Matching Items (76)
Description
There is a tremendous need for wireless biological signals acquisition for the microelectrode-based neural interface to reduce the mechanical impacts introduced by wire-interconnects system. Long wire connections impede the ability to continuously record the neural signal for chronic application from the rodent's brain. Furthermore, connecting and/or disconnecting Omnetics interconnects often introduces mechanical stress which causes blood vessel to rupture and leads to trauma to the brain tissue. Following the initial implantation trauma, glial tissue formation around the microelectrode and may possibly lead to the microelectrode signal degradation. The aim of this project is to design, develop, and test a compact and power efficient integrated system (IS) that is able to (a) wirelessly transmit triggering signal from the computer to the signal generator which supplies voltage waveforms that move the MEMS microelectrodes, (b) wirelessly transmit neural data from the brain to the external computer, and (c) provide an electrical interface for a closed loop control to continuously move the microelectrode till a proper quality of neural signal is achieved. One of the main challenges of this project is the limited data transmission rate of the commercially available wireless system to transmit 400 kbps of digitized neural signals/electrode, which include spikes, local field potential (LFP), and noise. A commercially available Bluetooth module is only capable to transmit at a total of 115 kbps data transfer rate. The approach to this challenge is to digitize the analog neural signal with a lower accuracy ADC to lower the data rate, so that is reasonable to wirelessly transfer neural data of one channel. In addition, due to the limited space and weight bearing capability to the rodent's head, a compact and power efficient integrated system is needed to reduce the packaged volume and power consumption. 3D SoP technology has been used to stack the PCBs in a 3D form-factor, proper routing designs and techniques are implemented to reduce the electrical routing resistances and the parasitic RC delay. It is expected that this 3D design will reduce the power consumption significantly in comparison to the 2D one. The progress of this project is divided into three different phases, which can be outlined as follow: a) Design, develop, and test Bluetooth wireless system to transmit the triggering signal from the computer to the signal generator. The system is designed for three moveable microelectrodes. b) Design, develop, and test Bluetooth wireless system to wirelessly transmit an amplified (200 gain) neural signal from one single electrode to an external computer. c) Design, develop, and test a closed loop control system that continuously moves a microelectrode in searching of an acceptable quality of neural spikes. The outcome of this project can be used not only for the need of neural application but also for a wider and general applications that requires customized signal generations and wireless data transmission.
ContributorsZhou, Li (Author) / Muthuswamy, Jitendran (Thesis advisor) / Sutanto, Jemmy (Thesis advisor) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012
Description
Neurostimulation methods currently include deep brain stimulation (DBS), optogenetic, transcranial direct-current stimulation (tDCS), and transcranial magnetic stimulation (TMS). TMS and tDCS are noninvasive techniques whereas DBS and optogenetic require surgical implantation of electrodes or light emitting devices. All approaches, except for optogenetic, have been implemented in clinical settings because they have demonstrated therapeutic utility and clinical efficacy for neurological and psychiatric disorders. When applied for therapeutic applications, these techniques suffer from limitations that hinder the progression of its intended use to treat compromised brain function. DBS requires an invasive surgical procedure that surfaces complications from infection, longevity of electrical components, and immune responses to foreign materials. Both TMS and tDCS circumvent the problems seen with DBS as they are noninvasive procedures, but they fail to produce the spatial resolution required to target specific brain structures. Realizing these restrictions, we sought out to use ultrasound as a neurostimulation modality. Ultrasound is capable of achieving greater resolution than TMS and tDCS, as we have demonstrated a ~2mm lateral resolution, which can be delivered noninvasively. These characteristics place ultrasound superior to current neurostimulation methods. For these reasons, this dissertation provides a developed protocol to use transcranial pulsed ultrasound (TPU) as a neurostimulation technique. These investigations implement electrophysiological, optophysiological, immunohistological, and behavioral methods to elucidate the effects of ultrasound on the central nervous system and raise questions about the functional consequences. Intriguingly, we showed that TPU was also capable of stimulating intact sub-cortical circuits in the anesthetized mouse. These data reveal that TPU can evoke synchronous oscillations in the hippocampus in addition to increasing expression of brain-derived neurotrophic factor (BDNF). Considering these observations, and the ability to noninvasively stimulate neuronal activity on a mesoscale resolution, reveals a potential avenue to be effective in clinical settings where current brain stimulation techniques have shown to be beneficial. Thus, the results explained by this dissertation help to pronounce the significance for these protocols to gain translational recognition.
ContributorsTufail, Yusuf Zahid (Author) / Tyler, William J (Thesis advisor) / Duch, Carsten (Committee member) / Muthuswamy, Jitendran (Committee member) / Santello, Marco (Committee member) / Tillery, Stephen H (Committee member) / Arizona State University (Publisher)
Created2011
Description
Computed tomography (CT) is one of the essential imaging modalities for medical diagnosis. Since its introduction in 1972, CT technology has been improved dramatically, especially in terms of its acquisition speed. However, the main principle of CT which consists in acquiring only density information has not changed at all until recently. Different materials may have the same CT number, which may lead to uncertainty or misdiagnosis. Dual-energy CT (DECT) was reintroduced recently to solve this problem by using the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between two low and high energy images or measurements, so that it is difficult to acquire the accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, a new model and an image enhancement technique for DECT are proposed, based on the fact that the attenuation of a high density material decreases more rapidly as X-ray energy increases. This fact has been previously ignored in most of DECT image enhancement techniques. The proposed technique consists of offset correction, spectral error correction, and adaptive noise suppression. It reduced noise, improved contrast effectively and showed better material differentiation in real patient images as well as phantom studies.
ContributorsPark, Kyung Kook (Author) / Metin, Akay (Thesis advisor) / Pavlicek, William (Committee member) / Akay, Yasemin (Committee member) / Towe, Bruce (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2011
Description
Development of post-traumatic epilepsy (PTE) after traumatic brain injury (TBI) is a major health concern (5% - 50% of TBI cases). A significant problem in TBI management is the inability to predict which patients will develop PTE. Such prediction, followed by timely treatment, could be highly beneficial to TBI patients. Six male Sprague-Dawley rats were subjected to a controlled cortical impact (CCI). A 6mm piston was pneumatically driven 3mm into the right parietal cortex with velocity of 5.5m/s. The rats were subsequently implanted with 6 intracranial electroencephalographic (EEG) electrodes. Long-term (14-week) continuous EEG recordings were conducted. Using linear (coherence) and non-linear (Lyapunov exponents) measures of EEG dynamics in conjunction with measures of network connectivity, we studied the evolution over time of the functional connectivity between brain sites in order to identify early precursors of development of epilepsy. Four of the six TBI rats developed PTE 6 to 10 weeks after the initial insult to the brain. Analysis of the continuous EEG from these rats showed a gradual increase of the connectivity between critical brain sites in terms of their EEG dynamics, starting at least 2 weeks prior to their first spontaneous seizure. In contrast, for the rats that did not develop epilepsy, connectivity levels did not change, or decreased during the whole course of the experiment across pairs of brain sites. Consistent behavior of functional connectivity changes between brain sites and the "focus" (site of impact) over time was demonstrated for coherence in three out of the four epileptic and in both non-epileptic rats, while for STLmax in all four epileptic and in both non-epileptic rats. This study provided us with the opportunity to quantitatively investigate several aspects of epileptogenesis following traumatic brain injury. Our results strongly support a network pathology that worsens with time. It is conceivable that the observed changes in spatiotemporal dynamics after an initial brain insult, and long before the development of epilepsy, could constitute a basis for predictors of epileptogenesis in TBI patients.
ContributorsTobin, Edward (Author) / Iasemidis, Leonidas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2012
Description
Biosensors offer excellent diagnostic methods through precise quantification of bodily fluid biomarkers and could fill an important niche in diagnostic screening. The long term goal of this research is the development of an impedance immunosensor for easy-to-use, rapid, sensitive and selective simultaneously multiplexed quantification of bodily fluid disease biomarkers. To test the hypothesis that various cytokines induce empirically determinable response frequencies when captured by printed circuit board (PCB) impedance immunosensor surface, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) methods were used to test PCB biosensors versus multiple cytokine biomarkers to determine limits of detection, background interaction and response at all sweep frequencies. Results indicated that sensors for cytokine Interleukin-12 (IL-12) detected their target over three decades of concentration and were tolerant to high levels of background protein. Further, the hypothesis that cytokine analytes may be rapidly detected via constant frequency impedance immunosensing without sacrificing undue sensitivity, CV, EIS, impedance-time (Zt) methods and modeling were used to test CHITM gold electrodes versus IL-12 over different lengths of time to determine limits of detection, detection time, frequency of response and consistent cross-platform sensor performance. Modeling and Zt studies indicate interrogation of the electrode with optimum frequency could be used for detection of different target concentrations within 90 seconds of sensor exposure and that interrogating the immunosensor with fixed, optimum frequency could be used for sensing target antigen. This informs usability of fixed-frequency impedance methods for biosensor research and particularly for clinical biosensor use. Finally, a multiplexing impedance immunosensor prototype for quantification of biomarkers in various body fluids was designed for increased automation of sample handling and testing. This enables variability due to exogenous factors and increased rapidity of assay with eased sensor fabrication. Methods were provided for simultaneous multiplexing through multisine perturbation of a sensor, and subsequent data processing. This demonstrated ways to observe multiple types of antibody-antigen affinity binding events in real time, reducing the number of sensors and target sample used in the detection and quantification of multiple biomarkers. These features would also improve the suitability of the sensor for clinical multiplex detection of disease biomarkers.
ContributorsFairchild, Aaron (Author) / La Belle, Jeffrey T (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Nagaraj, Vinay (Committee member) / Pizziconi, Vince (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2012
Description
Noninvasive neuromodulation could help treat many neurological disorders, but existing techniques have low resolution and weak penetration. Ultrasound (US) shows promise for stimulation of smaller areas and subcortical structures. However, the mechanism and parameter design are not understood. US can stimulate tail and hindlimb movements in rats, but not forelimb, for unknown reasons. Potentially, US could also stimulate peripheral or enteric neurons for control of blood glucose.
To better understand the inconsistent effects across rat motor cortex, US modulation of electrically-evoked movements was tested. A stimulation array was implanted on the cortical surface and US (200 kHz, 30-60 W/cm2 peak) was applied while measuring changes in the evoked forelimb and hindlimb movements. Direct US stimulation of the hindlimb was also studied. To test peripheral effects, rat blood glucose levels were measured while applying US near the liver.
No short-term motor modulation was visible (95% confidence interval: -3.5% to +5.1% forelimb, -3.8% to +5.5% hindlimb). There was significant long-term (minutes-order) suppression (95% confidence interval: -3.7% to -10.8% forelimb, -3.8% to -11.9% hindlimb). This suppression may be due to the considerable heating (+1.8°C between US
on-US conditions); effects of heat and US were not separable in this experiment. US directly evoked hindlimb and scrotum movements in some sessions. This required a long interval, at least 3 seconds between US bursts. Movement could be evoked with much shorter pulses than used in literature (3 ms). The EMG latency (10 ms) was compatible with activation of corticospinal neurons. The glucose modulation test showed a strong increase in a few trials, but across all trials found no significant effect.
The single motor response and the long refractory period together suggest that only the beginning of the US burst had a stimulatory effect. This would explain the lack of short-term modulation, and suggests future work with shorter pulses could better explore the missing forelimb response. During the refractory period there was no change in the electrically-evoked response, which suggests the US stimulation mechanism is independent of normal brain activity. These results challenge the literature-standard protocols and provide new insights on the unknown mechanism.
To better understand the inconsistent effects across rat motor cortex, US modulation of electrically-evoked movements was tested. A stimulation array was implanted on the cortical surface and US (200 kHz, 30-60 W/cm2 peak) was applied while measuring changes in the evoked forelimb and hindlimb movements. Direct US stimulation of the hindlimb was also studied. To test peripheral effects, rat blood glucose levels were measured while applying US near the liver.
No short-term motor modulation was visible (95% confidence interval: -3.5% to +5.1% forelimb, -3.8% to +5.5% hindlimb). There was significant long-term (minutes-order) suppression (95% confidence interval: -3.7% to -10.8% forelimb, -3.8% to -11.9% hindlimb). This suppression may be due to the considerable heating (+1.8°C between US
on-US conditions); effects of heat and US were not separable in this experiment. US directly evoked hindlimb and scrotum movements in some sessions. This required a long interval, at least 3 seconds between US bursts. Movement could be evoked with much shorter pulses than used in literature (3 ms). The EMG latency (10 ms) was compatible with activation of corticospinal neurons. The glucose modulation test showed a strong increase in a few trials, but across all trials found no significant effect.
The single motor response and the long refractory period together suggest that only the beginning of the US burst had a stimulatory effect. This would explain the lack of short-term modulation, and suggests future work with shorter pulses could better explore the missing forelimb response. During the refractory period there was no change in the electrically-evoked response, which suggests the US stimulation mechanism is independent of normal brain activity. These results challenge the literature-standard protocols and provide new insights on the unknown mechanism.
ContributorsGulick, Daniel Withers (Author) / Kleim, Jeffrey (Thesis advisor) / Towe, Bruce (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Herman, Richard (Committee member) / Helms Tillery, Steven (Committee member) / Arizona State University (Publisher)
Created2015
Description
Optical Fibers coupled to laser light sources, and Light Emitting Diodes are the two classes of technologies used for optogenetic experiments. Arizona State University's Flexible Display Center fabricates novel flexible Organic Light Emitting Diodes(OLEDs). These OLEDs have the capability of being monolithically fabricated over flexible, transparent plastic substrates and having power efficient ways of addressing high density arrays of LEDs. This thesis critically evaluates the technology by identifying the key advantages, current limitations and experimentally assessing the technology in in-vivo and in-vitro animal models. For in-vivo testing, the emitted light from a flat OLED panel was directly used to stimulate the neo-cortex in the M1 region of transgenic mice expressing ChR2 (B6.Cg-Tg (Thy1-ChR2/EYFP) 9Gfng/J). An alternative stimulation paradigm using a collimating optical system coupled with an optical fiber was used for stimulating neurons in layer 5 of the motor cortex in the same transgenic mice. EMG activity was recorded from the contralateral vastus lateralis muscles. In vitro testing of the OLEDs was done in primary cortical neurons in culture transfected with blue light sensitive ChR2. The neurons were cultured on a microelectrode array for taking neuronal recordings.
ContributorsShah, Ankur (Author) / Muthuswamy, Jitendran (Thesis advisor) / Greger, Bradley (Committee member) / Blain Christen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
There is a strong medical need and important therapeutic applications for improved wireless bioelectric interfaces to the nervous system. Multichannel devices are desired for neural control of robotic prosthetics that interface to remaining nerves in limb stumps of amputees and as alternatives to traditional wired arrays used in for some types of brain stimulation. This present work investigates a new approach to ultrasound-powering of implantable microelectronic devices within the tissue that may better support such applications. These devices are of ultra-miniature size that is enabled by a wireless technique. This study investigates two types of ultrasound-powered neural interfaces for multichannel sensory feedback in neurostimulation. The piezoceramics lead zirconate titanate (PZT) ceramic and polyvinylidene fluoride (PVDF) polymer were the primary materials used to build the devices. They convert ultrasound to electricity that when rectified by a diode produce a current output that is neuro stimulatory to peripheral nerve or the neurons in the brain. Multichannel devices employ a form of spatial multiplexing that directs focused ultrasound towards localized and segmented regions of PVDF or PZT that allows independent channels of nerve actuation. Different frequencies of ultrasound were evaluated for best results. Firstly, a 2.25 MHz frequency signal that is reasonably penetrating through body tissue to an implant several centimeters deep and also a 5 MHz frequency more suited to application for actuation of devices within a less than a centimeter of nerve. Results show multichannel device performance to have a complex inter-relationship with frequency, size and thickness, angular incidence, channel separations, and number of folds (layers connected in series and parallel). The output electrical port impedances of PVDF devices were examined in relationship to that of stimulating electrodes and tissue interfaces. Miniature multichannel devices were constructed using an unreported method of employing state of the art laser cutting systems. The results show that PVDF based devices have advantages over PZT, because of better acoustic coupling with tissue, known better biocompatibility, and better separation between multiple channels. However, the PZT devices proved to be better overall in terms of compactness and higher outputs for a given ultrasound power level.
ContributorsNanda Kumar, Yashwanth (Author) / Towe, Bruce (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Nikkhah, Mehdi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Epilepsy is a group of disorders that cause seizures in approximately 2.2 million people in the United States. Over 30% of these patients have epilepsies that do not respond to treatment with anti-epileptic drugs. For this population, focal resection surgery could offer long-term seizure freedom. Surgery candidates undergo a myriad of tests and monitoring to determine where and when seizures occur. The “gold standard” method for focus identification involves the placement of electrocorticography (ECoG) grids in the sub-dural space, followed by continual monitoring and visual inspection of the patient’s cortical activity. This process, however, is highly subjective and uses dated technology. Multiple studies were performed to investigate how the evaluation process could benefit from an algorithmic adjust using current ECoG technology, and how the use of new microECoG technology could further improve the process.
Computational algorithms can quickly and objectively find signal characteristics that may not be detectable with visual inspection, but many assume the data are stationary and/or linear, which biological data are not. An empirical mode decomposition (EMD) based algorithm was developed to detect potential seizures and tested on data collected from eight patients undergoing monitoring for focal resection surgery. EMD does not require linearity or stationarity and is data driven. The results suggest that a biological data driven algorithm could serve as a useful tool to objectively identify changes in cortical activity associated with seizures.
Next, the use of microECoG technology was investigated. Though both ECoG and microECoG grids are composed of electrodes resting on the surface of the cortex, changing the diameter of the electrodes creates non-trivial changes in the physics of the electrode-tissue interface that need to be accounted for. Experimenting with different recording configurations showed that proper grounding, referencing, and amplification are critical to obtain high quality neural signals from microECoG grids.
Finally, the relationship between data collected from the cortical surface with micro and macro electrodes was studied. Simultaneous recordings of the two electrode types showed differences in power spectra that suggest the inclusion of activity, possibly from deep structures, by macroelectrodes that is not accessible by microelectrodes.
Computational algorithms can quickly and objectively find signal characteristics that may not be detectable with visual inspection, but many assume the data are stationary and/or linear, which biological data are not. An empirical mode decomposition (EMD) based algorithm was developed to detect potential seizures and tested on data collected from eight patients undergoing monitoring for focal resection surgery. EMD does not require linearity or stationarity and is data driven. The results suggest that a biological data driven algorithm could serve as a useful tool to objectively identify changes in cortical activity associated with seizures.
Next, the use of microECoG technology was investigated. Though both ECoG and microECoG grids are composed of electrodes resting on the surface of the cortex, changing the diameter of the electrodes creates non-trivial changes in the physics of the electrode-tissue interface that need to be accounted for. Experimenting with different recording configurations showed that proper grounding, referencing, and amplification are critical to obtain high quality neural signals from microECoG grids.
Finally, the relationship between data collected from the cortical surface with micro and macro electrodes was studied. Simultaneous recordings of the two electrode types showed differences in power spectra that suggest the inclusion of activity, possibly from deep structures, by macroelectrodes that is not accessible by microelectrodes.
ContributorsAshmont, Kari Rich (Author) / Greger, Bradley (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Adelson, P David (Committee member) / Dudek, F Edward (Committee member) / Arizona State University (Publisher)
Created2015
Description
Robust and stable decoding of neural signals is imperative for implementing a useful neuroprosthesis capable of carrying out dexterous tasks. A nonhuman primate (NHP) was trained to perform combined flexions of the thumb, index and middle fingers in addition to individual flexions and extensions of the same digits. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon action potential firing rates. The effect of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis, and Mutual Information Maximization was compared based on SVM classification performance. SVM classification was used to examine the functional parameters of (i) efficacy (ii) endurance to simulated failure and (iii) longevity of classification. The effect of using isolated-neuron and multi-unit firing rates was compared as the feature vector supplied to the SVM. The best classification performance was on post-implantation day 36, when using multi-unit firing rates the worst classification accuracy resulted from features selected with Wilcoxon signed-rank test (51.12 ± 0.65%) and the best classification accuracy resulted from Mutual Information Maximization (93.74 ± 0.32%). On this day when using single-unit firing rates, the classification accuracy from the Wilcoxon signed-rank test was 88.85 ± 0.61 % and Mutual Information Maximization was 95.60 ± 0.52% (degrees of freedom =10, level of chance =10%)
ContributorsPadmanaban, Subash (Author) / Greger, Bradley (Thesis advisor) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2015