Deep Brain Stimulation for Parkinson’s Disease: Association between Stimulation Parameters and Cognitive Performance

2004 ◽  
Vol 82 (4) ◽  
pp. 191-193 ◽  
Author(s):  
P. Francel ◽  
K. Ryder ◽  
J. Wetmore ◽  
A. Stevens ◽  
K. Bharucha ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Cognitive Performance ◽  
Brain Stimulation ◽  
Disease Association ◽  
Stimulation Parameters ◽  
Deep Brain

scholarly journals A comparative study of asleep and awake deep brain stimulation robot-assisted surgery for Parkinson’s disease

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Hai Jin ◽  
Shun Gong ◽  
Yingqun Tao ◽  
Hua Huo ◽  
Xiao Sun ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Robot Assisted ◽  
Electrode Implantation ◽  
Stimulation Parameters ◽  
Procedure Duration ◽  
Electrophysiological Signal ◽  
Deep Brain

Abstract To compare the differences between asleep and awake robot-assisted deep brain stimulation (DBS) surgery for Parkinson’s Disease (PD), we conducted this retrospective cohort study included 153 PD patients undergoing bilateral robot-assisted DBS from June 2017 to August 2019, of which 58 cases were performed under general anesthesia (GA) and 95 cases under local anesthesia (LA). Procedure duration, stimulation parameters, electrode implantation accuracy, intracranial air, intraoperative electrophysiological signal length, complications, and Unified PD Rating Scale (UPDRS) measurements were recorded and compared. The clinical evaluation was conducted by two raters who were blinded to the choice of anesthesia. Procedure duration was significantly shorter in the GA group, while on stimulation off medication motor scores (UPDRS-III) were significantly improved in both the GA and LA group. ANCOVA covariated for the baseline UPDRS-III and levodopa challenge exhibited no significant differences. In terms of amplitude, frequency, and pulse width, the stimulation parameters used for DBS power-on were similar. There were no significant differences in electrode implantation accuracy, intraoperative electrophysiological signal length, or intracerebral hemorrhage (no occurrences in either group). The pneumocephalus volume was significantly smaller in the GA group. Six patients exhibited transient throat discomfort associated with tracheal intubation in the GA group. The occurrence of surgical incision infection was similar in both groups. Compared with the awake group, the asleep group exhibited a shorter procedure duration with a similar electrode implantation accuracy and short-term motor improvement. Robot-assisted asleep DBS surgery is a promising surgical method for PD.

scholarly journals Adjustment of Subthalamic Deep Brain Stimulation Parameters Improves Wheeze and Dyspnea in Parkinson's Disease

2019 ◽  
Vol 10 ◽  
Author(s):  
Hiroyasu Komiya ◽  
Katsuo Kimura ◽  
Hitaru Kishida ◽  
Takashi Kawasaki ◽  
Koichi Hamada ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Stimulation Parameters ◽  
Deep Brain

scholarly journals Deep Brain Stimulation Does Not Silence Neurons in Subthalamic Nucleus in Parkinson's Patients

2010 ◽  
Vol 103 (2) ◽  
pp. 962-967 ◽  
Author(s):  
Jonathan D. Carlson ◽  
Daniel R. Cleary ◽  
Justin S. Cetas ◽  
Mary M. Heinricher ◽  
Kim J. Burchiel
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Basal Ganglia ◽  
Firing Rate ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Animal Studies ◽  
Stimulation Parameters ◽  
Deep Brain

Two broad hypotheses have been advanced to explain the clinical efficacy of deep brain stimulation (DBS) in the subthalamic nucleus (STN) for treatment of Parkinson's disease. One is that stimulation inactivates STN neurons, producing a functional lesion. The other is that electrical stimulation activates the STN output, thus “jamming” pathological activity in basal ganglia-corticothalamic circuits. Evidence consistent with both concepts has been adduced from modeling and animal studies, as well as from recordings in patients. However, the stimulation parameters used in many recording studies have not been well matched to those used clinically. In this study, we recorded STN activity in patients with Parkinson's disease during stimulation delivered through a clinical DBS electrode using standard therapeutic stimulus parameters. A microelectrode was used to record the firing of a single STN neuron during DBS (3–5 V, 80–200 Hz, 90- to 200-μs pulses; 33 neurons/11 patients). Firing rate was unchanged during the stimulus trains, and the recorded neurons did not show prolonged (s) changes in firing rate on termination of the stimulation. However, a brief (∼1 ms), short-latency (6 ms) postpulse inhibition was seen in 10 of 14 neurons analyzed. A subset of neurons displayed altered firing patterns, with a predominant shift toward random firing. These data do not support the idea that DBS inactivates the STN and are instead more consistent with the hypothesis that this stimulation provides a null signal to basal ganglia-corticothalamic circuitry that has been altered as part of Parkinson's disease.

scholarly journals Does Quantitative Electroencephalography Refine Preoperative Cognitive Assessment in Parkinson’s Disease Patients Treated with Deep Brain Stimulation? A Follow-Up Study

2021 ◽  
pp. 1-8
Author(s):  
Christian Saleh ◽  
Antonia Meyer ◽  
Menorca Chaturvedi ◽  
Selina Beltrani ◽  
Ute Gschwandtner ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Cognitive Performance ◽  
Brain Stimulation ◽  
Verbal Fluency ◽  
Quantitative Electroencephalography ◽  
Cognitive Score ◽  
Increased Risk ◽  
Deep Brain

<b><i>Objective:</i></b> Deep brain stimulation (DBS) in Parkinson’s disease (PD) is associated with an increased risk of post-operative cognitive deterioration. Preoperative neuropsychological testing can be affected and limited by the patient’s collaboration in advanced disease. The purpose of this study was to determine whether preoperative quantitative electroencephalography (qEEG) may be a useful complementary examination technique during preoperative assessment to predict cognitive changes in PD patients treated with DBS. <b><i>Methods:</i></b> We compared the cognitive performance of 16 PD patients who underwent bilateral subthalamic nucleus DBS to the performance of 15 PD controls (matched for age, sex, and education) at baseline and at 24 months. Cognitive scores were calculated for all patients across 5 domains. A preoperative 256-channel resting EEG was recorded from each patient. We computed the global relative power spectra. Correlation and linear regression models were used to assess associations of preoperative EEG measures with post-operative cognitive scores. <b><i>Results:</i></b> Slow waves (relative delta and theta band power) were negatively correlated with post-operative cognitive performance, while faster waves (alpha 1) were strongly positively correlated with the same scores (the overall cognitive score, attention, and executive function). Linear models revealed an association of delta power with the overall cognitive score (<i>p</i> = 0.00409, adjusted <i>R</i><sup>2</sup> = 0.6341). Verbal fluency (VF) showed a significant decline after DBS surgery, which was correlated with qEEG measures. <b><i>Conclusions:</i></b> To analyse the side effects after DBS in PD patients, the most important parameter is verbal fluency capacity. In addition, correlation with EEG frequency bands might be useful to detect particularly vulnerable patients for cognitive impairment and be supportive in the selection process of patients considered for DBS.

scholarly journals Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson’s disease

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Kenneth H. Louie ◽  
Matthew N. Petrucci ◽  
Logan L. Grado ◽  
Chiahao Lu ◽  
Paul J. Tuite ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Stimulation Frequency ◽  
Trial And Error ◽  
Optimal Frequency ◽  
Stimulation Parameter ◽  
Stimulation Parameters ◽  
Deep Brain

Abstract Background Deep brain stimulation (DBS) is a treatment option for Parkinson’s disease patients when medication does not sufficiently manage their symptoms. DBS can be a highly effect therapy, but only after a time-consuming trial-and-error stimulation parameter adjustment process that is susceptible to clinician bias. This trial-and-error process will be further prolonged with the introduction of segmented electrodes that are now commercially available. New approaches to optimizing a patient’s stimulation parameters, that can also handle the increasing complexity of new electrode and stimulator designs, is needed. Methods To improve DBS parameter programming, we explored two semi-automated optimization approaches: a Bayesian optimization (BayesOpt) algorithm to efficiently determine a patient’s optimal stimulation parameter for minimizing rigidity, and a probit Gaussian process (pGP) to assess patient’s preference. Quantified rigidity measurements were obtained using a robotic manipulandum in two participants over two visits. Rigidity was measured, in 5Hz increments, between 10–185Hz (total 30–36 frequencies) on the first visit and at eight BayesOpt algorithm-selected frequencies on the second visit. The participant was also asked their preference between the current and previous stimulation frequency. First, we compared the optimal frequency between visits with the participant’s preferred frequency. Next, we evaluated the efficiency of the BayesOpt algorithm, comparing it to random and equal interval selection of frequency. Results The BayesOpt algorithm estimated the optimal frequency to be the highest tolerable frequency, matching the optimal frequency found during the first visit. However, the participants’ pGP models indicate a preference at frequencies between 70–110 Hz. Here the stimulation frequency is lowest that achieves nearly maximal suppression of rigidity. BayesOpt was efficient, estimating the rigidity response curve to stimulation that was almost indistinguishable when compared to the longer brute force method. Conclusions These results provide preliminary evidence of the feasibility to use BayesOpt for determining the optimal frequency, while pGP patient’s preferences include more difficult to measure outcomes. Both novel approaches can shorten DBS programming and can be expanded to include multiple symptoms and parameters.

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