Spectral characteristics of subthalamic nucleus local field potentials in Parkinson's disease: Phenotype and movement matter
| Autor: | Bruno Leonardo Bianqueti, Tiago P. Almeida, Diogo C. Soriano, Maria Sheila Guimarães Rocha, Paulo Roberto Terzian Filho, Andre Kazuo Takahata, Eduardo Varjão, Julia Baldi de Luccas, Arnaldo Fim Neto, Eberval Gadelha Figueiredo, Fabio Godinho, Takashi Yoneyama |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Deep brain stimulation Neurology Parkinson's disease medicine.medical_treatment Deep Brain Stimulation Movement Rest Local field potential 03 medical and health sciences 0302 clinical medicine Subthalamic Nucleus Medicine Humans 030304 developmental biology 0303 health sciences business.industry General Neuroscience Parkinson Disease medicine.disease Gait Phenotype Electrophysiology Subthalamic nucleus nervous system business Neuroscience 030217 neurology & neurosurgery |
| Zdroj: | The European journal of neuroscienceREFERENCES. 53(8) |
| ISSN: | 1460-9568 |
| Popis: | Parkinson's disease (PD) is clinically heterogeneous across patients and may be classified in three motor phenotypes: tremor dominant (TD), postural instability and gait disorder (PIGD), and undetermined. Despite the significant clinical characterization of motor phenotypes, little is known about how electrophysiological data, particularly subthalamic nucleus local field potentials (STN-LFP), differ between TD and PIGD patients. This is relevant since increased STN-LFP bandpower at α-β range (8-35 Hz) is considered a potential PD biomarker and, therefore, a critical setpoint to drive adaptive deep brain stimulation. Acknowledging STN-LFP differences between phenotypes, mainly in rest and movement states, would better fit DBS to clinical and motor demands. We studied this issue through spectral analyses on 35 STN-LFP in TD and PIGD patients during rest and movement. We demonstrated that higher β2 activity (22-35 Hz) was observed in PIGD only during rest. Additionally, bandpower differences between rest and movement occurred at the α-β range, but with different patterns as per phenotypes: movement-induced desynchronization concerned lower frequencies in TD (10-20 Hz) and higher frequencies in PIGD patients (21-28 Hz). Finally, when supervised learning algorithms were employed aiming to discriminate PD phenotypes based on STN-LFP bandpower features, movement information had improved the classification accuracy, achieving peak performances when TD and PIGD movement-induced desynchronization ranges were considered. These results suggest that STN-LFP β-band encodes phenotype-movement dependent information in PD patients. |
| Databáze: | OpenAIRE |
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