Objective: Changes in total power and entropy across raw data may enable the identification of comprehensive shifts in neural dynamics that may align with clinical symptoms, thus serving as markers for adaptive deep brain stimulation therapy.Changes in total power and entropy across raw data may enable the identification of comprehensive shifts in neural dynamics that may align with clinical symptoms, thus serving as markers for adaptive deep brain stimulation therapy.

Background: Parkinson disease (PD) and dystonia (DYS) are associated with changes in neural oscillations across different frequency bands, rather than being confined to one specific frequency band.

Method: Nine patients diagnosed with PD (age onset of disease: 28–58 years; eight male and one female) and six primary patients with DYS (age onset of disease: 33–51 years; four male and two female) participated in the study. We used EEG recordings from the motor cortex to investigate how the spontaneous power of classical cortical frequency bands and total power across broad bands manifest in PD patients compared to those with DYS. Additionally, we analyzed approximate entropy (ApEn) from the oscillatory activities across different frequency bands and across broad bands in the motor cortex.

Results: Our results show that in DYS enhanced theta (4-8 Hz) and gamma (30- 100 Hz) frequency bands were accompanied with lower values in theta entropy (p<0.01), whereas in PD patients enhanced beta frequency band (12-30 Hz) was accompanied with reduced values in beta entropy (p<0.01). Overall, the total ApEn was higher in DYS patients’ motor cortical areas as compared to PD patients.

Conclusion: In DYS patients lower ApEn values in the theta band signify higher energy availability in the lower frequency band, whereas higher ApEn values within the beta and gamma bands imply lower energy availability compared to those with PD. Entropy-based values may be used as biomarkers to evaluate the effectiveness of treatments and neuromodulation strategies for both PD and DYS.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/neural-oscillatory-dynamics-in-parkinson-disease-and-dystonia-insights-from-eeg-analysis/