Toward a closed-loop deep brain stimulation in Parkinson's disease using local field potential in parkinsonian rat model.

Deep brain stimulation (DBS) is an invasive method used for treating Parkinson's disease in its advanced stages. Nowadays, the initial adjustment of DBS parameters and their automatic matching proportion to the progression of the disease is viewed as one of the research areas discussed by the researchers, which is called closed-loop DBS. Various studies were conducted regarding finding the signal(s) which reflects different symptoms of the disease. Local Field Potential (LFP) is one of the signals that is suitable for using as feedback, because it can be recorded by the same implemented electrodes for stimulation. The present study aimed to identify the distinguishing features of patients from healthy individuals using LFP signals. METHODS: In the present study, LFP was recorded from the rats in sham and parkinsonian model groups. After evaluating the signals in the frequency domain, sixty-six features were extracted from power spectral density of LFPs. The features were classified by Support Vector Machine (SVM) to determine the ability of features for separating parkinsonian rats from healthy ones. Finally, the most effective features were selected for distinguishing between the sham and parkinsonian model groups using a genetic algorithm. RESULTS: The results indicated that the frequency domain features of LFP signals from rats have capacity of using them as a feedback for closed-loop DBS. The accuracy of the Support Vector Machine classification using all 66 features was 80.42% which increased to 84.41% using 38 features selected by genetic algorithm. The proposed method not only increase the accuracy, but it also reduce computation by decreasing the number of the effective features. The results indicate the significant capacity of the proposed method for identifying the effective high-frequency features to control the closed-loop DBS. CONCLUSIONS: The ability of using LFP signals as feedback in closed-loop DBS was shown by extracting useful information in frequency bands below and above 100 Hz regarding LFP signals of parkinsonian rats and sham ones. Based on the results, features at frequencies above 100 Hz were more powerful and robust than below 100 Hz. The genetic algorithm was used for optimizing the classification problem.

Peganum Harmala L. Extract Reduces Oxidative Stress and Improves Symptoms in 6-Hydroxydopamine-Induced Parkinson's Disease in Rats.

Parkinson's disease is one of the most common neurodegenerative disorders. There are many documents about the effects of oxidative stress in Parkinson's disease etiology. Angiotensin II activates NADPH dependent oxidases and causes superoxides formation. Peganum harmala L. extract, which has angiotensin converting enzyme (ACE) inhibitory effect, is considered to evaluate oxidative stress inhibition and Parkinson's disease improvement. Male rats weighting 200-250 g were divided into 5 groups: Control, Neurotoxin (injection of 6-hydroxydopamine into left hemisphere substantia nigra), Peganum harmala's seeds aqueous extract (10 mg/kg) and captopril (5 mg/kg). Peganum harmala and captopril were injected intraperitonealy -144, -120, -96, -72, -48, -24, -2, 4 and 24 h relative to 6-hydroxydopamine injection time. Muscle stiffness, apomorphine induced unilateral rotation, amount of brain's protein oxidation and lipid peroxidation, ACE activity and histology of substantia nigra were assayed in all groups. Peganum harmala improved Muscle stiffness and one-direction rotation behavior significantly. It also reduced brain's lipid and protein oxidation levels in neurotoxin-injected rats significantly. In Peganum harmala group compared to control group, brain's ACE activity was significantly inhibited. In histological study, Peganum harmala prevented degeneration of dopaminergic neurons, too. In conclusion, aqueous extract of Peganum harmala could prevent symptoms and reduced oxidative stress markers in rats with Parkinson's disease induced by 6-hydroxydopamine.