemma on g-inverse of a matrix and computation of correlation coefficients in the singular case. Commun. Stat. Theor. Methods 10, 1-10. doi: 10.1080/03610928108828015
45. Saito, Y., and Harashima, H. (1981). "Tracking of information within multichannel {EEG} record causal analysis in {EEG}, " in Recent Advances in {EEG} and {EMG} Data Processing, eds N. Yamaguchi and K. Fujisawa (Amsterdam: Elsevier). 133-146.
46. Schalk, G., McFarland, D. J., Hinterberger, T., Birbaumer, N., and Wolpaw, J. R. (2004). BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE Trans. Biomed. Eng. 51, 1034-1043. doi: 10.1109/TBME.2004.827072
47. Schelter, B., Timmer, J., and Eichler, M. (2009). Assessing the strength of directed influences among neural signals using renormalized partial directed coherence. J. Neurosci. Methods 179, 121-130. doi: 10.1016/j.jneumeth.2009.01.006
48. Sigala, R., Haufe, S., Roy, D., Dinse, H. R., and Ritter, P. (2014). The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models. Front. Comput. Neurosci. 8:36. doi: 10.3389/fncom.2014.00036
49. Valdes-Sosa, P. A., Roebroeck, A., Daunizeau, J., and Friston, K. (2011). Effective connectivity: influence, causality and biophysical modeling. Neuroimage 58, 339-361. doi: 10.1016/j.neuroimage.2011.03.058
50. Valdes-Sosa, P. A., Sanchez-Bornot, J. M., Lage-Castellanos, A., Vega-Hernandez, M., Bosch-Bayard, J., Melie-Garcia, L., et al. (2005). Estimating brain functional connectivity with sparse multivariate autoregression. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360, 969-981. doi: 10.1098/rstb.2005.1654
51. Weiss, S. A., McKhann, G. Jr. Goodman, R., Emerson, R. G., Trevelyan, A., Bikson, M., et al. (2013). Field effects and ictal synchronization: insights from in homine observations. Front. Hum. Neurosci. 7:828. doi: 10.3389/fnhum.2013.00828
52. Wibral, M., Vicente, R., and Lizier, J. T. (2014). Directed Information Measures in Neuroscience. Heidelberg: Springer. doi: 10.1007/978-3-642-54474-3
53. Yamashita, O., Sadato, N., Okada, T., and Ozaki, T. (2005). Evaluating frequency-wise directed connectivity of BOLD signals applying relative power contribution with the linear multivariate time-series models. Neuroimage 25, 478-490. doi: 10.1016/j.neuroimage.2004.11.042