Literature DB >> 15376503

Effect of electrode density and measurement noise on the spatial resolution of cortical potential distribution.

Outi R M Ryynänen1, Jari A K Hyttinen, Päivi H Laarne, Jaakko A Malmivuo.   

Abstract

The purpose of the present study was to examine the spatial resolution of electroencephalography (EEG) by means of inverse cortical EEG solution. The main interest was to study how the number of measurement electrodes and the amount of measurement noise affects the spatial resolution. A three-layer spherical head model was used to obtain the source-field relationship of cortical potentials and scalp EEG field. Singular value decomposition was used to evaluate the spatial resolution with various measurement noise estimates. The results suggest that as the measurement noise increases the advantage of dense electrode systems is decreased. With low realistic measurement noise, a more accurate inverse cortical potential distribution can be obtained with an electrode system where the distance between two electrodes is as small as 16 mm, corresponding to as many as 256 measurement electrodes. In clinical measurement environments, it is always beneficial to have at least 64 measurement electrodes.

Mesh:

Year:  2004        PMID: 15376503     DOI: 10.1109/TBME.2004.828036

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  10 in total

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2.  Electroencephalographic connectivity measures predict learning of a motor sequencing task.

Authors:  Jennifer Wu; Franziska Knapp; Steven C Cramer; Ramesh Srinivasan
Journal:  J Neurophysiol       Date:  2017-11-01       Impact factor: 2.714

3.  NoLiTiA: An Open-Source Toolbox for Non-linear Time Series Analysis.

Authors:  Immo Weber; Carina R Oehrn
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4.  Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

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Journal:  Brain Comput Interfaces (Abingdon)       Date:  2014-01

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Authors:  Phan Luu; Matthew Shane; Nikki L Pratt; Don M Tucker
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Authors:  Jennifer Wu; Ramesh Srinivasan; Arshdeep Kaur; Steven C Cramer
Journal:  Neuroimage       Date:  2014-01-25       Impact factor: 6.556

7.  Reconstruction of normal and abnormal gastric electrical sources using a potential based inverse method.

Authors:  J H K Kim; P Du; L K Cheng
Journal:  Physiol Meas       Date:  2013-09       Impact factor: 2.833

8.  Combined EMD-sLORETA Analysis of EEG Data Collected during a Contour Integration Task.

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Journal:  PLoS One       Date:  2016-12-09       Impact factor: 3.240

9.  Evaluating interhemispheric connectivity during midline object recognition using EEG.

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Journal:  PLoS One       Date:  2022-08-26       Impact factor: 3.752

10.  A Waveform-Independent Measure of Recurrent Neural Activity.

Authors:  Immo Weber; Carina Renate Oehrn
Journal:  Front Neuroinform       Date:  2022-03-07       Impact factor: 4.081

  10 in total

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