Literature DB >> 33946209

Analysis and Reduction of Nonlinear Distortion in AC-Coupled CMOS Neural Amplifiers with Tunable Cutoff Frequencies.

Beata Trzpil-Jurgielewicz1, Władysław Dąbrowski1, Paweł Hottowy1.   

Abstract

Integrated CMOS neural amplifiers are key elements of modern large-scale neuroelectronic interfaces. The neural amplifiers are routinely AC-coupled to electrodes to remove the DC voltage. The large resistances required for the AC coupling circuit are usually realized using MOSFETs that are nonlinear. Specifically, designs with tunable cutoff frequency of the input high‑pass filter may suffer from excessive nonlinearity, since the gate-source voltages of the transistors forming the pseudoresistors vary following the signal being amplified. Consequently, the nonlinear distortion in such circuits may be high for signal frequencies close to the cutoff frequency of the input filter. Here we propose a simple modification of the architecture of a tunable AC-coupled amplifier, in which the bias voltages Vgs of the transistors forming the pseudoresistor are kept constant independently of the signal levels, what results in significantly improved linearity. Based on numerical simulations of the proposed circuit designed in 180 nm technology we analyze the Total Harmonic Distortion levels as a function of signal frequency and amplitude. We also investigate the impact of basic amplifier parameters-gain, cutoff frequency of the AC coupling circuit, and silicon area-on the distortion and noise performance. The post-layout simulations of the complete test ASIC show that the distortion is very significantly reduced at frequencies near the cutoff frequency, when compared to the commonly used circuits. The THD values are below 1.17% for signal frequencies 1 Hz-10 kHz and signal amplitudes up to 10 mV peak-to-peak. The preamplifier area is only 0.0046 mm2 and the noise is 8.3 µVrms in the 1 Hz-10 kHz range. To our knowledge this is the first report on a CMOS neural amplifier with systematic characterization of THD across complete range of frequencies and amplitudes of neuronal signals recorded by extracellular electrodes.

Entities:  

Keywords:  AC coupling; CMOS neural amplifier; area-efficient design; nonlinear distortion; pseudoresistor

Year:  2021        PMID: 33946209     DOI: 10.3390/s21093116

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  21 in total

1.  The 128-channel fully differential digital integrated neural recording and stimulation interface.

Authors:  Farzaneh Shahrokhi; Karim Abdelhalim; Demitre Serletis; Peter L Carlen; Roman Genov
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2010-06       Impact factor: 3.833

2.  A Neural Probe With Up to 966 Electrodes and Up to 384 Configurable Channels in 0.13 $\mu$m SOI CMOS.

Authors:  Carolina Mora Lopez; Jan Putzeys; Bogdan Cristian Raducanu; Marco Ballini; Shiwei Wang; Alexandru Andrei; Veronique Rochus; Roeland Vandebriel; Simone Severi; Chris Van Hoof; Silke Musa; Nick Van Helleputte; Refet Firat Yazicioglu; Srinjoy Mitra
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2017-05-19       Impact factor: 3.833

3.  A 0.45 V 100-channel neural-recording IC with sub- μW/channel consumption in 0.18 μm CMOS.

Authors:  Dong Han; Yuanjin Zheng; Ramamoorthy Rajkumar; Gavin Stewart Dawe; Minkyu Je
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2013-12       Impact factor: 3.833

Review 4.  Low-Frequency Noise and Offset Rejection in DC-Coupled Neural Amplifiers: A Review and Digitally-Assisted Design Tutorial.

Authors:  Arezu Bagheri; Muhammad Tariqus Salam; Jose Luis Perez Velazquez; Roman Genov
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2016-06-10       Impact factor: 3.833

5.  Fully integrated silicon probes for high-density recording of neural activity.

Authors:  James J Jun; Nicholas A Steinmetz; Joshua H Siegle; Daniel J Denman; Marius Bauza; Brian Barbarits; Albert K Lee; Costas A Anastassiou; Alexandru Andrei; Çağatay Aydın; Mladen Barbic; Timothy J Blanche; Vincent Bonin; João Couto; Barundeb Dutta; Sergey L Gratiy; Diego A Gutnisky; Michael Häusser; Bill Karsh; Peter Ledochowitsch; Carolina Mora Lopez; Catalin Mitelut; Silke Musa; Michael Okun; Marius Pachitariu; Jan Putzeys; P Dylan Rich; Cyrille Rossant; Wei-Lung Sun; Karel Svoboda; Matteo Carandini; Kenneth D Harris; Christof Koch; John O'Keefe; Timothy D Harris
Journal:  Nature       Date:  2017-11-08       Impact factor: 49.962

6.  Spatio-temporal correlations and visual signalling in a complete neuronal population.

Authors:  Jonathan W Pillow; Jonathon Shlens; Liam Paninski; Alexander Sher; Alan M Litke; E J Chichilnisky; Eero P Simoncelli
Journal:  Nature       Date:  2008-07-23       Impact factor: 49.962

7.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

Authors:  Leigh R Hochberg; Daniel Bacher; Beata Jarosiewicz; Nicolas Y Masse; John D Simeral; Joern Vogel; Sami Haddadin; Jie Liu; Sydney S Cash; Patrick van der Smagt; John P Donoghue
Journal:  Nature       Date:  2012-05-16       Impact factor: 49.962

8.  A high-performance neural prosthesis enabled by control algorithm design.

Authors:  Vikash Gilja; Paul Nuyujukian; Cindy A Chestek; John P Cunningham; Byron M Yu; Joline M Fan; Mark M Churchland; Matthew T Kaufman; Jonathan C Kao; Stephen I Ryu; Krishna V Shenoy
Journal:  Nat Neurosci       Date:  2012-11-18       Impact factor: 24.884

Review 9.  Tools for probing local circuits: high-density silicon probes combined with optogenetics.

Authors:  György Buzsáki; Eran Stark; Antal Berényi; Dion Khodagholy; Daryl R Kipke; Euisik Yoon; Kensall D Wise
Journal:  Neuron       Date:  2015-04-08       Impact factor: 17.173

Review 10.  Revealing neuronal function through microelectrode array recordings.

Authors:  Marie Engelene J Obien; Kosmas Deligkaris; Torsten Bullmann; Douglas J Bakkum; Urs Frey
Journal:  Front Neurosci       Date:  2015-01-06       Impact factor: 4.677

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