Literature DB >> 16466806

Recursive artifact windowed-single tone extraction method (RAW-STEM) as periodic noise filter for electrophysiological signals with interfering transients.

Tongsheng Zhang1, Yoshio Okada.   

Abstract

The single tone extraction method (STEM) is a well developed algorithm for estimating the frequency, amplitude, and phase of one periodic signal or a single tone in complex temporal signals. This method is useful in neuroscience research since it provides an efficient simple means to remove line frequency noise present in many types of signal measurements. However, the method encounters problems when the signal contains transients such as a stimulus artifact which distort the estimation of power line parameters. Here we report a modification of STEM that overcomes this limitation. In this new method we call recursive artifact windowed (RAW)-STEM, the line frequency noise is removed for each single epoch by estimating the three parameters (frequency, amplitude and phase) of each line frequency after windowing the time period containing an interfering transient and iteratively applying the STEM. In a simulation study we evaluated its performance for electrophysiological data with a stimulus artifact and demonstrated advantages of the RAW-STEM over the classic STEM. The RAW-STEM is able to efficiently extract the 60 Hz parameter, requiring less than five iterations, with a precision of 0.007-2% depending on the parameters. It does not suffer from the problem of ringing following the stimulus artifact or distortion of electrophysiological signals. It is fast enough to be used for single trial analyses in electrophysiological studies. The RAW-STEM may be widely useful for the removal of periodic noise since it can be applied even when there are multiple interfering transients in the recording.

Mesh:

Year:  2006        PMID: 16466806     DOI: 10.1016/j.jneumeth.2005.12.022

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


  4 in total

1.  Quantitative assessment of cerebral connectivity deficiency and cognitive impairment in children with prenatal alcohol exposure.

Authors:  Lin Gao; Celso Grebogi; Ying-Cheng Lai; Julia Stephen; Tongsheng Zhang; Yuanli Li; Haipeng Ren; Dichen Li; Jue Wang; Bjoern Schelter; Linda Sommerlade
Journal:  Chaos       Date:  2019-04       Impact factor: 3.642

2.  Facilitating neuronal connectivity analysis of evoked responses by exposing local activity with principal component analysis preprocessing: simulation of evoked MEG.

Authors:  Lin Gao; Tongsheng Zhang; Jue Wang; Julia Stephen
Journal:  Brain Topogr       Date:  2012-08-24       Impact factor: 3.020

3.  Granger causal time-dependent source connectivity in the somatosensory network.

Authors:  Lin Gao; Linda Sommerlade; Brian Coffman; Tongsheng Zhang; Julia M Stephen; Dichen Li; Jue Wang; Celso Grebogi; Bjoern Schelter
Journal:  Sci Rep       Date:  2015-05-21       Impact factor: 4.379

4.  Method for spike detection from microelectrode array recordings contaminated by artifacts of simultaneous two-photon imaging.

Authors:  Gábor Orbán; Domokos Meszéna; Kinga Réka Tasnády; Balázs Rózsa; István Ulbert; Gergely Márton
Journal:  PLoS One       Date:  2019-08-20       Impact factor: 3.240

  4 in total

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