Matching Items (6)
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- All Subjects: Motor Control
- All Subjects: neural recording
- Creators: Buneo, Christopher
- Creators: Rahman, Qasim
- Member of: Theses and Dissertations
- Resource Type: Text
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
Anticipatory planning of digit positions and forces is critical for successful dexterous object manipulation. Anticipatory (feedforward) planning bypasses the inherent delays in reflex responses and sensorimotor integration associated with reactive (feedback) control. It has been suggested that feedforward and feedback strategies can be distinguished based on the profile of grip and load force rates during the period between initial contact with the object and object lift. However, this has not been validated in tasks that do not constrain digit placement. The purposes of this thesis were (1) to validate the hypothesis that force rate profiles are indicative of the control strategy used for object manipulation and (2) to test this hypothesis by comparing manipulation tasks performed with and without digit placement constraints. The first objective comprised two studies. In the first study an additional light or heavy mass was added to the base of the object. In the second study a mass was added, altering the object's center of mass (CM) location. In each experiment digit force rates were calculated between the times of initial digit contact and object lift. Digit force rates were fit to a Gaussian bell curve and the goodness of fit was compared across predictable and unpredictable mass and CM conditions. For both experiments, a predictable object mass and CM elicited bell shaped force rate profiles, indicative of feedforward control. For the second objective, a comparison of performance between subjects who performed the grasp task with either constrained or unconstrained digit contact locations was conducted. When digit location was unconstrained and CM was predictable, force rates were well fit to a bell shaped curve. However, the goodness of fit of the force rate profiles to the bell shaped curve was weaker for the constrained than the unconstrained digit placement condition. These findings seem to indicate that brain can generate an appropriate feedforward control strategy even when digit placement is unconstrained and an infinite combination of digit placement and force solutions exists to lift the object successfully. Future work is needed that investigates the role digit positioning and tactile feedback has on anticipatory control of object manipulation.
ContributorsCooperhouse, Michael A (Author) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2011
Description
Intracellular voltage recordings from single neurons in vitro and in vivo have been fundamental to our understanding of neuronal function. Conventional electrodes and associated positioning systems for intracellular recording in vivo are large and bulky, which has largely restricted their use to single-channel recording from anesthetized animals. Further, intracellular recordings are very cumbersome, requiring a high degree of skill not readily achieved in a typical laboratory. This dissertation presents a robotic, head-mountable, MEMS (Micro-Electro-Mechanical Systems) based intracellular recording system to overcome the above limitations associated with form-factor, scalability and highly skilled and tedious manual operations required for intracellular recordings. This system combines three distinct technologies: 1) novel microscale, polycrystalline silicon-based electrode for intracellular recording, 2) electrothermal microactuators for precise microscale navigation of the electrode and 3) closed-loop control algorithm for autonomous movement and positioning of electrode inside single neurons. First, two distinct designs of polysilicon-based microscale electrodes were fabricated and tested for intracellular recordings. In the first approach, tips of polysilicon microelectrodes were milled to nanoscale dimensions (<300 nm) using focused ion beam (FIB) to develop polysilicon nanoelectrodes. Polysilicon nanoelectrodes recorded >1.5 mV amplitude, positive-going action potentials and synaptic potentials from neurons in the abdominal ganglion of Aplysia Californica. In the second approach, polysilicon microelectrodes were integrated with miniaturized glass micropipettes filled with electrolyte to fabricate glass-polysilicon microelectrodes. These electrodes consistently recorded high fidelity intracellular potentials from neurons in the abdominal ganglion of Aplysia Californica (Resting Potentials < -35 mV, Action Potentials > 60 mV) as well as the rat motor cortex (Resting Potentials < -50 mV). Next, glass-polysilicon microelectrodes were coupled with microscale electrothermal actuators and controller for autonomous intracellular recordings from single neurons in the abdominal ganglion. Consistent resting potentials (< -35 mV) and action potentials (> 60 mV) were recorded after each successful penetration attempt with the controller and microactuated glass-polysilicon microelectrodes. The success rate of penetration and quality of recordings achieved using electrothermal microactuators were comparable to that of conventional positioning systems. Finally, the feasibility of this miniaturized system to obtain intracellular recordings from single neurons in the motor cortex of rats in vivo is also demonstrated. The MEMS-based system offers significant advantages: 1) reduction in overall size for potential use in behaving animals, 2) scalable approach to potentially realize multi-channel recordings and 3) a viable method to fully automate measurement of intracellular recordings.
ContributorsSampath Kumar, Swathy (Author) / Muthuswamy, Jit (Thesis advisor) / Abbas, James (Committee member) / Hamm, Thomas (Committee member) / Christen, Jennifer Blain (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
Description
Motor behavior is prone to variable conditions and deviates further in disorders affecting the nervous system. A combination of environmental and neural factors impacts the amount of uncertainty. Although the influence of these factors on estimating endpoint positions have been examined, the role of limb configuration on endpoint variability has been mostly ignored. Characterizing the influence of arm configuration (i.e. intrinsic factors) would allow greater comprehension of sensorimotor integration and assist in interpreting exaggerated movement variability in patients. In this study, subjects were placed in a 3-D virtual reality environment and were asked to move from a starting position to one of three targets in the frontal plane with and without visual feedback of the moving limb. The alternating of visual feedback during trials increased uncertainty between the planning and execution phases. The starting limb configurations, adducted and abducted, were varied in separate blocks. Arm configurations were setup by rotating along the shoulder-hand axis to maintain endpoint position. The investigation hypothesized: 1) patterns of endpoint variability of movements would be dependent upon the starting arm configuration and 2) any differences observed would be more apparent in conditions that withheld visual feedback. The results indicated that there were differences in endpoint variability between arm configurations in both visual conditions, but differences in variability increased when visual feedback was withheld. Overall this suggests that in the presence of visual feedback, planning of movements in 3D space mostly uses coordinates that are arm configuration independent. On the other hand, without visual feedback, planning of movements in 3D space relies substantially on intrinsic coordinates.
ContributorsRahman, Qasim (Author) / Buneo, Christopher (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Motor behavior is prone to variable conditions and deviates further in disorders affecting the nervous system. A combination of environmental and neural factors impacts the amount of uncertainty. Although the influence of these factors on estimating endpoint positions have been examined, the role of limb configuration on endpoint variability has been mostly ignored. Characterizing the influence of arm configuration (i.e. intrinsic factors) would allow greater comprehension of sensorimotor integration and assist in interpreting exaggerated movement variability in patients. In this study, subjects were placed in a 3-D virtual reality environment and were asked to move from a starting position to one of three targets in the frontal plane with and without visual feedback of the moving limb. The alternating of visual feedback during trials increased uncertainty between the planning and execution phases. The starting limb configurations, adducted and abducted, were varied in separate blocks. Arm configurations were setup by rotating along the shoulder-hand axis to maintain endpoint position. The investigation hypothesized: 1) patterns of endpoint variability of movements would be dependent upon the starting arm configuration and 2) any differences observed would be more apparent in conditions that withheld visual feedback. The results indicated that there were differences in endpoint variability between arm configurations in both visual conditions, but differences in variability increased when visual feedback was withheld. Overall this suggests that in the presence of visual feedback, planning of movements in 3D space mostly uses coordinates that are arm configuration independent. On the other hand, without visual feedback, planning of movements in 3D space relies substantially on intrinsic coordinates.
ContributorsRahman, Qasim (Author) / Buneo, Christopher (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Long-term monitoring of deep brain structures using microelectrode implants is critical for the success of emerging clinical applications including cortical neural prostheses, deep brain stimulation and other neurobiology studies such as progression of disease states, learning and memory, brain mapping etc. However, current microelectrode technologies are not capable enough of reaching those clinical milestones given their inconsistency in performance and reliability in long-term studies. In all the aforementioned applications, it is important to understand the limitations & demands posed by technology as well as biological processes. Recent advances in implantable Micro Electro Mechanical Systems (MEMS) technology have tremendous potential and opens a plethora of opportunities for long term studies which were not possible before. The overall goal of the project is to develop large scale autonomous, movable, micro-scale interfaces which can seek and monitor/stimulate large ensembles of precisely targeted neurons and neuronal networks that can be applied for brain mapping in behaving animals. However, there are serious technical (fabrication) challenges related to packaging and interconnects, examples of which include: lack of current industry standards in chip-scale packaging techniques for silicon chips with movable microstructures, incompatible micro-bonding techniques to elongate current micro-electrode length to reach deep brain structures, inability to achieve hermetic isolation of implantable devices from biological tissue and fluids (i.e. cerebrospinal fluid (CSF), blood, etc.). The specific aims are to: 1) optimize & automate chip scale packaging of MEMS devices with unique requirements not amenable to conventional industry standards with respect to bonding, process temperature and pressure in order to achieve scalability 2) develop a novel micro-bonding technique to extend the length of current polysilicon micro-electrodes to reach and monitor deep brain structures 3) design & develop high throughput packaging mechanism for constructing a dense array of movable microelectrodes. Using a combination of unique micro-bonding technique which involves conductive thermosetting epoxy’s with hermetically sealed support structures and a highly optimized, semi-automated, 90-minute flip-chip packaging process, I have now extended the repertoire of previously reported movable microelectrode arrays to bond conventional stainless steel and Pt/Ir microelectrode arrays of desired lengths to steerable polysilicon shafts. I tested scalable prototypes in rigorous bench top tests including Impedance measurements, accelerated aging and non-destructive testing to assess electrical and mechanical stability of micro-bonds under long-term implantation. I propose a 3D printed packaging method allows a wide variety of electrode configurations to be realized such as a rectangular or circular array configuration or other arbitrary geometries optimal for specific regions of the brain with inter-electrode distance as low as 25 um with an unprecedented capability of seeking and recording/stimulating targeted single neurons in deep brain structures up to 10 mm deep (with 6 μm displacement resolution). The advantage of this computer controlled moveable deep brain electrodes facilitates potential capabilities of moving past glial sheath surrounding microelectrodes to restore neural connection, counter the variabilities in signal amplitudes, and enable simultaneous recording/stimulation at precisely targeted layers of brain.
ContributorsPalaniswamy, Sivakumar (Author) / Muthuswamy, Jitendran (Thesis advisor) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2016