Closed-loop approaches for innovative neuroprostheses

The goal of this thesis is to study new ways to interact with the nervous system in case of damage or pathology. In particular, I focused my effort towards the development of innovative, closed-loop stimulation protocols in various scenarios: in vitro, ex vivo, in vivo

Neural networks-on-chip for hybrid bio-electronic systems

PhD ThesisBy modelling the brains computation we can further our understanding of its function and develop novel treatments for neurological disorders. The brain is incredibly powerful and energy e cient, but its computation does not t well with the traditional computer architecture developed over the previous 70 years. Therefore, there is growing research focus in developing alternative computing technologies to enhance our neural modelling capability, with the expectation that the technology in itself will also bene t from increased awareness of neural computational paradigms. This thesis focuses upon developing a methodology to study the design of neural computing systems, with an emphasis on studying systems suitable for biomedical experiments. The methodology allows for the design to be optimized according to the application. For example, di erent case studies highlight how to reduce energy consumption, reduce silicon area, or to increase network throughput. High performance processing cores are presented for both Hodgkin-Huxley and Izhikevich neurons incorporating novel design features. Further, a complete energy/area model for a neural-network-on-chip is derived, which is used in two exemplar case-studies: a cortical neural circuit to benchmark typical system performance, illustrating how a 65,000 neuron network could be processed in real-time within a 100mW power budget; and a scalable highperformance processing platform for a cerebellar neural prosthesis. From these case-studies, the contribution of network granularity towards optimal neural-network-on-chip performance is explored

Self-diagnosis implantable optrode for optogenetic stimulation

PhD ThesisAs a cell type-specific neuromodulation method, optogenetic technique holds remarkable potential for the realisation of advanced neuroprostheses. By genetically expressing light-sensitive proteins such as channelrhodopsin-2 (ChR2) in cell membranes, targeted neurons could be controlled by blue light. This new neuromodulation technique could then be applied into extensive brain networks and be utilised to provide effective therapies for neurological disorders. However, the development of novel optogenetic implants is still a key challenge in the field. The major requirements include small device dimensions, suitable spatial resolution, high safety, and strong controllability. In particular, appropriate implantable electronics are expected to be built into the device, accomplishing a new-generation intelligent optogenetic implant. To date, different microfabrication techniques, such as wave-guided laser/light-emitting diode (LED) structure and μLED-on-optrode structure, have been widely explored to create and miniaturise optogenetic implants. However, although these existing devices meet the requirements to some extent, there is still considerable room for improvement. In this thesis, a Complementary Metal-Oxide-Semiconductor (CMOS)-driven μLED approach is proposed to develop an advanced implantable optrode. This design is based on the μLED-on-optrode structure, where Gallium Nitride (GaN) μLEDs can be directly bonded to provide precise local light delivery and multi-layer stimulation. Moreover, an in-built diagnostic sensing circuitry is designed to monitor optrode integrity and degradation. This self-diagnosis function greatly improves system reliability and safety. Furthermore, in-situ temperature sensors are incorporated to monitor the local thermal effects of light emitters. This ensures both circuitry stability and tissue health. More importantly, external neural recording circuitry is integrated into the implant, which could observe local neural signals in the vicinity of the stimulation sites. Therefore, a CMOS-based multi-sensor optogenetic implant is achieved, and this closed-loop neural interface is capable of performing multichannel optical neural stimulation and electrical neural recording simultaneously. This optrode is expected to represent a promising neural interface for broad neuroprosthesis applications

A Closed-Loop Bidirectional Brain-Machine Interface System For Freely Behaving Animals

A brain-machine interface (BMI) creates an artificial pathway between the brain and the external world. The research and applications of BMI have received enormous attention among the scientific community as well as the public in the past decade. However, most research of BMI relies on experiments with tethered or sedated animals, using rack-mount equipment, which significantly restricts the experimental methods and paradigms. Moreover, most research to date has focused on neural signal recording or decoding in an open-loop method. Although the use of a closed-loop, wireless BMI is critical to the success of an extensive range of neuroscience research, it is an approach yet to be widely used, with the electronics design being one of the major bottlenecks. The key goal of this research is to address the design challenges of a closed-loop, bidirectional BMI by providing innovative solutions from the neuron-electronics interface up to the system level. Circuit design innovations have been proposed in the neural recording front-end, the neural feature extraction module, and the neural stimulator. Practical design issues of the bidirectional neural interface, the closed-loop controller and the overall system integration have been carefully studied and discussed.To the best of our knowledge, this work presents the first reported portable system to provide all required hardware for a closed-loop sensorimotor neural interface, the first wireless sensory encoding experiment conducted in freely swimming animals, and the first bidirectional study of the hippocampal field potentials in freely behaving animals from sedation to sleep. This thesis gives a comprehensive survey of bidirectional BMI designs, reviews the key design trade-offs in neural recorders and stimulators, and summarizes neural features and mechanisms for a successful closed-loop operation. The circuit and system design details are presented with bench testing and animal experimental results. The methods, circuit techniques, system topology, and experimental paradigms proposed in this work can be used in a wide range of relevant neurophysiology research and neuroprosthetic development, especially in experiments using freely behaving animals

Doctor of Philosophy

dissertationOptical methods are well-established in the fields of neuroscience, medical imaging, and diagnostics, etc. Optogenetics, for example, enables molecular specificity in optical neural stimulation and recording and has been named the "Method of the Year 2010" by Nature Methods. A novel microdevice was designed, fabricated, developed, and tested to facilitate three-dimensional (3D) deep-tissue light penetration with the capacity to accommodate spatiotemporal modulation of one or more wavelengths to advance a broad range of applications for optical neural interfaces. A 3D optrode array consisting of optically transparent "needles" can penetrate >1 mm directly into tissue, thereby creating multiple independent paths for light propagation that avoid attenuation due to tissue absorption and scattering, providing a high level of selectivity and comprehensive access to tissue not available in current interfaces. Arrays were developed based upon silicon and glass. The silicon optrode array is based upon the well-established Utah electrode array architectures and is suitable for near-infrared (NIR) applications; glass optrodes are appropriate waveguides for both visible and NIR wavelengths. Arrays were bulk-micromachined with high-aspect ratio, a process that has not been reported to be applied to glass previously. In addition to device fabrication, extensive laboratory testing was performed with various optical sources to determine loss mechanisms and emitted beam profiles in tissue across the relevant wavelength ranges, with particular focus on performance metrics for optogenetic and infrared neural stimulation applications. Optrode arrays were determined to be amenable to integration with typical neural stimulation and imaging light delivery mechanisms such as optical fibers and microscopes. Glass optrodes were able to transmit light at ~90% efficiency through depths many times greater than the tissue attenuation length, with negligible light in-coupling loss. Si optrodes were determined to be only ~40% efficient with losses mostly from high index contrast, tip backreflection, and taper radiation. The in-coupling technique and optrode geometry may be modified to produce illumination volumes appropriate for various experimental paradigms. While the focus of this work is on optical neural stimulation, optrode array devices have application in basic neuroscience research, highly selective photodynamic therapy, and deep tissue imaging for diagnostics and therapy

Real-time signal detection and classification algorithms for body-centered systems

El principal motivo por el cual los sistemas de comunicación en el entrono corporal se desean con el objetivo de poder obtener y procesar señales biométricas para monitorizar e incluso tratar una condición médica sea ésta causada por una enfermedad o el rendimiento de un atleta. Dado que la base de estos sistemas está en la sensorización y el procesado, los algoritmos de procesado de señal son una parte fundamental de los mismos. Esta tesis se centra en los algoritmos de tratamiento de señales en tiempo real que se utilizan tanto para monitorizar los parámetros como para obtener la información que resulta relevante de las señales obtenidas. En la primera parte se introduce los tipos de señales y sensores en los sistemas en el entrono corporal. A continuación se desarrollan dos aplicaciones concretas de los sistemas en el entorno corporal así como los algoritmos que en las mismas se utilizan. La primera aplicación es el control de glucosa en sangre en pacientes con diabetes. En esta parte se desarrolla un método de detección mediante clasificación de patronones de medidas erróneas obtenidas con el monitor contínuo comercial "Minimed CGMS". La segunda aplicacióin consiste en la monitorizacióni de señales neuronales. Descubrimientos recientes en este campo han demostrado enormes posibilidades terapéuticas (por ejemplo, pacientes con parálisis total que son capaces de comunicarse con el entrono gracias a la monitorizacióin e interpretación de señales provenientes de sus neuronas) y también de entretenimiento. En este trabajo, se han desarrollado algoritmos de detección, clasificación y compresión de impulsos neuronales y dichos algoritmos han sido evaluados junto con técnicas de transmisión inalámbricas que posibiliten una monitorización sin cables. Por último, se dedica un capítulo a la transmisión inalámbrica de señales en los sistemas en el entorno corporal. En esta parte se estudia las condiciones del canal que presenta el entorno corporal para la transmisión de sTraver Sebastiá, L. (2012). Real-time signal detection and classification algorithms for body-centered systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16188Palanci

Microsystème implantable dédié à la stimulation du cortex visuel

Notions fondamentales au sujet des stimulateurs implantables -- La stimulation électrique fonctionnelle -- Généralités au sujet des stimulateurs implantables -- Restitution de la vision par la stimulation électrique fonctionnelle -- Le système visuel biologique -- Principes et historique des implants visuels -- Considérations spécifiques aux implants intra-corticaux -- Travaux de pointe dans le domaine -- Dispositifs implantables -- Liens inductifs -- Composants externes -- Travaux du laboratoire de neurotechnologies polystim -- Conception et validation du dispositif implantable -- Architecture globale de l'implant -- Module de stimulation -- Module d'interface -- Implémentation et résultats expérimentaux -- Faisabilité d'une prothèse complète sur la base de l'implant proposé -- Conception et validatin du contrôleur externe -- Optimisation au niveau de la puissance dissipée -- Description du système externe -- Implémentation et validation -- Système d'expérimentation in-vivo -- Parotocoles d'expérimentation comportementale -- Description du système expérimental -- Fabrication du système expérimental

Wired, wireless and wearable bioinstrumentation for high-precision recording of bioelectrical signals in bidirectional neural interfaces

It is widely accepted by the scientific community that bioelectrical signals, which can be used for the identification of neurophysiological biomarkers indicative of a diseased or pathological state, could direct patient treatment towards more effective therapeutic strategies. However, the design and realisation of an instrument that can precisely record weak bioelectrical signals in the presence of strong interference stemming from a noisy clinical environment is one of the most difficult challenges associated with the strategy of monitoring bioelectrical signals for diagnostic purposes. Moreover, since patients often have to cope with the problem of limited mobility being connected to bulky and mains-powered instruments, there is a growing demand for small-sized, high-performance and ambulatory biopotential acquisition systems in the Intensive Care Unit (ICU) and in High-dependency wards. Furthermore, electrical stimulation of specific target brain regions has been shown to alleviate symptoms of neurological disorders, such as Parkinson’s disease, essential tremor, dystonia, epilepsy etc. In recent years, the traditional practice of continuously stimulating the brain using static stimulation parameters has shifted to the use of disease biomarkers to determine the intensity and timing of stimulation. The main motivation behind closed-loop stimulation is minimization of treatment side effects by providing only the necessary stimulation required within a certain period of time, as determined from a guiding biomarker. Hence, it is clear that high-quality recording of local field potentials (LFPs) or electrocorticographic (ECoG) signals during deep brain stimulation (DBS) is necessary to investigate the instantaneous brain response to stimulation, minimize time delays for closed-loop neurostimulation and maximise the available neural data. To our knowledge, there are no commercial, small, battery-powered, wearable and wireless recording-only instruments that claim the capability of recording ECoG signals, which are of particular importance in closed-loop DBS and epilepsy DBS. In addition, existing recording systems lack the ability to provide artefact-free high-frequency (> 100 Hz) LFP recordings during DBS in real time primarily because of the contamination of the neural signals of interest by the stimulation artefacts. To address the problem of limited mobility often encountered by patients in the clinic and to provide a wide variety of high-precision sensor data to a closed-loop neurostimulation platform, a low-noise (8 nV/√Hz), eight-channel, battery-powered, wearable and wireless multi-instrument (55 × 80 mm2) was designed and developed. The performance of the realised instrument was assessed by conducting both ex vivo and in vivo experiments. The combination of desirable features and capabilities of this instrument, namely its small size (~one business card), its enhanced recording capabilities, its increased processing capabilities, its manufacturability (since it was designed using discrete off-the-shelf components), the wide bandwidth it offers (0.5 – 500 Hz) and the plurality of bioelectrical signals it can precisely record, render it a versatile tool to be utilized in a wide range of applications and environments. Moreover, in order to offer the capability of sensing and stimulating via the same electrode, novel real-time artefact suppression methods that could be used in bidirectional (recording and stimulation) system architectures are proposed and validated. More specifically, a novel, low-noise and versatile analog front-end (AFE), which uses a high-order (8th) analog Chebyshev notch filter to suppress the artefacts originating from the stimulation frequency, is presented. After defining the system requirements for concurrent LFP recording and DBS artefact suppression, the performance of the realised AFE is assessed by conducting both in vitro and in vivo experiments using unipolar and bipolar DBS (monophasic pulses, amplitude ranging from 3 to 6 V peak-to-peak, frequency 140 Hz and pulse width 100 µs). Under both in vitro and in vivo experimental conditions, the proposed AFE provided real-time, low-noise and artefact-free LFP recordings (in the frequency range 0.5 – 250 Hz) during stimulation. Finally, a family of tunable hardware filter designs and a novel method for real-time artefact suppression that enables wide-bandwidth biosignal recordings during stimulation are also presented. This work paves the way for the development of miniaturized research tools for closed-loop neuromodulation that use a wide variety of bioelectrical signals as control signals.Open Acces