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LAMOŠ, M. MAREČEK, R. SLAVÍČEK, T. HAVLÍČEK, M. JAN, J.
Original Title
Does EEG help to identify the epilepsy-related spatial independent component of fMRI data?
Type
abstract
Language
English
Original Abstract
Independent component analysis (ICA) has advantage of being a completely data-driven approach. However, no idea on the importance of a particular independent component (IC) is available without some prior knowledge about processes that we are looking for [Hyvärinen and Oja, 2000]. A step preceding ICA is data reduction by principal component analysis (PCA). Effects of interest (here the interictal epileptic activity) may be minor compared to other processes in the brain and thus we can remove them accidentally. However, in our retrospective study [Slavíček et al., submitted for publication] we showed that ICA with proper settings applied to fMRI data is capable of finding ICs corresponding to epileptic activity. This contribution aims at the next step – identification of features, which would enable discovering epilepsy related fMRI ICs prospectively.
Keywords
fMRI, EEG, epilepsy, ICA
Authors
LAMOŠ, M.; MAREČEK, R.; SLAVÍČEK, T.; HAVLÍČEK, M.; JAN, J.
Released
12. 6. 2014
Pages count
3
URL
https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095
BibTex
@misc{BUT109017, author="Martin {Lamoš} and Radek {Mareček} and Tomáš {Slavíček} and Martin {Havlíček} and Jiří {Jan}", title="Does EEG help to identify the epilepsy-related spatial independent component of fMRI data?", booktitle="20th Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2014.", year="2014", pages="3", url="https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095", note="abstract" }