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We present a study on wavelet detection methods of neuronal action potentials (APs). Our final goal is to implement the selected algorithms on custom integrated electronics for on-line processing of neural signals; therefore we take real-time computing as a hard specification and silicon area as a price to pay. Using simulated neural signals including APs, we characterize an efficient wavelet method for AP extraction by evaluating its detection rate and its implementation cost. We comparedoi:10.3389/fneng.2011.00007 pmid:21811455 pmcid:PMC3139942 fatcat:5o36ouiyh5fwzdkpcytustohaq
more »... re implementation for three methods: adaptive threshold, discrete wavelet transform (DWT), and stationary wavelet transform (SWT). We evaluate detection rate and implementation cost for detection functions dynamically comparing a signal with an adaptive threshold proportional to its SD, where the signal is the raw neural signal, respectively: (i) non-processed; (ii) processed by a DWT; (iii) processed by a SWT. We also use different mother wavelets and test different data formats to set an optimal compromise between accuracy and silicon cost. Detection accuracy is evaluated together with false negative and false positive detections. Simulation results show that for on-line AP detection implemented on a configurable digital integrated circuit, APs underneath the noise level can be detected using SWT with a well-selected mother wavelet, combined to an adaptive threshold.
Electrical stimulation of the nervous system is commonly based on biphasic stimulation waveforms, which limits its relevance for some applications, such as selective stimulation. We propose in this paper a stimulator capable of delivering arbitrary waveforms to electrodes, and suitable for non-conventional stimulation strategies. Such a system enables in vivo stimulation protocols with optimized efficacy or energy efficiency. The designed system comprises a High Voltage CMOS ASIC generating adoi:10.3390/electronics10151867 fatcat:7kgqowr6xrbhtc5o222fotttvu
more »... nfigurable stimulating current, driven by a digital circuitry implemented on a FPGA. After fabrication, the ASIC and system were characterized and tested; they successfully generated programmable waveforms with a frequential content up to 1.2 MHz and a voltage compliance between [−17.9; +18.3] V. The system is not optimum when compared to single application stimulators, but no embedded stimulator in the literature offers an equivalent bandwidth which allows the wide range of stimulation paradigms, including high-frequency blocking stimulation. We consider that this stimulator will help test unconventional stimulation waveforms and can be used to generate proof-of-concept data before designing implantable and application-dedicated implantable stimulators.
Cervical spinal cord injury can disrupt connections between the brain respiratory network and the respiratory muscles which can lead to partial or complete loss of ventilatory control and require ventilatory assistance. Unlike current open-loop technology, a closed-loop diaphragmatic pacing system could overcome the drawbacks of manual titration as well as respond to changing ventilation requirements. We present an original bio-inspired assistive technology for real-time ventilation assistance,doi:10.3389/fnins.2016.00275 pmid:27378844 pmcid:PMC4909776 fatcat:fdgrgypchnbq7ky6g7swni7d3m
more »... implemented in a digital configurable Field Programmable Gate Array (FPGA). The bio-inspired controller, which is a spiking neural network (SNN) inspired by the medullary respiratory network, is as robust as a classic controller while having a flexible, low-power and low-cost hardware design. The system was simulated in MATLAB with FPGA-specific constraints and tested with a computational model of rat breathing; the model reproduced experimentally collected respiratory data in eupneic animals. The open-loop version of the bio-inspired controller was implemented on the FPGA. Electrical test bench characterizations confirmed the system functionality. Open and closed-loop paradigm simulations were simulated to test the FPGA system real-time behavior using the rat computational model. The closed-loop system monitors breathing and changes in respiratory demands to drive diaphragmatic stimulation. The simulated results inform future acute animal experiments and constitute the first step toward the development of a neuromorphic, adaptive, compact, low-power, implantable device. The bio-inspired hardware design optimizes the FPGA resource and time costs while harnessing the computational power of spike-based neuromorphic hardware. Its real-time feature makes it suitable for in vivo applications.
Electrical stimulation of nerve tissue and recording of neural electrical activity are the basis of emerging prostheses and treatments for many neurological disorders. Here we present closed-loop biohybrid experiment using in vitro Biological Neuronal Network (BNN) with an Artificial Neural Network (ANN) implemented in a neuromorphic board. We adopted a neuromorphic board which is able to perform real-time event detection and trigger an electrical stimulation of the BNN. This system embeds andoi:10.1007/s10015-017-0366-1 fatcat:aehudp76nnh33o7ahm4qlzrnva
more »... N, based on Izhikevich neurons which can be put in uni-and bi-directional communication with the BNN. The ANN used in the following experiments was made up of 20 excitatory neurons with inhibition synapse and with synaptic plasticity to design Central Pattern Generator (CPG). Open-loop and closed-loop hybrid experiments shows that the biological dynamics can be modified. This work can be seen as the first step towards the realization of an innovative neuroprosthesis.
Bornat, M. Raoux, J. Lang, S. Renaud, paper presented at the IEEE International Symposium 846 on Circuits and Systems (ISCAS), Seoul, South Korea, 20-23 May 2012. 847 68. R. R. ...doi:10.1101/514836 fatcat:xjhbukbfmrhk5lkzt3s6nq2qhu
We introduce and test a system for simulating networks of conductance-based neuron models using analog circuits. At the single-cell level, we use custom-designed analog circuits (ASICs) that simulate two types of spiking neurons based on Hodgkin-Huxley like dynamics: "regular spiking" excitatory neurons with spike-frequency adaptation, and "fast spiking" inhibitory neurons. Synaptic interactions are mediated by conductance-based synaptic currents described by kinetic models. Connectivity anddoi:10.1080/09548980600711124 pmid:17162612 fatcat:jkjorhpywrg3hk4bbsrnqdwe3a
more »... sticity rules are implemented digitally through a real time interface between a computer and a PCI board containing the ASICs. We show a prototype system of a few neurons interconnected with synapses undergoing spike-timing dependent plasticity (STDP), and compare this system with numerical simulations. We use this system to evaluate the effect of parameter dispersion on the behavior of small circuits of neurons. It is shown that, although the exact spike timings are not precisely emulated by the ASIC neurons, the behavior of small networks with STDP matches that of numerical simulations. Thus, this mixed analog-digital architecture provides a valuable tool for real-time simulations of networks of neurons with STDP. They should be useful for any real-time application, such as hybrid systems interfacing network models with biological neurons.
Aims/hypothesis Ion fluxes constitute a major integrative signal in beta cells that leads to insulin secretion and regulation of gene expression. Understanding these electrical signals is important for deciphering the endogenous algorithms used by islets to attain homeostasis and for the design of new sensors for monitoring beta cell function. Methods Mouse and human islets were cultured on multielectrode arrays (MEAs) for 3-13 days. Extracellular electrical activities received on eachdoi:10.1007/s00125-015-3558-z pmid:25788295 fatcat:mhgc2a2mh5c2rhe67lxohx7o6m
more »... were continuously amplified and recorded for offline characterisation. Results Differential band-pass filtering of MEA recordings of mouse islets showed two extracellular voltage waveforms: action potentials (lasting 40-60 ms) and very robust slow potentials (SPs, lasting 800-1,500 ms), the latter of which have not been described previously. The frequency of SPs directly correlated with glucose concentration, peaked at 10 mmol/l glucose and was further augmented by picomolar concentrations of glucagon-like peptide-1. SPs required the closure of ATP-dependent potassium channels as they were induced by glucose or glibenclamide but were not elicited by KCl-induced depolarisation. Pharmacological tools and the use of beta cell specific knockout mice showed that SPs reflected cell coupling via connexin 36. Moreover, increasing and decreasing glucose ramps showed hysteresis with reduced glucose sensitivity during the decreasing phase. SPs were also observed in human islets and could be continuously recorded over 24 h. Conclusions/interpretation This novel electrical signature reflects the syncytial function of the islets and is specific to beta M. Raoux and J. Lang contributed equally to this work. Electronic supplementary material The online version of this article (doi:10.1007/s00125-015-3558-z) contains peer-reviewed but unedited supplementary material, which is available to authorised users. cells. Moreover, the observed hysteresis provides evidence for an endogenous algorithm naturally present in islets to protect against hypoglycaemia.
Pflugers Arch 411: 429-435 Raoux M, Bontorin G, Bornat Y, Lang J, Renaud S. (2011). Bioelectronic sensing of insulin demand. In Biohybrid Systems -Nerves, Interfaces and Machines, Jung R (ed). ...doi:10.1113/jphysiol.2011.220038 pmid:22199167 fatcat:h3usqst7pfdgxlohvrhmtir6x4
This paper aims at discussing the implementation of simulation systems for SNN based on analog computation cores (neuromimetic ICs). Such systems are an alternative to completely digital solutions for the simulation of spiking neurons or neural networks. Design principles for the neuromimetic ICs and the hosting systems are presented together with their features and performances. We summarize the existing architectures and neuron models used in such systems, when configured as stand-alone toolsdoi:10.1109/iscas.2007.378286 dblp:conf/iscas/RenaudTBDS07 fatcat:akxbcmtur5gtflchxqcftoux7i
more »... for simulating ANN or together with a neurophysiology set-up to study hybrid living artificial neural networks. As a primary illustration, we present results from one of the platforms: hardware simulations of single neurons and adaptive neural networks modeled using the Hodgkin-Huxley formalism for point neurons and spike-timing dependent plasticity algorithms for the network adaptation. Additional examples are detailed in the other papers of the session.
Pirog, A., Bornat, Y., Perrier, R., Raoux, M., Jaffredo, M., Quotb, A., Lang, J., Lewis, N., and Renaud, S. (2018). ... ., Bornat, Y., Tedesco, M., Bisio, M., et al. (2013). In vitro largescale experimental and theoretical studies for the realization of bi-directional brain-prostheses. Front. ...doi:10.1016/j.isci.2019.07.046 pmid:31421595 pmcid:PMC6706626 fatcat:n2lk5zws3nfulobeckryb3vqn4
Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With that aim, we designed Multimed, which is a versatile hardware platform for the real-time recording and processing of biosignals. Digital processing in Multimed is an arrangement of genericdoi:10.3390/s18072099 pmid:29966339 pmcid:PMC6069272 fatcat:ukdul5rc6rduxcgbwaw6wbmebi
more »... rocessing units from a custom library. These can freely be rearranged to match the needs of the application. Embedded onto a Field Programmable Gate Array (FPGA), these modules utilize full-hardware signal processing to lower processing latency. It achieves constant latency, and sub-millisecond processing and decision-making on 64 channels. The FPGA core processing unit makes Multimed suitable as either a reconfigurable electrophysiology system or a prototyping platform for VLSI implantable medical devices. It is specifically designed for open-and closed-loop experiments and provides consistent feedback rules, well within biological microseconds timeframes. This paper presents the specifications and architecture of the Multimed system, then details the biosignal processing algorithms and their digital implementation. Finally, three applications utilizing Multimed in neuroscience and diabetes research are described. They demonstrate the system's configurability, its multi-channel, real-time processing, and its feedback control capabilities.
We present a reconfigurable acquisition and wavelet-based detection circuit, NeuroBetaMed, for in vitro biological signals. It is implemented on a configurable digital integrated circuit (FPGA). We consider real-time computing as a hard specification and silicon area as a price to pay. It is designed for noisy signals like those recorded from in vitro cellular preparations, by extracellular electrodes. NeuroBetaMed performs biological signal acquisition, stationary wavelet transform (SWT) anddoi:10.1109/iscas.2012.6271542 dblp:conf/iscas/QuotbBRLR12 fatcat:vibhr6xx6jez5opsrprxaird2q
more »... aptive thresholding to detect action potentials (APs). Initially developed to detect pancreatic islet cells action potentials, this system is also suitable for neural signals.
In this position paper we propose a new approach to provide online in-vivo recordings of organ activity in real time and to overcome three major shortcuts of currently used invasive glucose sensors. In the context of diabetes, standard glucosensors recognize only glucose, whereas circulating lipids as well as amino acids are known to increase the demand in insulin and, under physiological circumstances, its secretion. Furthermore, the integration of other relevant signals such as hormonesdoi:10.1109/delta.2010.60 dblp:conf/delta/BornatRBMCLR10 fatcat:3l4fjormfbafve3tjxqlpzfd6e
more »... es a clear advantage. Consequently, using the -cell as a signal integrator combined with ASIC technology ensures a physiological signal and its read-out in real time thus avoiding complex algorithms. We describe a closed-loop architecture for exploiting those bio-sensors and potentially able to provide a control feedback for real-time insulin delivery.
Bornat, J. Tomas, and S. Renaud are with the IMS Laboratory at the University of Bordeaux, Talence 33400, France (e-mail: sylvain. email@example.com). G. ...doi:10.1109/tbcas.2010.2078816 pmid:23850974 fatcat:mrizhahjvjawnebbkmmwps3jea
Neural prostheses based on electrical microstimulation offer promising perspectives to restore functions following lesions of the central nervous system (CNS). They require the identification of appropriate stimulation sites and the coordination of their activation to achieve the restoration of functional activity. On the long term, a challenging perspective is to control microstimulation by artificial neural networks hybridized to the living tissue. Regarding the use of this strategy todoi:10.3389/fnins.2016.00067 pmid:27013936 pmcid:PMC4779903 fatcat:w2v3h74nrbg35ixp7a7emxljim
more »... locomotor activity in the spinal cord, to date, there has been no proof of principle of such hybrid approach driving intraspinal microstimulation (ISMS). Here, we address a first step toward this goal in the neonatal rat spinal cord isolated ex vivo, which can display locomotor-like activity while offering an easy access to intraspinal circuitry. Microelectrode arrays were inserted in the lumbar region to determine appropriate stimulation sites to elicit elementary bursting patterns on bilateral L2/L5 ventral roots. Two intraspinal sites were identified at L1 level, one on each side of the spinal cord laterally from the midline and approximately at a median position dorso-ventrally. An artificial CPG implemented on digital integrated circuit (FPGA) was built to generate alternating activity and was hybridized to the living spinal cord to drive electrical microstimulation on these two identified sites. Using this strategy, sustained left-right and flexor-extensor alternating activity on bilateral L2/L5 ventral roots could be generated in either whole or thoracically transected spinal cords. These results are a first step toward hybrid artificial/biological solutions based on electrical microstimulation for the restoration of lost function in the injured CNS.
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