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Computational Intelligence and Neuroscience
Volume 2016 (2016), Article ID 6391807, 10 pages
Research Article

Discovering Patterns in Brain Signals Using Decision Trees

Federal University of Rio Grande (FURG), Rio Grande, RS, Brazil

Received 29 April 2016; Revised 26 July 2016; Accepted 2 August 2016

Academic Editor: Placido Rogerio Pinheiro

Copyright © 2016 Narusci S. Bastos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Even with emerging technologies, such as Brain-Computer Interfaces (BCI) systems, understanding how our brains work is a very difficult challenge. So we propose to use a data mining technique to help us in this task. As a case of study, we analyzed the brain’s behaviour of blind people and sighted people in a spatial activity. There is a common belief that blind people compensate their lack of vision using the other senses. If an object is given to sighted people and we asked them to identify this object, probably the sense of vision will be the most determinant one. If the same experiment was repeated with blind people, they will have to use other senses to identify the object. In this work, we propose a methodology that uses decision trees (DT) to investigate the difference of how the brains of blind people and people with vision react against a spatial problem. We choose the DT algorithm because it can discover patterns in the brain signal, and its presentation is human interpretable. Our results show that using DT to analyze brain signals can help us to understand the brain’s behaviour.