This title appears in the Scientific Report :
2008
Please use the identifier:
http://dx.doi.org/10.1016/j.jneumeth.2007.10.025 in citations.
An automatic procedure for the analysis of electric and magnetic mismatch negativity based on anatomical brain mapping
An automatic procedure for the analysis of electric and magnetic mismatch negativity based on anatomical brain mapping
Data processing techniques in electroencephalography (EEG) and magnetoencephalography (MEG) need user interactions. However, particularly in clinical applications, fast and objective data processing is important. Here we present an observer-independent method for EEG and MEG analysis of mismatch neg...
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Personal Name(s): | Zvyagintsev, M. |
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Thönnessen, H. / Dammers, J. / Boers, F. / Mathiak, K. | |
Contributing Institute: |
Institut für Neurowissenschaften und Biophysik - Medizin; INB-3 JARA-BRAIN; JARA-BRAIN |
Published in: | Journal of neuroscience methods, 168 (2008) S. 325 - 333 |
Imprint: |
Amsterdam [u.a.]
Elsevier Science
2008
|
Physical Description: |
325 - 333 |
DOI: |
10.1016/j.jneumeth.2007.10.025 |
PubMed ID: |
18093661 |
Document Type: |
Journal Article |
Research Program: |
Funktion und Dysfunktion des Nervensystems |
Series Title: |
Journal of Neuroscience Methods
168 |
Subject (ZB): | |
Publikationsportal JuSER |
Data processing techniques in electroencephalography (EEG) and magnetoencephalography (MEG) need user interactions. However, particularly in clinical applications, fast and objective data processing is important. Here we present an observer-independent method for EEG and MEG analysis of mismatch negativity (MMN) that allows reliable estimation of source activity based on objective anatomical references. The procedure integrates several steps including artifact rejection, source estimation and statistical analysis. It enables the evaluation of source activity in a fully automatic and unsupervised manner. To test its feasibility we obtained EEG and MEG responses in an auditory oddball paradigm in 12 healthy volunteers. The automatized method of EEG and MEG data analysis estimated source activity. The automatically detected MMN was closely comparable with the results obtained by a user-controlled method based on the dipole fitting. The presented workflow can be performed easily, rapidly, and reliably. This development may open new fields in research and clinical applications of source-based EEG and MEG. |