Deep Brain Stimulation

Author(s):  
Tipu Aziz ◽  
Holly Roy

Deep brain stimulation (DBS) is a neurosurgical technology that allows the manipulation of activity within specific brain regions through delivery of electrical stimulation via implanted electrodes. The growth of DBS has led to research around the development of novel interventions for a wide range of neurological and neuropsychiatric conditions, including Parkinson’s disease, dystonia, chronic pain, Tourette’s syndrome, treatment-resistant depression, anorexia nervosa, and Alzheimer’s disease. Some of these treatment approaches have a high level of efficacy as well as an established place in the clinical armamentarium for the diseases in question, such as DBS for movement disorders, including Parkinson’s disease. Other interventions are at a more developmental stage, such as DBS for depression and Alzheimer’s disease. Success both in clinical aspects of DBS and new innovations depends on a close-knit multidisciplinary team incorporating experts in the underlying condition (often neurologists and psychiatrists); neurosurgeons; nurse specialists, who may be involved in device programming and other aspects of patient care; and researchers including neuroscientists, imaging specialists, engineers, and signal analysts. Directly linked to the growth of DBS as a specialty is allied research around neural signals analysis and device development, which feed directly back into further clinical progress. The close links between clinical DBS and basic and translational research make it an exciting and fast-moving area of neuroscience.

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Polyvios Demetriades ◽  
Hugh Rickards ◽  
Andrea Eugenio Cavanna

Parkinson's disease (PD) has been associated with the development of impulse control disorders (ICDs), possibly due to overstimulation of the mesolimbic system by dopaminergic medication. Preliminary reports have suggested that deep brain stimulation (DBS), a neurosurgical procedure offered to patients with treatment-resistant PD, affects ICD in a twofold way. Firstly, DBS allows a decrease in dopaminergic medication and hence causes an improvement in ICDs. Secondly, some studies have proposed that specific ICDs may develop after DBS. This paper addresses the effects of DBS on ICDs in patients with PD. A literature search identified four original studies examining a total of 182 patients for ICDs and nine case reports of 39 patients that underwent DBS and developed ICDs at some point. Data analysis from the original studies did not identify a significant difference in ICDs between patients receiving dopaminergic medication and patients on DBS, whilst the case reports showed that 56% of patients undergoing DBS had poor outcome with regards to ICDs. We discuss these ambivalent findings in the light of proposed pathogenetic mechanisms. Longitudinal, prospective studies with larger number of patients are required in order to fully understand the role of DBS on ICDs in patients with PD.


2016 ◽  
Author(s):  
Victor M Saenger ◽  
Joshua Kahan ◽  
Tom Foltynie ◽  
Karl Friston ◽  
Tipu Z Aziz ◽  
...  

Deep brain stimulation (DBS) for Parkinson's disease is a highly effective treatment in controlling otherwise debilitating symptoms yet the underlying brain mechanisms are currently not well understood. We used whole-brain computational modeling to disclose the effects of DBS ON and OFF during collection of resting state fMRI in ten Parkinson's Disease patients. Specifically, we explored the local and global impact of DBS in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts the global brain dynamics of patients nearer to that of healthy people by significantly changing the bifurcation parameters in brain regions implicated in Parkinson's Disease. We also found higher communicability and coherence brain measures during DBS ON compared to DBS OFF. Finally, by modeling stimulation we identified possible novel DBS targets. These results offer important insights into the underlying effects of DBS, which may in time offer a route to more efficacious treatments.


Author(s):  
Thea Knowles ◽  
Scott G. Adams ◽  
Mandar Jog

Purpose The purpose of this study was to quantify changes in acoustic distinctiveness in two groups of talkers with Parkinson's disease as they modify across a wide range of speaking rates. Method People with Parkinson's disease with and without deep brain stimulation and older healthy controls read 24 carrier phrases at different speech rates. Target nonsense words in the carrier phrases were designed to elicit stop consonants and corner vowels. Participants spoke at seven self-selected speech rates from very slow to very fast, elicited via magnitude production. Speech rate was measured in absolute words per minute and as a proportion of each talker's habitual rate. Measures of segmental distinctiveness included a temporal consonant measure, namely, voice onset time, and a spectral vowel measure, namely, vowel articulation index. Results All talkers successfully modified their rate of speech from slow to fast. Talkers with Parkinson's disease and deep brain stimulation demonstrated greater baseline speech impairment and produced smaller proportional changes at the fast end of the continuum. Increasingly slower speaking rates were associated with increased temporal contrasts (voice onset time) but not spectral contrasts (vowel articulation). Faster speech was associated with decreased contrasts in both domains. Talkers with deep brain stimulation demonstrated more aberrant productions across all speaking rates. Conclusions Findings suggest that temporal and spectral segmental distinctiveness are asymmetrically affected by speaking rate modifications in Parkinson's disease. Talkers with deep brain stimulation warrant further investigation with regard to speech changes they make as they adjust their speaking rate.


2016 ◽  
Vol 27 (5) ◽  
pp. 549-555 ◽  
Author(s):  
Jacob J. Crouse ◽  
Joseph R. Phillips ◽  
Marjan Jahanshahi ◽  
Ahmed A. Moustafa

AbstractPostural instability (PI) is one of the most debilitating motor symptoms of Parkinson’s disease (PD), as it is associated with an increased risk of falls and subsequent medical complications (e.g. fractures), fear of falling, decreased mobility, self-restricted physical activity, social isolation, and decreased quality of life. The pathophysiological mechanisms underlying PI in PD remain elusive. This short review provides a critical summary of the literature on PI in PD, covering the clinical features, the neural and cognitive substrates, and the effects of dopaminergic medications and deep brain stimulation. The delayed effect of dopaminergic medication combined with the success of extrastriatal deep brain stimulation suggests that PI involves neurotransmitter systems other than dopamine and brain regions extending beyond the basal ganglia, further challenging the traditional view of PD as a predominantly single-system neurodegenerative disease.


2014 ◽  
Vol 120 (1) ◽  
pp. 140-151 ◽  
Author(s):  
Vincent A. Jourdain ◽  
Gastón Schechtmann ◽  
Thérèse Di Paolo

Parkinson's disease (PD) is a neurodegenerative condition that can be pharmacologically treated with levodopa. However, important motor and nonmotor symptoms appear with its long-term use. The subthalamic nucleus (STN) is known to be involved in the pathophysiology of PD and to contribute to levodopa-induced complications. Surgery is considered in patients who have advanced PD that is refractory to pharmacotherapy and who display disabling dyskinesia. Deep brain stimulation of the STN is currently the main surgical procedure for PD, but lesioning is still performed. This review covers the clinical aspects and complications of subthalamotomy as one of the lesion-based options for PD patients with levodopa-induced dyskinesias. Moreover, the authors discuss the possible effects of subthalamic lesioning.


2020 ◽  
Vol 10 (11) ◽  
pp. 809
Author(s):  
Jeremy Watts ◽  
Anahita Khojandi ◽  
Oleg Shylo ◽  
Ritesh A. Ramdhani

Deep brain stimulation (DBS) is a surgical treatment for advanced Parkinson’s disease (PD) that has undergone technological evolution that parallels an expansion in clinical phenotyping, neurophysiology, and neuroimaging of the disease state. Machine learning (ML) has been successfully used in a wide range of healthcare problems, including DBS. As computational power increases and more data become available, the application of ML in DBS is expected to grow. We review the literature of ML in DBS and discuss future opportunities for such applications. Specifically, we perform a comprehensive review of the literature from PubMed, the Institute for Scientific Information’s Web of Science, Cochrane Database of Systematic Reviews, and Institute of Electrical and Electronics Engineers’ (IEEE) Xplore Digital Library for ML applications in DBS. These studies are broadly placed in the following categories: (1) DBS candidate selection; (2) programming optimization; (3) surgical targeting; and (4) insights into DBS mechanisms. For each category, we provide and contextualize the current body of research and discuss potential future directions for the application of ML in DBS.


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