184 research outputs found

    An Optoelectronic Stimulator for Retinal Prosthesis

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    Retinal prostheses require the presence of viable population of cells in the inner retina. Evaluations of retina with Age-Related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP) have shown a large number of cells remain in the inner retina compared with the outer retina. Therefore, vision loss caused by AMD and RP is potentially treatable with retinal prostheses. Photostimulation based retinal prostheses have shown many advantages compared with retinal implants. In contrary to electrode based stimulation, light does not require mechanical contact. Therefore, the system can be completely external and not does have the power and degradation problems of implanted devices. In addition, the stimulating point is flexible and does not require a prior decision on the stimulation location. Furthermore, a beam of light can be projected on tissue with both temporal and spatial precision. This thesis aims at fi nding a feasible solution to such a system. Firstly, a prototype of an optoelectronic stimulator was proposed and implemented by using the Xilinx Virtex-4 FPGA evaluation board. The platform was used to demonstrate the possibility of photostimulation of the photosensitized neurons. Meanwhile, with the aim of developing a portable retinal prosthesis, a system on chip (SoC) architecture was proposed and a wide tuning range sinusoidal voltage-controlled oscillator (VCO) which is the pivotal component of the system was designed. The VCO is based on a new designed Complementary Metal Oxide Semiconductor (CMOS) Operational Transconductance Ampli er (OTA) which achieves a good linearity over a wide tuning range. Both the OTA and the VCO were fabricated in the AMS 0.35 µm CMOS process. Finally a 9X9 CMOS image sensor with spiking pixels was designed. Each pixel acts as an independent oscillator whose frequency is controlled by the incident light intensity. The sensor was fabricated in the AMS 0.35 µm CMOS Opto Process. Experimental validation and measured results are provided

    Real-time encoding and compression of neuronal spikes by metal-oxide memristors

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    Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology’s potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces

    SpikeSEE: An Energy-Efficient Dynamic Scenes Processing Framework for Retinal Prostheses

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    Intelligent and low-power retinal prostheses are highly demanded in this era, where wearable and implantable devices are used for numerous healthcare applications. In this paper, we propose an energy-efficient dynamic scenes processing framework (SpikeSEE) that combines a spike representation encoding technique and a bio-inspired spiking recurrent neural network (SRNN) model to achieve intelligent processing and extreme low-power computation for retinal prostheses. The spike representation encoding technique could interpret dynamic scenes with sparse spike trains, decreasing the data volume. The SRNN model, inspired by the human retina special structure and spike processing method, is adopted to predict the response of ganglion cells to dynamic scenes. Experimental results show that the Pearson correlation coefficient of the proposed SRNN model achieves 0.93, which outperforms the state of the art processing framework for retinal prostheses. Thanks to the spike representation and SRNN processing, the model can extract visual features in a multiplication-free fashion. The framework achieves 12 times power reduction compared with the convolutional recurrent neural network (CRNN) processing-based framework. Our proposed SpikeSEE predicts the response of ganglion cells more accurately with lower energy consumption, which alleviates the precision and power issues of retinal prostheses and provides a potential solution for wearable or implantable prostheses

    Data analysis of retinal recordings from multi-electrode arrays under in situ electrical stimulation

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    The development of retinal implants has become an important field of study in recent years, with increasing numbers of people falling victim to legal or physical blindness as a result of retinal damage. Important weaknesses in current retinal implants include a lack of the resolution necessary to give a patient a viable level of visual acuity, question marks over the amount of power and energy required to deliver adequate stimulation, and the removal of eye movements from the analysis of the visual scene. This thesis documents investigations by the author into a new CMOS stimulation and imaging chip with the potential to overcome these difficulties. An overview is given of the testing and characterisation of the componments incorporated in the device to mimic the normal functioning of the human retina. Its application to in situ experimental studies of frog retina is also described, as well as how the data gathered from these experiments enables the optimisation of the geometry of the electrode array through which the device will interface with the retina. Such optimisation is important as the deposit of excess electrical charge and energy can lead to detrimental medical side effects. Avoidance of such side effects is crucial to the realisation of the next generation of retinal implants

    A combined experimental and computational approach to investigate emergent network dynamics based on large-scale neuronal recordings

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    Sviluppo di un approccio integrato computazionale-sperimentale per lo studio di reti neuronali mediante registrazioni elettrofisiologich

    The potential of microelectrode arrays and microelectronics for biomedical research and diagnostics

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    Planar microelectrode arrays (MEAs) are devices that can be used in biomedical and basic in vitro research to provide extracellular electrophysiological information about biological systems at high spatial and temporal resolution. Complementary metal oxide semiconductor (CMOS) is a technology with which MEAs can be produced on a microscale featuring high spatial resolution and excellent signal-to-noise characteristics. CMOS MEAs are specialized for the analysis of complete electrogenic cellular networks at the cellular or subcellular level in dissociated cultures, organotypic cultures, and acute tissue slices; they can also function as biosensors to detect biochemical events. Models of disease or the response of cellular networks to pharmacological compounds can be studied in vitro, allowing one to investigate pathologies, such as cardiac arrhythmias, memory impairment due to Alzheimer's disease, or vision impairment caused by ganglion cell degeneration in the retin

    Novel flexible multielectrode arrays for neuronal stimulation and recording

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    This thesis will focus on developments in coupling the multidisciplinary research interests of Physics, Micro-engineering and neurobiology towards the development of a proof of concept retinal prosthetic device. With recent developments in low-power electronics and semiconductor fabrication techniques many applications in the life sciences have emerged. One such application is in the development of a retinal prosthetic device which relies on the ability to record information from and feed information directly to small retinal neuronal cells which are approximately 5mum diameter. Where successful, we achieve the possibility of restoring sight to people affected by degenerative visual diseases such as Age Related Macular Degeneration and Retinitis Pigmentosa. Both these conditions affect the photosensitive elements of the eye yet leave the remaining pathways to the visual cortex, the area of the brain responsible for our visual precept, intact. High-density electrode arrays axe becoming well established as tools for the measurement of neuronal signals. The fabrication of arrays on flexible materials allows for 2D position sensitive recording of cellular activity in vivo and for the possibility of direct in vivo stimulus. Using flexible polymer materials (Pryalin PI2545), compliant with semiconductor fabrication techniques, a process allowing the fabrication of flexible multi-site microelectrode neuronal recording and stimulating arrays is presented. The development of both 8 and 74 electrode arrays on polyimide substrates with 50mum and 5mum minimum linewidths respectively is described. Implementing low noise amplification, 8muV rms (bandpass typically 80-2000 Hz), the polyimide 8-electrode arrays have been used to stimulate and record electroretinogram and ganglion cell action potentials in vivo from the frog retina (Rana lemporaria). Such arrays coupled to our application specific pixellated CMOS sensors, the IPIX, incorporating an ability to apply neural network algorithms should allow for the recovery of basic functionality in the human retina. The IPIX detector is an Active Pixel Sensor which responds to incident light in the visible region. It responds to the varying intensity of light over 3 log units and outputs varying frequency voltage pulses of similar form to that of a healthy retina. Stimulation studies for electro-deposited platinum electrodes of 4 nA/mum2 indicate upper breakdown limits for charge density approaching 100 muCm-2. Investigations of lifetime stimulation of a 50 mum diameter electrode, of typical impedance less than 20 kO at 1 kHz, suggest operational limits over lifetime in the order of 10 muCm-2. These charge densities are adequate for neuronal cell stimulation. It is believed that the system described in this thesis can form the basis on which to deploy a retinal prosthetic device. Moreover, in the short term, the information provided by this system will allow for investigations into deciphering the 'wiring diagram' of the retina

    MAPPING LOW-FREQUENCY FIELD POTENTIALS IN BRAIN CIRCUITS WITH HIGH-RESOLUTION CMOS ELECTRODE ARRAY RECORDINGS

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    Neurotechnologies based on microelectronic active electrode array devices are on the way to provide the capability to record electrophysiological neural activity from a thousands of closely spaced microelectrodes. This generates increasing volumes of experimental data to be analyzed, but also offers the unprecedented opportunity to observe bioelectrical signals at high spatial and temporal resolutions in large portions of brain circuits. The overall aim of this PhD was to study the application of high-resolution CMOS-based electrode arrays (CMOS-MEAs) for electrophysiological experiments and to investigate computational methods adapted to the analysis of the electrophysiological data generated by these devices. A large part of my work was carried out on cortico-hippocampal brain slices by focusing on the hippocampal circuit. In the history of neuroscience, a major technological advance for hippocampal research, and also for the field of neurobiology, was the development of the in vitro hippocampal slice preparation. Neurobiological principles that have been discovered from work on in vitro hippocampal preparations include, for instance, the identification of excitatory and inhibitory synapses and their localization, the characterization of transmitters and receptors, the discovery of long-term potentiation (LTP) and long-term depression (LTD) and the study of oscillations in neuronal networks. In this context, an initial aim of my work was to optimize the preparation and maintenance of acute cortico-hippocampal brain slices on planar CMOS-MEAs. At first, I focused on experimental methods and computational data analysis tools for drug-screening applications based on LTP quantifications. Although the majority of standard protocols still use two electrodes platforms for quantifying LTP, in my PhD I investigate the potential advantages of recording the electrical activity from many electrodes to spatiotemporally characterized electrically induced responses. This work also involved the collaboration with 3Brain AG and a CRO involved in drug-testing, and led to a software tool that was licensed for developing its exploitation. In a second part of my work I focused on exploiting the recording resolution of planar CMOS-MEAs to study the generation of sharp wave ripples (SPW-Rs) in the hippocampal circuit. This research activity was carried out also by visiting the laboratory of Prof. A. Sirota (Ludwig Maximilians University, Munich). In addition to set-up the experimental conditions to record SPW-Rs from planar CMOS-MEAs integrating 4096 microelectrodes, I also explored the implementation of a data analysis pipeline to identify spatiotemporal features that might characterize different type of in-vitro generated SPW-R events. Finally, I also contributed to the initial implementation of high-density implantable CMOS-probes for in-vivo electrophysiology with the aim of evaluating in vivo the algorithms that I developed and investigated on brain slices. With this aim, in the last period of my PhD I worked on the development of a Graphical User Interface for controlling active dense CMOS probes (or SiNAPS probes) under development in our laboratory. I participated to preliminary experimental recordings using 4-shank CMOS-probes featuring 1024 simultaneously recording electrodes and I contributed to the development of a software interface for executing these experiments
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