The Research Of FMRI Data Processing Using Temporal-Spatial Model Based On CCA

It's an interesting and challenging work to investigate the structure and function of the brain. In last 20 years, the Functional magnetic resonance imaging ( fMRI ) is extensively developed It is a non-invade brain functional imaging technique , whose general principle is that when the brain is performing a cognitive task, the MRI signals will change with the changes of its blood-oxygen level in its related regions . Based on such parallelism relation,we could investigate brain's cognitive activations and functional position . The fMRI can get high spatial resolution by detecting the simulated cortex active regions , usually less than 1 mm .Obviously , fMRI is much better than other traditional techniques such as the positron emission tomography ( PET ).fMRI also has high speed . Even we can get thousands of pictures in just 10 minutes . Besides, the fMRI experiment is repeatable. For these reasons the fMRI is applied widely in the neurology, psychology recognition, clinical application and so on.For analysis of fMRI data , which algorithm is adopted is very important, because the brain functional localization is depended on the discrepancy between the signal of magnetism resonance and the noise.Now the Chinese researchers usually use standard software to process the fMRI data such as the SPM, but the results are...