A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
作者： Wouter D. Weeda , Raoul P. P. P. Grasman , Lourens J. Waldorp , Maria C. van de Laar , Maurits W. van der Molen
DOI: 10.1371/JOURNAL.PONE.0038292
关键词: Basis function 、 Computer science 、 Electroencephalography 、 Linear least squares 、 Noise 、 Latency (engineering) 、 Algorithm 、 Magnetoencephalography 、 Signal-to-noise ratio 、 Amplitude 、 Filter (signal processing) 、 Waveform
摘要: The amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate signals. advantages the are fourfold. First, no a-priori specified template function is required. Second, allows for multiple that vary independently in and/or latency. Third, less sensitive noise as it models data with parsimonious set basis functions. Finally, very fast since based on an iterative linear least squares algorithm. A simulation study shows yields reliable estimates under different levels variation signal-to-noise ratioOs. Furthermore, existence can be correctly determined. An application empirical from choice reaction time indicates describes these accurately.
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