A New Theory of Trial-by-Trial P300 Amplitude Fluctuations

Antonio Kolossa ()
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Antonio Kolossa: Technische Universität Braunschweig, Institut für Nachrichtentechnik

Chapter Chapter 3 in Computational Modeling of Neural Activities for Statistical Inference, 2016, pp 41-69 from Springer

Abstract: Abstract This chapter reviews state-of-the-art observer models of the P300 event-related potential and introduces a new digital filtering (DIF) model. It starts with a brief overview of the models known from literature and of the approach proposed in this work. After a description of the employed variant of the oddball task and specific methods for capturing trial-by-trial fluctuations in the P300 amplitudes y(n), the models and response functions constituting the model space $$\mathcal {M}$$ are presented in detail and the two most renowned ones are integrated into the digital filtering model. Next, the parameter optimization schemes as well as the composition of the design matrices for model estimation and selection (see Chap. 2 ) are specified. Results and conclusions complete this chapter.

Keywords: Finite Impulse Response; P300 Amplitude; Visual Working Memory; Infinite Impulse Response; Oddball Task (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-32285-8_3

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DOI: 10.1007/978-3-319-32285-8_3

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