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- All Subjects: Neurosciences
- All Subjects: Microelectromechanical Systems
- Creators: Muthuswamy, Jitendran
- 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
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
Microelectrodes have been used as the neural interface to record brain's neural activities. Most of these electrodes are fixed positioned. Neural signal normally degrades over time due to the body immune response and brain micromotion that move the neurons away from the microelectrode. MEMS technology under SUMMiT VTM processes has developed miniaturized version of moveable microelectrodes that have the ability to recover the neural signal degradation by searching new cluster of neurons. To move the MEMS microelectrode a combination of four voltage waveforms must be applied to four thermally actuated microactuators. Previous design has used OmneticTM interconnect to transfer the waveforms from the external signal generators to the MEMS device. Unfortunately, the mechanism to attach and detach the OmneticTM interconnect introduce mechanical stress into the brain tissue that often caused raptures in the blood vessel. The goal of this project is to create an integrated System-On-Package Signal Generator that can be implanted on the brain of a rodent. A wireless system and a microcontroller are integrated together with the signal generators. The integrated system can be used to generate a series of voltage waveforms that can be customized to drive an array of MEMS movable microelectrodes when a triggered signal is received wirelessly. 3D stacking technique has been used to develop this Integrated System. 3D stacks lead to several favorable factors, such as (a) reduction in the power consumption of the system, (b) reduction in the overall form-factor of the package, and (c) significant reduction the weight of the package. There are a few challenges that must be overcome in this project, such as a commercially available microcontroller normally have an output voltage of 3.3 V to 5.5 V; however, a voltage of 7 - 8V is required to move the MEMS movable microelectrodes. To acquire higher density neural recording, more number of microelectrodes are needed. In this project, SoP Signal Generator is design to drive independently 3 moveable microelectrodes. Therefore, 12 voltage waveform are required. . However, the use of 12 signal generators is not a workable option since the system will be significantly large. This brings us to the other challenge, the limiting size of the rodent brain. Due to this factor, the SoP Signal Generator has to be deisgned to be able to fit without causing much pressure to the rodent's brain. For the first challenge, which is the limited output voltage of 3.3V on the microcontroller, the RC555 timers are used as an amplifier in addition to generating the signals. Demultiplexers have been for the next challenge, which is the need of 24 waveforms to drive 3 electrodes. For each waveform, 1 demultiplexer is used, making a total of 4 demultiplexers used in the entire system, which is a significant improvement from using 12 signal generators. The last challenge can be approached using 3D system stacking technique as mentioned above. The research aims of this project can be described as follows: (1) the testing and realization of the system part, and the designing of the system in a PCB level, (2) implementing and testing the SoP Signal Generator with the MEMS movable microelectrodes, The final outcome of this project can be used not only for neural applications, but also for more general applications that requires customized signal generations and wireless data transmission.
ContributorsTee, Zikai (Author) / Muthuswamy, Jitendran (Thesis advisor) / Sutanto, Jemmy (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012
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
A direct Magnetic Resonance (MR)-based neural activity mapping technique with high spatial and temporal resolution may accelerate studies of brain functional organization.
The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced by the vasculature in each voxel and can be affected by capillary orientation and vessel size. Functional MRI analysis may, therefore, produce misleading results when voxels are nearby large vessels. Another problem in fMRI is that hemodynamic responses are slower than the neuronal activity. Therefore, temporal resolution is limited in fMRI. Furthermore, the correlation between neural activity and the hemodynamic response is not fully understood. fMRI can only be considered an indirect method of functional brain imaging.
Another MR-based method of functional brain mapping is neuronal current magnetic resonance imaging (ncMRI), which has been studied over several years. However, the amplitude of these neuronal current signals is an order of magnitude smaller than the physiological noise. Works on ncMRI include simulation, phantom experiments, and studies in tissue including isolated ganglia, optic nerves, and human brains. However, ncMRI development has been hampered due to the extremely small signal amplitude, as well as the presence of confounding signals from hemodynamic changes and other physiological noise.
Magnetic Resonance Electrical Impedance Tomography (MREIT) methods could have the potential for the detection of neuronal activity. In this technique, small external currents are applied to a body during MR scans. This current flow produces a magnetic field as well as an electric field. The altered magnetic flux density along the main magnetic field direction caused by this current flow can be obtained from phase images. When there is neural activity, the conductivity of the neural cell membrane changes and the current paths around the neurons change consequently. Neural spiking activity during external current injection, therefore, causes differential phase accumulation in MR data. Statistical analysis methods can be used to identify neuronal-current-induced magnetic field changes.
The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced by the vasculature in each voxel and can be affected by capillary orientation and vessel size. Functional MRI analysis may, therefore, produce misleading results when voxels are nearby large vessels. Another problem in fMRI is that hemodynamic responses are slower than the neuronal activity. Therefore, temporal resolution is limited in fMRI. Furthermore, the correlation between neural activity and the hemodynamic response is not fully understood. fMRI can only be considered an indirect method of functional brain imaging.
Another MR-based method of functional brain mapping is neuronal current magnetic resonance imaging (ncMRI), which has been studied over several years. However, the amplitude of these neuronal current signals is an order of magnitude smaller than the physiological noise. Works on ncMRI include simulation, phantom experiments, and studies in tissue including isolated ganglia, optic nerves, and human brains. However, ncMRI development has been hampered due to the extremely small signal amplitude, as well as the presence of confounding signals from hemodynamic changes and other physiological noise.
Magnetic Resonance Electrical Impedance Tomography (MREIT) methods could have the potential for the detection of neuronal activity. In this technique, small external currents are applied to a body during MR scans. This current flow produces a magnetic field as well as an electric field. The altered magnetic flux density along the main magnetic field direction caused by this current flow can be obtained from phase images. When there is neural activity, the conductivity of the neural cell membrane changes and the current paths around the neurons change consequently. Neural spiking activity during external current injection, therefore, causes differential phase accumulation in MR data. Statistical analysis methods can be used to identify neuronal-current-induced magnetic field changes.
ContributorsFu, Fanrui (Author) / Sadleir, Rosalind (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Kleim, Jeffrey (Committee member) / Muthuswamy, Jitendran (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Vagal Nerve Stimulation (VNS) has been shown to be a promising therapeutic technique in treating many neurological diseases, including epilepsy, stroke, traumatic brain injury, and migraine headache. The mechanisms by which VNS acts, however, are not fully understood but may involve changes in cerebral blood flow. The vagus nerve plays a significant role in the regulation of heart rate and cerebral blood flow that are altered during VNS. Here, the effects of acute vagal nerve stimulation using varying stimulation parameters on both heart rate and cerebral blood flow were examined. Laser Speckle Contrast Analysis (LASCA) was used to analyze the cerebral blood flow of male Long–Evans rats. In the first experiment, results showed two distinct patterns of responses to 0.8mA of stimulation whereby animals either experienced a mild or severe decrease in heart rate. Further, animals that displayed mild heart rate decreases showed an increase in cerebral blood flow that persisted beyond VNS. Animals that displayed severe decreases showed a transient decrease in cerebral blood flow followed by an increase that was greater than that observed in mild animals but progressively decreased after VNS. The results suggest two distinct patterns of changes in both heart rate and blood flow that may be related to the intensity of VNS. To investigate the effects of lower levels of stimulation, an additional group of animals were stimulated at 0.4mA. The results showed moderate changes in heart rate but no significant changes in cerebral blood flow in these animals. The results demonstrate that VNS alters both heart rate and cerebral blood flow and that these effects are dependent on current intensity.
ContributorsHillebrand, Peter (M.S.) (Author) / Kleim, Jeffrey A (Thesis advisor) / Helms Tillery, Stephen I (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2019
Description
There is a critical need for creating an implantable microscale neural interface that can chronically monitor neural activity and oxygenation. These are key aspects for understating the development of impaired neural circuits and their functions. A technology with such capability would foster new insights in the studies of brain diseases and disorders. The propose is that MR-PISTOL (Proton imaging of Siloxane to Map Tissue Oxygenation Levels) imaging technique can be used for direct measurements of oxygen partial pressure at microelectrode-tissue interface. The strategy consists of coating microelectrodes with soft-silicone, a ultra-soft conductive PDMS (polydimethylsiloxane), as a carrier for liquid siloxanes MR-PISTOL contrast agents. This work presents a proof-of-concept of an injection molding technique for batch fabricate microelectrodes with such coating. Also, reports stability studies of soft-silicone loaded with liquid polydimethylsiloxane (PDMSO) in rodent brains. A batch of thirty coated carbon electrodes was achieved using candy molds. Coating uniformity was evaluated in twelve probes. They were randomly chosen and imaged with a custom image setup that allows 90o rotation of the probes. The total average coating thickness before and after rotation were 0.397 millimeters with standard deviation of 0.070 millimeters and 0.442 millimeters with standard deviation of 0.062 millimeters. Therefore, data confirms that this technique yields uniform coating. Stability of fabricated coated carbon electrodes unloaded (n= 3) and loaded with PDMSO (n= 3) was assessed. 3D X-ray imaging using Zeiss Xradia 520 machine was chosen for studying coatings mechanical stability in ex-vivo rat brain. Transmission electron microscopy (TEM) and scanning electron microscope (SEM) with an energy dispersive x-ray microanalysis (EDS) detector were used to investigate their chemical stability in in vivo mouse brain. Initial EDS analysis from TEM and SEM of acute (6 hours) and chronic (2 weeks) brain slices suggest that PDMSO does not leach into brain. More experiments should be done to confirm and endorse this finding. The mechanical study shows that coating loaded with PDMSO delaminated during insertion. This was not observed with electrodes used in the chemical stability studies. Further experiments need to be done to identify possible causes of mechanical failures.
Contributorsde Mesquita Teixeira, Livia (Author) / Muthuswamy, Jitendran (Thesis advisor, Committee member) / Kodibagkar, Vikram (Thesis advisor, Committee member) / Sridharan, Arati (Committee member) / Arizona State University (Publisher)
Created2018
Description
Graphene is a very strong two-dimensional material with a lot of potential applications in microelectromechanical systems (MEMS). In this research, graphene is being optimized for use in a 5 m x 5 m graphene resonator. To work properly, this graphene resonator must have a uniform strain across all manufactured devices. To reduce strain induced in graphene sheets grown for use in these resonators, evaporated platinum has been used in this investigation due to its relatively lower surface roughness compared to copper films. The final goal is to have the layer of ultrathin platinum (<=200 nm) deposited on the MEMS graphene resonator and used to grow graphene directly onto the devices to remove the manual transfer step due to its inscalability. After growth, graphene is coated with polymer and the platinum is then etched. This investigation concentrated on the transfer process of graphene onto Si/SiO2 substrate from the platinum films. It was determined that the ideal platinum etchant was aqua regia at a volumetric ratio of 6:3:1 (H2O:HCl:HNO3). This concentration was dilute enough to preserve the polymer and graphene layer, but strong enough to etch within a day. Type and thickness of polymer support layers were also investigated. PMMA at a thickness of 200 nm was ideal because it was easy to remove with acetone and strong enough to support the graphene during the etch process. A reference growth recipe was used in this investigation, but now that the transfer has been demonstrated, growth can be optimized for even thinner films.
ContributorsCayll, David Richard (Author) / Tongay, Sefaattin (Thesis director) / Lee, Hyunglae (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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