Neuronal signatures of abnormal globus pallidus activity in patients with Parkinson’s disease and dystonia
- Authors: Sedov A.S.1, Dzhalagoniia I.Z.1, Filiushkina V.I.1, Usova S.V.1, Semenova Y.N.1, Gamaleya A.A.2, Tomskiy A.A.2
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Affiliations:
- N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences
- Burdenko National Scientific and Practical Center for Neurosurgery
- Issue: Vol 18, No 4 (2023)
- Pages: 683-686
- Section: Conference proceedings
- URL: https://genescells.ru/2313-1829/article/view/623411
- DOI: https://doi.org/10.17816/gc623411
- ID: 623411
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Abstract
Parkinson’s disease (PD) is a hypokinetic movement disorder. It is characterized by bradykinesia, rigidity, tremor, and postural unsteadiness. Dystonia is a hyperkinetic movement disorder characterized by involuntary sustained or intermittent muscle contractions that cause abnormal, often repetitive movements, postures, or both. The traditional functional model posits that there is greater neuronal activity in the internal segment of the globus pallidus (GPi) in PD, a hypokinetic movement disorder, and reduced neuronal activity in dystonia, a hyperactive movement disorder [1, 2]. Deep brain stimulation (DBS) of this structure was shown to have a positive clinical effect in both cases. This paradox remains unresolved, necessitating further research on the neuronal processes in the basal ganglia, enhancing motor control models, and analyzing the impact of DBS stimulation on brain activity. Increased synchronization of beta (13–35 Hz) rhythms in patients with PD indicates an excessive amount of antikinetic inhibitory motor signals. Meanwhile, increased synchronization of theta-alpha (4–12 Hz) rhythms is associated with dystonia pathology [3, 4]. Although frequency and spatial synchronization have been actively studied, the functional role of these rhythms in the organization of motor control in normal and pathological states remains unknown.
The study compared the activity of the internal and external segments of the globus pallidus (GPi and GPe) in patients with PD and patients with generalized (GD) and cervical (CD) dystonia. The analysis was conducted at both the single-neuron and neuronal population levels. Microelectrode recording was performed on single-unit activity of the globus pallidus during neurosurgical procedures. The purpose was to implant DBS electrodes into the internal segment of the GPi in studied patients. A total of 20 procedures were conducted. Multichannel recording of local field potentials (using 16 channels) from the globus pallidus was obtained postoperatively through temporary externalized electrodes in 8 patients. The study’s ethical approval was obtained from the committee at the N.N. Burdenko Center for Neurosurgery. Neuronal activity analysis used a previously established method separating neurons’ activity into tonic, burst, and pause patterns through hierarchical clusterization [5]. We analyzed the distribution of patterns and their main quantitative characteristics, such as the average firing rate, coefficient of variation of interspike intervals, asymmetry index, burst and pause indices, percentage of bursting discharges, oscillation scores, and other relevant parameters. Spectral analysis and quantitative assessment of oscillatory processes in various frequency ranges were used to analyze the local field potentials (LFP). An examination of periodic and aperiodic (1/f) constituents of local field potentials was performed using the neural signal spectrum parametrization algorithm as a combination of aperiodic elements and periodic oscillatory crests [6].
The study demonstrates comparable firing rates of GPi cells across all groups examined. However, the PD group exhibited a higher level of tonic neuronal activity with decreased theta-alpha oscillations. The analysis of GPi neuron distribution reveals a significant increase in tonic cells (11% GD, 15% CD, 49% PD) and a decrease in paused neurons (28% GD, 25% CD, 11% PD). The patient group with Parkinson’s disease exhibited a markedly elevated firing rate of tonic neurons (33 imp/sec GD, 51 imp/sec CD, 91 imp/sec PD) compared to the control groups, as well as a reduced firing rate of burst neurons (62 imp/sec GD, 68 imp/sec CD, 56 imp/sec PD), with statistical significance at p <0.001. Multifactor analysis using machine learning algorithms demonstrated the significance of non-linear characteristics in neuronal activity for classifying patients by disease type, including differential entropy, theta oscillations, pause index, among others. Activity of neurons in the GPe and GPi activity in the DBS stimulation area did not exhibit significant differences between the patient groups studied.
Spectral analysis of local field potentials revealed a marked elevation of theta activity and a decline in alpha, low-, and high-beta activity in both segments of the globus pallidus of patients with dystonia compared to those with PD. The random forest algorithm indicated that the most crucial factors for identifying the patients under study were oscillations in the high-frequency beta range and the slope of the aperiodic component. The area of stimulation via DBS exhibited increased theta activity and decreased low beta activity and an aperiodic component in patients with dystonia. No significant differences were found in the area of DBS stimulation and beyond for patients with PD. Significant differences were observed in theta and beta activity when comparing the DBS stimulation area activity among the examined patients.
The study revealed the neural organization of globus pallidus as heterogeneous, displaying diverse activity patterns. Multidirectional changes in neuronal activity, differences in activity pattern distribution, and non-linear characteristics are supported by both firing rate and firing pattern models of the basal ganglia. The analysis of local field potentials revealed a shift in both periodic and aperiodic components of globus pallidus activity in movement disorders. The interplay of these components determines the pathology of movement disorders, rather than heightened oscillations in a single frequency range. The lack of variance in neural activity in the stimulated area provides partial resolution to the enigma of the GPi-DBS’s efficacy in hypo- and hyperkinetic conditions. To accurately anticipate the area of stimulation and clinical outcomes, a comprehensive strategy is required, which integrates a blend of linear and non-linear components of single unit activity, along with periodic and aperiodic elements of local field potentials of the globus pallidus.
Full Text
Parkinson’s disease (PD) is a hypokinetic movement disorder. It is characterized by bradykinesia, rigidity, tremor, and postural unsteadiness. Dystonia is a hyperkinetic movement disorder characterized by involuntary sustained or intermittent muscle contractions that cause abnormal, often repetitive movements, postures, or both. The traditional functional model posits that there is greater neuronal activity in the internal segment of the globus pallidus (GPi) in PD, a hypokinetic movement disorder, and reduced neuronal activity in dystonia, a hyperactive movement disorder [1, 2]. Deep brain stimulation (DBS) of this structure was shown to have a positive clinical effect in both cases. This paradox remains unresolved, necessitating further research on the neuronal processes in the basal ganglia, enhancing motor control models, and analyzing the impact of DBS stimulation on brain activity. Increased synchronization of beta (13–35 Hz) rhythms in patients with PD indicates an excessive amount of antikinetic inhibitory motor signals. Meanwhile, increased synchronization of theta-alpha (4–12 Hz) rhythms is associated with dystonia pathology [3, 4]. Although frequency and spatial synchronization have been actively studied, the functional role of these rhythms in the organization of motor control in normal and pathological states remains unknown.
The study compared the activity of the internal and external segments of the globus pallidus (GPi and GPe) in patients with PD and patients with generalized (GD) and cervical (CD) dystonia. The analysis was conducted at both the single-neuron and neuronal population levels. Microelectrode recording was performed on single-unit activity of the globus pallidus during neurosurgical procedures. The purpose was to implant DBS electrodes into the internal segment of the GPi in studied patients. A total of 20 procedures were conducted. Multichannel recording of local field potentials (using 16 channels) from the globus pallidus was obtained postoperatively through temporary externalized electrodes in 8 patients. The study’s ethical approval was obtained from the committee at the N.N. Burdenko Center for Neurosurgery. Neuronal activity analysis used a previously established method separating neurons’ activity into tonic, burst, and pause patterns through hierarchical clusterization [5]. We analyzed the distribution of patterns and their main quantitative characteristics, such as the average firing rate, coefficient of variation of interspike intervals, asymmetry index, burst and pause indices, percentage of bursting discharges, oscillation scores, and other relevant parameters. Spectral analysis and quantitative assessment of oscillatory processes in various frequency ranges were used to analyze the local field potentials (LFP). An examination of periodic and aperiodic (1/f) constituents of local field potentials was performed using the neural signal spectrum parametrization algorithm as a combination of aperiodic elements and periodic oscillatory crests [6].
The study demonstrates comparable firing rates of GPi cells across all groups examined. However, the PD group exhibited a higher level of tonic neuronal activity with decreased theta-alpha oscillations. The analysis of GPi neuron distribution reveals a significant increase in tonic cells (11% GD, 15% CD, 49% PD) and a decrease in paused neurons (28% GD, 25% CD, 11% PD). The patient group with Parkinson’s disease exhibited a markedly elevated firing rate of tonic neurons (33 imp/sec GD, 51 imp/sec CD, 91 imp/sec PD) compared to the control groups, as well as a reduced firing rate of burst neurons (62 imp/sec GD, 68 imp/sec CD, 56 imp/sec PD), with statistical significance at p <0.001. Multifactor analysis using machine learning algorithms demonstrated the significance of non-linear characteristics in neuronal activity for classifying patients by disease type, including differential entropy, theta oscillations, pause index, among others. Activity of neurons in the GPe and GPi activity in the DBS stimulation area did not exhibit significant differences between the patient groups studied.
Spectral analysis of local field potentials revealed a marked elevation of theta activity and a decline in alpha, low-, and high-beta activity in both segments of the globus pallidus of patients with dystonia compared to those with PD. The random forest algorithm indicated that the most crucial factors for identifying the patients under study were oscillations in the high-frequency beta range and the slope of the aperiodic component. The area of stimulation via DBS exhibited increased theta activity and decreased low beta activity and an aperiodic component in patients with dystonia. No significant differences were found in the area of DBS stimulation and beyond for patients with PD. Significant differences were observed in theta and beta activity when comparing the DBS stimulation area activity among the examined patients.
The study revealed the neural organization of globus pallidus as heterogeneous, displaying diverse activity patterns. Multidirectional changes in neuronal activity, differences in activity pattern distribution, and non-linear characteristics are supported by both firing rate and firing pattern models of the basal ganglia. The analysis of local field potentials revealed a shift in both periodic and aperiodic components of globus pallidus activity in movement disorders. The interplay of these components determines the pathology of movement disorders, rather than heightened oscillations in a single frequency range. The lack of variance in neural activity in the stimulated area provides partial resolution to the enigma of the GPi-DBS’s efficacy in hypo- and hyperkinetic conditions. To accurately anticipate the area of stimulation and clinical outcomes, a comprehensive strategy is required, which integrates a blend of linear and non-linear components of single unit activity, along with periodic and aperiodic elements of local field potentials of the globus pallidus.
ADDITIONAL INFORMATION
Funding sources. The study was supported by the Russian Science Foundation, grant No. 23-15-00487.
About the authors
A. S. Sedov
N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences
Author for correspondence.
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
I. Z. Dzhalagoniia
N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
V. I. Filiushkina
N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
S. V. Usova
N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
Yu. N. Semenova
N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
A. A. Gamaleya
Burdenko National Scientific and Practical Center for Neurosurgery
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
A. A. Tomskiy
Burdenko National Scientific and Practical Center for Neurosurgery
Email: alexeys.sedov@gmail.com
Russian Federation, Moscow
References
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- Nambu A, et al. Reduced Pallidal Output Causes Dystonia. Frontiers in Systems Neuroscience. 2011;5:89. doi:
- Geng X, et al. Comparison of oscillatory activity in subthalamic nucleus in Parkinson’s disease and dystonia. Neurobiology of Disease. 2017;98:100–107. doi:
- Neumann WJ, Horn A, Ewert S, et al. A localized pallidal physiomarker in cervical dystonia. Annals of Neurology. 2017;82(6). doi: 10.1002/ana.25095
- Myrov V, Sedov A, Belova E. Neural activity clusterization for estimation of firing pattern. Journal of Neuroscience Methods. 2019;311:164–169. doi: 10.1016/j.jneumeth.2018.10.017.
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