The Basic Research Of Large Sample Body Rhythmic Based On The Amplitude Of Low-frequency Fluctuation In Resting State

As the functional magnetic resonance imaging has been more and more widely used in field of neuroscience, more investigators would look forward to explore the hidden physical and psychological significance by fMRI technology. And the spontaneous neural activities in resting-state brain could be reflected by changing in blood oxygenation level analysis. What's more, there are some reliable data for regular fluctuations in brain activity in one day. While there is seldom system research about human neural activity in daily rhythmicity, just based on a hypothesis. So we make some research about it by analyzing fMRI data of large numbers of normal subjects in resting-state for the human rhythmic system.We have studied this issue through analyzing the synchronicity among different brain regions, consistency in some rhythmic networks and closed relationship between several networks. It is useful to rely on the brain functional connectivity and network partitioning method for studying that whether there is some relationship between the circadian and the spontaneous signals. And there are certain research had proved this kind of spontaneous neuronal activity always performance the physiological significance. We choose ALFF as an indicator to measure brain activity. We take the previous study of brain network as the reference, and analyze the statistical relationship between brain areas based on the large scale method to observe the change in single brain region. In addition, to divisive brain networks based on hierarchical clustering algorithm for studying the synchronization of different brain regions and some changes in the network in one day. At last, we just get by means of the fluctuations image of the two significantly associated networks to determine whether there is correlation between the presence of two networks and the human rhythmicity.The analysis of abundant experimental data in resting state 90 brain regions in one day, and that there is volatile in every single brain region. As the amount of central auditory back brain regions, responsible for learning and memory in the hippocampus, produce emotion and recognition regulating emotion amygdala and visual supervisor occipital gyrus regions of the brain were drawn each time period fluctuation image. It is concluded these brain regions have certain fluctuation in a certain period of time compared to the fluctuation of low frequency amplitude. In addition, seven functional networks are obtained by dividing the hierarchical clustering algorithm, namely visual network, attention network, default network, the implementation of the control network, sensorimotor network and so on. Through statistical analysis of the average time series of seven rhythm network, we also get regular fluctuation images in one day, and it is in line with the daily activities of the human body. By analyzing the correlation between the networks, the executive control network and sensory motor network, and they are synchronous. The paper has been shown to prove the existence of human rhythmicity and provide a new research method for early diagnosis and monitoring of brain diseases.