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Analysis of the Local Dynamics of Interictal Discharge Propagation Using a Traveling Wave Model

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Epilepsy is one of the most common neurological diseases in the world, with about 30% of cases not amenable to pharmacological intervention and potentially requiring surgical intervention. The process of localizing the epileptogenic zone – the area associated with seizure initiation in patients with focal epilepsy – involves examining different areas of the brain for the presence of interictal discharges. In this paper, we propose a new methodology for noninvasive investigation of the fi ne spatiotemporal structure of interictal discharges observed on the magnetoencephalogram (MEG). We applied a traveling wave model to regularize the inverse MEG problem. The algorithm represents the neural activity generating an interictal discharge as a superimposition of local waves propagating along radial paths and generated by a single point source. The LASSO method with positive coeffi cients was applied to determine the combination of waves generated with different parameters giving the best match with the recorded MEG for each discharge. The properties of the algorithm were analyzed using realistic simulations of MEG data. The method was then applied to analysis of MEG data from three patients with drug-resistant multifocal epilepsy. Some of the discharges yielded wave-like patterns with clear propagation dynamics, while for others, the observed activity could not be explained by the wave superimposition model. Moreover, discharges with clear propagation dynamics showed marked spatial clustering correlating with the epileptogenic zones described in the case histories of two of the three patients.

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References

  • Adrian, E. D. and Matthews, B. H. C., “The interpretation of potential waves in the cortex,” J. Physiol., 81, No. 4, 440–471 (1934).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Adrian, E. D. and Yamagiwa, K., “The origin of the Berger rhythm,” Brain, 58, No. 3, 323–351 (1935).

    Article  Google Scholar 

  • Bahramisharif, A., van Gerven, M. A. J., Aarnoutse, E. J., et al., “Propagating neocortical gamma bursts are coordinated by traveling alpha waves,” J. Neurosci., 33, No. 48, 18,849–18,854 (2013).

  • Chamberlain, A., Viventi, J., Blanco, J., et al., “Millimeterscale epileptiform spike patterns and their relationship to seizures,” in: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2011), pp. 761–764.

  • Chizhov, A. V., Zefirov, A. V., Amakhin, D. V., et al., “Minimal model of interictal and ictal discharges Epileptor-2,” PLoS Comput. Biol., 14, No. 5, e1006186 (2018).

  • Donders, F. C., “On the speed of mental processes,” Acta Psychol., 30, 412–431 (1969).

    Article  CAS  Google Scholar 

  • Ermentrout, G. B. and Kleinfeld, D., “Traveling electrical waves in cortex,” Neuron, 29, No. 1, 33–44 (2001).

    Article  CAS  PubMed  Google Scholar 

  • Ferezou, I., Haiss, F., Gentet, L. J., et al., “Spatiotemporal dynamics of cortical sensorimotor integration in behaving mice,” Neuron, 56, No. 5, 907–923 (2007).

    Article  CAS  PubMed  Google Scholar 

  • Fischl, B., “FreeSurfer,” NeuroImage, 62, No. 2, 774–781 (2012).

    Article  PubMed  Google Scholar 

  • Freeman, W. J. and Barrie, J. M., “Analysis of spatial patterns of phase in neocortical gamma EEGs in rabbit,” J. Neurophysiol., 84, No. 3, 1266–1278 (2000).

    Article  CAS  PubMed  Google Scholar 

  • Fries, P., “A mechanism for cognitive dynamics: neuronal communication through neuronal coherence,” Trends Cogn. Sci., 9, No. 10, 474–480 (2005).

    Article  PubMed  Google Scholar 

  • Fries, P., “Rhythms for cognition: Communication through coherence,” Neuron, 88, No. 1, 220–235 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Giannini, M., Alexander, D. M., Nikolaev, A. R., and van Leeuwen, C., “Large-scale traveling waves in EEG activity following eye movement,” Brain Topogr., 31, No. 4, 608–622 (2018).

    Article  PubMed  Google Scholar 

  • Gramfort, A., Luessi, M., Larson, E., et al., “MEG and EEG data analysis with MNE-Python,” Front. Neurosci., 7, No. 267, 1–13 (2013).

    Google Scholar 

  • Hamalainen, M., Hari, R., Ilmoniemi, R. J., et al., “Magnetoencephalography – theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys., 65, No. 2 (1993).

  • Hangya, B., Tihanyi, B. T., Entz, L., et al., “Complex propagation patterns characterize human cortical activity during slow-wave sleep,” J. Neurosci., 31, No. 24, 8770–8779 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hindriks, R., van Putten, M., and Deco, G., “Intra-cortical propagation of EEG alpha oscillations,” NeuroImage, 103, 444–453 (2014).

    Article  PubMed  Google Scholar 

  • Huang, X., Troy, W. C., Yang, Q., et al., “Spiral waves in disinhibited mammalian neocortex,” J. Neurosci., 24, No. 44, 9897–9902 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Komoltsev, I. G., Sinkin, M. V., Volkova, A. A., et al., “A translational study on acute traumatic brain injury: high incidence of epileptiform activity on human and rat electrocorticograms and histological correlates in rats,” Brain Sci., 10, No. 9), 570 (2020).

  • Koptelova, A., Bikmullina, R., Medvedovsky, M., et al., “Ictal and interictal MEG in pediatric patients with tuberous sclerosis and drug resistant epilepsy,” Epilepsy Res., 140, 162–165 (2018).

    Article  CAS  PubMed  Google Scholar 

  • Krylov, V. V., Gekht, A. B., Trifonov, I. S., et al., “Outcomes of the surgical treatment of patients with drug-resistant forms of epilepsy,” Zh. Nevrol. Psikhiatr., 119, No. 9–2, 13–18 (2016).

    Article  Google Scholar 

  • Lubenov, E. V. and Siapas, A. G., “Hippocampal theta oscillations are travelling waves,” Nature, 459, No. 7246, 534–539 (2009).

    Article  CAS  PubMed  Google Scholar 

  • Mak-McCully, R. A., Rosen, B. Q., Rolland, M., et al., “Distribution, amplitude, incidence, co-occurrence, and propagation of human k-complexes in focal transcortical recordings,” eNeuro, 2, No. 4, Eneuro. 0028-15.2015 (2015).

  • Martinet, L.-E., Fiddyment, G., Madsen, J. R., et al., “Human seizures couple across spatial scales through travelling wave dynamics,” Nat. Commun., 8, No. 1) (2017).

  • Massimini, M., “The sleep slow oscillation as a traveling wave,” J. Neurosci., 24, No. 31, 6862–6870 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mosher, J. C. and Leahy, R. M., “Source localization using recursively applied and projected (RAP) MUSIC,” IEEE Trans. Signal Proc., 47, No. 2, 332–340 (1999).

    Article  Google Scholar 

  • Muller, L., Chavane, F., Reynolds, J., and Sejnowski, T. J., “Cortical travelling waves: mechanisms and computational principles,” Nat. Rev. Neurosci., 19, No. 5, 255–268 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Muller, L., Reynaud, A., Chavane, F., and Destexhe, A., “The stimulus- evoked population response in visual cortex of awake monkey is a propagating wave,” Nat. Commun., 5, No. 1 (2014).

  • Nasiotis, K., Clavagnier, S., Baillet, S., and Pack, C. C., “High-resolution retinotopic maps estimated with magnetoencephalography,” Neuro- Image, 145, 107–117 (2017).

    PubMed  Google Scholar 

  • Oostenveld, R., Fries, P., Maris, E., and Schoffelen, J. M., “FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data,” Computat. Intell. Neurosci., 2011, Article ID 156869 (2011).

    Google Scholar 

  • Ossadtchi, A., Baillet, S., Mosher, J. C., et al., “Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatiotemporal clustering,” Clin. Neurophysiol., 115, No. 3, 508–522 (2004).

    Article  CAS  PubMed  Google Scholar 

  • Ossadtchi, A., Mosher, J. C., Sutherling, W. W., et al., “Hidden Markov modelling of spike propagation from interictal MEG data,” Phys. Med. Biol., 50, No. 14, 3447–3469 (2005).

    Article  CAS  PubMed  Google Scholar 

  • Patten, T. M., Rennie, C. J., Robinson, P. A., and Gong, P., “Human cortical traveling waves: Dynamical properties and correlations with responses,” PLoS One, 7, No. 6, e38392 (2012).

  • Petrov, Y., “Harmony: EEG/MEG linear inverse source reconstruction in the anatomical basis of spherical harmonics,” PLoS One, 7, No. 10, e44439 (2012).

  • Prechtl, J. C., Cohen, L. B., Pesaran, B., et al., “Visual stimuli induce waves of electrical activity in turtle cortex,” Proc. Natl. Acad. Sci. USA, 94, No. 14, 7621–7626 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Stead, M., Bower, M., Brinkmann, B. H., et al., “Microseizures and the spatiotemporal scales of human partial epilepsy,” Brain, 133, No. 9, 2789–2797 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  • Tadel, F., Baillet, S., Mosher, J., et al., “Brainstorm: A user-friendly application for MEG/EEG analysis,” Computat. Intell. Neurosci., (2011).

  • Tibshirani, R., “Regression shrinkage and selection via the lasso,” J. R. Stat. Soc., 58, No. 1, 267–288 (1996).

    Google Scholar 

  • Tomlinson, S. B., Bermudez, C., Conley, C., et al., “Spatiotemporal mapping of interictal spike propagation: A novel methodology applied to pediatric intracranial EEG recordings,” Front. Neurol., 7, 229 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • Wu, J.-Y., Huang, X., and Zhang, C., “Propagating waves of activity in the neocortex: What they are, what they do,” Neuroscientist, 14, No. 5, 487–502 (2007).

    Article  Google Scholar 

  • Zhang, H., Watrous, A. J., Patel, A., and Jacobs, J., “Theta and alpha oscillations are traveling waves in the human neocortex,” Neuron, 98, No. 6, 1269–1281. e4 (2018).

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Correspondence to A. E. Ossadtchi.

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Translated from Zhurnal Vysshei Nervnoi Deyatel’nosti imeni I. P. Pavlova, Vol. 72, No. 3, pp. 370–386, May–June, 2022.

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Kuznetsova, A.A., Ossadtchi, A.E. Analysis of the Local Dynamics of Interictal Discharge Propagation Using a Traveling Wave Model. Neurosci Behav Physi 52, 1436–1447 (2022). https://doi.org/10.1007/s11055-023-01375-y

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