Subthalamic nucleus neuronal activity entropy in the effective stimulation area in patients with Parkinson’s disease
- Authors: Zakharov N.I.1,2, Belova E.M.2, Gamaleya A.A.3, Tomskiy A.A.3, Sedov A.S.1,2
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Affiliations:
- Moscow Institute of Physics and Technology (National Research University)
- N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences
- Burdenko National Medical Research Center of Neurosurgery, Ministry of Health of Russia
- Issue: Vol 18, No 4 (2023)
- Pages: 894-897
- Section: Conference proceedings
- URL: https://genescells.ru/2313-1829/article/view/623521
- DOI: https://doi.org/10.17816/gc623521
- ID: 623521
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Abstract
One of the most successful and promising treatments for Parkinson’s disease today is deep brain stimulation (DBS). Accurate localization of the stimulation area is critical for the outcome of surgical DBS electrode implantation in the subthalamic nucleus (STN). To achieve this, microelectrode recording is used during surgery to precisely locate the STN borders [1], while test stimulations with a macroelectrode are widely employed to enhance DBS electrode placement accuracy. Thus, through testing multiple trajectories, the most clinically effective one can be selected. However, a comprehensive and reliable description of the specific single neuron activity associated with successful DBS electrode implantation is currently lacking.
A study was conducted using microelectrode recordings (MER) of single neuron activity in the STN of 21 Parkinson’s disease patients (UPDRS III off/on=46.9/12.8) to identify the neuronal activity features associated with the most favorable clinical outcome of test stimulation. A comparative analysis of 29 activity parameters, such as firing rate, oscillatory activity intensity in different frequency ranges (Oscores), coefficient of variation, burst, pause index, among others [2], was conducted for 618 identified neurons. In addition, the approach of computing the entropy of the change in interspike intervals (ISI) of the pulse sequence [3] and the process of identifying patterns of neural activity using hierarchical clustering [4] were implemented.
A comparative analysis of single neuron activity indicated notable (p <0.05) variations between disregarded and selected paths for the ultimate implantation of DBS electrode, solely relying on entropy parameters. Trajectories that delivered optimal test stimulation outcomes demonstrated reduced entropy of interspike intervals. Only the patterns of neuronal activity characterized by extended periods of steady firing and brief pauses, referred to as tonic and pause activity, respectively, were found to contribute to the difference in entropy between trajectories. In contrast, there were no statistically significant differences detected in entropy values associated with neurons demonstrating burst activity. Furthermore, we observed a positive and significant correlation between entropy values and the degree of improvement in disease presentation before and after administration of medication.
A comparative analysis was conducted on the activity of single neurons along different trajectories with varied test stimulation responses. The results showed a weak effectiveness of linear parameters in determining the optimal electrode insertion path for improved clinical outcomes. However, the use of non-linear activity parameters, specifically entropy, in single neurons effectively differentiated trajectories with significant versus absent/insignificant test stimulation results. Furthermore, the significance of entropy in establishing the basal ganglia functions and describing information transfer processes in movement control is emphasized by interpreting this parameter as a measure of uncertainty or unpredictability of the information system in relation to the findings of other studies [5].
Full Text
One of the most successful and promising treatments for Parkinson’s disease today is deep brain stimulation (DBS). Accurate localization of the stimulation area is critical for the outcome of surgical DBS electrode implantation in the subthalamic nucleus (STN). To achieve this, microelectrode recording is used during surgery to precisely locate the STN borders [1], while test stimulations with a macroelectrode are widely employed to enhance DBS electrode placement accuracy. Thus, through testing multiple trajectories, the most clinically effective one can be selected. However, a comprehensive and reliable description of the specific single neuron activity associated with successful DBS electrode implantation is currently lacking.
A study was conducted using microelectrode recordings (MER) of single neuron activity in the STN of 21 Parkinson’s disease patients (UPDRS III off/on=46.9/12.8) to identify the neuronal activity features associated with the most favorable clinical outcome of test stimulation. A comparative analysis of 29 activity parameters, such as firing rate, oscillatory activity intensity in different frequency ranges (Oscores), coefficient of variation, burst, pause index, among others [2], was conducted for 618 identified neurons. In addition, the approach of computing the entropy of the change in interspike intervals (ISI) of the pulse sequence [3] and the process of identifying patterns of neural activity using hierarchical clustering [4] were implemented.
A comparative analysis of single neuron activity indicated notable (p <0.05) variations between disregarded and selected paths for the ultimate implantation of DBS electrode, solely relying on entropy parameters. Trajectories that delivered optimal test stimulation outcomes demonstrated reduced entropy of interspike intervals. Only the patterns of neuronal activity characterized by extended periods of steady firing and brief pauses, referred to as tonic and pause activity, respectively, were found to contribute to the difference in entropy between trajectories. In contrast, there were no statistically significant differences detected in entropy values associated with neurons demonstrating burst activity. Furthermore, we observed a positive and significant correlation between entropy values and the degree of improvement in disease presentation before and after administration of medication.
A comparative analysis was conducted on the activity of single neurons along different trajectories with varied test stimulation responses. The results showed a weak effectiveness of linear parameters in determining the optimal electrode insertion path for improved clinical outcomes. However, the use of non-linear activity parameters, specifically entropy, in single neurons effectively differentiated trajectories with significant versus absent/insignificant test stimulation results. Furthermore, the significance of entropy in establishing the basal ganglia functions and describing information transfer processes in movement control is emphasized by interpreting this parameter as a measure of uncertainty or unpredictability of the information system in relation to the findings of other studies [5].
ADDITIONAL INFORMATION
Authors’ contribution. All authors made a substantial contribution to the conception of the work, acquisition, analysis, interpretation of data for the work, drafting and revising the work, final approval of the version to be published and agree to be accountable for all aspects of the work.
Funding sources. This study was supported by the Russian Science Foundation (grant No. 22-15-00344).
Competing interests. The authors declare that they have no competing interests.
About the authors
N. I. Zakharov
Moscow Institute of Physics and Technology (National Research University); N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences
Author for correspondence.
Email: zaharov.ni@phystech.edu
Russian Federation, Moscow; Moscow
E. M. Belova
N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences
Email: zaharov.ni@phystech.edu
Russian Federation, Moscow
A. A. Gamaleya
Burdenko National Medical Research Center of Neurosurgery, Ministry of Health of Russia
Email: zaharov.ni@phystech.edu
Russian Federation, Moscow
A. A. Tomskiy
Burdenko National Medical Research Center of Neurosurgery, Ministry of Health of Russia
Email: zaharov.ni@phystech.edu
Russian Federation, Moscow
A. S. Sedov
Moscow Institute of Physics and Technology (National Research University); N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences
Email: zaharov.ni@phystech.edu
Russian Federation, Moscow; Moscow
References
- Koirala N, Serrano L, Paschen S, et al. Mapping of subthalamic nucleus using microelectrode recordings during deep brain stimulation. Sci Rep. 2020;10(1):19241. doi: 10.1038/s41598-020-74196-5
- Myrov V, Sedov A, Salova E, et al. Single unit activity of subthalamic nucleus of patients with Parkinson’s disease under local and generalized anaesthesia: multifactor analysis. Neurosci Res. 2019;145:54–61. doi: 10.1016/j.neures.2018.08.006
- Sherry CJ, Klemm WR. Entropy as an index of the informational state of neurons. Int J Neurosci. 1981;15(3):171–178. doi: 10.3109/00207458108985911
- Myrov V, Sedov A, Belova E. Neural activity clusterization for estimation of firing pattern. J Neurosci Methods. 2019;311:164–169. doi: 10.1016/j.jneumeth.2018.10.017
- Darbin O, Dees D, Martino A, et al. An entropy-based model for basal ganglia dysfunctions in movement disorders. Biomed Res Int. 2013;2013:742671. doi: 10.1155/2013/742671
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