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On utilizing uncertainty information in template-based EEG-fMRI ballistocardiogram artifact removal

Lookup NU author(s): Dr Andreas FinkelmeyerORCiD

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Abstract

The correction of ballistocardiogram artifacts in simultaneous EEG-fMRI often yields unsatisfactory results. To improve the signal-to-noise ratio (SNR) of results, we inferred EEG signal uncertainty from postcorrection artifact residuals and computed the uncertainty-weighted mean of ERPs. Using an uncertainty-weighted mean significantly and consistently reduced both inter- and intrasubject SEM in the analysis of auditory evoked responses (AER, indicated by the N1-P2 complex) and in the effects of an auditory oddball paradigm (N1-P3 complex, standard-deviant difference). SNR increased by 3% on average for the AER amplitude (intrasubject) and 17% on average for the auditory oddball ERP (intersubject). This demonstrates that weighting by uncertainty complements existing artifact correction algorithms to increase SNR in ERPs. More specifically, it is an efficient method to utilize seemingly corrupt (difficult-to-correct) EEG data that might otherwise be discarded.


Publication metadata

Author(s): Schulz MA, Regenbogen C, Moessnang C, Neuner I, Finkelmeyer A, Habel U, Kellermann T

Publication type: Article

Publication status: Published

Journal: Psychophysiology

Year: 2015

Volume: 52

Issue: 6

Pages: 857-863

Print publication date: 01/06/2015

Online publication date: 04/02/2014

Acceptance date: 07/11/2014

ISSN (print): 0048-5772

ISSN (electronic): 1469-8986

Publisher: Wiley-Blackwell Publishing, Inc.

URL: http://dx.doi.org/10.1111/psyp.12406

DOI: 10.1111/psyp.12406

PubMed id: 25649223


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Funding

Funder referenceFunder name
START 135/14START-Program of the Faculty of Medicine, RWTH Aachen
DAAD postdoctoral fellowship
Federal State of Nordrhein-Westfalen (NRW, Germany)
European Union through the NRW Ziel2 Program as a part of the European Fund for Regional Development
ICCR N4-4Interdisciplinary Center for Clinical Research of the Faculty of Medicine, RWTH Aachen
IRTG 1328Deutsche Forschungsgemeinschaft (DFG)

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