Dynamic Functional Network And The Application In Epilepsy In The Time-frequency Domain

Studies have shown that the functional connectivity of the human brain may be dynamic and time-dependent,and is related to ongoing rhythmic activities.Studying the dynamic characteristics of functional connectivity over time may better discover the basic characteristics of the brain network.At present,in the time-frequency domain the algorithm of constructing dynamic network mainly adopts Wavelet Transform.However,Wavelet Transform processing signal needs to select the basis function in advance and is not the optimal choice to analyze non-linearly and non-stationary signal.The BOLD signal is non-linearly and non-stationary.Hilbert-Huang Transform(HHT)algorithm can adaptively generate basis functions based on the data itself,avoiding inaccurate results on account of selecting inappropriate basis functions.In this paper,a new method of constructing dynamic network based on HHT algorithm on fMRI was proposed in the time-frequency domain.This method was applied to brain dynamic network analysis of temporal lobe epilepsy in the time-frequency domain.The main contents of the research are as follows:1.Implement HHT-based to construct dynamic network on fMRI in the time-frequency domain.First,perform routine preprocessing on fMRI;then Group Independent Component Analysis(GICA)identify functional networks with strong correlation and their corresponding time sequences;finally perform postprocessing on time sequences to further reduce noise interference to dynamic networks.The postprocessing time sequences is decomposed by Empirical Mode Decomposition(EMD)algorithm in HHT to obtain Intrinsic Mode Function(IMF),which is then mapped to the time-frequency domain by Hilbert transform.Then,time-frequency coherence is calculated and build dynamic network.This study investigated the resting-state fMRI of 40 cases of normal subjects in the HCP database.It was found that in the time-frequency domain dynamic network constructed by HHT was consistent with dynamic network constructed by wavelet transform,and the parameter settings are more concise.Verify the effectiveness of dynamic network constructed by HHT in the time-frequency domain.2.In the time-frequency domain use HHT-based dynamic network to analyze the whole brain functional connectivity model of temporal lobe epilepsy.The fMRI data of epileptic patients and normal controls constructed dynamic network in the time-frequency domain according to the process of dynamic network constructed by HHT.In the state of dynamic network connectivity carrying frequency and phase information,the abnormality of network connectivity and the frequency and phase distribution of brain regions in temporal lobe epilepsy were studied.Based on dynamic network connectivity state that carries frequency and phase information,studied the differences of network connectivity and frequency and phase distribution with temporal lobe epilepsy.In this study,the resting-state fMRI of 9 patients with temporal lobe epilepsy and 11 normal subjects were used.It was found that in the time-frequency domain dynamic network with epilepsy patients was significantly different from that of normal subjects.First,the brain areas associated with cognitive function are significantly fewer in epilepsy patients obtained by GICA,demonstrating that seizures do damage brain cognitive function.Secondly,compared with normal controls,functional connectivity in the hippocampus and thalamus is also significantly different in patients with epilepsy.Finally,the frequency and phase distributions of the network connectivity states on both also show prominent differences.This study proposed and implemented a new method of dynamic network based on HHT in the time-frequency domain.It can capture information of brain functional connectivity in detail and present a more accurate network connectivity pattern with more concise parameter settings.This research also applied this method to the study of dynamic network connectivity with temporal lobe epilepsy in the time-frequency domain,and discovered the abnormality of the whole brain dynamic network connectivity with temporal lobe epilepsy in the time-frequency domain,which provides the basis for the pathological mechanism research and treatment of drug development with temporal lobe epilepsy.