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Introducing Concepts of MDX into EEG Analysis

2008; Frontiers Media; Volume: 2; Linguagem: Inglês

10.3389/conf.neuro.09.2009.01.351

1662-5161

Johannes Rentzsch,

EEG and Brain-Computer Interfaces

Event Abstract Back to Event Introducing Concepts of MDX into EEG Analysis Matthias Faix1* and J. Rentzsch2 1 University of Bonn, Germany 2 FU University, Germany EEG Signals do have an unknown origin. There are some approaches to reveal the origins based upon EEG Signals. ERP studies produced by EEG are inexpensive and can be reproduced in any hospital because EEG is available in almost any hospital. Sharpening those signs would open new possibilities in developing screening methods. This could be especially important in the detection of problems in the early childhood. Exploring the brain and the development of the brain in early days of childhood may offer the chance to start a catch-up program for those children. The main problem of studying EEG is, that the strength and the origin of the sign within the brain are difficult to determine. This is known in literature as the “Inverse Problem”. A main approach to this problem is described in literature as the ICA solution sets. These mathematical methods try to distinctly determine the location and strength. ICA is abbreviation for “independent components analysis”. ICA is a method embedded in the well known program “EEGLAB” by Scott Makeig. Another program which could be linked to the results of an ICA study is Loretta. This program helps to visualize the brain centers involved in brain activity. Storing EEG data in common databases to analyze the signs is of low value, because pattern searching methods in relational databases are slow. Since the past years there have been developments to build new cube oriented databases. ESSBASE by Hyperion is one of these databases. It is a so called multidimensional database. There are methods available to determine extremely fast – ESSBASE is a tree based database – patterns in a data stream. A language is available to work on the database called MDX. It is a language derived from standard SQL and optimized for information cubes. MDX is supported by the companies SAS, Microsoft and Hyperion. It is well known for finding independent components in business and technical data. Yet this language is an industrial standard but not an ISO Standard. The idea of the study is to show that EEG signs can be easily administered by this framework, patterns of interest can be found and solutions for the inverse problem can be optimized by this multidimensional database. We have datasets of “ERP” studies and datasets of studies related to the “Wisconsin Card Sorting”- test. Our main interest is centered on signals produced in the prefrontal cortex inflicted by “WCS-Test”. Import Filters for the multidimensional database are prepared and we have user front ends in order to study the data. Conference: 10th International Conference on Cognitive Neuroscience, Bodrum, Turkey, 1 Sep - 5 Sep, 2008. Presentation Type: Poster Presentation Topic: Neuroinformatics of Cognition Citation: Faix M and Rentzsch J (2008). Introducing Concepts of MDX into EEG Analysis. Conference Abstract: 10th International Conference on Cognitive Neuroscience. doi: 10.3389/conf.neuro.09.2009.01.351 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: 15 Dec 2008; Published Online: 15 Dec 2008. * Correspondence: Matthias Faix, University of Bonn, Bonn, Germany, Matthias.Faix@ukb.uni-bonn.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 Faix J. Rentzsch Google Matthias Faix J. Rentzsch Google Scholar Matthias Faix J. Rentzsch PubMed Matthias Faix J. Rentzsch 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.