Abstract
Objective
Deep brain stimulation (DBS) is an effective treatment for movement disorders, including
Parkinson disease and essential tremor. However, the underlying mechanisms of DBS
remain elusive. Despite the capability of existing models in interpreting experimental
data qualitatively, there are very few unified computational models that quantitatively
capture the dynamics of the neuronal activity of varying stimulated nuclei—including
subthalamic nucleus (STN), substantia nigra pars reticulata (SNr), and ventral intermediate
nucleus (Vim)—across different DBS frequencies.
Materials and Methods
Both synthetic and experimental data were used in the model fitting; the synthetic
data were generated by an established spiking neuron model that was reported in our
previous work, and the experimental data were provided using single-unit microelectrode
recordings (MERs) during DBS (microelectrode stimulation). Based on these data, we
developed a novel mathematical model to represent the firing rate of neurons receiving
DBS, including neurons in STN, SNr, and Vim—across different DBS frequencies. In our
model, the DBS pulses were filtered through a synapse model and a nonlinear transfer
function to formulate the firing rate variability. For each DBS-targeted nucleus,
we fitted a single set of optimal model parameters consistent across varying DBS frequencies.
Results
Our model accurately reproduced the firing rates observed and calculated from both
synthetic and experimental data. The optimal model parameters were consistent across
different DBS frequencies.
Conclusions
The result of our model fitting was in agreement with experimental single-unit MER
data during DBS. Reproducing neuronal firing rates of different nuclei of the basal
ganglia and thalamus during DBS can be helpful to further understand the mechanisms
of DBS and to potentially optimize stimulation parameters based on their actual effects
on neuronal activity.
Keywords
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Article info
Publication history
Published online: May 02, 2023
Accepted:
March 2,
2023
Received in revised form:
January 27,
2023
Received:
November 13,
2022
Publication stage
In Press Corrected ProofFootnotes
Source(s) of financial support: This project was supported by Milad Lankarany’s NSERC Discovery Grant (RGPIN-2020-05868). Leon A. Steiner received grant support from Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 424778381 – TRR 295. Leon A. Steiner received additional funding through the Junior Clinician Scientist Program of the Berlin Institute of Health and though a post doc scholarship provided by the German Academic Exchange Service - DAAD.
Conflict of Interest: Suneil K. Kalia reports consulting fees from Boston Scientific, Medtronic, and Abbott. Andres M. Lozano reports consulting fees from Abbott, Boston Scientific, Medtronic, and Insightec. The remaining authors reported no conflict of interest.
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© 2023 International Neuromodulation Society. Published by Elsevier Inc. All rights reserved.
