Single trial classification for the categories of perceived emotional facial expressions: an event-related fMRI study

Sutao Song; Yuxia Huang; Zhiying Long; Jiacai Zhang; Gongxiang Chen; Shuqing Wang

doi:10.1117/12.2216342

21 March 2016 Single trial classification for the categories of perceived emotional facial expressions: an event-related fMRI study

Sutao Song, Yuxia Huang, Zhiying Long, Jiacai Zhang, Gongxiang Chen, Shuqing Wang

Author Affiliations +

Proceedings Volume 9784, Medical Imaging 2016: Image Processing; 97841T (2016) https://doi.org/10.1117/12.2216342
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Recently, several studies have successfully applied multivariate pattern analysis methods to predict the categories of emotions. These studies are mainly focused on self-experienced emotions, such as the emotional states elicited by music or movie. In fact, most of our social interactions involve perception of emotional information from the expressions of other people, and it is an important basic skill for humans to recognize the emotional facial expressions of other people in a short time. In this study, we aimed to determine the discriminability of perceived emotional facial expressions. In a rapid event-related fMRI design, subjects were instructed to classify four categories of facial expressions (happy, disgust, angry and neutral) by pressing different buttons, and each facial expression stimulus lasted for 2s. All participants performed 5 fMRI runs. One multivariate pattern analysis method, support vector machine was trained to predict the categories of facial expressions. For feature selection, ninety masks defined from anatomical automatic labeling (AAL) atlas were firstly generated and each were treated as the input of the classifier; then, the most stable AAL areas were selected according to prediction accuracies, and comprised the final feature sets. Results showed that: for the 6 pair-wise classification conditions, the accuracy, sensitivity and specificity were all above chance prediction, among which, happy vs. neutral , angry vs. disgust achieved the lowest results. These results suggested that specific neural signatures of perceived emotional facial expressions may exist, and happy vs. neutral, angry vs. disgust might be more similar in information representation in the brain.

Citation Download Citation

Sutao Song, Yuxia Huang, Zhiying Long, Jiacai Zhang, Gongxiang Chen, and Shuqing Wang "Single trial classification for the categories of perceived emotional facial expressions: an event-related fMRI study", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97841T (21 March 2016); https://doi.org/10.1117/12.2216342

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Functional magnetic resonance imaging

Brain

Feature selection

Image classification

Brain imaging

Neuroimaging

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years