Application of Self-organizing Maps in Functional Magnetic Resonance Imaging

Anderson Campelo, Valcir Farias, Marcus Rocha, Heliton Tavares, Antonio Pereira

2010

Abstract

In the present work, we used Kohonen’s self-organizing map algorithm (SOM) to analyze functional magnetic resonance imaging (fMRI) data. As a first step to increase computational efficiency in data handling by the SOM algorithm, we performed an entropy analysis on the input dataset. The resulting map allowed us to define the pattern of active voxels correlated with auditory stimulation in the data matrix. The validity of the algorithm was tested using both real and simulated data.

Paper Citation

in Harvard Style

Campelo A., Farias V., Rocha M., Tavares H. and Pereira A. (2010). Application of Self-organizing Maps in Functional Magnetic Resonance Imaging . In Proceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2010) ISBN 978-989-8425-03-4, pages 72-80. DOI: 10.5220/0002951300720080

in Bibtex Style

@conference{workshop anniip10,
author={Anderson Campelo and Valcir Farias and Marcus Rocha and Heliton Tavares and Antonio Pereira},
title={Application of Self-organizing Maps in Functional Magnetic Resonance Imaging},
booktitle={Proceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2010)},
year={2010},
pages={72-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002951300720080},
isbn={978-989-8425-03-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2010)
TI - Application of Self-organizing Maps in Functional Magnetic Resonance Imaging
SN - 978-989-8425-03-4
AU - Campelo A.
AU - Farias V.
AU - Rocha M.
AU - Tavares H.
AU - Pereira A.
PY - 2010
SP - 72
EP - 80
DO - 10.5220/0002951300720080