| Autor: |
Zhang Y; School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China., Wu X; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Sun J; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Yue K; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Lu S; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Wang B; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Liu W; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Shi H; The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China., Zou L; School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China.; School of Computer and Artificial Intelligence, Changzhou University, Changzhou, Jiangsu 213164, China.; Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou 310018, China. |
| Abstrakt: |
Research on functional changes in the brain of inflammatory bowel disease (IBD) patients is emerging around the world, which brings new perspectives to medical research. In this paper, the methods of canonical correlation analysis (CCA), kernel canonical correlation analysis (KCCA), and sparsity preserving canonical correlation analysis (SPCCA) were applied to the fusion of simultaneous EEG-fMRI data from 25 IBD patients and 15 healthy individuals. The CCA, KCCA and SPCCA fusion methods were used for data processing to compare the results obtained by the three methods. The results clearly show that there is a significant difference in the activation intensity between IBD and healthy control (HC), not only in the frontal lobe (p < 0.01) and temporal lobe (p < 0.01) regions, but also in the posterior cingulate gyrus (p < 0.01), gyrus rectus (p < 0.01), and amygdala (p < 0.01) regions, which are usually neglected. The mean difference in the SPCCA activation intensity was 60.1. However, the mean difference in activation intensity was only 36.9 and 49.8 by using CCA and KCCA. In addition, the correlation of the relevant components selected during the SPCCA calculation was high, with correlation components of up to 0.955; alternatively, the correlations obtained from CCA and KCCA calculations were only 0.917 and 0.926, respectively. It can be seen that SPCCA is indeed superior to CCA and KCCA in processing high-dimensional multimodal data. This work reveals the process of analyzing the brain activation state in IBD disease, provides a further perspective for the study of brain function, and opens up a new avenue for studying the SPCCA method and the change in the intensity of brain activation in IBD disease. |
