The Analysis And Application Of Instan- Taneously Co-activation Method Using FMRI BOLD Signal

As a non-invasive imaging technique, functional magnetic resonance imaging (fMRI) has already been an important tool on the research of brain. By the analysis on BOLD signal, we’ve already indicated the characteristics of many brain regions, as well as the functional combination or competition relationships of different regions.Ordinary BOLD signal analysis always based on a settled length of time, which reflected the overall activity of our brain in a period of time. In this period, the activity of our brain is relatively stable. Actually, brain’s activity is always fluctuant, and the dynamic activity is also worth to research. There are a lot of papers paying attention to this new field. These researches focused on a much more shorter time window, even the activity on specific time frames.Among all those methods which study dynamic, co-activation method caught our eyes as its easy hypothesis and less dependence on parameters. Depending on the co-activation regions at the same time, this method can separate our brain into different modes, in which different regions can show a cooperation or competition relationships.Two studies are included in this paper. First one is the application of co-activation method on real/sham finger force feedback task. With the hypothesis that attention and internal/external information processing interaction could be manipulated by different (real and sham) feedback conditions, we investigated functional network dynamics of the default mode network, executive control network and sensorimotor networks. They were decomposed into several modes. During real feedback, the occurrence of "default mode-executive control competition-related" mode was higher than that during sham feedback (p= 0.0003); the "default mode-visual facilitation-related" mode more frequently appeared during sham than real feedback (p= 0.0004). However, the dynamics of the sensorimotor network did not change significantly between two conditions (p> 0.05). Our results indicated that the visual-guided motor feedback involves higher cognitive functional networks rather than primary motor network. The dynamics monitoring of inner and outside environment and multi-sensory integration could be the mechanisms.The second study is an improvement of co-activation method based on independent component analysis (ICA). We believed the time series extracted from ICA can have a better representation of functional networks comparing that of a seed region. We applied this improved method on a group of resting-state fMRI data, and found the modes effectively avoided the bias of a single seed region. Beside this, networks in these modes also showed more clear patterns. Using this improved method, we compared the occurrence of different modes under eyes open and eyes closed conditions. The results showed that the task-positive network as well as "visual area-other sensory areas competition-related" mode showed more frequently under eyes open condition, while frontal-parietal network and "visual area-other sensory areas facilitation-related" mode showed more frequently under eyes closed condition. The results reminded us the modulation of eyes conditions on modes, especially the influence of outside environment’s visual input.