@inproceedings{
    KarpICA09,
    editor = "et al., T. Adali",
    author = "Karp, Elina and Parkkonen, Lauri and Vig\'{a}rio, Ricardo",
    volume = "LNCS 5441",
    publisher = "Springer-Verlag",
    title = "Denoising Single Trial Event Related Magnetoencephalographic Recordings",
    booktitle = "Proceedings of 8th International Conference on Independent Component Analysis and Signal Separation (ICA 2009)",
    year = "2009",
    abstract = "Functional brain mapping is often performed by analysing neuronal responses evoked by external stimulation. Assuming constant brain responses to repeated identical stimuli, averaging across trials is usually applied to improve the typically poor signal-to-noise ratio. However, since wave shape and latency vary from trial to trial, information is lost when averaging. In this work, trial-to-trial jitter in visually evoked magnetoencephalograms (MEG) was estimated and compensated for, improving the characterisation of neuronal responses. A denoising source separation (DSS) algorithm including a template based denoising strategy was applied. Independent component analysis (ICA) was used to compute a seed necessary for the template construction. The results are physiologically plausible and indicate a clear improvement compared to the classical averaging method.",
    responsibleauthor = "Karp, Elina",
    internalpdf = "KarpICA09.pdf",
    flags = "AIRC",
    address = "Paraty, Brazil",
    keywords = "single trial, event related, denoising, magnetoencephalography (MEG), independent component analysis (ICA), denoising source separation (DSS)",
    impactfactor = "D3",
    pages = "427--434"
}