Abstrato

Study on the classification and the relationship with brain function regions of multiple intelligences

Zhang Sheng, Wang Wei, Yu Linsheng

The researchers collect the 19-lead EEG signals corresponding to visual-spatial intelligence, logical-mathematical intelligence and bodily-kinesthetic intelligence in the multiple intelligences, extract the frequency characteristics of the δ、θ、αãÃ‚Â€Ã‚Âß bands as the features of classifier to study the classification performance based on SVM, and then analyze the corresponding relationship between multiple intelligences and brain function regions by ranking the contribution of the lead features to the classification. The result shows that: (1) The identify rate of various intelligences reaches 61% or better, while the classification result of α, β bands is better than θ, δ band, among which α band is the best; (2) Experiment result shows that there is a significant intelligence difference between the people of different professions, it also shows that professional education and training can make changes in the structure of a person's multiple intelligences; (3) From the contribution of the lead-features to the classification we can find that leads Cz, T4, C4, Pz respond more to visual-spatial intelligence, while leads P3, O1, T5, T3 respond more to logical-mathematical intelligence. This conclusion is important to the further development of cognitive science and the analysis of brain function