Exploiting pallidal plasticity for stimulation in Parkinson’s disease

Marcel Antonius Johannes Lourens, B.C. Schwab, Jasmine A. Nirody, Hil Gaétan Ellart Meijer, Stephanus A. van Gils

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)

Abstract

Objective. Continuous application of high-frequency deep brain stimulation (DBS) often effectively reduces motor symptoms of Parkinson’s disease patients. While there is a growing need for more effective and less traumatic stimulation, the exact mechanism of DBS is still unknown. Here, we present a methodology to exploit the plasticity of GABAergic synapses inside the external globus pallidus (GPe) for the optimization of DBS. Approach. Assuming the existence of spike-timing-dependent plasticity (STDP) at GABAergic GPe–GPe synapses, we simulate neural activity in a network model of the subthalamic nucleus and GPe. In particular, we test different DBS protocols in our model and quantify their influence on neural synchrony. Main results. In an exemplary set of biologically plausible model parameters, we show that STDP in the GPe has a direct influence on neural activity and especially the stability of firing patterns. STDP stabilizes both uncorrelated firing in the healthy state and correlated firing in the parkinsonian state. Alternative stimulation protocols such as coordinated reset stimulation can clearly profit from the stabilizing effect of STDP. These results are widely independent of the STDP learning rule. Significance. Once the model settings, e.g., connection architectures, have been described experimentally, our model can be adjusted and directly applied in the development of novel stimulation protocols. More efficient stimulation leads to both minimization of side effects and savings in battery power.
Original languageUndefined
Pages (from-to)026005
Number of pages20
JournalJournal of neural engineering
Volume12
Issue number2
DOIs
Publication statusPublished - Apr 2015

Keywords

  • neuronal synchrony
  • EWI-25762
  • spike-timing-dependent plasticity
  • IR-94368
  • External Globus Pallidus
  • alternative stimulation protocols
  • METIS-312505
  • GPe–GPe synapses

Cite this

Lourens, Marcel Antonius Johannes ; Schwab, B.C. ; Nirody, Jasmine A. ; Meijer, Hil Gaétan Ellart ; van Gils, Stephanus A. / Exploiting pallidal plasticity for stimulation in Parkinson’s disease. In: Journal of neural engineering. 2015 ; Vol. 12, No. 2. pp. 026005.
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Exploiting pallidal plasticity for stimulation in Parkinson’s disease. / Lourens, Marcel Antonius Johannes; Schwab, B.C.; Nirody, Jasmine A.; Meijer, Hil Gaétan Ellart; van Gils, Stephanus A.

In: Journal of neural engineering, Vol. 12, No. 2, 04.2015, p. 026005.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Exploiting pallidal plasticity for stimulation in Parkinson’s disease

AU - Lourens, Marcel Antonius Johannes

AU - Schwab, B.C.

AU - Nirody, Jasmine A.

AU - Meijer, Hil Gaétan Ellart

AU - van Gils, Stephanus A.

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N2 - Objective. Continuous application of high-frequency deep brain stimulation (DBS) often effectively reduces motor symptoms of Parkinson’s disease patients. While there is a growing need for more effective and less traumatic stimulation, the exact mechanism of DBS is still unknown. Here, we present a methodology to exploit the plasticity of GABAergic synapses inside the external globus pallidus (GPe) for the optimization of DBS. Approach. Assuming the existence of spike-timing-dependent plasticity (STDP) at GABAergic GPe–GPe synapses, we simulate neural activity in a network model of the subthalamic nucleus and GPe. In particular, we test different DBS protocols in our model and quantify their influence on neural synchrony. Main results. In an exemplary set of biologically plausible model parameters, we show that STDP in the GPe has a direct influence on neural activity and especially the stability of firing patterns. STDP stabilizes both uncorrelated firing in the healthy state and correlated firing in the parkinsonian state. Alternative stimulation protocols such as coordinated reset stimulation can clearly profit from the stabilizing effect of STDP. These results are widely independent of the STDP learning rule. Significance. Once the model settings, e.g., connection architectures, have been described experimentally, our model can be adjusted and directly applied in the development of novel stimulation protocols. More efficient stimulation leads to both minimization of side effects and savings in battery power.

AB - Objective. Continuous application of high-frequency deep brain stimulation (DBS) often effectively reduces motor symptoms of Parkinson’s disease patients. While there is a growing need for more effective and less traumatic stimulation, the exact mechanism of DBS is still unknown. Here, we present a methodology to exploit the plasticity of GABAergic synapses inside the external globus pallidus (GPe) for the optimization of DBS. Approach. Assuming the existence of spike-timing-dependent plasticity (STDP) at GABAergic GPe–GPe synapses, we simulate neural activity in a network model of the subthalamic nucleus and GPe. In particular, we test different DBS protocols in our model and quantify their influence on neural synchrony. Main results. In an exemplary set of biologically plausible model parameters, we show that STDP in the GPe has a direct influence on neural activity and especially the stability of firing patterns. STDP stabilizes both uncorrelated firing in the healthy state and correlated firing in the parkinsonian state. Alternative stimulation protocols such as coordinated reset stimulation can clearly profit from the stabilizing effect of STDP. These results are widely independent of the STDP learning rule. Significance. Once the model settings, e.g., connection architectures, have been described experimentally, our model can be adjusted and directly applied in the development of novel stimulation protocols. More efficient stimulation leads to both minimization of side effects and savings in battery power.

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KW - METIS-312505

KW - GPe–GPe synapses

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JO - Journal of neural engineering

JF - Journal of neural engineering

SN - 1741-2560

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ER -