DocumentCode
2252720
Title
Multivariate approach toward classification of competition and collaboration: An fMRI study
Author
Eun Kyung Jung ; Jong-Hwan Lee ; Jun Zhang ; Soo-Young Lee
Author_Institution
Dept. of Brain & Cognitive Eng., Korea Univ., Seoul, South Korea
fYear
2015
fDate
12-14 Jan. 2015
Firstpage
1
Lastpage
2
Abstract
This functional magnetic resonance imaging (fMRI) study aimed to distinguish neural activation associated with competition and collaboration using multivoxel pattern analysis (MVPA). For each participant, a searchlight-based MVPA was applied to select informative voxels within training data. The support vector machine with a radial basis function kernel was used to obtain classification accuracy of the informative regions. As a result, within-individual maximum classification performance for the test data reached maximally 94.6%. Important regions classifying competition and collaboration were mainly found within prefrontal cortex (e.g., superior/middle frontal gyri) and visual area (e.g., calcarine sulcus and lingual gyrus). Furthermore, visual regions and dorsolateral prefrontal regions showed average accuracy around 70% across participants. In short, neural contribution during competition or collaboration was characterized as differences in multivoxel pattern with a high accuracy.
Keywords
biomedical MRI; image classification; medical image processing; radial basis function networks; support vector machines; calcarine sulcus; collaboration classification; competition classification; dorsolateral prefrontal regions; fMRI; functional magnetic resonance imaging; informative regions; informative voxel selection; lingual gyrus; middle-frontal gyri; multivariate approach; multivoxel pattern analysis; neural activation; prefrontal cortex; radial basis function kernel; searchlight-based MVPA; superior-frontal gyri; support vector machine; test data; training data; visual area; visual regions; within-individual maximum classification performance; Collaboration; Data analysis; Decision support systems; Magnetic resonance imaging; Pattern analysis; Support vector machines; Functional magnetic resonance imaging; collaboration; competition; multivoxel pattern analysis; searchlight analysis; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Brain-Computer Interface (BCI), 2015 3rd International Winter Conference on
Conference_Location
Sabuk
Print_ISBN
978-1-4799-7494-8
Type
conf
DOI
10.1109/IWW-BCI.2015.7073044
Filename
7073044
Link To Document