ABSTRACT
Objective At present, the grading evaluation of patients with disorders of consciousness (DOC) is still a focus and difficulty in related fields. Electroencephalogram (EEG) can directly read and continuously reflect scalp electrical activity generated by brain tissue structure, with high temporal resolution. Auditory stimulation is easy to operate and has broad application prospects in clinical detection of DOC. The causal network can intuitively reflect the direction of information transmission through the causal relationship between time series, helping us better understand the information interaction between different regions of the brain of patients. This paper combines EEG and causal networks to explore the differences in brain functional connectivity between patients with unresponsive arousal syndrome (VS) and those with minimum state of consciousness (MCS) under auditory stimulation. MethodsA total of 23 DOC patients were included, including 11 MCS patients and 12 VS patients. Based on the Oddball paradigm, auditory naming stimulation was performed on DOC patients and EEG signals of DOC patients were synchronously collected. The brain functional networks were constructed using multivariate Granger causality method, and the differences in node degree, clustering coefficient, global efficiency, and causal flow of the brain networks between MCS patients and VS patients were calculated. The differences in network characteristics of patients with different levels of consciousness under auditory stimulation were compared from the perspective of cooperation between brain regions. ResultsThe causal connectivity between most brain regions in MCS patients was stronger than that in VS patients, and MCS patients had more brain network connectivity edges than VS patients. The average degree (P<0.05), average clustering coefficient, and global efficiency (P<0.05) of MCS patients under naming stimulation were higher than those of VS patients. The difference in out-degree between each node of VS patients was larger, and the difference in in-degree between each node of MCS patients was smaller. The difference in in-degree of MCS patients was more significant than that of VS patients, and the inflow and outflow of information in the brain functional network of MCS patients were stronger than those of VS patients. MCS and VS patients had differences of causal flow in the frontal and temporal lobes, the direction of information transmission in the parietal lobe and central region was not the same, and MCS patients had more electrodes as causal sources than VS patients. ConclusionThe information transmission ability of MCS patients is stronger than that of VS patients under auditory naming stimulation. Compared with VS patients, MCS patients have an increase in the number of electrode channels as the causal source, an increase in information output to other brain regions, and also an increase in the information output within brain regions, which may indicate a better state of consciousness in patients. MCS patients have more electrode channels for information output in the frontal lobe than VS patients, and the number of electrode channels for changing the direction of information transmission in the frontal lobe is the highest. The frontal lobe is closely related to the level of consciousness in patients with consciousness disorders. This study can provide a theoretical basis for the grading evaluation of consciousness levels in DOC patients.
ABSTRACT
Objective:To investigate the effects of high frequency repetitive transcranial magnetic stimulation (rTMS) on learning memory and neuroelectric activity in rats. Methods:Eight Wistar rats were randomly divided into control group (n = 4) and rTMS group (n = 4). rTMS group was stimulated 14 days by rTMS with the frequency of 5 Hz, and the stimulation intensity was 100% motor threshold. The control group did not accepted rTMS. Then, the 16 channel local field potentials (LFPs) and spikes were recorded from their prefrontal cortex (PFC) in each group during the working memory tasks. The time-frequency analysis based on the short-time Fourier transform was performed on the LFPs, and the spike was analyzed by the release rate method. Multitaper Spectral Coherence was used to analyze the Synchronization Degree of LFPs-spike. Results:In the working memory experiment, rTMS group needed less days than the control group to reach the task correction criterion (t = 2.51, P = 0.046). The energy intensity of the θ-band and γ-band of the LFPs was significantly higher in rTMS group than in the control group (t > 12.49, P < 0.001), θ-band and γ-band LFPs-spike were more synchronized (t > 8.82, P < 0.001), but there was no significant difference in the average rate of spike between groups (t = 1.73, P = 0.067). Conclusion:High frequency rTMS could increase the LFPs energy in working memory experiment, enhance cooperative coding process for LFPs and spike, and improve the working memory ability of the rats.
ABSTRACT
Objective To develop a new algorithm to reconstruct the distribution of acoustic sources of magnetoacoustic tomography with magnetic induction(MAT-MI)in the acoustic inhomogeneous media,which is developed on the basis of generalized finite element method (GFEM) and modified time inversion algorithm. Methods The acoustic and acoustic coupling theory and the basic equations of acoustics were used to study the forward and inverse problems of the acoustic inhomogeneous concentric sphere magneticacoustic coupling model. The solution of acoustic non-uniform media wave equation based on GFEM was proposed.The method solved the problem of acoustically inhomogeneous media sound source reconstruction and conductivity reconstruction.At the same time,the distribution of velocity was reconstructed by rotating the pairs of transducers and the time reversal algorithm. Results The proposed algorithm could accurately reconstruct the acoustic source distribution in acoustic inhomogeneous media,and could obtain the distribution of sound velocity during the reconstruction of sound source and recover the image well. Conclusion The proposed algorithm had its feasibility and effectiveness verified,and gains advantages in MAT-MI reconstruction of acoustic inhomogeneous media.