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• W2324852170 abstract "Event Abstract Back to Event Integration of Temporal Information Across Trials in EEG Data Analysis Matthias Ihrke1, 2*, Hecke Schrobsdorff1, 2 and Michael J. Herrmann1, 3 1 BCCN , Germany 2 Max-Planck-Institute for Dynamics and Self-Organization, Germany 3 University of Edinburgh, Germany We propose an averaging method for segments of electrophysiological data (Event-Related Potentials, ERPs) that has been specifically designed to compensate for processing speed in different realizations of the same experiment in individual subjects. The algorithm is based on the estimation of single-trial ERPs by wavelet-denoising combined with a parametrized dynamic time-warping algorithm to guide selective averaging. The hierarchical averaging scheme is based on dendrograms generated by agglomerative cluster-analysis. External knowledge about the temporal alignment of cognitive processing steps is incorporated by using time-markers of observable events (e.g. saccades, response-markers) by independently combining corresponding segments between to time-markers. This method has several advantages over previous averaging schemes: (i) the questionable assumption of an identical ERP signal in different realizations is dropped and different processing speeds are considered explicitly, (ii) the choice of the warping function is estimated from the data and does not require an a priori specification as in [1] and (iii) external knowledge in the form of arbitrarily many time-markers can be integrated. A cross-validation approach is taken to estimate optimal parameter-settings for the restricted timewarping procedure and to contrast the procedure with other relevant averaging schemes. We define the average temporal distortion as the measure obtained by averaging warping functions computed on all pairs of trials independently. We find that electrodes are well divisible into distinct regions of physically neighbouring electrodes applying cluster-analysis with this measure. This indicates that the timecourse of cognitive processing as measured by the structure and distribution of the ERP's components are independent in different brain regions. A software library written in the C-programming language (with partial Matlab-support) that implements the described algorithms is available from http://www.bccn-goettingen.de/projects/libeegtools. References 1. Gibbons, H. & Stahl, J. (2007). Response-time corrected averaging of event-related potentials. Clinical Neurophysiology, 118 (1), 197-208.2. Ihrke, M., Schrobsdorff, H. & Herrmann, J. M. (in press). Compensation for Speed-of-Processing Effects in EEG-Data Analysis. Lecture Notes in Computer Science (Proceedings IDEAL 2008). Springer3. Ihrke, M., Schrobsdorff, H & Michael, J.M. (in press). Denoising and Averaging Techniques for Electrophysiological Data. In Wennberg, R. & Perez-Velazquez, J. L. (Eds.), Coordinated Activity in the Brain: measurements and relevance to brain function and behaviour. Springer. Conference: Bernstein Symposium 2008, Munich, Germany, 8 Oct - 10 Oct, 2008. Presentation Type: Poster Presentation Topic: All Abstracts Citation: Ihrke M, Schrobsdorff H and Herrmann MJ (2008). Integration of Temporal Information Across Trials in EEG Data Analysis. Front. Comput. Neurosci. Conference Abstract: Bernstein Symposium 2008. doi: 10.3389/conf.neuro.10.2008.01.065 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 16 Nov 2008; Published Online: 16 Nov 2008. * Correspondence: Matthias Ihrke, BCCN, Göttingen, Germany, mihrke@uni-goettingen.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Matthias Ihrke Hecke Schrobsdorff Michael J Herrmann Google Matthias Ihrke Hecke Schrobsdorff Michael J Herrmann Google Scholar Matthias Ihrke Hecke Schrobsdorff Michael J Herrmann PubMed Matthias Ihrke Hecke Schrobsdorff Michael J Herrmann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page." @default.
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• W2324852170 title "Integration of Temporal Information Across Trials in EEG Data Analysis" @default.
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