Research On Characterization Of Consciousness Level Based On Multi-scale Spatio-temporal Dynamics Of EEG

Assessing the level of consciousness in patients with Disorder of Consciousness(DOC)is of great significance in clinical prognosis.Neuronal oscillations extracted from electroencephalogram(EEG)can reflect the conscious state and are used to provide effective objective electrophysiological basis for clinical assessment.Recent studies have shown that long-range temporal correlations(LRTC)of spontaneous oscillations in brain regions,and neural coupling among these oscillations are associated with consciousness.However,the alternation of neural oscillations in short time scale in local brain regions and the relationship between those oscillations in different time scales in DOC patients are rarely reported,as well as the influence of those local oscillations on the temporal dynamics in global brain.Therefore,based on the autocorrelation characteristics of both local and global neural oscillations,this thesis investigates the relationships among temporal correlation of local neural oscillations,the temporal dynamic of functional connections on the whole brain,and the consciousness level.Firstly,to characterize the abnormal temporal structure of neural oscillations in DOC patients,we analyzed the neural oscillation on different time scales with different level of consciousness,and the relationship between them.The results reveal:(1)The life time and waiting time of alpha oscillations over temporal lobe were greatly increased with the consciousness levels,suggesting that short-range temporal correlation of neural oscillations is directly proportional to the level of consciousness.(2)And compared to the controls,the patients with DOC showed weaker LRTC in central brain area in alpha band.(3)Moreover,accompanied by the loss of consciousness,the relationship between the LRTC and the short-range temporal correlation also decreased significantly among the different subjects.The present results suggest that the autocorrelation structure of neuronal oscillation amplitude on multiple time scale is abnormal in patients with DOC.Secondly,on whole brain,we characterized the LRTC of connection weight sequence and node degree sequence by using detrended fluctuation analysis(DFA)aimed to establish the relationship between LRTC of the dynamic functional connection(FC)and the level of consciousness.The LRTC and spatial heterogeneity of functional connection were verified by comparing with random sequence.And the connection weight sequence and node degree sequence in spatial distribution of LRTC differed between patients with DOC and healthy controls.Moreover,in alpha band,they were positively correlated with consciousness level,which suggested that the abnormal changes of temporal correlation of dynamic functional connections are the potential causes of DOC.Finally,we constructed the instantaneous amplitude correlation FC matrix and extracted the meta-states by means of community detection.And we calculated the metrics of meta-state activation sequence,such as average dwell time,switching frequency.In addition,the relationship between the metrics and LRTC of FC was analyzed.We aim to reveal how the effect of LRTC of FC on global temporal dynamics(state transition)in DOC patients.Results show that the meta-state sequences in DOC patients display shorter dwell times,higher complexity and higher transition cost,which means the brains of DOC patients operate at a point with increased randomness.And the correlation between the LRTC of FC and metrics of state transition in DOC patients is weak.Whereas,state transition in healthy controls diverge from randomness and the correlation between the LRTC of FC and metrics of state transition in healthy controls is significantly higher than that in DOC patients.These results suggest that the damage to the LRTC of FC may be one of the reasons of abnormal state transition in DOC patients.