Mitchell Tom M, Hutchinson Rebecca, Just Marcel A, Niculescu Radu S, Pereira Francisco, Wang Xuerui
Carnegie Mellon University, Computer Science, Pittsburgh, PA 15213, USA.
AMIA Annu Symp Proc. 2003;2003:465-9.
We consider the problem of detecting the instantaneous cognitive state of a human subject based on their observed functional Magnetic Resonance Imaging (fMRI) data. Whereas fMRI has been widely used to determine average activation in different brain regions, our problem of automatically decoding instantaneous cognitive states has received little attention. This problem is relevant to diagnosing cognitive processes in neurologically normal and abnormal subjects. We describe a machine learning approach to this problem, and report on its successful use for discriminating cognitive states such as observing a picture versus reading a sentence, and reading a word about people versus reading a word about buildings.
我们考虑基于人类受试者的功能性磁共振成像（fMRI）观测数据来检测其瞬时认知状态的问题。虽然fMRI已被广泛用于确定不同脑区的平均激活情况，但我们自动解码瞬时认知状态的问题却很少受到关注。这个问题与诊断神经正常和异常受试者的认知过程相关。我们描述了一种针对此问题的机器学习方法，并报告了其在区分认知状态方面的成功应用，例如观察图片与阅读句子，以及阅读关于人的单词与阅读关于建筑物的单词。
