Browsing by Subject "Deep brain stimulation"

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    Advanced methodologies for neuromodulation and quantitative MRI with MB-SWIFT
    (2023) WU, Lin
    Introduction: Deep Brain Stimulation (DBS) treatment for Alzheimer’s disease (AD) is becoming increasingly evident. In this study, we exploited a novel orientation-selective (OS) strategy recently introduced by our group for DBS, entitled orientation-selective DBS (OS-DBS). This strategy entails that, by using multiple contacts with independent current sources within a multi-electrode array, the electric field can be oriented along any desired orientation in space. Therefore, axons parallel to the electric field spatial gradients are preferentially activated. Moreover, we applied the OS methodology to epidural spinal cord stimulation. In order to detect pathological processes of AD non-invasively with magnetic resonance imaging (MRI) technology, an alternating Look-Locker (aLL) method was developed to study novel MRI biomarkers such as T1? based on rotating frame MRI methods tailored to reveal neurodegeneration. Objectives and Methods: 1) For OS-ESCS, we introduced a similar OS approach for ESCS, and demonstrated orientation dependent brain activations as detected by brain fMRI. 2) To study OS-DBS of the subthalamic nucleus (STN), AD related targets including the entorhinal cortex (EC) and medial septal nucleus (MSN), to demonstrate the basic principle of OS and prove its feasibility and advantage in optimizing the stimulation of the target. Here, OS-DBS with a three-channel electrode was utilized to stimulate the rat STN, EC, and MSN to modulate the activation of brain networks connected to the stimulation sites. The induced brain activity was monitored with fMRI by Multi-Band Sweep Imaging with Fourier Transformation (MB-SWIFT) readout at 9.4 T. 3) The aLL method was proposed to perform simultaneous quantitative T1 and T1?, or T1 and B1 3D MRI mapping. Look-Locker scheme that alternates magnetization from the laboratory frame’s +Z and -Z axes is combined with a 3D MB-SWIFT readout. The analytical solution describing the spin evolution during aLL and the correction required for segmented acquisition were derived. The simultaneous B1 and T1 mapping were demonstrated on a phantom. T1? values in the rat brain in vivo and the Gd-DTPA phantom were compared to those obtained with a previously introduced steady–state (SS) method. Results: 1) For ESCS, orientation dependent activations were detected in brain areas that transmit the motor and sensory information. 2) OS-DBS of the STN reached maximal activation of related brain areas in correspondence with an in-plane 180° stimulation angle, which was consistent with the main mediolateral direction of the STN fibers confirmed with high resolution diffusion imaging and histology. Varying the in-plane OS-DBS stimulation angle in the EC resulted in the modulation of multiple downstream brain areas involved in memory and cognition. In contrast, no angle dependence of brain activation was observed when stimulating the MSN, consistent with predictions based on the electrode configuration and on the main axonal directions of the targets derived from diffusion MRI tractography and histology. 3) The aLL method allows for simultaneous T1 and B1 mapping, while the aLL method with the application of MP modules can provide simultaneous T1 and T1? maps. T1? values were similar with both aLL and SS techniques. However, aLL resulted in more robust quantitative mapping as compared with the SS method and provided the advantage of generating T1 maps in a single acquisition. Conclusions: 1) OS-ESCS allows the targeting of spinal fibers of different orientations, ultimately making stimulation less dependent on the precision of the electrode implantation. 2) OS-DBS stimulation angle modulates the activation of brain areas relevant to AD and Parkinson’s disease (PD), thus holding great promise for DBS treatment of the diseases. 3) The proposed aLL method offers a new flexible tool for quantitative T1, T1?, and B1 mappings.
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    Advances in Bidirectional Deep Brain Stimulation Interfaces
    (2014-12) Connolly, Allison
    Deep brain stimulation (DBS) is a neurosurgical therapy for Parkinson's disease that involves the implantation of a four contact lead into subcortical brain structures for delivering continuous, high frequency electrical stimulation. This doctoral dissertation has aimed to advance DBS technology for the treatment of Parkinson's disease by: 1) elucidating biomarkers of the disease and DBS therapy, 2) evaluating novel, 32 contact high-density electrode arrays to improve sensing and stimulation within the basal ganglia, and 3) developing computational algorithms that can capture complex neurophysiological interactions in high-dimensional feature spaces of these biomarkers. The primary studies employed the MPTP non-human primate model of Parkinsonism to invasively probe how neural oscillations in the form of local field potentials (LFPs) are modulated in conjunction with disease severity, therapies, and behavior. These results demonstrate that high-density electrode arrays are superior to the current state- of-the-art, because they improve the spatial selectivity of sensing LFPs and enable the delivery of directional stimulation. Subsequently, I have shown how non-invasive imag- ing techniques and commercially available implantable devices could be used to study Parkinson's disease in patients. Ultimately, these results motivate the use of higher-density DBS leads for sensing and stimulation, and facilitate the implementation of more complex therapeutic algorithms, such as closed-loop stimulation.
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    Development of Computational Models of Pedunculopontine Nucleus Stimulation for Clinical Trials and Mechanistic Studies
    (2016-03) Zitella Verbick, Laura
    Deep brain stimulation (DBS) in the pedunculopontine nucleus (PPN), a component of the mesencephalic locomotor region in the brainstem, has been proposed to alleviate gait and balance disturbances associated with Parkinson’s disease; however, clinical trials results have been highly inconsistent. Such variability may stem from inaccurate targeting in the PPN region, modulation of fiber pathways implicated in side effects, and lack of understanding of the modulatory effects of DBS in the brainstem. Here, we describe the development and refinement of computational models that can predict the neuromodulatory effects of PPN-DBS in both the non-human primate and human. These models included (1) brain atlas-based models that combined detailed biophysically realistic neuron and axon models with a finite element model simulating the voltage distribution in the brain during DBS, (2) high-field 7T MRI techniques to visualize and create volumetric morphologies of structures in the brainstem for use in the models, and (3) clinically relevant subject-specific computational models that incorporate the anisotropic conductivity of the brain tissue. Based on the validated results of these models, we can conclude that the neuronal pathways modulated by DBS in the brainstem are highly sensitive to both lead location and stimulation parameters. These computational models of DBS will be useful in future clinical trials, both prospectively to plan DBS lead trajectories and improve stimulation titration and retrospectively to investigate the underlying mechanisms of therapy and side effects of stimulation.
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    Factors Contributing to Rigidity Expression and Response to Pallidal Deep Brain Stimulation in People with Parkinson’s Disease
    (2021-09) Linn-Evans, Maria
    Parkinson’s disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic cells in the substantia nigra, buildup of alpha-synuclein in specific regions of the brain, and the emergence of cardinal motor symptoms including rigidity, slowness of movement, tremor, and gait dysfunction. Despite these shared characteristics, there is a great deal of heterogeneity in symptom presentation and response to therapies within the population of individuals with PD. Understanding the driving factors behind this heterogeneity is crucial for developing targeted and effective therapies for the disease and improving outcomes for those living with Parkinson’s disease. In this dissertation, two studies are described: 1) an investigation into the effects of rapid eye movement (REM) sleep without atonia (RSWA) on the presentation of rigidity in a population of individuals with mild-to-moderate Parkinson’s disease and 2) the development and implementation of a computational model of pallidal deep brain stimulation (GP-DBS) to identify neural pathways associated with rigidity suppression in individuals with PD. Both studies utilize a quantitative measure of rigidity as a tool to assess symptom severity. In the first study, our findings demonstrate that people with mild to moderate PD and RSWA have dysfunctional regulation of muscle tone during both sleep and wakefulness. The results show that the presence of RSWA is associated with increased forearm rigidity magnitude and symmetry. In the second study, a patient-specific computational model of GP-DBS was developed and implemented. By combining pathway activation estimates from the model with quantitative measurements of rigidity, the analyses identified the internal capsule as an important pathway for reducing parkinsonian rigidity. In particular, profound decreases in rigidity were associated with activation of internal capsule fibers projecting from Brodmann’s area 6, which contains axons from premotor cortex and supplementary motor area. The results of these studies reveal the importance of understanding factors like RSWA that may drive heterogeneity in PD, while also identifying potential pipelines for developing symptom-specific targets for treatment.
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    Using Phase Response Curves to Optimize Deep Brain Stimulation
    (2016-04) Becker, Abbey
    Deep brain stimulation (DBS) is a neuromodulation therapy effective at treating motor symptoms of patients with Parkinson’s disease (PD). Currently, an open-loop approach is used to set stimulus parameters, where stimulation settings are programmed by a clinician using a time intensive trial-and-error process. There is a need for a systematic approach to tuning stimulation parameters based on a patient’s physiology. An effective biomarker in the recorded neural signal is needed for this approach. It is hypothesized that DBS may work by disrupting enhanced oscillatory activity seen in PD. In this thesis I propose and provide evidence for using a simple measure, called a phase response curve, to systematically tune stimulation parameters and develop novel approaches to stimulation to suppress pathological oscillations. In this work I show that PRCs can be used to optimize stimulus frequency, waveform, and stimulus phase to disrupt a pathological oscillation in a computational model of Parkinson’s disease and/or to disrupt entrainment of single neurons in vitro. This approach has the potential to improve efficacy and reduce post-operative programming time.
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    Using Quantified Motor Behavior Outcomes to Improve Deep Brain Stimulation in Parkinson’s Disease
    (2020-06) Louie, Kenneth
    Deep brain stimulation (DBS) is a highly effective therapeutic option for Parkinson’s disease (PD). However, it can take 50 or more hours to obtain stimulation settings that optimally treat a patient’s symptoms. Additionally, axial symptoms, such as gait, are not adequately treated in the long term. In my work I explore the use of quantified motor behavior outcomes to reduce the time needed to obtain optimal stimulation parameters, and to develop a novel stimulation delivery approaches to better treat gait. First, I tested a Bayesian optimization approach to quickly and accurately model the input/output response of rigidity to stimulation frequency. I found, for PD patients that have a high degree of rigidity, Bayesian optimization models their response needing fewer samples than a traditional trial-and-error approach. Next, I tested a novel closed-loop stimulation delivery approach that delivered short duration pulse trains at specific phases of gait. I found that the patients that respond strongly to this type of stimulation delivery have a worse gait with their clinical settings. Overall, many patients saw small changes to their gait with this approach. Lastly, I analyzed the effects of turning stimulation on and off on gait. I found that a repeated measures of gait with short duration, 1 minute, wash-in and -out can detect significant changes. This is in contrast to previous reports that significant changes are only seen between 30-60 minutes. Through these studies I demonstrate the use of quantified motor behavior outcomes to improve DBS for PD.