Literature DB >> 15848245

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

Erwin B Montgomery1, John T Gale, He Huang.   

Abstract

Recent successes in treating neurological disorders with electrical stimulation of the brain have spurred interest in studying the neuronal mechanisms by which such therapies work. However, microelectrode recordings can be confounded by stimulation artifact. Also, large microelectrode arrays now allow recording amounts of data that would otherwise overwhelm current analytic methods that depend heavily on human intervention and interpretation. A set of algorithms is described for automatically removing stimulus artifacts that minimize signal loss with minimum human involvement. Other algorithms automatically differentiate between the extracellular action potentials of individual neurons.

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Year:  2004        PMID: 15848245     DOI: 10.1016/j.jneumeth.2004.10.017

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


  17 in total

1.  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

2.  Deep brain stimulation of the globus pallidus internus in the parkinsonian primate: local entrainment and suppression of low-frequency oscillations.

Authors:  Kevin W McCairn; Robert S Turner
Journal:  J Neurophysiol       Date:  2009-01-21       Impact factor: 2.714

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

Authors:  Thomas Wichmann; Annaelle Devergnas
Journal:  J Neurosci Methods       Date:  2011-07-01       Impact factor: 2.390

4.  Memory-enhancing amygdala stimulation elicits gamma synchrony in the hippocampus.

Authors:  David I Bass; Joseph R Manns
Journal:  Behav Neurosci       Date:  2015-06       Impact factor: 1.912

5.  A Point Process Model-based Framework Reveals Reinforcement Mechanisms in Striatum during High Frequency STN DBS.

Authors:  Sabato Santaniello; John T Gale; Erwin B Montgomery; Sridevi V Sarma
Journal:  Proc IEEE Conf Decis Control       Date:  2013-02-04

6.  Activation of subthalamic neurons by contralateral subthalamic deep brain stimulation in Parkinson disease.

Authors:  Harrison C Walker; Ray L Watts; Christian J Schrandt; He Huang; Stephanie L Guthrie; Barton L Guthrie; Erwin B Montgomery
Journal:  J Neurophysiol       Date:  2010-12-22       Impact factor: 2.714

7.  Deep brain stimulation does not silence neurons in subthalamic nucleus in Parkinson's patients.

Authors:  Jonathan D Carlson; Daniel R Cleary; Justin S Cetas; Mary M Heinricher; Kim J Burchiel
Journal:  J Neurophysiol       Date:  2009-12-02       Impact factor: 2.714

8.  A retrofitted neural recording system with a novel stimulation IC to monitor early neural responses from a stimulating electrode.

Authors:  Yoonkey Nam; Edgar A Brown; James D Ross; Richard A Blum; Bruce C Wheeler; Stephen P DeWeerth
Journal:  J Neurosci Methods       Date:  2008-11-30       Impact factor: 2.390

9.  Reinforcement mechanisms in putamen during high frequency STN DBS: A point process study.

Authors:  Sabato Santaniello; John T Gale; Erwin B Montgomery; Sridevi V Sarma
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2012

10.  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

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