Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)

The Application of kNN and SVM in the Decoding of fMRI Data

Authors
Fangyuan Ma, Junhai Xu
Corresponding Author
Fangyuan Ma
Available Online November 2016.
DOI
10.2991/aiie-16.2016.78How to use a DOI?
Keywords
functional magnetic resonance imaging; support vector machine; k-nearest neighbor
Abstract

For the decoding analysis of functional magnetic resonance imaging (fMRI) data, the appropriate method for feature selection and classification algorithm was a core issue. Given the high dimensionality of fMRI data in whole brain, the localization of regions of interest (ROI) usually was used to select voxels relevant to task, which was based on the physiological evidence. K-nearest neighbor (kNN) and linear support vector machine (SVM) were performed to classify the fMRI data. The result indicated that the method of ROI could indeed select voxels involved in the recognition task. The accuracy of ROI relevant to task was significantly higher than chance level and different stimuli could be decoded successfully. Additionally, by the comparison of kNN and SVM, the performance of SVM was better than that of kNN on the whole.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-271-8
ISSN
1951-6851
DOI
10.2991/aiie-16.2016.78How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Fangyuan Ma
AU  - Junhai Xu
PY  - 2016/11
DA  - 2016/11
TI  - The Application of kNN and SVM in the Decoding of fMRI Data
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 343
EP  - 345
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.78
DO  - 10.2991/aiie-16.2016.78
ID  - Ma2016/11
ER  -