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Sporer M, Vasilas IG, Adzemovic A, Graber N, Reich S, Gueli C, Eickenscheidt M, Diester I, Stieglitz T, Ortmanns M. NeuroBus - Architecture for an Ultra-Flexible Neural Interface. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2024; 18:247-262. [PMID: 38227403 DOI: 10.1109/tbcas.2024.3354785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
This article presents the system architecture for an implant concept called NeuroBus. Tiny distributed direct digitizing neural recorder ASICs on an ultra-flexible polyimide substrate are connected in a bus-like structure, allowing short connections between electrode and recording front-end with low wiring effort and high customizability. The small size (344 μm × 294 μm) of the ASICs and the ultraflexible substrate allow a low bending stiffness, enabling the implant to adapt to the curvature of the brain and achieving high structural biocompatibility. We introduce the architecture, the integrated building blocks, and the post-CMOS processes required to realize a NeuroBus, and we characterize the prototyped direct digitizing neural recorder front-end as well as polyimide-based ECoG brain interface. A rodent animal model is further used to validate the joint capability of the recording front-end and thin-film electrode array.
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Jang M, Hays M, Yu WH, Lee C, Caragiulo P, Ramkaj A, Wang P, Phillips AJ, Vitale N, Tandon P, Yan P, Mak PI, Chae Y, Chichilnisky EJ, Murmann B, Muratore DG. A 1024-Channel 268 nW/pixel 36×36 μm 2/channel Data-Compressive Neural Recording IC for High-Bandwidth Brain-Computer Interfaces. IEEE JOURNAL OF SOLID-STATE CIRCUITS 2024; 59:1123-1136. [PMID: 39391047 PMCID: PMC11463976 DOI: 10.1109/jssc.2023.3344798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/12/2024]
Abstract
This paper presents a data-compressive neural recording IC for single-cell resolution high-bandwidth brain-computer interfaces. The IC features wired-OR lossy compression during digitization, thus preventing data deluge and massive data movement. By discarding unwanted baseline samples of the neural signals, the output data rate is reduced by 146× on average while allowing the reconstruction of spike samples. The recording array consists of pulse position modulation-based active digital pixels with a global single-slope analog-to-digital conversion scheme, which enables a low-power and compact pixel design with significantly simple routing and low array readout energy. Fabricated in a 28-nm CMOS process, the neural recording IC features 1024 channels (i.e., 32 × 32 array) with a pixel pitch of 36 μm that can be directly matched to a high-density microelectrode array. The pixel achieves 7.4 μVrms input-referred noise with a -3 dB bandwidth of 300-Hz to 5-kHz while consuming only 268 nW from a single 1-V supply. The IC achieves the smallest area per channel (36 × 36 μm2) and the highest energy efficiency among the state-of-the-art neural recording ICs published to date.
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Affiliation(s)
- MoonHyung Jang
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Maddy Hays
- Department of Bioengineering, Stanford University, CA 94305 USA
| | - Wei-Han Yu
- Institute of Microelectronics, University of Macau, Avenida da Universidade, Taipa, Macau, China
| | - Changuk Lee
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, CA 94720, USA
| | - Pietro Caragiulo
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Athanasios Ramkaj
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Pingyu Wang
- Department of Materials Science and Engineering, Stanford University, CA 94305 USA
| | - A J Phillips
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Nick Vitale
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Pulkit Tandon
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Pumiao Yan
- Department of Electrical Engineering, Stanford University, CA 94305 USA
| | - Pui-In Mak
- Institute of Microelectronics, University of Macau, Avenida da Universidade, Taipa, Macau, China
| | - Youngcheol Chae
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea
| | - E J Chichilnisky
- Hansen Experimental Physics Laboratory, Department of Neurosurgery and Ophthalmology, Stanford University, CA 94305 USA
| | - Boris Murmann
- Department of Electrical Engineering, Stanford University; Department of Electrical & Computer Engineering, University of Hawaii at Mānoa, HI 96822
| | - Dante G Muratore
- Department of Microelectronics, Delft University of Technology, Delft, The Netherlands
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Oh S, Song H, Slager N, Ruiz JRL, Park SY, Yoon E. Power-Efficient LFP-Adaptive Dynamic Zoom-and-Track Incremental ΔΣ Front-End for Dual-Band Subcortical Recordings. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2023; 17:741-753. [PMID: 37490369 DOI: 10.1109/tbcas.2023.3298662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
We report a power-efficient analog front-end integrated circuit (IC) for multi-channel, dual-band subcortical recordings. In order to achieve high-resolution multi-channel recordings with low power consumption, we implemented an incremental ΔΣ ADC (IADC) with a dynamic zoom-and-track scheme. This scheme continuously tracks local field potential (LFP) and adaptively adjusts the input dynamic range (DR) into a zoomed sub-LFP range to resolve tiny action potentials. Thanks to the reduced DR, the oversampling rate of the IADC can be reduced by 64.3% compared to the conventional approach, leading to significant power reduction. In addition, dual-band recording can be easily attained because the scheme continuously tracks LFPs without additional on-chip hardware. A prototype four-channel front-end IC has been fabricated in 180 nm standard CMOS processes. The IADC achieved 11.3-bit ENOB at 6.8 μW, resulting in the best Walden and SNDR FoMs, 107.9 fJ/c-s and 162.1 dB, respectively, among two different comparison groups: the IADCs reported up to date in the state-of-the-art neural recording front-ends; and the recent brain recording ADCs using similar zooming or tracking techniques to this work. The intrinsic dual-band recording feature reduces the post-processing FPGA resources for subcortical signal band separation by >45.8%. The front-end IC with the zoom-and-track IADC showed an NEF of 5.9 with input-referred noise of 8.2 μVrms, sufficient for subcortical recording. The performance of the whole front-end IC was successfully validated through in vivo animal experiments.
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Luan L, Yin R, Zhu H, Xie C. Emerging Penetrating Neural Electrodes: In Pursuit of Large Scale and Longevity. Annu Rev Biomed Eng 2023; 25:185-205. [PMID: 37289556 PMCID: PMC11078330 DOI: 10.1146/annurev-bioeng-090622-050507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Penetrating neural electrodes provide a powerful approach to decipher brain circuitry by allowing for time-resolved electrical detections of individual action potentials. This unique capability has contributed tremendously to basic and translational neuroscience, enabling both fundamental understandings of brain functions and applications of human prosthetic devices that restore crucial sensations and movements. However, conventional approaches are limited by the scarce number of available sensing channels and compromised efficacy over long-term implantations. Recording longevity and scalability have become the most sought-after improvements in emerging technologies. In this review, we discuss the technological advances in the past 5-10 years that have enabled larger-scale, more detailed, and longer-lasting recordings of neural circuits at work than ever before. We present snapshots of the latest advances in penetration electrode technology, showcase their applications in animal models and humans, and outline the underlying design principles and considerations to fuel future technological development.
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Affiliation(s)
- Lan Luan
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
- Department of Bioengineering, Rice University, Houston, Texas, USA
| | - Rongkang Yin
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
| | - Hanlin Zhu
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
| | - Chong Xie
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
- Department of Bioengineering, Rice University, Houston, Texas, USA
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Yang X, Ballini M, Sawigun C, Hsu WY, Weijers JW, Putzeys J, Lopez CM. An AC-Coupled 1st-order Δ-ΔΣ Readout IC for Area-Efficient Neural Signal Acquisition. IEEE JOURNAL OF SOLID-STATE CIRCUITS 2023; 58:949-960. [PMID: 37840542 PMCID: PMC10572039 DOI: 10.1109/jssc.2023.3234612] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
The current demand for high-channel-count neural-recording interfaces calls for more area- and power-efficient readout architectures that do not compromise other electrical performances. In this paper, we present a miniature 128-channel neural recording integrated circuit (NRIC) for the simultaneous acquisition of local field potentials (LFPs) and action potentials (APs), which can achieve a very good compromise between area, power, noise, input range and electrode DC offset cancellation. An AC-coupled 1st-order digitally-intensive Δ - Δ Σ architecture is proposed to achieve this compromise and to leverage the advantages of a highly-scaled technology node. A prototype NRIC, including 128 channels, a newly-proposed area-efficient bulk-regulated voltage reference, biasing circuits and a digital control, has been fabricated in 22-nm FDSOI CMOS and fully characterized. Our proposed architecture achieves a total area per channel of 0.005 mm2, a total power per channel of 12.57 μ W , and an input-referred noise of 7.7 ± 0.4 μ V rms in the AP band and 11.9 ± 1.1 μ V rms in the LFP band. A very good channel-to-channel uniformity is demonstrated by our measurements. The chip has been validated in vivo, demonstrating its capability to successfully record full-band neural signals.
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Affiliation(s)
| | - Marco Ballini
- imec, Leuven, Belgium. He is now with TDK InvenSense, Milan, Italy
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Kouhalvandi L, Matekovits L, Peter I. Amplifiers in Biomedical Engineering: A Review from Application Perspectives. SENSORS (BASEL, SWITZERLAND) 2023; 23:2277. [PMID: 36850873 PMCID: PMC9961860 DOI: 10.3390/s23042277] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 01/22/2023] [Accepted: 02/15/2023] [Indexed: 05/31/2023]
Abstract
Continuous monitoring and treatment of various diseases with biomedical technologies and wearable electronics has become significantly important. The healthcare area is an important, evolving field that, among other things, requires electronic and micro-electromechanical technologies. Designed circuits and smart devices can lead to reduced hospitalization time and hospitals equipped with high-quality equipment. Some of these devices can also be implanted inside the body. Recently, various implanted electronic devices for monitoring and diagnosing diseases have been presented. These instruments require communication links through wireless technologies. In the transmitters of these devices, power amplifiers are the most important components and their performance plays important roles. This paper is devoted to collecting and providing a comprehensive review on the various designed implanted amplifiers for advanced biomedical applications. The reported amplifiers vary with respect to the class/type of amplifier, implemented CMOS technology, frequency band, output power, and the overall efficiency of the designs. The purpose of the authors is to provide a general view of the available solutions, and any researcher can obtain suitable circuit designs that can be selected for their problem by reading this survey.
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Affiliation(s)
- Lida Kouhalvandi
- Department of Electrical and Electronics Engineering, Dogus University, Istanbul 34775, Turkey
| | - Ladislau Matekovits
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
- Department of Measurements and Optical Electronics, Politehnica University Timisoara, 300006 Timisoara, Romania
- Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, National Research Council, 10129 Turin, Italy
| | - Ildiko Peter
- Department of Industrial Engineering and Management, University of Medicine, Pharmacy, Science and Technology “George Emil Palade”, 540139 Targu Mures, Romania
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Erofeev A, Antifeev I, Bolshakova A, Bezprozvanny I, Vlasova O. In Vivo Penetrating Microelectrodes for Brain Electrophysiology. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22239085. [PMID: 36501805 PMCID: PMC9735502 DOI: 10.3390/s22239085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 05/13/2023]
Abstract
In recent decades, microelectrodes have been widely used in neuroscience to understand the mechanisms behind brain functions, as well as the relationship between neural activity and behavior, perception and cognition. However, the recording of neuronal activity over a long period of time is limited for various reasons. In this review, we briefly consider the types of penetrating chronic microelectrodes, as well as the conductive and insulating materials for microelectrode manufacturing. Additionally, we consider the effects of penetrating microelectrode implantation on brain tissue. In conclusion, we review recent advances in the field of in vivo microelectrodes.
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Affiliation(s)
- Alexander Erofeev
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
| | - Ivan Antifeev
- Laboratory of Methods and Instruments for Genetic and Immunoassay Analysis, Institute for Analytical Instrumentation of the Russian Academy of Sciences, 198095 Saint Petersburg, Russia
| | - Anastasia Bolshakova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
| | - Ilya Bezprozvanny
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Department of Physiology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390, USA
| | - Olga Vlasova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
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8
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Lee HS, Eom K, Park M, Ku SB, Lee K, Lee HM. High-density neural recording system design. Biomed Eng Lett 2022; 12:251-261. [DOI: 10.1007/s13534-022-00233-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/10/2022] [Accepted: 05/20/2022] [Indexed: 10/18/2022] Open
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9
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Wang L, Ge C, Wang F, Guo Z, Hong W, Jiang C, Ji B, Wang M, Li C, Sun B, Liu J. Dense Packed Drivable Optrode Array for Precise Optical Stimulation and Neural Recording in Multiple-Brain Regions. ACS Sens 2021; 6:4126-4135. [PMID: 34779610 DOI: 10.1021/acssensors.1c01650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The input-output function of neural networks is complicated due to the huge number of neurons and synapses, and some high-density implantable electrophysiology recording tools with a plane structure have been developed for neural circuit studies in recent years. However, traditional plane probes are limited by the record-only function and inability to monitor multiple-brain regions simultaneously, and the complete cognition of neural networks still has a long way away. Herein, we develop a three-dimensional (3D) high-density drivable optrode array for multiple-brain recording and precise optical stimulation simultaneously. The optrode array contains four-layer probes with 1024 microelectrodes and two thinned optical fibers assembled into a 3D-printed drivable module. The recording performance of microelectrodes is optimized by electrochemical modification, and precise implantation depth control of drivable optrodes is verified in agar. Moreover, in vivo experiments indicate neural activities from CA1 and dentate gyrus regions are monitored, and a tracking of the neuron firing for 2 weeks is achieved. The suppression of neuron firing by blue light has been realized through high-density optrodes during optogenetics experiments. With the feature of large-scale recording, optoelectronic integration, and 3D assembly, the high-density drivable optrode array possesses an important value in the research of brain diseases and neural networks.
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Affiliation(s)
- Longchun Wang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chaofan Ge
- Institute of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Fang Wang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200020, China
| | - Zhejun Guo
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Wen Hong
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chunpeng Jiang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bowen Ji
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an 710072, China
| | - Minghao Wang
- College of Electronics and Information Hangzhou Dianzi University, Hangzhou 310018, China
| | - Chengyu Li
- Institute of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200020, China
| | - Jingquan Liu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
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Cisneros-Fernandez J, Garcia-Cortadella R, Illa X, Martinez-Aguilar J, Paetzold J, Mohrlok R, Kurnoth M, Jeschke C, Teres L, Garrido JA, Guimera-Brunet A, Serra-Graells F. A 1024-Channel 10-Bit 36- μW/ch CMOS ROIC for Multiplexed GFET-Only Sensor Arrays in Brain Mapping. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2021; 15:860-876. [PMID: 34543202 DOI: 10.1109/tbcas.2021.3113556] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
This paper presents a 1024-channel neural read-out integrated circuit (ROIC) for solution-gated GFET sensing probes in massive μECoG brain mapping. The proposed time-domain multiplexing of GFET-only arrays enables low-cost and scalable hybrid headstages. Low-power CMOS circuits are presented for the GFET analog frontend, including a CDS mechanism to improve preamplifier noise figures and 10-bit 10-kS/s A/D conversion. The 1024-channel ROIC has been fabricated in a standard 1.8-V 0.18- μm CMOS technology with 0.012 mm 2 and 36 μ W per channel. An automated methodology for the in-situ calibration of each GFET sensor is also proposed. Experimental ROIC tests are reported using a custom FPGA-based μECoG headstage with 16×32 and 32×32 GFET probes in saline solution and agar substrate. Compared to state-of-art neural ROICs, this work achieves the largest scalability in hybrid platforms and it allows the recording of infra-slow neural signals.
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11
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Somappa L, Baghini MS. A 400 mV 160 nW/Ch Compact Energy Efficient ∆Σ Modulator for Multichannel Biopotential Signal Acquisition System. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2021; 15:765-776. [PMID: 34310319 DOI: 10.1109/tbcas.2021.3098722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Analog to digitalconverter circuit design for biomedical systems with multiple recording channels presents challenges in high density and very low power consumption. Passive integrator and loop-filter based delta-sigma modulators (DSMs) have been recently reported for ultra-low-power and highly energy-efficient data converters for multi-channel biopotential acquisition. However, these modulators rely on a very high oversampling ratio (OSR) to achieve the target resolution. Higher OSR leads to higher power consumption in the modulator and the digital low-pass and decimation filter succeeding the DSM. We present a low OSR passive integrator-based DSM in this work by relying on a duty-cycled resistor (DCR). DCR enables the realization of large time constants in the already passive loop-filter, with minimal area and overhead power consumption. This leads to design of DSMs that are highly area, power and energy-efficient, suitable for multi-channel biopotential recording systems. We demonstrate a second order, duty-cycled passive integrator based CTDSM in a 65 nm CMOS technology for a 10 kHz biopotential bandwidth. Measurement results show that the fabricated design achieves an SNDR/DR of 56.36/63.1 dB while consuming only 160 nW power with an OSR of 32 and occupies an area of 0.035 mm 2 with a state-of-the-art energy efficiency of 14.9 fJ/conv. In-vitro and in-vivo measurements are provided to further demonstrate the operation of the proposed DSM.
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12
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Samiei A, Hashemi H. A Bidirectional Neural Interface SoC With Adaptive IIR Stimulation Artifact Cancelers. IEEE JOURNAL OF SOLID-STATE CIRCUITS 2021; 56:2142-2157. [PMID: 34483356 PMCID: PMC8409175 DOI: 10.1109/jssc.2021.3056040] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We present a 180-nm CMOS bidirectional neural interface system-on-chip that enables simultaneous recording and stimulation with on-chip stimulus artifact cancelers. The front-end cancellation scheme incorporates a least-mean-square engine that adapts the coefficients of a 2-tap infinite-impulse-response filter to replicate the stimulation artifact waveform and subtract it at the front-end. Measurements demonstrate the efficacy of the canceler in mitigating artifacts up to 700 mVpp and reducing the front-end amplifier saturation recovery time in response to a 2.5 Vpp artifact. Each recording channel houses a pair of adaptive infinite-impulse-response filters, which enable cancellation of the artifacts generated by the simultaneous operation of the 2 on-chip stimulators. The analog front-end consumes 2.5 μW of power per channel, has a maximum gain of 50 dB and a bandwidth of 9.0 kHz with 6.2 μVrms integrated input-referred noise.
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Affiliation(s)
- Aria Samiei
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Hossein Hashemi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089 USA
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13
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Park SY, Na K, Voroslakos M, Song H, Slager N, Oh S, Seymour J, Buzsaki G, Yoon E. A Miniaturized 256-Channel Neural Recording Interface with Area-Efficient Hybrid Integration of Flexible Probes and CMOS Integrated Circuits. IEEE Trans Biomed Eng 2021; 69:334-346. [PMID: 34191721 DOI: 10.1109/tbme.2021.3093542] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We report a miniaturized, minimally invasive high-density neural recording interface that occupies only a 1.53 mm2 footprint for hybrid integration of a flexible probe and a 256-channel integrated circuit chip. To achieve such a compact form factor, we developed a custom flip-chip bonding technique using anisotropic conductive film and analog circuit-under-pad in a tiny pitch of 75 m. To enhance signal-to-noise ratios, we applied a reference-replica topology that can provide the matched input impedance for signal and reference paths in low-noise aimpliers (LNAs). The analog front-end (AFE) consists of LNAs, buffers, programmable gain amplifiers, 10b ADCs, a reference generator, a digital controller, and serial-peripheral interfaces (SPIs). The AFE consumes 51.92 W from 1.2 V and 1.8 V supplies in an area of 0.0161 mm2 per channel, implemented in a 180 nm CMOS process. The AFE shows > 60 dB mid-band CMRR, 6.32 Vrms input-referred noise from 0.5 Hz to 10 kHz, and 48 M input impedance at 1 kHz. The fabricated AFE chip was directly flip-chip bonded with a 256-channel flexible polyimide neural probe and assembled in a tiny head-stage PCB. Full functionalities of the fabricated 256-channel interface were validated in both in vitro and in vivo experiments, demonstrating the presented hybrid neural recording interface is suitable for various neuroscience studies in the quest of large scale, miniaturized recording systems.
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Sharifshazileh M, Burelo K, Sarnthein J, Indiveri G. An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG. Nat Commun 2021; 12:3095. [PMID: 34035249 PMCID: PMC8149394 DOI: 10.1038/s41467-021-23342-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 04/20/2021] [Indexed: 02/04/2023] Open
Abstract
The analysis of biomedical signals for clinical studies and therapeutic applications can benefit from embedded devices that can process these signals locally and in real-time. An example is the analysis of intracranial EEG (iEEG) from epilepsy patients for the detection of High Frequency Oscillations (HFO), which are a biomarker for epileptogenic brain tissue. Mixed-signal neuromorphic circuits offer the possibility of building compact and low-power neural network processing systems that can analyze data on-line in real-time. Here we present a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing iEEG, and show how it can reliably detect HFO, thereby achieving state-of-the-art accuracy, sensitivity, and specificity. This is a first feasibility study towards identifying relevant features in iEEG in real-time using mixed-signal neuromorphic computing technologies.
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Affiliation(s)
- Mohammadali Sharifshazileh
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Karla Burelo
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Johannes Sarnthein
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Giacomo Indiveri
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
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Kim J, Fengel CV, Yu S, Minot ED, Johnston ML. Frequency-Division Multiplexing with Graphene Active Electrodes for Neurosensor Applications. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS. II, EXPRESS BRIEFS : A PUBLICATION OF THE IEEE CIRCUITS AND SYSTEMS SOCIETY 2021; 68:1735-1739. [PMID: 34017221 PMCID: PMC8130868 DOI: 10.1109/tcsii.2021.3066556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Multielectrode arrays are used broadly for neural recording, both in vivo and for ex vivo cultured neurons. In most cases, recording sites are passive electrodes wired to external read-out circuitry, and the number of wires is at least equal to the number of recording sites. We present an approach to break the conventional N-wire, N-electrode array architecture using graphene active electrodes, which allow signal upconversion at the recording site and sharing of each interface wire among multiple active electrodes using frequency-division multiplexing (FDM). The presented work includes the design and implementation of a frequency modulation and readout architecture using graphene FET electrodes, a custom integrated circuit (IC) analog front-end (AFE), and digital demodulation. The AFE was fabricated in 0.18 μm CMOS; electrical characterization and multi-channel FDM results are provided, including GFET-based signal modulation and IC/DSP demodulation. Long-term, this approach can simultaneously enable high signal count, high spatial resolution, and high temporal precision to infer functional interactions between neurons while markedly decreasing access wires.
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Affiliation(s)
- Jinyong Kim
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331 USA
| | - Carly V Fengel
- Department of Physics, Oregon State University, Corvallis, OR 97331 USA
| | - Siyuan Yu
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331 USA
| | - Ethan D Minot
- Department of Physics, Oregon State University, Corvallis, OR 97331 USA
| | - Matthew L Johnston
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331 USA
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16
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Steinmetz NA, Aydin C, Lebedeva A, Okun M, Pachitariu M, Bauza M, Beau M, Bhagat J, Böhm C, Broux M, Chen S, Colonell J, Gardner RJ, Karsh B, Kloosterman F, Kostadinov D, Mora-Lopez C, O'Callaghan J, Park J, Putzeys J, Sauerbrei B, van Daal RJJ, Vollan AZ, Wang S, Welkenhuysen M, Ye Z, Dudman JT, Dutta B, Hantman AW, Harris KD, Lee AK, Moser EI, O'Keefe J, Renart A, Svoboda K, Häusser M, Haesler S, Carandini M, Harris TD. Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings. Science 2021. [PMID: 33859006 DOI: 10.1101/2020.10.27.358291] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.
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Affiliation(s)
- Nicholas A Steinmetz
- UCL Institute of Ophthalmology, University College London, London, UK.
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | | | - Anna Lebedeva
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marius Pachitariu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Marius Bauza
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Maxime Beau
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Jai Bhagat
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia Böhm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Richard J Gardner
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bill Karsh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Fabian Kloosterman
- Neuroelectronics Research Flanders, Leuven, Belgium
- IMEC, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
- Brain and Cognition, KU Leuven, Leuven, Belgium
| | - Dimitar Kostadinov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Junchol Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Britton Sauerbrei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Rik J J van Daal
- ATLAS Neuroengineering, Leuven, Belgium
- Neuroelectronics Research Flanders, Leuven, Belgium
- Micro- and Nanosystems, KU Leuven, Leuven, Belgium
| | - Abraham Z Vollan
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Zhiwen Ye
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Joshua T Dudman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Adam W Hantman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Albert K Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - John O'Keefe
- Sainsbury Wellcome Centre, University College London, London, UK
| | | | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Sebastian Haesler
- Neuroelectronics Research Flanders, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, UK.
| | - Timothy D Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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17
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Steinmetz NA, Aydin C, Lebedeva A, Okun M, Pachitariu M, Bauza M, Beau M, Bhagat J, Böhm C, Broux M, Chen S, Colonell J, Gardner RJ, Karsh B, Kloosterman F, Kostadinov D, Mora-Lopez C, O'Callaghan J, Park J, Putzeys J, Sauerbrei B, van Daal RJJ, Vollan AZ, Wang S, Welkenhuysen M, Ye Z, Dudman JT, Dutta B, Hantman AW, Harris KD, Lee AK, Moser EI, O'Keefe J, Renart A, Svoboda K, Häusser M, Haesler S, Carandini M, Harris TD. Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings. Science 2021; 372:eabf4588. [PMID: 33859006 PMCID: PMC8244810 DOI: 10.1126/science.abf4588] [Citation(s) in RCA: 382] [Impact Index Per Article: 127.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/01/2021] [Indexed: 12/22/2022]
Abstract
Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.
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Affiliation(s)
- Nicholas A Steinmetz
- UCL Institute of Ophthalmology, University College London, London, UK.
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | | | - Anna Lebedeva
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marius Pachitariu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Marius Bauza
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Maxime Beau
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Jai Bhagat
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia Böhm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Richard J Gardner
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bill Karsh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Fabian Kloosterman
- Neuroelectronics Research Flanders, Leuven, Belgium
- IMEC, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
- Brain and Cognition, KU Leuven, Leuven, Belgium
| | - Dimitar Kostadinov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Junchol Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Britton Sauerbrei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Rik J J van Daal
- ATLAS Neuroengineering, Leuven, Belgium
- Neuroelectronics Research Flanders, Leuven, Belgium
- Micro- and Nanosystems, KU Leuven, Leuven, Belgium
| | - Abraham Z Vollan
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Zhiwen Ye
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Joshua T Dudman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Adam W Hantman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Albert K Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - John O'Keefe
- Sainsbury Wellcome Centre, University College London, London, UK
| | | | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Sebastian Haesler
- Neuroelectronics Research Flanders, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, UK.
| | - Timothy D Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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18
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Fiáth R, Meszéna D, Somogyvári Z, Boda M, Barthó P, Ruther P, Ulbert I. Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings. Sci Rep 2021; 11:2028. [PMID: 33479289 PMCID: PMC7819990 DOI: 10.1038/s41598-021-81127-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 12/28/2020] [Indexed: 12/17/2022] Open
Abstract
Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.
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Affiliation(s)
- Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary. .,Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
| | - Domokos Meszéna
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.,Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Zoltán Somogyvári
- Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
| | - Mihály Boda
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Péter Barthó
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Patrick Ruther
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany.,Cluster of Excellence, BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.,Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
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19
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Fiáth R, Meszéna D, Somogyvári Z, Boda M, Barthó P, Ruther P, Ulbert I. Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings. Sci Rep 2021; 11:2028. [PMID: 33479289 DOI: 10.1101/2020.06.01.127308] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 12/28/2020] [Indexed: 05/27/2023] Open
Abstract
Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.
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Affiliation(s)
- Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
| | - Domokos Meszéna
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Zoltán Somogyvári
- Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
| | - Mihály Boda
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Péter Barthó
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Patrick Ruther
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany
- Cluster of Excellence, BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
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20
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Egert D, Pettibone JR, Lemke S, Patel PR, Caldwell CM, Cai D, Ganguly K, Chestek CA, Berke JD. Cellular-scale silicon probes for high-density, precisely localized neurophysiology. J Neurophysiol 2020; 124:1578-1587. [PMID: 32965150 DOI: 10.1152/jn.00352.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared with the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at a cellular scale (5 × 10 µm cross section), with ultra-high-density packing (as little as 66 µm between shanks) and 64 or 256 closely spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and record large spikes in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal µ-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits and potentially for human brain-machine interfaces.NEW & NOTEWORTHY Devices with many electrodes penetrating into the brain are an important tool for investigating neural information processing, but they are typically large compared with neurons. This results in substantial damage and makes it harder to reconstruct recording locations within brain circuits. This paper presents high-channel-count silicon probes with much smaller features and a method for slicing through probe, brain, and skull all together. This allows probe tips to be directly observed relative to immunohistochemical markers.
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Affiliation(s)
- Daniel Egert
- Department of Neurology, University of California, San Francisco, California
| | - Jeffrey R Pettibone
- Department of Neurology, University of California, San Francisco, California
| | - Stefan Lemke
- Neuroscience Graduate Program, University of California, San Francisco, California
| | - Paras R Patel
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Ciara M Caldwell
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Dawen Cai
- Department of Molecular and Cell Biology, University of Michigan, Ann Arbor, Michigan
| | - Karunesh Ganguly
- Department of Neurology, University of California, San Francisco, California.,Veterans Affairs Medical Center, San Francisco, California.,Weill Institute for Neurosciences and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, California
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan.,Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan.,Neurosciences Program, University of Michigan, Ann Arbor, Michigan.,Robotics Program, University of Michigan, Ann Arbor, Michigan
| | - Joshua D Berke
- Department of Neurology, University of California, San Francisco, California.,Weill Institute for Neurosciences and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, California
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21
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De Marcellis A, Stanchieri GDP, Faccio M, Palange E, Constandinou TG. A 300 Mbps 37 pJ/bit Pulsed Optical Biotelemetry. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; 14:441-451. [PMID: 32054584 DOI: 10.1109/tbcas.2020.2972733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
This article reports an implantable transcutaneous telemetry for a brain machine interface that uses a novel optical communication system to achieve a highly energy-efficient link. Based on an pulse-based coding scheme, the system uses sub-nanosecond laser pulses to achieve data rates up to 300 Mbps with relatively low power levels when compared to other methods of wireless communication. This has been implemented using a combination of discrete components (semiconductor laser and driver, fast-response Si photodiode and interface) integrated at board level together with reconfigurable logic (encoder, decoder and processing circuits implemented using Xilinx KCU105 board with Kintex UltraScale FPGA). Experimental validation has been performed using a tissue sample that achieves representative level of attenuation/scattering (porcine skin) in the optical path. Results reveal that the system can operate at data rates up to 300 Mbps with a bit error rate (BER) of less than 10 -10, and an energy efficiency of 37 pJ/bit. This can communicate, for example, 1,024 channels of broadband neural data sampled at 18 kHz, 16-bit with only 11 mW power consumption.
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22
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Liu Y, Urso A, Martins da Ponte R, Costa T, Valente V, Giagka V, Serdijn WA, Constandinou TG, Denison T. Bidirectional Bioelectronic Interfaces: System Design and Circuit Implications. ACTA ACUST UNITED AC 2020. [DOI: 10.1109/mssc.2020.2987506] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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