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Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies
We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolutio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5835340/ https://www.ncbi.nlm.nih.gov/pubmed/29670667 http://dx.doi.org/10.1155/2018/4638903 |
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author | Bosch, Paul Herrera, Mauricio López, Julio Maldonado, Sebastián |
author_facet | Bosch, Paul Herrera, Mauricio López, Julio Maldonado, Sebastián |
author_sort | Bosch, Paul |
collection | PubMed |
description | We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections. |
format | Online Article Text |
id | pubmed-5835340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-58353402018-04-18 Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies Bosch, Paul Herrera, Mauricio López, Julio Maldonado, Sebastián Behav Neurol Research Article We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections. Hindawi 2018-01-11 /pmc/articles/PMC5835340/ /pubmed/29670667 http://dx.doi.org/10.1155/2018/4638903 Text en Copyright © 2018 Paul Bosch et al. http://creativecommons.org/licenses/by/4.0/ 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. |
spellingShingle | Research Article Bosch, Paul Herrera, Mauricio López, Julio Maldonado, Sebastián Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies |
title | Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies |
title_full | Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies |
title_fullStr | Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies |
title_full_unstemmed | Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies |
title_short | Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies |
title_sort | mining eeg with svm for understanding cognitive underpinnings of math problem solving strategies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5835340/ https://www.ncbi.nlm.nih.gov/pubmed/29670667 http://dx.doi.org/10.1155/2018/4638903 |
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