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Reply to: "Levodopa‐induced dyskinesia are mediated by cortical gamma oscillations in experimental Parkinsonism"

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Nikulin,  Vadim V.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Güttler, C., Altschüler, J., Tanev, K., Böckmann, S., Haumesser, J. K., Nikulin, V. V., et al. (2021). Reply to: "Levodopa‐induced dyskinesia are mediated by cortical gamma oscillations in experimental Parkinsonism". Movement Disorders, 36(4), 1045-1047. doi:10.1002/mds.28576.


Cite as: http://hdl.handle.net/21.11116/0000-0008-6ED9-9
Abstract
Background Levodopa is the most efficacious drug in the symptomatic therapy of motor symptoms in Parkinson's disease (PD); however, long‐term treatment is often complicated by troublesome levodopa‐induced dyskinesia (LID). Recent evidence suggests that LID might be related to increased cortical gamma oscillations. Objective The objective of this study was to test the hypothesis that cortical high‐gamma network activity relates to LID in the 6‐hydroxydopamine model and to identify new biomarkers for adaptive deep brain stimulation (DBS) therapy in PD. Methods We recorded and analyzed primary motor cortex (M1) electrocorticogram data and motor behavior in freely moving 6‐OHDA lesioned rats before and during a daily treatment with levodopa for 3 weeks. The results were correlated with the abnormal involuntary movement score (AIMS) and used for generalized linear modeling (GLM). Results Levodopa reverted motor impairment, suppressed beta activity, and, with repeated administration, led to a progressive enhancement of LID. Concurrently, we observed a highly significant stepwise amplitude increase in finely tuned gamma (FTG) activity and gamma centroid frequency. Whereas AIMS and FTG reached their maximum after the 4th injection and remained on a stable plateau thereafter, the centroid frequency of the FTG power continued to increase thereafter. Among the analyzed gamma activity parameters, the fraction of longest gamma bursts showed the strongest correlation with AIMS. Using a GLM, it was possible to accurately predict AIMS from cortical recordings. Conclusions FTG activity is tightly linked to LID and should be studied as a biomarker for adaptive DBS.