Modeling Deep Brain Stimulation for Parkinson's Disease

Lowery, Madeleine M.

doi:10.1002/9781119159193.ch9

Cited by 5 publications

(4 citation statements)

References 62 publications

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“…Frequency and voltage values are not comparable without considering the location of the electrodes and the entirety of the DBS settings. They become comparable only when they are inserted in complex nonlinear biophysical volume conductor models, that are tted to each patient's anatomy to approximate the anatomical extent of the stimulation [32,33].…”

Section: Discussionmentioning

confidence: 99%

Does Vestibular Motion Perception Correlate with Axonal Pathways Stimulated by Subthalamic Deep Brain Stimulation in Parkinson’s Disease?

et al. 2023

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Perception of our linear motion -heading -is critical for postural control, gait, and locomotion, and it is impaired in Parkinson's Disease (PD). Deep brain stimulation (DBS) has variable effects on vestibular heading perception, depending on the location of the electrodes within the subthalamic nucleus (STN). Here, we aimed to nd the anatomical correlates of heading perception in PD. Fourteen PD participants with bilateral STN DBS performed a two-alternative forced-choice discrimination task where a motion platform delivered translational forward movements with a heading angle varying between 0 and 30 degrees to the left or to the right with respect to the straight-ahead direction. Using psychometric curves, we derived the heading discrimination threshold angle of each patient from the response data. We created patient-speci c DBS models and calculated the percentages of stimulated axonal pathways that are anatomically adjacent to the STN and known to play a major role in vestibular information processing. We performed correlation analyses to investigate the extent of these white matter tracts' involvement in heading perception. Signi cant positive correlations were identi ed between improved heading discrimination for rightward heading and the percentage of activated streamlines of the contralateral hyperdirect, pallido-subthalamic, and subthalamo-pallidal pathways. The hyperdirect pathways are thought to provide top-down control over STN connections to the cerebellum. In addition, STN may also antidromically activate collaterals of hyperdirect pathway that projects to the precerebellar pontine nuclei. In select cases there was strong activation of the cerebello-thalamic projections, but it was not consistently present in all participants. Large volumetric overlap between the volume of tissue activation and the STN in the left hemisphere positively impacted rightward heading perception. Altogether, the results suggest heavy involvement of basal ganglia cerebellar network in STN-induced modulation of vestibular heading perception in PD.

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Section: Discussionmentioning

confidence: 99%

Does Vestibular Motion Perception Correlate with Axonal Pathways Stimulated by Subthalamic Deep Brain Stimulation in Parkinson’s Disease?

et al. 2023

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“…Comparing the differences in the stimulation outcome of simple and more complex models could help to evaluate the important factors shaping the model response in the latter case. Such a model-based approach is aimed to assess and optimize the effects of DBS configurations, where both open-loop and closed-loop setups received much attention, see, for example, refs 28–41,45,66–68,71–73,85–90 , and recent comprehensive reviews 92,93 and references therein. Several sophisticated closed-loop control designs were suggested for DBS based on modulation of the stimulation waveform including stimulation timing, amplitude, spatiotemporal patterns of stimulation, and other parameters 94–100 .…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, antidromic activation of GPe projections and reentrant and reinforcement effects of HF DBS along the entire basal ganglia-thalamo-cortical motor loop may play an important role in the mechanism of DBS 83,111 . It is therefore necessary to extend the model from an isolated STN-GPe network to larger circuits 45,92,93,97,111,112 and, for instance, take into account the cortical involvement in the abnormal synchronization process 59 . However, the more detailed and complex a model is, the more difficult it gets to perform a systematic analysis of its dynamics and obtain reasonably reliable and general predictions.…”

Section: Discussionmentioning

confidence: 99%

Adaptive delivery of continuous and delayed feedback deep brain stimulation - a computational study

Popovych

Tass

2019

Sci Rep

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Adaptive deep brain stimulation (aDBS) is a closed-loop method, where high-frequency DBS is turned on and off according to a feedback signal, whereas conventional high-frequency DBS (cDBS) is delivered permanently. Using a computational model of subthalamic nucleus and external globus pallidus, we extend the concept of adaptive stimulation by adaptively controlling not only continuous, but also demand-controlled stimulation. Apart from aDBS and cDBS, we consider continuous pulsatile linear delayed feedback stimulation (cpLDF), specifically designed to induce desynchronization. Additionally, we combine adaptive on-off delivery with continuous delayed feedback modulation by introducing adaptive pulsatile linear delayed feedback stimulation (apLDF), where cpLDF is turned on and off using pre-defined amplitude thresholds. By varying the stimulation parameters of cDBS, aDBS, cpLDF, and apLDF we obtain optimal parameter ranges. We reveal a simple relation between the thresholds of the local field potential (LFP) for aDBS and apLDF, the extent of the stimulation-induced desynchronization, and the integral stimulation time required. We find that aDBS and apLDF can be more efficient in suppressing abnormal synchronization than continuous simulation. However, apLDF still remains more efficient and also causes a stronger reduction of the LFP beta burst length. Hence, adaptive on-off delivery may further improve the intrinsically demand-controlled pLDF.

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“…We provide a review of the quantitative approaches that have been recently developed for the treatment of PD via DBS, with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. Several modeling approaches have been proposed to describe the brain dynamics under PD and to personalize the DBS therapy, for example, see (Lowery, 2017) for a comprehensive overview. Our goal here is to review the implications and insights that have been gained by using a systems theoretical approach in association with these models to analyze the neural dynamics and optimize the DBS therapy via model-based techniques.…”

mentioning

confidence: 99%

Systems approaches to optimizing deep brain stimulation therapies in Parkinson’s disease

Santaniello

Gale

Sarma

2018

WIREs Mechanisms of Disease

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Over the last 30 years, deep brain stimulation (DBS) has been used to treat chronic neurological diseases like dystonia, obsessive-compulsive disorders, essential tremor, Parkinson's disease, and more recently, dementias, depression, cognitive disorders, and epilepsy. Despite its wide use, DBS presents numerous challenges for both clinicians and engineers. One challenge is the design of novel, more efficient DBS therapies, which are hampered by the lack of complete understanding about the cellular mechanisms of therapeutic DBS. Another challenge is the existence of redundancy in clinical outcomes, that is, different DBS programs can result in similar clinical benefits but very little information (e.g., predictive models, longitudinal data, metrics, etc.) is available to select one program over another. Finally, there is high variability in patients' responses to DBS, which forces clinicians to carefully adjust the stimulation settings to each patient via lengthy programming sessions. Researchers in neural engineering and systems biology have been tackling these challenges over the past few years with the specific goal of developing novel DBS therapies, design methodologies, and computational tools that optimize the therapeutic effects of DBS in each patient. Furthermore, efforts are being made to automatically adapt the DBS treatment to the fluctuations of disease symptoms. A review of the quantitative approaches currently available for the treatment of Parkinson's disease is presented here with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. This article is categorized under: Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Computational Methods Analytical and Computational Methods > Dynamical Methods Physiology > Mammalian Physiology in Health and Disease.

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Modeling Deep Brain Stimulation for Parkinson's Disease

Cited by 5 publications

References 62 publications

Does Vestibular Motion Perception Correlate with Axonal Pathways Stimulated by Subthalamic Deep Brain Stimulation in Parkinson’s Disease?

Does Vestibular Motion Perception Correlate with Axonal Pathways Stimulated by Subthalamic Deep Brain Stimulation in Parkinson’s Disease?

Adaptive delivery of continuous and delayed feedback deep brain stimulation - a computational study

Systems approaches to optimizing deep brain stimulation therapies in Parkinson’s disease

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