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Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks

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Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks. / Goncharenko, Iuliia; Kros, Lieke; Maex, Reinoud; Davey, Neil; Metzner, Christoph; De Zeeuw, C.I.; Hoebeek, F.E.; Steuber, Volker.

In: BMC Neuroscience, Vol. 20, No. (Suppl 1), 56, 14.11.2019, p. 157-157.

Research output: Contribution to journalMeeting abstractpeer-review

Harvard

Goncharenko, I, Kros, L, Maex, R, Davey, N, Metzner, C, De Zeeuw, CI, Hoebeek, FE & Steuber, V 2019, 'Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks', BMC Neuroscience, vol. 20, no. (Suppl 1), 56, pp. 157-157. https://doi.org/10.1186/s12868-019-0538-0

APA

Goncharenko, I., Kros, L., Maex, R., Davey, N., Metzner, C., De Zeeuw, C. I., Hoebeek, F. E., & Steuber, V. (2019). Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks. BMC Neuroscience, 20((Suppl 1)), 157-157. [56]. https://doi.org/10.1186/s12868-019-0538-0

Vancouver

Goncharenko I, Kros L, Maex R, Davey N, Metzner C, De Zeeuw CI et al. Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks. BMC Neuroscience. 2019 Nov 14;20((Suppl 1)):157-157. 56. https://doi.org/10.1186/s12868-019-0538-0

Author

Goncharenko, Iuliia ; Kros, Lieke ; Maex, Reinoud ; Davey, Neil ; Metzner, Christoph ; De Zeeuw, C.I. ; Hoebeek, F.E. ; Steuber, Volker. / Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks. In: BMC Neuroscience. 2019 ; Vol. 20, No. (Suppl 1). pp. 157-157.

Bibtex

@article{03761ea7461f4c7c9ceeb80ccf533d61,
title = "Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks",
abstract = "Absence seizures are the most common form of epilepsy in children. They start and finish abruptly, last for 10–20 seconds and can be detected by generalised spike-and-wave discharges (GSWDs) in the electroencephalogram. These GSWDs are based on neuronal oscillations in thalamocortical networks, which can be caused by excessive inhibition in the thalamus or excessive cortical activity. Absence seizures can be triggered by switching of the normal asynchronous neuronal activity in thalamocortical networks to synchronised oscillations, and terminated by the reverse process, switching from synchronised oscillations to asynchronous activity.Experimental studies have shown that thalamic stimulation can disrupt oscillatory activity in thalamocortical networks. More recently, it was also found that optogenetic activation of neurons in the cerebellar nuclei (CN) can stop epileptic absence seizures and reset the oscillatory activity, for example in a closed loop system [1]. However, the underlying mechanism of the termination of absence seizures by CN stimulation is not yet clear.To investigate the mechanism of the termination of absence seizures by thalamic input from the CN we used computer simulations. We simulate a thalamocortical network model with adaptive exponential integrate-and-fire neurons, displaying complex intrinsic properties such as low-threshold spiking, regular spiking, fast spiking and adaptation [2]. The network activity can exhibit oscillatory or asynchronous irregular (AI) dynamics, depending on the time constants of the inhibitory synaptic conductance, which are 5 ms (AI) and 15 ms (oscillatory), respectively. An increase in the inhibitory decay time constant reflects a change from GABAA dominated inhibition to more GABAB, which can result in GSWDs, given that the “wave” components of GSWDs are related to slow GABAB -mediated K+ currents [3].We provide CN input to all thalamocortical neurons to analyse the mechanism of reverting from abnormal oscillatory activity to the normal AI state. Our results confirm that input from the CN can control oscillatory activity in thalamocortical networks. Furthermore, they show that the effectiveness of this input exhibits phase-dependence. In our simulations, CN input terminates epileptic absence seizures most effectively when it arrives at the peak of GSWDs, while seizure termination is least efficient for input between the GSWD bursts. This finding is potentially relevant for therapeutic applications of CN stimulation to terminate seizures. However, the simulations in silico did not take several biological factors such as indirect pathways from the CN to the thalamus into account that may explain differences with animal models of epilepsy [1].",
author = "Iuliia Goncharenko and Lieke Kros and Reinoud Maex and Neil Davey and Christoph Metzner and {De Zeeuw}, C.I. and F.E. Hoebeek and Volker Steuber",
note = "{\textcopyright} The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.; 28th Annual Computational Neuroscience Meeting, CNS*2019 ; Conference date: 13-07-2019 Through 17-07-2019",
year = "2019",
month = nov,
day = "14",
doi = "10.1186/s12868-019-0538-0",
language = "English",
volume = "20",
pages = "157--157",
journal = "BMC Neuroscience",
issn = "1471-2202",
publisher = "BioMed Central",
number = "(Suppl 1)",
url = "https://www.cnsorg.org/cns-2019",

}

RIS

TY - JOUR

T1 - Phase dependence of the termination of absence seizures by cerebellar input to thalamocortical networks

AU - Goncharenko, Iuliia

AU - Kros, Lieke

AU - Maex, Reinoud

AU - Davey, Neil

AU - Metzner, Christoph

AU - De Zeeuw, C.I.

AU - Hoebeek, F.E.

AU - Steuber, Volker

N1 - © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

PY - 2019/11/14

Y1 - 2019/11/14

N2 - Absence seizures are the most common form of epilepsy in children. They start and finish abruptly, last for 10–20 seconds and can be detected by generalised spike-and-wave discharges (GSWDs) in the electroencephalogram. These GSWDs are based on neuronal oscillations in thalamocortical networks, which can be caused by excessive inhibition in the thalamus or excessive cortical activity. Absence seizures can be triggered by switching of the normal asynchronous neuronal activity in thalamocortical networks to synchronised oscillations, and terminated by the reverse process, switching from synchronised oscillations to asynchronous activity.Experimental studies have shown that thalamic stimulation can disrupt oscillatory activity in thalamocortical networks. More recently, it was also found that optogenetic activation of neurons in the cerebellar nuclei (CN) can stop epileptic absence seizures and reset the oscillatory activity, for example in a closed loop system [1]. However, the underlying mechanism of the termination of absence seizures by CN stimulation is not yet clear.To investigate the mechanism of the termination of absence seizures by thalamic input from the CN we used computer simulations. We simulate a thalamocortical network model with adaptive exponential integrate-and-fire neurons, displaying complex intrinsic properties such as low-threshold spiking, regular spiking, fast spiking and adaptation [2]. The network activity can exhibit oscillatory or asynchronous irregular (AI) dynamics, depending on the time constants of the inhibitory synaptic conductance, which are 5 ms (AI) and 15 ms (oscillatory), respectively. An increase in the inhibitory decay time constant reflects a change from GABAA dominated inhibition to more GABAB, which can result in GSWDs, given that the “wave” components of GSWDs are related to slow GABAB -mediated K+ currents [3].We provide CN input to all thalamocortical neurons to analyse the mechanism of reverting from abnormal oscillatory activity to the normal AI state. Our results confirm that input from the CN can control oscillatory activity in thalamocortical networks. Furthermore, they show that the effectiveness of this input exhibits phase-dependence. In our simulations, CN input terminates epileptic absence seizures most effectively when it arrives at the peak of GSWDs, while seizure termination is least efficient for input between the GSWD bursts. This finding is potentially relevant for therapeutic applications of CN stimulation to terminate seizures. However, the simulations in silico did not take several biological factors such as indirect pathways from the CN to the thalamus into account that may explain differences with animal models of epilepsy [1].

AB - Absence seizures are the most common form of epilepsy in children. They start and finish abruptly, last for 10–20 seconds and can be detected by generalised spike-and-wave discharges (GSWDs) in the electroencephalogram. These GSWDs are based on neuronal oscillations in thalamocortical networks, which can be caused by excessive inhibition in the thalamus or excessive cortical activity. Absence seizures can be triggered by switching of the normal asynchronous neuronal activity in thalamocortical networks to synchronised oscillations, and terminated by the reverse process, switching from synchronised oscillations to asynchronous activity.Experimental studies have shown that thalamic stimulation can disrupt oscillatory activity in thalamocortical networks. More recently, it was also found that optogenetic activation of neurons in the cerebellar nuclei (CN) can stop epileptic absence seizures and reset the oscillatory activity, for example in a closed loop system [1]. However, the underlying mechanism of the termination of absence seizures by CN stimulation is not yet clear.To investigate the mechanism of the termination of absence seizures by thalamic input from the CN we used computer simulations. We simulate a thalamocortical network model with adaptive exponential integrate-and-fire neurons, displaying complex intrinsic properties such as low-threshold spiking, regular spiking, fast spiking and adaptation [2]. The network activity can exhibit oscillatory or asynchronous irregular (AI) dynamics, depending on the time constants of the inhibitory synaptic conductance, which are 5 ms (AI) and 15 ms (oscillatory), respectively. An increase in the inhibitory decay time constant reflects a change from GABAA dominated inhibition to more GABAB, which can result in GSWDs, given that the “wave” components of GSWDs are related to slow GABAB -mediated K+ currents [3].We provide CN input to all thalamocortical neurons to analyse the mechanism of reverting from abnormal oscillatory activity to the normal AI state. Our results confirm that input from the CN can control oscillatory activity in thalamocortical networks. Furthermore, they show that the effectiveness of this input exhibits phase-dependence. In our simulations, CN input terminates epileptic absence seizures most effectively when it arrives at the peak of GSWDs, while seizure termination is least efficient for input between the GSWD bursts. This finding is potentially relevant for therapeutic applications of CN stimulation to terminate seizures. However, the simulations in silico did not take several biological factors such as indirect pathways from the CN to the thalamus into account that may explain differences with animal models of epilepsy [1].

U2 - 10.1186/s12868-019-0538-0

DO - 10.1186/s12868-019-0538-0

M3 - Meeting abstract

VL - 20

SP - 157

EP - 157

JO - BMC Neuroscience

JF - BMC Neuroscience

SN - 1471-2202

IS - (Suppl 1)

M1 - 56

T2 - 28th Annual Computational Neuroscience Meeting

Y2 - 13 July 2019 through 17 July 2019

ER -