Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 209, Issue 1, Pages 212-218Publisher
ELSEVIER
DOI: 10.1016/j.jneumeth.2012.06.011
Keywords
ERP; ERF; High-pass filtering; Data processing; C1
Categories
Funding
- Doctoral Training Centre in Neuroinformatics
- EPSRC
- MRC
- BBSRC
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The event-related potential (ERP) and event-related field (ERF) techniques provide valuable insights into the time course of processes in the brain. Because neural signals are typically weak, researchers commonly filter the data to increase the signal-to-noise ratio. However, filtering may distort the data, leading to false results. Using our own EEG data, we show that acausal high-pass filtering can generate a systematic bias easily leading to misinterpretations of neural activity. In particular, we show that the early ERP component C1 is very sensitive to such effects. Moreover, we found that about half of the papers reporting modulations in the C1 range used a high-pass digital filter cut-off above the recommended maximum of 0.1 Hz. More generally, among 185 relevant ERP/ERF publications, 80 used cutoffs above 0.1 Hz. As a consequence, part of the ERP/ERF literature may need to be re-analyzed. We provide guidelines on how to minimize filtering artifacts. (c) 2012 Elsevier B.V. All rights reserved.
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