ABSTRACT
Objective:To investigate the effect of a single-trial transcranial direct current stimulation(tDCS) of the dorsolateral prefrontal cortex (DLPFC) on fairness-related decision-making behavior.Methods:From September 2018 to February 2019, a total of 60 healthy participants between the ages of 18 and 45 were enrolled.Then, the participants were randomly divided into 3 groups with 20 in each group to receive left anode stimulation/right cathode stimulation (left anode /right cathode group), left cathode/right anode stimulation (left cathode /right anode group) or bilateral control electrodes (sham stimulation group) on the bilateral dorsolateral prefrontal cortices (DLPFC), respectively.After tDCS, the participants immediately completed the ultimatum game (UG) task as responders and a fairness questionnaire in turn.SPSS 22.0 statistical software was used to analyze the data with repeated measurement ANOVA and nonparametric test.Results:In the UG task, there was no significant difference in the acceptance rate among the three groups of participants as responders (all P>0.05). When analyzing the acceptance rate facing different proposers (" computer" and " human" ) under different fairness levels in the three stimulus types through the paired samples Wilcoxon test, it was found that the acceptance rate of the sham stimulation group to the extremely unfair proposals proposed by the human opponent was lower than that proposed by the computer(0.28 (0, 0.67), 0.44 (0.33, 0.89), Z=-2.14, P=0.032), while there was no difference in acceptance rates (both P>0.05) in the face of fair or unfair proposals proposed by computer and human opponents.The acceptance rate of the left cathode /right anode group to the unfair(0.90 (0.50, 1.00), 1.00 (0.70, 1.00), Z=-1.90, P=0.046)or extremely unfair(0.44 (0, 1.00), 0.89 (0.50, 1.00), Z=-2.73, P=0.006) proposals proposed by human opponents was significantly lower than the proposals proposed by computer opponent, and there was no differences in acceptance rate when facing fair proposals proposed by computer and human opponents ( P> 0.05). There were no significant differences in acceptance rates in the left anode /right cathode group when faced with fair, unfair, and extremely unfair schemes proposed by computer and human opponents (all P>0.05). For fairness questionnaire scores, a repeated measurements ANOVA showed that the interaction effect between group and proposer types was not significant ( F(2, 54)=2.037, P=0.140), and the group main effect was not significant ( F(1, 54)=0.165, P=0.848), but the proposer type main effect was significant ( F(1, 54)=6.363, P=0.015), indicating that the fairness questionnaire score in the face of the human opponents was lower than when facing the computer opponents( P<0.05). Conclusion:Although a single-trial tDCS on bilateral DLPFC has no significant effect on the overall acceptance rate of fairness-related decision-making, it affects the decision-making of unfair distribution scheme proposed by human or computer.
ABSTRACT
Anxiety disorder is a common emotional handicap, which seriously affects the normal life of patients and endangers their physical and mental health. The prefrontal cortex is a key brain region which is responsible for anxiety. Action potential and behavioral data of rats in the elevated plus maze (EPM) during anxiety (an innate anxiety paradigm) can be obtained simultaneously by using the and in conscious animal multi-channel microelectrode array recording technique. Based on maximum likelihood estimation (MLE), the action potential causal network was established, network connectivity strength and global efficiency were calculated, and action potential causal network connectivity pattern of the medial prefrontal cortex was quantitatively characterized. We found that the entries (44.13±6.99) and residence period (439.76±50.43) s of rats in the closed arm of the elevated plus maze were obviously higher than those in the open arm [16.50±3.25, <0.001; (160.23±48.22) s, <0.001], respectively. The action potential causal network connectivity strength (0.017 3±0.003 6) and the global efficiency (0.044 2±0.012 8) in the closed arm were both higher than those in the open arm (0.010 4±0.003 2, <0.01; 0.034 8±0.011 4, <0.001), respectively. The results suggest that the changes of action potential causal network in the medial prefrontal cortex are related to anxiety state. These data could provide support for the study of the brain network mechanism in prefrontal cortex during anxiety.
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Objective To study the synchronization of electroencephalogram (EEG) in the patients with Alzheimer's disease (AD). Methods Sixteen-channel EEG was recorded under resting, eyes-closed condition in 8 AD patients and 8 control subjects. After data preprocessing, the synchronization likelihood was measured between pairs of EEG channels for the full band,δband (0.5-4 Hz),θband (4-8 Hz),αband (8-13 Hz) andβband (13-30 Hz) in the AD and control groups. Mean synchronization likelihood values of each frequency band were compared between the two groups. Results At the full band,θband andαband, the mean synchronization likelihood values of the AD group were lower than that of the control group (P0.05). Conclusions The EEG synchronization of AD patients decreases at the full band,θandαbands, suggesting that collaborative information processing ability atθandαbands reduces between different brain regions in the AD patients. The research provides support for further study of the brain functional connectivity characteristics in the AD patients.
ABSTRACT
Alzheimer's disease (AD) is the most common type of dementia and a neurodegenerative disease with progressive cognitive dysfunction as the main feature. How to identify the early changes of cognitive dysfunction and give appropriate treatments is of great significance to delay the onset of dementia. Some other researches have shown that AD is associated with abnormal changes of brain networks. To study human brain functional connectivity characteristics in AD, 16 channels electroencephalogram (EEG) were recorded under resting and eyes-closed condition in 15 AD patients and 15 subjects in the control group. The synchronization likelihood of the full-band and alpha-band (8-13 Hz) data were evaluated, which resulted in the synchronization likelihood coefficient matrices. Considering a threshold T, the matrices were converted into binary graphs. Then the graphs of two groups were measured by topological parameters including the clustering coefficient and global efficiency. The results showed that the global efficiency of the network in full-band EEG was significantly smaller in AD group for the values of T = 0.06 and T = 0.07, but there was no statistically significant difference in the clustering coefficients between the two groups for the values of T (0.05-0.07). However, the clustering coefficient and global efficiency were significantly lower in AD patients at alpha-band for the same threshold range than those of subjects in the control group. It suggests that there may be decreases of the brain connectivity strength in AD patients at alpha-band of the resting-state EEG. This study provides a support for quantifying functional brain state of AD from the brain network perspective.
Subject(s)
Humans , Alzheimer Disease , Brain , Brain Mapping , Case-Control Studies , Cluster Analysis , Cognition Disorders , Electroencephalography , Probability , RestABSTRACT
It is the functional connectivity between motor cortex and muscle that directly relates to the rehabilitation of the dysfunction in upper limbs and neuromuscular activity status, which can be detected by electroencephalogram-electromyography (EEG-EMG) coherence analysis. In this study, based on coherence analysis method, we process the acquisition signals which consist of 9 channel EEG signal from motor cortex and 4 channel EMG signal from forearm, by using 4 groups of hand motions in the healthy subjects, including flexor digitorum, extensor digitorum, wrist flexion, and wrist extension. The results showed that in the β-band, the coherence coefficients between C3 and flexor digitorum (FD) was greater than extensor digitorum (ED) in the right hand flexor digitorum movement; the coherence coefficients between C3 and ED was greater than FD in the right hand extensor digitorum movement; the coherence coefficients between C3 and flexor carpi ulnaris (FCU) was greater than extensor carpi radialis (ECR) in the right hand wrist flexion movement; the coherence coefficients between C3 and ECR was greater than FCU in the right hand wrist extension movement. This analysis provides experimental basis to explore the information decoding of hand motion based on corticomuscular coherence (CMC).
Subject(s)
Humans , Electroencephalography , Electromyography , Healthy Volunteers , Motor Cortex , Physiology , Movement , Muscle, Skeletal , Physiology , Range of Motion, Articular , Wrist , Physiology , Wrist Joint , PhysiologyABSTRACT
This paper proposed a morphological component analysis (MCA) method, which is based on sparse representation, to detect the spike wave in electroencephalogram (EEG) signals. It takes the advantage of MCA being able to extract the background waves and the spike waves from the EEG signals, respectively,as the dictionaries and chooses the discrete cosine transform (DCT) and the daubechies order 4 wavelet (db4) transformation as the dictionaries of MCA to detect the spike waves from the epileptic EEG. The experiment results showed that the MCA could detect epileptic spike waves in EEG signals very effectively, and it yielded high selectivity of 89.01% and sensitivity of 90.71%. As a feature extraction/decomposition algorithm, MCA can be used to extract the spike waves from EEG signals.
Subject(s)
Humans , Algorithms , Electroencephalography , Methods , Epilepsy , Classification , Diagnosis , Principal Component Analysis , Methods , Signal Processing, Computer-Assisted , Wavelet AnalysisABSTRACT
ObjectiveMatching pursuit algorithm(MAP),for its good parametric characterization,was applied in epileptic electroencephalography(EEG) to study time-frequency distribution.MethodsSimulation experiment of time-frequency analysis was carried out to verify the matching pursuit algorithm s superiority on frequency resolution and parametric characterization.Fourier transform,Wigner-Ville distribution and matching pursuit algorithm were applied to the time-frequency analysis on normal EEG and epileptic EEG to study epileptic discharge in the time-frequency plane and the results were compared.ResultsSimulation results showed that the matching pursuit algorithm obtained a better time-frequency distribution.Distributions of epileptic EEG and normal EEG had significant difference in time-frequency plane.ConclusionTime-frequency analysis based on matching pursuit can better reveal the EEG characteristics.