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- Creators: Abbas, James
Description
The efficacy of deep brain stimulation (DBS) in Parkinson's disease (PD) has been convincingly demonstrated in studies that compare motor performance with and without stimulation, but characterization of performance at intermediate stimulation amplitudes has been limited. This study investigated the effects of changing DBS amplitude in order to assess dose-response characteristics, inter-subject variability, consistency of effect across outcome measures, and day-to-day variability. Eight subjects with PD and bilateral DBS systems were evaluated at their clinically determined stimulation (CDS) and at three reduced amplitude conditions: approximately 70%, 30%, and 0% of the CDS (MOD, LOW, and OFF, respectively). Overall symptom severity and performance on a battery of motor tasks - gait, postural control, single-joint flexion-extension, postural tremor, and tapping - were assessed at each condition using the motor section of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and quantitative measures. Data were analyzed to determine whether subjects demonstrated a threshold response (one decrement in stimulation resulted in ≥ 70% of the maximum change) or a graded response to reduced stimulation. Day-to-day variability was assessed using the CDS data from the three testing sessions. Although the cohort as a whole demonstrated a graded response on several measures, there was high variability across subjects, with subsets exhibiting graded, threshold, or minimal responses. Some subjects experienced greater variability in their CDS performance across the three days than the change induced by reducing stimulation. For several tasks, a subset of subjects exhibited improved performance at one or more of the reduced conditions. Reducing stimulation did not affect all subjects equally, nor did it uniformly affect each subject's performance across tasks. These results indicate that altered recruitment of neural structures can differentially affect motor capabilities and demonstrate the need for clinical consideration of the effects on multiple symptoms across several days when selecting DBS parameters.
ContributorsConovaloff, Alison (Author) / Abbas, James (Thesis advisor) / Krishnamurthi, Narayanan (Committee member) / Mahant, Padma (Committee member) / Jung, Ranu (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
In order to successfully implement a neural prosthetic system, it is necessary to understand the control of limb movements and the representation of body position in the nervous system. As this development process continues, it is becoming increasingly important to understand the way multiple sensory modalities are used in limb representation. In a previous study, Shi et al. (2013) examined the multimodal basis of limb position in the superior parietal lobule (SPL) as monkeys reached to and held their arm at various target locations in a frontal plane. Visual feedback was withheld in half the trials, though non-visual (i.e. somatic) feedback was available in all trials. Previous analysis showed that some of the neurons were tuned to limb position and that some neurons had their response modulated by the presence or absence of visual feedback. This modulation manifested in decreases in firing rate variability in the vision condition as compared to nonvision. The decreases in firing rate variability, as shown through decreases in both the Fano factor of spike counts and the coefficient of variation of the inter-spike intervals, suggested that changes were taking place in both trial-by-trial and intra-trial variability. I sought to further probe the source of the change in intra-trial variability through spectral analysis. It was hypothesized that the presence of temporal structure in the vision condition would account for a regularity in firing that would have decreased intra-trial variability. While no peaks were apparent in the spectra, differences in spectral power between visual conditions were found. These differences are suggestive of unique temporal spiking patterns at the individual neuron level that may be influential at the population level.
ContributorsDyson, Keith (Author) / Buneo, Christopher A (Thesis advisor) / Helms-Tillery, Stephen I (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following issues pose significant challenges as brain tissue is both functionally and structurally dynamic: a) time varying mechanical properties of the brain tissue-microelectrode interface due to the hyperelastic, viscoelastic nature of brain tissue b) non-stationarities in the neural signal caused by mechanical and physiological events in the interface and c) the lack of visual feedback of microelectrode position in brain tissue. A closed loop control algorithm is proposed here for autonomous navigation of microelectrodes in brain tissue while optimizing the signal-to-noise ratio of multi-unit neural recordings. The algorithm incorporates a quantitative understanding of constitutive mechanical properties of soft viscoelastic tissue like the brain and is guided by models that predict stresses developed in brain tissue during movement of the microelectrode. An optimal movement strategy is developed that achieves precise positioning of microelectrodes in the brain by minimizing the stresses developed in the surrounding tissue during navigation and maximizing the speed of movement. Results of testing the closed-loop control paradigm in short-term rodent experiments validated that it was possible to achieve a consistently high quality SNR throughout the duration of the experiment. At the systems level, new generation of MEMS actuators for movable microelectrode array are characterized and the MEMS device operation parameters are optimized for improved performance and reliability. Further, recommendations for packaging to minimize the form factor of the implant; design of device mounting and implantation techniques of MEMS microelectrode array to enhance the longevity of the implant are also included in a top-down approach to achieve a reliable brain interface.
ContributorsAnand, Sindhu (Author) / Muthuswamy, Jitendran (Thesis advisor) / Tillery, Stephen H (Committee member) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
The basal ganglia are four sub-cortical nuclei associated with motor control and reward learning. They are part of numerous larger mostly segregated loops where the basal ganglia receive inputs from specific regions of cortex. Converging on these inputs are dopaminergic neurons that alter their firing based on received and/or predicted rewarding outcomes of a behavior. The basal ganglia's output feeds through the thalamus back to the areas of the cortex where the loop originated. Understanding the dynamic interactions between the various parts of these loops is critical to understanding the basal ganglia's role in motor control and reward based learning. This work developed several experimental techniques that can be applied to further study basal ganglia function. The first technique used micro-volume injections of low concentration muscimol to decrease the firing rates of recorded neurons in a limited area of cortex in rats. Afterwards, an artificial cerebrospinal fluid flush was injected to rapidly eliminate the muscimol's effects. This technique was able to contain the effects of muscimol to approximately a 1 mm radius volume and limited the duration of the drug effect to less than one hour. This technique could be used to temporarily perturb a small portion of the loops involving the basal ganglia and then observe how these effects propagate in other connected regions. The second part applied self-organizing maps (SOM) to find temporal patterns in neural firing rate that are independent of behavior. The distribution of detected patterns frequency on these maps can then be used to determine if changes in neural activity are occurring over time. The final technique focused on the role of the basal ganglia in reward learning. A new conditioning technique was created to increase the occurrence of selected patterns of neural activity without utilizing any external reward or behavior. A pattern of neural activity in the cortex of rats was selected using an SOM. The pattern was then reinforced by being paired with electrical stimulation of the medial forebrain bundle triggering dopamine release in the basal ganglia. Ultimately, this technique proved unsuccessful possibly due to poor selection of the patterns being reinforced.
ContributorsBaldwin, Nathan Aaron (Author) / Helms Tillery, Stephen I (Thesis advisor) / Castaneda, Edward (Committee member) / Buneo, Christopher A (Committee member) / Muthuswamy, Jitendran (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014
Description
Flow measurement has always been one of the most critical processes in many industrial and clinical applications. The dynamic behavior of flow helps to define the state of a process. An industrial example would be that in an aircraft, where the rate of airflow passing the aircraft is used to determine the speed of the plane. A clinical example would be that the flow of a patient's breath which could help determine the state of the patient's lungs. This project is focused on the flow-meter that are used for airflow measurement in human lungs. In order to do these measurements, resistive-type flow-meters are commonly used in respiratory measurement systems. This method consists of passing the respiratory flow through a fluid resistive component, while measuring the resulting pressure drop, which is linearly related to volumetric flow rate. These types of flow-meters typically have a low frequency response but are adequate for most applications, including spirometry and respiration monitoring. In the case of lung parameter estimation methods, such as the Quick Obstruction Method, it becomes important to have a higher frequency response in the flow-meter so that the high frequency components in the flow are measurable. The following three types of flow-meters were: a. Capillary type b. Screen Pneumotach type c. Square Edge orifice type To measure the frequency response, a sinusoidal flow is generated with a small speaker and passed through the flow-meter that is connected to a large, rigid container. True flow is proportional to the derivative of the pressure inside the container. True flow is then compared with the measured flow, which is proportional to the pressure drop across the flow-meter. In order to do the characterization, two LabVIEW data acquisition programs have been developed, one for transducer calibration, and another one that records flow and pressure data for frequency response testing of the flow-meter. In addition, a model that explains the behavior exhibited by the flow-meter has been proposed and simulated. This model contains a fluid resistor and inductor in series. The final step in this project was to approximate the frequency response data to the developed model expressed as a transfer function.
ContributorsHu, Jianchen (Author) / Macia, Narciso (Thesis advisor) / Pollat, Scott (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2013
Description
Gait and balance disorders are the second leading cause of falls in the elderly. Investigating the changes in static and dynamic balance due to aging may provide a better understanding of the effects of aging on postural control system. Static and dynamic balance were evaluated in a total of 21 young (21-35 years) and 22 elderly (50-75 years) healthy subjects while they performed three different tasks: quiet standing, dynamic weight shifts, and over ground walking. During the quiet standing task, the subjects stood with their eyes open and eyes closed. When performing dynamic weight shifts task, subjects shifted their Center of Pressure (CoP) from the center target to outward targets and vice versa while following real-time feedback of their CoP. For over ground walking tasks, subjects performed Timed Up and Go test, tandem walking, and regular walking at their self-selected speed. Various quantitative balance and gait measures were obtained to evaluate the above respective balance and walking tasks. Total excursion, sway area, and mean frequency of CoP during quiet standing were found to be the most reliable and showed significant increase with age and absence of visual input. During dynamic shifts, elderly subjects exhibited higher initiation time, initiation path length, movement time, movement path length, and inaccuracy indicating deterioration in performance. Furthermore, the elderly walked with a shorter stride length, increased stride variability, with a greater turn and turn-to-sit duration. Significant correlations were also observed between measures derived from the different balance and gait tasks. Thus, it can be concluded that aging deteriorates the postural control system affecting static and dynamic balance and some of the alterations in CoP and gait measures may be considered as protective mechanisms to prevent loss of balance.
ContributorsBalasubramanian, Shruthi (Author) / Krishnamurthi, Narayanan (Thesis advisor) / Abbas, James (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2014
Description
Although tremor, rigidity, and bradykinesia are cardinal symptoms of Parkinson's disease (PD), impairments of gait and balance significantly affect quality of life, especially as the disease progresses, and do not respond well to anti-parkinsonism medications. Many studies have shown that people with PD can walk better when appropriate cues are presented but, to the best of our knowledge, the effects of real-time feedback of step length and uprightness of posture on gait and posture have not been specifically investigated. If it can be demonstrated that real-time feedback can improve posture and gait, the resultant knowledge could be used to design effective rehabilitation strategies to improve quality of life in this population.
In this feasibility study, we have developed a treadmill-based experimental paradigm to provide feedback of step length and upright posture in real-time. Ten subjects (mean age 65.9 ± 7.6 years) with mild to moderate PD (Hoehn and Yahr stage III or below) were evaluated in their ability to successfully utilize real-time feedback presented during quiet standing and treadmill walking tasks during a single data collection session in their medication-on state. During quiet standing tasks in which back angle feedback was provided, subjects were asked to utilize the feedback to maintain upright posture. During treadmill walking tasks, subjects walked at their self-selected speed for five minutes without feedback, with feedback of back angle, or with feedback of step length. During walking tasks with back angle feedback, subjects were asked to utilize the feedback to maintain upright posture. During walking tasks with step length feedback, subjects were asked to utilize the feedback to walk with increased step length. During quiet standing tasks, measurements of back angle were obtained; during walking tasks, measurements of back angle, step length, and step time were obtained.
Subjects stood and walked with significantly increased upright posture during the tasks with real-time back angle feedback compared to tasks without feedback. Similarly, subjects walked with significantly increased step length during tasks with real-time step length feedback compared to tasks without feedback. These results demonstrate that people with PD can utilize real-time feedback to improve upright posture and gait.
In this feasibility study, we have developed a treadmill-based experimental paradigm to provide feedback of step length and upright posture in real-time. Ten subjects (mean age 65.9 ± 7.6 years) with mild to moderate PD (Hoehn and Yahr stage III or below) were evaluated in their ability to successfully utilize real-time feedback presented during quiet standing and treadmill walking tasks during a single data collection session in their medication-on state. During quiet standing tasks in which back angle feedback was provided, subjects were asked to utilize the feedback to maintain upright posture. During treadmill walking tasks, subjects walked at their self-selected speed for five minutes without feedback, with feedback of back angle, or with feedback of step length. During walking tasks with back angle feedback, subjects were asked to utilize the feedback to maintain upright posture. During walking tasks with step length feedback, subjects were asked to utilize the feedback to walk with increased step length. During quiet standing tasks, measurements of back angle were obtained; during walking tasks, measurements of back angle, step length, and step time were obtained.
Subjects stood and walked with significantly increased upright posture during the tasks with real-time back angle feedback compared to tasks without feedback. Similarly, subjects walked with significantly increased step length during tasks with real-time step length feedback compared to tasks without feedback. These results demonstrate that people with PD can utilize real-time feedback to improve upright posture and gait.
ContributorsJellish, Jeremy (Author) / Abbas, James (Thesis advisor) / Krishnamurthi, Narayanan (Thesis advisor) / Ingalls, Todd (Committee member) / Arizona State University (Publisher)
Created2014
Description
An accurate sense of upper limb position is crucial to reaching movements where sensory information about upper limb position and target location is combined to specify critical features of the movement plan. This dissertation was dedicated to studying the mechanisms of how the brain estimates the limb position in space and the consequences of misestimation of limb position on movements. Two independent but related studies were performed. The first involved characterizing the neural mechanisms of limb position estimation in the non-human primate brain. Single unit recordings were obtained in area 5 of the posterior parietal cortex in order to examine the role of this area in estimating limb position based on visual and somatic signals (proprioceptive, efference copy). When examined individually, many area 5 neurons were tuned to the position of the limb in the workspace but very few neurons were modulated by visual feedback. At the population level however decoding of limb position was somewhat more accurate when visual feedback was provided. These findings support a role for area 5 in limb position estimation but also suggest that visual signals regarding limb position are only weakly represented in this area, and only at the population level. The second part of this dissertation focused on the consequences of misestimation of limb position for movement production. It is well known that limb movements are inherently variable. This variability could be the result of noise arising at one or more stages of movement production. Here we used biomechanical modeling and simulation techniques to characterize movement variability resulting from noise in estimating limb position ('sensing noise') and in planning required movement vectors ('planning noise'), and compared that to the variability expected due to noise in movement execution. We found that the effects of sensing and planning related noise on movement variability were dependent upon both the planned movement direction and the initial configuration of the arm and were different in many respects from the effects of execution noise.
ContributorsShi, Ying (Author) / Buneo, Christopher A (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Santello, Marco (Committee member) / He, Jiping (Committee member) / Santos, Veronica (Committee member) / Arizona State University (Publisher)
Created2011
Description
The ability to plan, execute, and control goal oriented reaching and grasping movements is among the most essential functions of the brain. Yet, these movements are inherently variable; a result of the noise pervading the neural signals underlying sensorimotor processing. The specific influences and interactions of these noise processes remain unclear. Thus several studies have been performed to elucidate the role and influence of sensorimotor noise on movement variability. The first study focuses on sensory integration and movement planning across the reaching workspace. An experiment was designed to examine the relative contributions of vision and proprioception to movement planning by measuring the rotation of the initial movement direction induced by a perturbation of the visual feedback prior to movement onset. The results suggest that contribution of vision was relatively consistent across the evaluated workspace depths; however, the influence of vision differed between the vertical and later axes indicate that additional factors beyond vision and proprioception influence movement planning of 3-dimensional movements. If the first study investigated the role of noise in sensorimotor integration, the second and third studies investigate relative influence of sensorimotor noise on reaching performance. Specifically, they evaluate how the characteristics of neural processing that underlie movement planning and execution manifest in movement variability during natural reaching. Subjects performed reaching movements with and without visual feedback throughout the movement and the patterns of endpoint variability were compared across movement directions. The results of these studies suggest a primary role of visual feedback noise in shaping patterns of variability and in determining the relative influence of planning and execution related noise sources. The final work considers a computational approach to characterizing how sensorimotor processes interact to shape movement variability. A model of multi-modal feedback control was developed to simulate the interaction of planning and execution noise on reaching variability. The model predictions suggest that anisotropic properties of feedback noise significantly affect the relative influence of planning and execution noise on patterns of reaching variability.
ContributorsApker, Gregory Allen (Author) / Buneo, Christopher A (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Santello, Marco (Committee member) / Santos, Veronica (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2012
Description
Spinal cord injury (SCI) disrupts the communication between supraspinal circuits and spinal circuits distal to the injury. This disruption causes changes in the motor abilities of the affected individual, but it can also be used as an opportunity to study motor control in the absence or limited presence of control from the brain. In the case of incomplete paraplegia, locomotion is impaired and often results in increased incidence of foot drag and decreased postural stability after injury. The overall goal of this work is to understand how changes in kinematics of movement and neural control of muscles effect locomotor coordination following SCI. Toward this end, we examined musculoskeletal parameters and kinematics of gait in rats with and without incomplete SCI (iSCI) and used an empirically developed computational model to test related hypotheses. The first study tested the hypothesis that iSCI causes a decrease in locomotor and joint angle movement complexity. A rat model was used to measure musculoskeletal properties and gait kinematics following mild iSCI. The data indicated joint-specific changes in kinematics in the absence of measurable muscle atrophy, particularly at the ankle as a result of the injury. Kinematic changes manifested as a decrease in complexity of ankle motion as indicated by measures of permutation entropy. In the second study, a new 2-dimensional computational model of the rat ankle combining forward and inverse dynamics was developed using the previously collected data. This model was used to test the hypothesis that altered coordination of flexor and extensor muscles (specifically alteration in burst shape and timing) acting at the ankle joint could be responsible for increases in incidence of foot drag following injury. Simulation results suggest a time course for changes in neural control following injury that begins with foot drag and decreased delay between antagonistic muscle activations. Following this, beneficial adaptations in muscle activation profile and ankle kinematics counteract the decreased delay to allow foot swing. In both studies, small changes in neural control caused large changes in behavior, particularly at the ankle. Future work will further examine the role of neural control of hindlimb in rat locomotion following iSCI.
ContributorsHillen, Brian (Author) / Jung, Ranu (Thesis advisor) / Abbas, James (Committee member) / Muthuswamy, Jit (Committee member) / Jindrich, Devin (Committee member) / Yamaguchi, Gary (Committee member) / Arizona State University (Publisher)
Created2012