Classifying Judging States from fMRI Data of Visual Recognition Task

Identifying the subject's simple judging states from fMRI data is the basis of studying complex logical relationship and has great theoretical significance. In this paper, we study judging states from fMRI data in terms of logical recognition classifications. We found that the ROI (Regions of Interest) regions played an important role in visual recognition task and identified what ROI regions were crucial for the correct judgments. We indicated that the correct and wrong judging states could be identified. In general, our work can answer the questions: (1) what are the judging states when one is performing a visual recognition task, and (2) whether the differences of brain activity pattern exist between the situations of correct and wrong judgments.