×

Interaction between synaptic inhibition and glial-potassium dynamics leads to diverse seizure transition modes in biophysical models of human focal seizures. (English) Zbl 1382.92155

Summary: How focal seizures initiate and evolve in human neocortex remains a fundamental problem in neuroscience. Here, we use biophysical neuronal network models of neocortical patches to study how the interaction between inhibition and extracellular potassium \(([K^+]_o)\) dynamics may contribute to different types of focal seizures. Three main types of propagated focal seizures observed in recent intracortical microelectrode recordings in humans were modelled: seizures characterized by sustained (\(\sim 30-60\) Hz) gamma local field potential (LFP) oscillations; seizures where the onset in the propagated site consisted of LFP spikes that later evolved into rhythmic (\(\sim 2-3\) Hz) spike-wave complexes (SWCs); and seizures where a brief stage of low-amplitude fast-oscillation (\(\sim 10-20\) Hz) LFPs preceded the SWC activity. Our findings are fourfold: (1) The interaction between elevated \([K^+]_o\) (due to abnormal potassium buffering by glial cells) and the strength of synaptic inhibition plays a predominant role in shaping these three types of seizures. (2) Strengthening of inhibition leads to the onset of sustained narrowband gamma seizures. (3) Transition into SWC seizures is obtained either by the weakening of inhibitory synapses, or by a transient strengthening followed by an inhibitory breakdown (e.g. GABA depletion). This reduction or breakdown of inhibition among fast-spiking (FS) inhibitory interneurons increases their spiking activity and leads them eventually into depolarization block. Ictal spike-wave discharges in the model are then sustained solely by pyramidal neurons. (4) FS cell dynamics are also critical for seizures where the evolution into SWC activity is preceded by low-amplitude fast oscillations. Different levels of elevated \([K^+]_o\) were important for transitions into and maintenance of sustained gamma oscillations and SWC discharges. Overall, our modelling study predicts that the interaction between inhibitory interneurons and \([K^+]_o\) glial buffering under abnormal conditions may explain different types of ictal transitions and dynamics during propagated seizures in human focal epilepsy.

MSC:

92C45 Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.)
92C50 Medical applications (general)

Software:

XPPAUT
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Ahmed, O. J., Kramer, M. A., Truccolo, W., Naftulin, J. S., Donoghue, J. A., Eskandar, E. N., Cosgrove, G. R., Blum, A. S., Potter, N. S., Hochberg, L. R., & Cash, S. S. (2014). Inhibitory single neuron control of seizures and epileptic traveling waves in humans. BMC Neuroscience, 15(Suppl 1), F3. · doi:10.1186/1471-2202-15-S1-F3
[2] Alfonsa, H., Merricks, E. M., Codadu, N. K., Cunningham, M. O., Deisseroth, K., Racca, C., & Trevelyan, A. J. (2015). The contribution of raised intraneuronal chloride to epileptic network activity. The Journal of Neuroscience, 35(20), 7715-7726. · doi:10.1523/JNEUROSCI.4105-14.2015
[3] Anderson, W. S., Kudela, P., Cho, J., Bergey, G. K., & Franaszczuk, P. J. (2007). Studies of stimulus parameters for seizure disruption using neural network simulations. Biological Cybernetics, 97, 173-194. · Zbl 1122.92005 · doi:10.1007/s00422-007-0166-0
[4] Anderson, W., Azhar, F., Kudela, P., Bergey, G., & Franaszczuk, P. (2012). Epileptic seizures from abnormal networks: why some seizures defy predictability. Epilepsy Research, 99, 202-213. · doi:10.1016/j.eplepsyres.2011.11.006
[5] Bazhenov, M., Timofeev, I., Steriade, M., & Sejnowski, T. J. (2004). Potassium model for slow (2-3 Hz) in vivo neocortical paroxysmal oscillations. Journal of Neurophysiology, 92, 1116-1132. · doi:10.1152/jn.00529.2003
[6] Brunel, N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of Computational Neuroscience, 8, 183-208. · Zbl 1036.92008 · doi:10.1023/A:1008925309027
[7] Brunel, N., & Wang, X. J. (2003). What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance. Journal of Neurophysiology, 90, 415-430. · doi:10.1152/jn.01095.2002
[8] Buxhoeveden, D. P., & Casanova, M. F. (2002). The minicolumn hypothesis in neuroscience. Brain: A Journal of Neurology, 125, 935-951. · doi:10.1093/brain/awf110
[9] Cammarota, M., Losi, G., Chiavegato, A., Zonta, M., & Carmignoto, G. (2013). Fast spiking interneuron control of seizure propagation in a cortical slice model of focal epilepsy. The Journal of Physiology, 591(4), 807-822. · doi:10.1113/jphysiol.2012.238154
[10] Cressman, J.R. Jr, Ullah, G., Ziburkus, J., Schiff, S., & Barreto, E. (2009). The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: I. Single neuron dyamics. Journal of Computational Neuroscience, 26, 159-170. · doi:10.1007/s10827-008-0132-4
[11] D’Antuono, M., Louvel, J., Köhling, R., Mattia, D., Bernasconi, A., Olivier, A., Turak, B., Devaux, A., Pumain, R., & Avoli, M. (2004). Gabaa receptor-dependent synchronization leads to ictogenesis in the human dysplastic cortex. Brain: A Journal of Neurology, 127, 1626-1640. · doi:10.1093/brain/awh181
[12] Dur-e-Ahmad, M., Nicola, W., Campbell, S., & Skinner, F. (2012). Network bursting using experimentally constrained single compartment CA3 hippocampal neuron models with adaptation. Journal of Computational Neuroscience, 33(1), 21-40. · Zbl 1446.92043 · doi:10.1007/s10827-011-0372-6
[13] Ermentrout, B. (2002). Simulating, analyzing, and animating dynamical systems: A guide to XPPAUT for researchers and students (SIAM). · Zbl 1003.68738
[14] Ferguson, K., Njap, F., Nicola, W., Skinner, F., & Campbell, S. (2015). Examining the limits of cellular adaptation bursting mechanisms in biologically-based excitatory networks of the hippocampus. Journal of Computational Neuroscience, 39, 289-309. · Zbl 1382.92052 · doi:10.1007/s10827-015-0577-1
[15] Freyer, F., Aquino, K., Robinson, P. A., Ritter, P., & Breakspear, M. (2009). Bistability and non-Gaussian fluctuations in spontaneous cortical activity. The Journal of Neuroscience, 29(26), 8512-8524. · doi:10.1523/JNEUROSCI.0754-09.2009
[16] Fröhlich, F., Bazhenov, M., Iragui-Madoz, V., & Sejnowski, T. J. (2008). Potassium dynamics in the epileptic cortex: New insights on an old topic. The Neuroscientist, 14, 422. · doi:10.1177/1073858408317955
[17] Fröhlich, F., Sejnowski, T. J., & Bazhenov, M. (2010). Network bistability mediates spontaneous transitions between normal and pathological brain states. The Journal of Neuroscience, 30(32), 10734-10743. · doi:10.1523/JNEUROSCI.1239-10.2010
[18] González-Ramírez, L.R., Ahmed, O. J., Cash, S. S., Wayne, C. E., & Kramer, M. A. (2015). A biologically constrained, mathematical model of cortical wave propagation preceding seizure termination. PLoS Computational Biology, 11(2), e1004065. · doi:10.1371/journal.pcbi.1004065
[19] Grasse, D., Karunakaran, S., & Moxon, K. (2013). Neuronal synchrony and the transition to spontaneous seizures. Experimental Neurology, 248, 72-84. · doi:10.1016/j.expneurol.2013.05.004
[20] He, B. J. (2014). Scale-free brain activity: past, present, and future. Trends in Cognitive Sciences, 18, 480-487. · doi:10.1016/j.tics.2014.04.003
[21] Ho, E. C. Y., Strüber, M., Bartos, M., Zhang, L., & Skinner, F. K. (2012). Inhibitory networks of fast-spiking interneurons generate slow population activities due to excitatory fluctuations and network multistability. The Journal of Neuroscience, 32(29), 9931-9946. · doi:10.1523/JNEUROSCI.5446-11.2012
[22] Ho, E. C. Y., Eubanks, J. H., Zhang, L., & Skinner, F. K. (2014). Network models predict that reduced excitatory fluctuations can give rise to hippocampal network hyper-excitability in meCP2-null mice. PloS One, 9, e91148. · doi:10.1371/journal.pone.0091148
[23] Hübel, N., Scholl, E., & Dahlem, M. A. (2014). Bistable dynamics underlying excitability of ion homeostasis in neuron models. PLoS Computational Biology, 10, e1003551. · doi:10.1371/journal.pcbi.1003551
[24] Ingram, J., Zhang, C., Cressman, J., Hazra, A., Wei, Y., Koo, Y., žIburkus, J., Kopelman, R., Xu, J., & Schiff, S. (2014). Oxygen and seizure dynamics: I. experiments. Journal of Neurophysiology, 112, 205-212. · doi:10.1152/jn.00540.2013
[25] Jirsa, V. K., Stacey, W. C., Quilichini, P. P., Ivanov, A. I., & Bernard, C. (2014). On the nature of seizure dynamics. Brain: A Journal of Neurology, 133, 2210-2230. · doi:10.1093/brain/awu133
[26] Kager, H., Wadman, W. J., & Somjen, G. G. (2000). Simulated seizures and spreading depression in a neuron model incorporating interstitial space and ion concentrations. Journal of Neurophysiology, 84, 495-512.
[27] Kim, C., & Nykamp, D. (2014). Dynamics of a network of excitatory and inhibitory neurons induced by depolarization block. BMC Neuroscience, 15(Suppl 1), P76. · doi:10.1186/1471-2202-15-S1-P76
[28] Kramer, M. A., Truccolo, W., Eden, U. T., Lepage, K. Q., Hochberg, L. R., Eskandar, E. N., Madsen, J. R., Lee, J. W., Maheshwari, A., Halgren, E., Chu, C. J., & Cash, S. S. (2012). Human seizures self-terminate across spatial scales via a critical transition. Proc Natl Acad Sci U S A, 109, 21116-21121. · doi:10.1073/pnas.1210047110
[29] Krishnan, G. P., & Bazhenov, M. (2011). Ionic dynamics mediate spontaneous termination of seizures and postictal depression state. The Journal of Neuroscience, 31(24), 8870-8882. · doi:10.1523/JNEUROSCI.6200-10.2011
[30] Krishnan, G., Filatov, G., & Bazhenov, M. (2013). Dynamics of high-frequency synchronization during seizures. Journal of Neurophysiology, 109, 2423-2437. · doi:10.1152/jn.00761.2012
[31] Lado, F. A., & Moshé, S.L. (2008). How do seizures stop? Epilepsia, 49, 1651-1664. · doi:10.1111/j.1528-1167.2008.01669.x
[32] Lu, Y., Truccolo, W., Wagner, F., Vargas-Irwin, C., Ozden, I., Zimmermann, J., May, T., Agha, N., Wang, J., & Nurmikko, A. (2015). Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex. Journal of Neurophysiology, 113, 3574-3587. · doi:10.1152/jn.00792.2014
[33] Naze, S., Bernard, C., & Jirsa, V. (2015). Computational modeling of seizure dynamics using coupled neuronal networks: Factors shaping epileptiform activity. PLoS Computational Biology, 11, e1004209. · doi:10.1371/journal.pcbi.1004209
[34] Nicola, W., & Campbell, S. (2013a). Bifurcations of large networks of two-dimensional integrate and fire neurons. Journal of Computational Neuroscience, 35, 87-108. · Zbl 1276.92018
[35] Nicola, W., & Campbell, S. A. (2013b). Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons. Frontiers in Computational Neuroscience, 7(184), 1-25.
[36] Nicola, W., & Campbell, S. (2014). Non-smooth bifurcations of mean field systems of two-dimensional integrate and fire neurons. arXiv:1408.4767.
[37] Park, E. H., & Durand, D. M. (2006). Role of potassium lateral diffusion in non-synaptic epilepsy: a computational study. Journal of Theoretical Biology, 238, 666-682. · Zbl 1445.92081 · doi:10.1016/j.jtbi.2005.06.015
[38] Paz, J., & Huguenard, J. R. (2015). Microcircuits and their interactions in epilepsy: is the focus out of focus? Nature Neuroscience, 18, 351-359. · doi:10.1038/nn.3950
[39] Perucca, P., Dubeau, F., & Gotman, J. (2014). Intracranial electroencephalographic seizure-onset patterns: effect of underlying pathology. Brain: A Journal of Neurology, 137, 183-196. · doi:10.1093/brain/awt299
[40] Richardson, K., Fanselow, E., & Connors, B. (2008). Neocortical anatomy and physiology. In Engel, J., & Pedley, T. (Eds.) Epilepsy: A Comprehensive Textbook (pp. 323-336): Lippincott-Williams & Wilkins.
[41] Rudolph, M., Piwkowska, Z., Badoual, M., Bal, T., & Destexhe, A. (2004). A method to estimate synaptic conductances from membrane potential fluctuations. Journal of Neurophysiology, 91(6), 2884-2896. · doi:10.1152/jn.01223.2003
[42] Sasaki, T., Matsuki, N., & Ikegaya, Y. (2007). Metastability of active CA3 networks. The Journal of Neuroscience, 27(3), 517-528. · doi:10.1523/JNEUROSCI.4514-06.2007
[43] Schevon, C. A., Weiss, S. A., McKhann, G. Jr, Goodman, R. R., Yuste, R., Emerson, R. G., & Trevelyan, A. J. (2012). Evidence Of an inhibitory restraint of seizure activity in humans. Nature Communications, 3(1060), 1-11.
[44] Skinner, F. K. (2006). Conductance-based models. Scholarpedia 1:1408 revision #125663. · Zbl 1122.92005
[45] Skinner, F. K., Zhang, L., Perez-Velazquez, J. L., & Carlen, P. L. (1999). Bursting in inhibitory interneuronal networks: a role for gap-junctional coupling. Journal of Neurophysiology, 81, 1274- 1283.
[46] Sritharan, D., & Sarma, S. V. (2014). Fragility in dynamic networks: application to neural networks in the epileptic cortex. Neural Computation, 26(10), 2294-2327. · Zbl 1305.92020 · doi:10.1162/NECO_a_00644
[47] Thurman, D. J., Beghi, E., Begley, C. E., Berg, A. T., Buchhalter, J. R., Ding, D., Hesdorffer, D. C., Hauser, W. A., Kazis, L., Kobau, R., Kroner, B., Labiner, D., Liow, K., Logroscino, G., Medina, M. T., Newton, C. R., Parko, K., Paschal, A., Preux, P. M., Sander, J. W., Selassie, A., Theodore, W., Tomson, T., & Wiebe, S. (2011). Standards for epidemiologic studies and surveillance of epilepsy. Epilepsia, 52, 2-26. · doi:10.1111/j.1528-1167.2011.03121.x
[48] Touboul, J. (2008). Bifurcation analysis of a general class of nonlinear integrate-and-fire neurons. SIAM Journal of Applied Mathematics, 68, 1045-1079. · Zbl 1149.34027 · doi:10.1137/070687268
[49] Traub, R. D., Kopell, N., Bibbig, A., Buhl, E. H., LeBeau, F. E. N., & Whittington, M. A. (2001). Gap junctions between interneuron dendrites can enhance synchrony of gamma oscillations in distributed networks. The Journal of Neuroscience, 21(23), 9478-9486.
[50] Traub, R. D., Contreras, D., Cunningham, M. O., Murray, H., LeBeau, F. E. N., Roopun, A., Bibbig, A., Wilent, W. B., Higley, M. J., & Whittington, M. A. (2005). Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. Journal of Neurophysiology, 93(4), 2194-2232. · doi:10.1152/jn.00983.2004
[51] Trevelyan, A. J., Sussillo, D., Watson, B. O., & Yuste, R. (2006). Modular propagation of epileptiform activity: evidence for an inhibitory veto in neocortex. The Journal of Neuroscience, 26(48), 12447-12455. · doi:10.1523/JNEUROSCI.2787-06.2006
[52] Truccolo, W., Donoghue, J. A., Hochberg, L. R., Eskandar, E. N., Madsen, J. R., Anderson, W. S., Brown, E. N., Halgren, E., & Cash, S. S. (2011). Single-neuron dynamics in human focal epilepsy. Nature Neuroscience, 14(5), 635-643. · doi:10.1038/nn.2782
[53] Truccolo, W., Ahmed, O. J., Harrison, M. T., Eskandar, E. N., Cosgrove, G. R., Madsen, J. R., Blum, A. S., Potter, N. S., Hochberg, L. R., & Cash, S. S. (2014). Neuronal ensemble synchrony during human focal seizures. The Journal of Neuroscience, 34(30), 9927-9944. · doi:10.1523/JNEUROSCI.4567-13.2014
[54] Ullah, G., Cressman, J.R. Jr, Barreto, E., & Schiff, S. J. (2009). The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: II. Network and glial dynamics. Journal of Computational Neuroscience, 29, 171-183. · doi:10.1007/s10827-008-0130-6
[55] Uva, L., Breschi, G. L., Gnatkovsky, V., Taverna, S., & de Curtis, M. (2015). Synchronous inhibitory potentials precede seizure-like events in acute models of focal limbic seizures. The Journal of Neuroscience, 35, 3048-3055. · doi:10.1523/JNEUROSCI.3692-14.2015
[56] Van Ooyen, A., Van Pelt, J., Corner, M. A., & Lopes da Silva, F. H. (1992). The emergence of long-lasting transients of activity in simple neural networks. Biological Cybernetics, 67, 269-277. · doi:10.1007/BF00204400
[57] Van Vreeswijk, C., & Hansel, D. (2001). Patterns of synchrony in neural networks with spike adaptation. Neural Computation, 13, 959-992. · Zbl 1004.92011 · doi:10.1162/08997660151134280
[58] Wagner, F., Eskandar, E., Cosgrove, G., Madsen, J., Blum, A., Potter, N., Hochberg, L., Cash, S., & Truccolo, W. (2015). Microscale spatiotemporal dynamics during neocortical propagation of human focal seizures. Neuroimage, 122, 114-130. · doi:10.1016/j.neuroimage.2015.08.019
[59] Wang, Y., Goodfellow, M., Taylor, P. N., & Baier, G. (2014). Dynamic mechanisms of neocortical focal seizure onset. PLoS Computational Biology, 10, e1003787. · doi:10.1371/journal.pcbi.1003787
[60] Wang, X. J., & Buzsáki, G. (1996). Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. The Journal of Neuroscience, 16(20), 6402-6413.
[61] Wei, Y., Ullah, G., & Schiff, S. (2014a). Oxygen and seizure dynamics: II. computational modeling. Journal of Neurophysiology, 112, 213-223.
[62] Wei, Y., Ullah, G., & Schiff, S. (2014b). Unification of neuronal spikes, seizures, and spreading depression. The Journal of Neuroscience, 34, 11733-11743.
[63] Wen, B., Qian, H., Feng, J., Ge, R. J., Xu, X., Cui, Z. Q., Zhu, R. Y., Pan, L. S., Lin, Z. P., & Wang, J. H. (2015). A portion of inhibitory neurons in human temporal lobe epilepsy are functionally upregulated: an endogenous mechanism for seizure termination. CNS Neuroscience & Therapeutics, 21, 204-214. · doi:10.1111/cns.12336
[64] Zhang, Z. J., Koifman, J., Shin, D. S., Ye, H., Florez, C. M., Zhang, L., Valiante, T. A., & Carlen, P. L. (2012). Transition to seizure: Ictal discharge is preceded by exhausted presynaptic GABA release in the hippocampal CA3 region. The Journal of Neuroscience, 32(7), 2499-2512. · doi:10.1523/JNEUROSCI.4247-11.2012
[65] žiburkus, J., Cressman, J., Barreto, E., & Schiff, S. (2006). Interneuron and pyramidal cell interplay during in vitro seizure-like events. Journal of Neurophysiology, 95, 3948-3954. · doi:10.1152/jn.01378.2005
[66] žiburkus, J., Cressman, J. R., & Schiff, S. J. (2013). Seizures as imbalanced up states: excitatory and inhibitory conductances during seizure-like events. Journal of Neurophysiology, 109, 1296-1306. · doi:10.1152/jn.00232.2012
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.