Literature DB >> 21745499

A novel device to suppress electrical stimulus artifacts in electrophysiological experiments.

Thomas Wichmann1, Annaelle Devergnas.   

Abstract

Electrophysiological studies of the effects of electrical brain stimulation have to contend with stimulus artifacts, which complicate both the maintenance of recorded neuron waveforms at recording time, and the post-hoc analysis of the data. The artifacts can be removed by digitally averaging some or all of the (stereotypic) artifact waveforms across artifacts, and then subtracting the resulting template from the recorded waveform at the time of artifact production. Available software-based approaches to this problem are effective but time consuming, and do not help with the problem of maintaining the recording quality at recording time. Alternative hardware-based methods are effective as well, but relatively inflexible and very expensive. We here provide a detailed description of a simple high-performance artifact removal device based on a multi-processor microcontroller as well as analog-to-digital and digital-to-analog converters. This device provides the benefits of self-adapting online-removal of stimulus artifacts for a fraction of the price of the commercially available devices. The device is fully customizable, and can be easily adjusted to various stimulation conditions, as well as AC line noise removal.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21745499      PMCID: PMC3167981          DOI: 10.1016/j.jneumeth.2011.06.026

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  14 in total

1.  A digital averaging method for removal of stimulus artifacts in neurophysiologic experiments.

Authors:  T Wichmann
Journal:  J Neurosci Methods       Date:  2000-05-15       Impact factor: 2.390

2.  A template subtraction method for stimulus artifact removal in high-frequency deep brain stimulation.

Authors:  Takao Hashimoto; Christopher M Elder; Jerrold L Vitek
Journal:  J Neurosci Methods       Date:  2002-01-30       Impact factor: 2.390

3.  Stimulus artifact removal using a software-based two-stage peak detection algorithm.

Authors:  D T O'Keeffe; G M Lyons; A E Donnelly; C A Byrne
Journal:  J Neurosci Methods       Date:  2001-08-30       Impact factor: 2.390

4.  Digital subtraction method for transient evoked otoacoustic emission recording with ipsilateral noise suppression: an application to stimulus artifact reduction.

Authors:  R B Arslan; O Ozdamar; Y Ulgen
Journal:  Audiology       Date:  2001 Mar-Apr

5.  Stimulation of the subthalamic nucleus changes the firing pattern of pallidal neurons.

Authors:  Takao Hashimoto; Christopher M Elder; Michael S Okun; Susan K Patrick; Jerrold L Vitek
Journal:  J Neurosci       Date:  2003-03-01       Impact factor: 6.167

6.  Generalized framework for stimulus artifact removal.

Authors:  Yaara Erez; Hadass Tischler; Anan Moran; Izhar Bar-Gad
Journal:  J Neurosci Methods       Date:  2010-06-11       Impact factor: 2.390

7.  Methods for isolating extracellular action potentials and removing stimulus artifacts from microelectrode recordings of neurons requiring minimal operator intervention.

Authors:  Erwin B Montgomery; John T Gale; He Huang
Journal:  J Neurosci Methods       Date:  2004-12-13       Impact factor: 2.390

8.  A digital technique for stimulus artifact reduction.

Authors:  T Blogg; W D Reid
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1990-12

9.  A novel stimulus artifact removal technique for high-rate electrical stimulation.

Authors:  Leon F Heffer; James B Fallon
Journal:  J Neurosci Methods       Date:  2008-02-03       Impact factor: 2.390

10.  Stimulus artifact removal in EMG from muscles adjacent to stimulated muscles.

Authors:  A E Hines; P E Crago; G J Chapman; C Billian
Journal:  J Neurosci Methods       Date:  1996-01       Impact factor: 2.390

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  6 in total

1.  VLSI implementation of a template subtraction algorithm for real-time stimulus artifact rejection.

Authors:  Kanokwan Limnuson; Hui Lu; Hillel J Chiel; Pedram Mohseni
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

2.  Suppression of stimulus artifact contaminating electrically evoked electromyography.

Authors:  Jie Liu; Sheng Li; Xiaoyan Li; Cliff Klein; William Z Rymer; Ping Zhou
Journal:  NeuroRehabilitation       Date:  2014       Impact factor: 2.138

3.  Online Artifact Cancelation in Same-Electrode Neural Stimulation and Recording Using a Combined Hardware and Software Architecture.

Authors:  Stanislav Culaclii; Brian Kim; Yi-Kai Lo; Lin Li; Wentai Liu
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2018-06       Impact factor: 3.833

4.  ERAASR: an algorithm for removing electrical stimulation artifacts from multielectrode array recordings.

Authors:  Daniel J O'Shea; Krishna V Shenoy
Journal:  J Neural Eng       Date:  2018-04       Impact factor: 5.379

5.  Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays.

Authors:  Gonzalo E Mena; Lauren E Grosberg; Sasidhar Madugula; Paweł Hottowy; Alan Litke; John Cunningham; E J Chichilnisky; Liam Paninski
Journal:  PLoS Comput Biol       Date:  2017-11-13       Impact factor: 4.475

6.  A Novel Technique to Reject Artifact Components for Surface EMG Signals Recorded During Walking With Transcutaneous Spinal Cord Stimulation: A Pilot Study.

Authors:  Minjae Kim; Yaejin Moon; Jasmine Hunt; Kelly A McKenzie; Adam Horin; Matt McGuire; Keehoon Kim; Levi J Hargrove; Arun Jayaraman
Journal:  Front Hum Neurosci       Date:  2021-06-03       Impact factor: 3.169

  6 in total

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