ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

›› 2010, Vol. 18 ›› Issue (12): 1934-1941.

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Decoding the Representation of Cognition: the Principles and Applications of MVPA

LEI Wei;YANG Zhi;ZHAN Min-Ye;LI Hong;WENG Xu-Chu   

  1. (1Southwest University, School of Psychology, Chongqing 400715, China)
    (2 Lab for Higher Brain Function, Institute of Psychology, Chinese Academy of Science, Beijing 100101, China)
  • Received:2010-09-15 Revised:1900-01-01 Online:2010-12-15 Published:2010-12-15
  • Contact: LI Hong

Abstract: Multi-voxel pattern analysis (MVPA), which is based on machine learning theories, has gained great popularity over the past years as a new approach for fMRI data analysis. By training a classifier, MVPA categorizes multi-voxel patterns tuned by different cognitive states. Compared to conventional voxel-wise methods, this new approach provide higher sensitivity for detecting cognitive representations in the brain. It opens up the possibility for “reading out” mental states of human beings from the non-invasive recordings of brain activities.This paper introduce the fundamental principles of MVPA and the basic realization procedures. Scientific questions that may be properly addressed with this new approach and potential problems in its applications are also discussed.

Key words: MVPA, representation, fMRI, classification