Abstract
It is useful to find the sequence of hidden cognitive states that subjects pass through when performing some complex task. We present a method to classify cognitive states from fMRI data using SVMs. A dataset of the study of Chinese character vs. Pinyin is considered. The data images are firstly processed and transformed to normalized coordinates. The features are extracted based on activities of voxel and index of Brodmann's areas. Then, they are used as input vectors to train the classifiers of SVMs. The results indicate that it is feasible for either single subject cognitive classification or multiple subjects'. The method is helpful to decode cognitive states.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
