Current-efficient preamplifier architecture for CMRR sensitive neural recording applications

Este trabajo fue parcialmente financiado por CSIC (Comisión Sectorial de Investigación Científica, Uruguay), ANII (Agencia Nacional de Investigación e Innovación, Uruguay) y CAP (Comisión Académica de Posgrado, Uruguay).There are neural recording applications in which the amplitude of common-mode interfering signals is several orders of magnitude higher than the amplitude of the signals of interest. This challenging situation for neural amplifiers occurs, among other applications, in neural recordings of weakly electric fish or nerve activity recordings made with cuff electrodes. This paper reports an integrated neural amplifier architecture targeting invivo recording of local field potentials and unitary signals from the brain stem of a weakly electric fish Gymnotus omarorum. The proposed architecture offers low noise, high common-mode rejection ratio (CMRR), current-efficiency, and a high-pass frequency fixed without MOS pseudoresistors. The main contributions of this work are the overall architecture coupled with an efficient and simple single-stage circuit for the amplifier main transconductor, and the ability of the amplifier to acquire biopotential signals from high-amplitude common-mode interference in an unshielded environment. A fully-integrated neural preamplifier, which performs well in line with the state-of-the-art of the field while providing enhanced CMRR performance, was fabricated in a 0.5 μm CMOS process. Results from measurements show that the gain is 49.5 dB, the bandwidth ranges from 13 Hz to 9.8 kHz, the equivalent input noise is 1.88 μVrms, the CMRR is 87 dB and the Noise Efficiency Factor is 2.1. In addition, in-vivo recordings of weakly electric fish neural activity performed by the proposed amplifier are introduced and favorably compared with those of a commercial laboratory instrumentation system

A high performance skin impedance measurement circuit for biomedical applications

This paper describes a high-performance impedance measurement circuit for the application of skin impedance measurement in the early detection of skin cancer. A CMRR improvement technique has been adopted for OTAs to reduce the impact of high frequency common mode interference. A modified 3-OTA IA has been proposed to help with the impedance measurement. Such systems offer a quick, non-invasive and painless procedure, thus having considerable advantages over the currently used approach, which is based upon the testing of a biopsy sample. The sensor has been implemented in 65nm CMOS technology and post layout simulations confirms the theoretical claims we made and sensor exhibits sensitivity. Circuit consumes 45uW from 1.5V power supply. The circuit occupies 0.01954mm2 silicon area

Current efficient integrated architecture for common mode rejection sensitive neural recordings

In the last decade we have seen a significant growth of research and potential applications of electronic circuits that interact with the nervous system, in a wide range of applications, from basic neuroscience research to medical clinic, or from the entertainment industry to transport services. The real time acquisition and analysis of brain signals, either through wearable electroencephalography (EEG) or invasive or implantable recordings, in order to perform actions (brain machine interface) or to understand aspects of brain operation, has become scientifically and technologically feasible. This thesis aims to support neural recording applications with low noise, currentefficiency and high common-mode rejection ratio (CMRR) as main features of the recording system. One emblematic example of these applications in the neuroscience domain is the weakly electric fish neural activity recording, where the interference produced by the discharge of the fish electric organ is a key factor. Another example, from the implantable devices domain, is the nerve activity recorded with cuff electrodes, where the desired signal is interfered by electromyographic potentials generated by muscles near the cuff. In these cases, the amplitude of the interfering signals, which mainly appear in common mode, is several orders of magnitude higher than the amplitude of the signals of interest. Therefore, this thesis introduces a novel integrated neural preamplifier architecture targeting CMRR sensitive neural recording applications. The architecture is presented and analyzed in depth, deriving the preamplifier transfer function and the main design equations. We present a detailed analysis of a technique for blocking the input dc component and setting the high-pass frequency without using MOS pseudo-resistors. One of the main contributions of this work is the overall architecture coupled with an efficient and simple single-stage circuit for the preamplifier main transconductor. A fully-integrated neural preamplifier, which performs well in line with the state-ofthe-art of the field while providing enhanced CMRR performance, was fabricated in a 0.5 um CMOS process. Results from measurements show that the measured gain is 49.5 dB, bandwidth ranges from 13 Hz to 9.8 kHz, CMRR is very high (greater than 87 dB), and it is achieved jointly with a remarkable low noise (1.88 uVrms) and current-efficiency (NEF = noise efficiency factor = 2.1). A second version of the preamplifier with one external capacitor achieves a high-pass frequency of 0.1 Hz while keeping the performance of the fully-integrated version. In addition, we present in-vivo measurements made with the proposed architecture in a weakly electric fish (Gymnotus omarorum), showing the ability of the preamplifier to acquire neural signals from high amplitude common mode interference in an unshielded environment. This was the first in-vivo testing of a neural recording integrated circuit designed in Uruguay done in a local lab. Furthermore, signals recorded with our unshielded low-power battery-powered preamplifier perfectly match with those of a shielded commercially-available amplifier (ac-plugged, without power restrictions). To the best of our knowledge, the proposed preamplifier is the best option for applications that simultaneously need low noise, high CMRR and current-efficiency. Furthermore, in this thesis we applied the aforementioned architecture to bandpass biquad filters, specially but not only, to those with differential input. The new architecture provides a significant reduction in consumption (up to 30%) and/or makes it possible to block a higher level of dc at the input (up to the double, without using decoupling capacitors). Next, we applied the novel architecture to the design of the different stages of an integrated programmable analog front-end. Results from simulations shows that the gain is programmable between 57 dB and 99 dB, the low-pass frequency is programmable between 116 Hz and 5.2 kHz, the maximum power consumption is 11.2 uA and the maximum equivalent input-referred noise voltage is 1.87 uVrms. The comparison between our front-end and other works in the state-of-the-art shows that our front-end presents the best results in terms of CMRR and noise, has the greatest value of gain and equals the best NEF reported. Finally, some system-level topics were addressed during this thesis, including the design and implementation of three prototypes of end-to-end wireless biopotentials recording systems based on off-the-shelf components. Developing and applying circuits, systems and methods, for synchronized largescale monitoring of neural activity, sensory images, and behavior, would produce a dynamic picture of the brain function, which is essential for understanding the brain in action. In this context, we hope that the present thesis become our first step to further contribute to this area

Improving the mechanistic study of neuromuscular diseases through the development of a fully wireless and implantable recording device

Neuromuscular diseases manifest by a handful of known phenotypes affecting the peripheral nerves, skeletal muscle fibers, and neuromuscular junction. Common signs of these diseases include demyelination, myasthenia, atrophy, and aberrant muscle activity—all of which may be tracked over time using one or more electrophysiological markers. Mice, which are the predominant mammalian model for most human diseases, have been used to study congenital neuromuscular diseases for decades. However, our understanding of the mechanisms underlying these pathologies is still incomplete. This is in part due to the lack of instrumentation available to easily collect longitudinal, in vivo electrophysiological activity from mice. There remains a need for a fully wireless, batteryless, and implantable recording system that can be adapted for a variety of electrophysiological measurements and also enable long-term, continuous data collection in very small animals. To meet this need a miniature, chronically implantable device has been developed that is capable of wirelessly coupling energy from electromagnetic fields while implanted within a body. This device can both record and trigger bioelectric events and may be chronically implanted in rodents as small as mice. This grants investigators the ability to continuously observe electrophysiological changes corresponding to disease progression in a single, freely behaving, untethered animal. The fully wireless closed-loop system is an adaptable solution for a range of long-term mechanistic and diagnostic studies in rodent disease models. Its high level of functionality, adjustable parameters, accessible building blocks, reprogrammable firmware, and modular electrode interface offer flexibility that is distinctive among fully implantable recording or stimulating devices. The key significance of this work is that it has generated novel instrumentation in the form of a fully implantable bioelectric recording device having a much higher level of functionality than any other fully wireless system available for mouse work. This has incidentally led to contributions in the areas of wireless power transfer and neural interfaces for upper-limb prosthesis control. Herein the solution space for wireless power transfer is examined including a close inspection of far-field power transfer to implanted bioelectric sensors. Methods of design and characterization for the iterative development of the device are detailed. Furthermore, its performance and utility in remote bioelectric sensing applications is demonstrated with humans, rats, healthy mice, and mouse models for degenerative neuromuscular and motoneuron diseases

Um amplificador de transcondutância cmos de baixa potência com melhoria da cmrr

This work presents a topology of a low power Transconductance Operational Amplifier (OTA) for the compensation of Common Mode Rejection Ratio (CMRR), in which the transistors operate in the strong inversion mode. Initially, a theoretical review of the differential amplifier and OTA is presented. Then, an OTA architecture was proposed based on a symmetric differential amplifier structure with additional transistors in parallel to the input MOS transistors, in order to increase the CMRR rate, as well as the proposed compensation strategy. The OTA was designed using IBM 130 nm CMOS technology. Monte Carlo and Corner simulations were performed to analyze the compensation strategy and to obtain a more realistic assessment. The results obtained demonstrate that the proposed circuit for common mode control operates correctly, since the proposed OTA enabled common mode control in parallel, obtaining a CMRR of 87.34 dB and power consumption of 9.65 μW, validating its compatibility with low power circuits.Agência 1Este trabalho apresenta uma topologia de um Amplificador Operacional de Transcondutância (OTA) de baixa potência para a compensação da Razão de Rejeição de Modo Comum (CMRR), onde os transistores operam no modo de inversão forte. Inicialmente, é apresentada uma revisão teórica acerca do amplificador diferencial e do OTA. Em seguida, foi proposta uma arquitetura de OTA baseado em uma estrutura de amplificador diferencial simétrico com transistores adicionais em paralelo aos transistores MOS de entrada, a fim de aumentar a taxa de CMRR, bem como a estratégia de compensação proposta. O OTA foi projetado utilizando a tecnologia CMOS IBM 130 nm. Para analisar a estratégia de compensação e obter uma avaliação mais realista foram realizadas as simulações de Monte Carlo e Corner. Os resultados obtidos demonstram que o circuito proposto para controle de modo comum opera corretamente, uma vez que o OTA proposto possibilitou o controle de modo comum em paralelo obtendo uma CMRR de 87,34 dB e consumo de potência de 9,65 μW, validando sua compatibilidade com circuitos de baixa potência

A Novel Power-Efficient Wireless Multi-channel Recording System for the Telemonitoring of Electroencephalography (EEG)

This research introduces the development of a novel EEG recording system that is modular, batteryless, and wireless (untethered) with the supporting theoretical foundation in wireless communications and related design elements and circuitry. Its modular construct overcomes the EEG scaling problem and makes it easier for reconfiguring the hardware design in terms of the number and placement of electrodes and type of standard EEG system contemplated for use. In this development, portability, lightweight, and applicability to other clinical applications that rely on EEG data are sought. Due to printer tolerance, the 3D printed cap consists of 61 electrode placements. This recording capacity can however extend from 21 (as in the international 10-20 systems) up to 61 EEG channels at sample rates ranging from 250 to 1000 Hz and the transfer of the raw EEG signal using a standard allocated frequency as a data carrier. The main objectives of this dissertation are to (1) eliminate the need for heavy mounted batteries, (2) overcome the requirement for bulky power systems, and (3) avoid the use of data cables to untether the EEG system from the subject for a more practical and less restrictive setting. Unpredictability and temporal variations of the EEG input make developing a battery-free and cable-free EEG reading device challenging. Professional high-quality and high-resolution analog front ends are required to capture non-stationary EEG signals at microvolt levels. The primary components of the proposed setup are the wireless power transmission unit, which consists of a power amplifier, highly efficient resonant-inductive link, rectification, regulation, and power management units, as well as the analog front end, which consists of an analog to digital converter, pre-amplification unit, filtering unit, host microprocessor, and the wireless communication unit. These must all be compatible with the rest of the system and must use the least amount of power possible while minimizing the presence of noise and the attenuation of the recorded signal A highly efficient resonant-inductive coupling link is developed to decrease power transmission dissipation. Magnetized materials were utilized to steer electromagnetic flux and decrease route and medium loss while transmitting the required energy with low dissipation. Signal pre-amplification is handled by the front-end active electrodes. Standard bio-amplifier design approaches are combined to accomplish this purpose, and a thorough investigation of the optimum ADC, microcontroller, and transceiver units has been carried out. We can minimize overall system weight and power consumption by employing battery-less and cable-free EEG readout system designs, consequently giving patients more comfort and freedom of movement. Similarly, the solutions are designed to match the performance of medical-grade equipment. The captured electrical impulses using the proposed setup can be stored for various uses, including classification, prediction, 3D source localization, and for monitoring and diagnosing different brain disorders. All the proposed designs and supporting mathematical derivations were validated through empirical and software-simulated experiments. Many of the proposed designs, including the 3D head cap, the wireless power transmission unit, and the pre-amplification unit, are already fabricated, and the schematic circuits and simulation results were based on Spice, Altium, and high-frequency structure simulator (HFSS) software. The fully integrated head cap to be fabricated would require embedding the active electrodes into the 3D headset and applying current technological advances to miniaturize some of the design elements developed in this dissertation

Recent Advances in Neural Recording Microsystems

The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field

Interfaces neuronales CMOS haute résolution pour l'électrophysiologie et l'optogénétique en boucle fermée

L’avenir de la recherche sur les maladies du cerveau repose sur le développement de nouvelles technologies qui permettront de comprendre comment cet organe si complexe traite, intègre et transfère l’information. Parmi celles-ci, l’optogénétique est une technologie révolutionnaire qui permet d’utiliser de la lumière afin d’activer sélectivement les neurones du cortex d’animaux transgéniques pour observer leur effet dans un vaste réseau biologique. Ce cadre expérimental repose typiquement sur l’observation de l’activité neuronale de souris transgéniques, car elles peuvent exprimer une grande variété de gènes et de maladies et qu’elles sont peu couteuses. Toutefois, la plupart des appareils de mesure ou de stimulation optogénétique disponible ne sont pas appropriés, car ils sont câblés, trop lourds et/ou trop simplistes. Malheureusement, peu de systèmes sans fil existent, et ces derniers sont grandement limités par la bande passante requise pour transmettre les données neuronales, et ils ne fournissent pas de stimulation optogénétique multicanal afin de stimuler et observer plusieurs régions du cerveau. Dans les dispositifs actuels, l’interprétation des données neuronales est effectuée ex situ, alors que la recherche bénéficierait grandement de systèmes sans fil assez intelligents pour interpréter et stimuler les neurones en boucle fermée, in situ. Le but de ce projet de recherche est de concevoir des circuits analogiques-numériques d’acquisition et de traitement des signaux neuronaux, des algorithmes d’analyse et de traitement de ces signaux et des systèmes electro-optiques miniatures et sans fil pour : i) Mener des expériences combinant l’enregistrement neuronal et l’optogénétique multicanal haute résolution avec des animaux libres de leurs mouvements. ii) Mener des expériences optogénétiques synchronisées avec l’observation, c.-à-d. en boucle fermée, chez des animaux libres de leurs mouvements. iii) Réduire la taille, le poids et la consommation énergétique des systèmes optogénétiques sans fil afin de minimiser l’impact de la recherche chez de petits animaux. Ce projet est en 3 phases, et ses principales contributions ont été rapportées dans dix conférences internationales (ISSCC, ISCAS, EMBC, etc.) et quatre articles de journaux publiés ou soumis, ainsi que dans un brevet et deux divulgations. La conception d’un système optogénétique haute résolution pose plusieurs défis importants. Notamment, puisque les signaux neuronaux ont un contenu fréquentiel élevé (_10 kHz), le nombre de canaux sous observation est limité par la bande passante des transmetteurs sans fil (2-4 canaux en général). Ainsi, la première phase du projet a visé le développement d’algorithmes de compression des signaux neuronaux et leur intégration dans un système optogénétique sans fil miniature et léger (2.8 g) haute résolution possédant 32 canaux d’acquisition et 32 canaux de stimulation optique. Le système détecte, compresse et transmet les formes d’onde des potentiels d’action (PA) produits par les neurones avec un field programmable gate array (FPGA) embarqué à faible consommation énergétique. Ce processeur implémente un algorithme de détection des PAs basé sur un seuillage adaptatif, ce qui permet de compresser les signaux en transmettant seulement les formes détectées. Chaque PA est davantage compressé par une transformée en ondelette discrète (DWT) de type Symmlet-2 suivie d’une technique de discrimination et de requantification dynamique des coefficients. Les résultats obtenus démontrent que cet algorithme est plus robuste que les méthodes existantes tout en permettant de reconstruire les signaux compressés avec une meilleure qualité (SNDR moyen de 25 dB _ 5% pour un taux de compression (CR) de 4.2). Avec la détection, des CR supérieurs à 500 sont rapportés lors de la validation in vivo. L’utilisation de composantes commerciales dans des systèmes optogénétiques sans fil augmentela taille et la consommation énergétique, en plus de ne pas être optimisée pour cette application. La seconde phase du projet a permis de concevoir un système sur puce (SoC) complementary metal oxide semiconductor (CMOS) pour faire de l’enregistrement neuronal et de optogénétique multicanal, permettant de réduire significativement la taille et la consommation énergétique comparativement aux alternatives commerciales. Ceci est une contribution importante, car c’est la première puce à être doté de ces deux fonctionnalités. Le SoC possède 10 canaux d’enregistrement et 4 canaux de stimulation optogénétique. La conception du bioamplificateur inclut une bande passante programmable (0.5 Hz - 7 kHz) et un faible bruit referré à l’entré (IRN de 3.2 μVrms), ce qui permet de cibler différents types de signaux biologiques (PA, LFP, etc.). Le convertisseur analogique numérique (ADC) de type Delta- Sigma (DS) MASH 1-1-1 est conçu pour fonctionner de faibles taux de sur-échantillonnage (OSR _50) pour réduire sa consommation et possède une résolution programmable (ENOB de 9.75 Bits avec un OSR de 25). Cet ADC exploite une nouvelle technique réduisant la taille du circuit en soustrayant la sortie de chaque branche du DS dans le domaine numérique, comparativement à la méthode analogique classique. La consommation totale d’un canal d’enregistrement est de 11.2 μW. Le SoC implémente un nouveau circuit de stimulation optique basé sur une source de courant de type cascode avec rétroaction, ce qui permet d’accommoder une large gamme de LED et de tensions de batterie comparativement aux circuits existants. Le SoC est intégré dans un système optogénétique sans fil et validé in vivo. À ce jour et en excluant ce projet, aucun système sans-fil ne fait de l’optogénétique en boucle fermée simultanément au suivi temps réel de l’activité neuronale. Une contribution importante de ce travail est d’avoir développé le premier système optogénétique multicanal qui est capable de fonctionner en boucle fermée et le premier à être validé lors d’expériences in vivo impliquant des animaux libres de leurs mouvements. Pour ce faire, la troisième phase du projet a visé la conception d’un SoC CMOS numérique, appelé neural decoder integrated circuit (ND-IC). Le ND-IC et le SoC développé lors de la phase 2 ont été intégrés dans un système optogénétique sans fil. Le ND-IC possède 3 modules : 1) le détecteur de PA adaptatif, 2) le module de compression possédant un nouvel arbre de tri pour discriminer les coefficients, et 3) le module de classement automatique des PA qui réutilise les données générées par le module de détection et de compression pour réduire sa complexité. Un lien entre un canal d’enregistrement et un canal de stimulation est établi selon l’association de chaque PA à un neurone, grâce à la classification, et selon l’activité de ce neurone dans le temps. Le ND-IC consomme 56.9 μW et occupe 0.08 mm2 par canal. Le système pèse 1.05 g, occupe un volume de 1.12 cm3, possède une autonomie de 3h, et est validé in vivo.The future of brain research lies in the development of new technologies that will help understand how this complex organ processes, integrates and transfers information. Among these, optogenetics is a recent technology that allows the use of light to selectively activate neurons in the cortex of transgenic animals to observe their effect in a large biological network. This experimental setting is typically based on observing the neuronal activity of transgenic mice, as they express a wide variety of genes and diseases, while being inexpensive. However, most available neural recording or optogenetic devices are not suitable, because they are hard-wired, too heavy and/or too simplistic. Unfortunately, few wireless systems exist, and they are greatly limited by the required bandwidth to transmit neural data, while not providing simultaneous multi-channel neural recording and optogenetic, a must for stimulating and observing several areas of the brain. In current devices, the analysis of the neuronal data is performed ex situ, while the research would greatly benefit from wireless systems that are smart enough to interpret and stimulate the neurons in closed-loop, in situ. The goal of this project is to design analog-digital circuits for acquisition and processing of neural signals, algorithms for analysis and processing of these signals and miniature electrooptical wireless systems for: i) Conducting experiments combining high-resolution multi-channel neuronal recording and high-resolution multi-channel optogenetics with freely-moving animals. ii) Conduct optogenetic experiments synchronized with the neural recording, i.e. in closed loop, with freely-moving animals. iii) Increase the resolution while reducing the size, weight and energy consumption of the wireless optogenetic systems to minimize the impact of research with small animals. This project is in 3 phases, and its main contributions have been reported in ten conferences (ISSCC, ISCAS, EMBC, etc.) and four published journal papers, or submitted, as well as in a patent and two disclosures. The design of a high resolution optogenetic system poses several challenges. In particular, since the neuronal signals have a high frequency content (10 kHz), the number of chanv nels under observation is limited by the bandwidth of the wireless transmitters (2-4 channels in general). Thus, the first phase of the project focused on the development of neural signal compression algorithms and their integration into a high-resolution miniature and lightweight wireless optogenetics system (2.8g), having 32 recording channels and 32 optical stimulation channels. This system detects, compresses and transmits the waveforms of the signals produced by the neurons, i.e. action potentials (AP), in real time, via an embedded low-power field programmable gate array (FPGA). This processor implements an AP detector algorithm based on adaptive thresholding, which allows to compress the signals by transmitting only the detected waveforms. Each AP is further compressed by a Symmlet-2 discrete wavelet transform (DWT) followed dynamic discrimination and requantification of the DWT coefficients, making it possible to achieve high compression ratios with a good reconstruction quality. Results demonstrate that this algorithm is more robust than existing approach, while allowing to reconstruct the compressed signals with better quality (average SNDR of 25 dB 5% for a compression ratio (CR) of 4.2). With detection, CRs greater than 500 are reported during the in vivo validation. The use of commercial components in wireless optogenetic systems increases the size and power consumption, while not being optimized for this application. The second phase of the project consisted in designing a complementary metal oxide semiconductor (CMOS) system-on-chip (SoC) for neural recording and multi-channel optogenetics, which significantly reduces the size and energy consumption compared to commercial alternatives. This is important contribution, since it’s the first chip to integrate both features. This SoC has 10 recording channels and 4 optogenetic stimulation channels. The bioamplifier design includes a programmable bandwidth (0.5 Hz -7 kHz) and a low input-referred noise (IRN of 3.2 μVrms), which allows targeting different biological signals (AP, LFP, etc.). The Delta-Sigma (DS) MASH 1-1-1 low-power analog-to-digital converter (ADC) is designed to work with low OSR (50), as to reduce its power consumption, and has a programmable resolution (ENOB of 9.75 bits with an OSR of 25). This ADC uses a new technique to reduce its circuit size by subtracting the output of each DS branch in the digital domain, rather than in the analog domain, as done conventionally. A recording channel, including the bioamplifier, the DS and the decimation filter, consumes 11.2 μW. Optical stimulation is performed with an on-chip LED driver using a regulated cascode current source with feedback, which accommodates a wide range of LED parameters and battery voltages. The SoC is integrated into a wireless optogenetic platform and validated in vivo.To date and excluding this project, no wireless system is making closed-loop optogenetics simultaneously to real-time monitoring of neuronal activity. An important contribution of this work is to have developed the first multi-channel optogenetic system that is able to work in closed-loop, and the first to be validated during in vivo experiments involving freely-moving animals. To do so, the third phase of the project aimed to design a digital CMOS chip, called neural decoder integrated circuit (ND-IC). The ND-IC and the SoC developed in Phase 2 are integrated within a wireless optogenetic system. The ND-IC has 3 main cores: 1) the adaptive AP detector core, 2) the compression core with a new sorting tree for discriminating the DWT coefficients, and 3 ) the AP automatic classification core that reuses the data generated by the detection and compression cores to reduce its complexity. A link between a recording channel and a stimulation channel is established according to the association of each AP with a neuron, thanks to the classification, and according to the bursting activity of this neuron. The ND-IC consumes 56.9 μW and occupies 0.08 mm2 per channel. The system weighs 1.05 g, occupies a volume of 1.12 cm3, has an autonomy of 3h, and is validated in vivo