Effect of electroconvulsive therapy on brain functional network in major depressive disorder / 生物医学工程学杂志

Electroconvulsive therapy (ECT) is an interventional technique capable of highly effective neuromodulation in major depressive disorder (MDD), but its antidepressant mechanism remains unclear. By recording the resting-state electroencephalogram (RS-EEG) of 19 MDD patients before and after ECT, we analyzed the modulation effect of ECT on the resting-state brain functional network of MDD patients from multiple perspectives: estimating spontaneous EEG activity power spectral density (PSD) using Welch algorithm; constructing brain functional network based on imaginary part coherence (iCoh) and calculate functional connectivity; using minimum spanning tree theory to explore the topological characteristics of brain functional network. The results show that PSD, functional connectivity, and topology in multiple frequency bands were significantly changed after ECT in MDD patients. The results of this study reveal that ECT changes the brain activity of MDD patients, which provides an important reference in the clinical treatment and mechanism analysis of MDD.

A research on epilepsy source localization from scalp electroencephalograph based on patient-specific head model and multi-dipole model / 生物医学工程学杂志

Accurate source localization of the epileptogenic zone (EZ) is the primary condition of surgical removal of EZ. The traditional localization results based on three-dimensional ball model or standard head model may cause errors. This study intended to localize the EZ by using the patient-specific head model and multi-dipole algorithms using spikes during sleep. Then the current density distribution on the cortex was computed and used to construct the phase transfer entropy functional connectivity network between different brain areas to obtain the localization of EZ. The experiment result showed that our improved methods could reach the accuracy of 89.27% and the number of implanted electrodes could be reduced by (19.34 ± 7.15)%. This work can not only improve the accuracy of EZ localization, but also reduce the additional injury and potential risk caused by preoperative examination and surgical operation, and provide a more intuitive and effective reference for neurosurgeons to make surgical plans.

Advances in methods and applications of electroencephalogram microstate analysis / 生物医学工程学杂志

Electroencephalogram (EEG) is characterized by high temporal resolution, and various EEG analysis methods have developed rapidly in recent years. The EEG microstate analysis method can be used to study the changes of the brain in the millisecond scale, and can also present the distribution of EEG signals in the topological level, thus reflecting the discontinuous and nonlinear characteristics of the whole brain. After more than 30 years of enrichment and improvement, EEG microstate analysis has penetrated into many research fields related to brain science. In this paper, the basic principles of EEG microstate analysis methods are summarized, and the changes of characteristic parameters of microstates, the relationship between microstates and brain functional networks as well as the main advances in the application of microstate feature extraction and classification in brain diseases and brain cognition are systematically described, hoping to provide some references for researchers in this field.

Research on electroencephalogram power spectral density of stroke patients under transcranial direct current stimulation / 生物医学工程学杂志

Transcranial direct current stimulation (tDCS) has become a new method of post-stroke rehabilitation treatment and is gradually accepted by people. However, the neurophysiological mechanism of tDCS in the treatment of stroke still needs further study. In this study, we recruited 30 stroke patients with damage to the left side of the brain and randomly divided them into a real tDCS group (15 cases) and a sham tDCS group (15 cases). The resting EEG signals of the two groups of subjects before and after stimulation were collected, then the difference of power spectral density was analyzed and compared in the band of delta, theta, alpha and beta, and the delta/alpha power ratio (DAR) was calculated. The results showed that after real tDCS, delta band energy decreased significantly in the left temporal lobes, and the difference was statistically significant ( P < 0.05); alpha band energy enhanced significantly in the occipital lobes, and the difference was statistically significant ( P < 0.05); the difference of theta and beta band energy was not statistically significant in the whole brain region ( P > 0.05). Furthermore, the difference of delta, theta, alpha and beta band energy was not statistically significant after sham tDCS ( P > 0.05). On the other hand, the DAR value of stroke patients decreased significantly after real tDCS, and the difference was statistically significant ( P < 0.05), and there was no significant difference in sham tDCS ( P > 0.05). This study reveals to a certain extent the neurophysiological mechanism of tDCS in the treatment of stroke.

Phase amplitude coupling analysis of local field potentials in working memory of rats affected by transcranial magneto-acoustic-electrical stimulation / 生物医学工程学杂志

Transcranial magneto-acoustic-electrical stimulation is a new non-invasive neuromodulation technology, in which the induced electric field generated by the coupling effect of ultrasound and static magnetic field are used to regulate the neural rhythm oscillation activity in the corresponding brain region. The purpose of this paper is to investigate the effects of transcranial magneto-acoustic-electrical stimulation on the information transfer and communication in neuronal clusters during memory. In the experiment, twenty healthy adult Wistar rats were randomly divided into a control group (five rats) and stimulation groups (fifteen rats). Transcranial magneto-acoustic-electrical stimulation of 0.05~0.15 T and 2.66~13.33 W/cm 2 was applied to the rats in stimulation groups, and no stimulation was applied to the rats in the control group. The local field potentials signals in the prefrontal cortex of rats during the T-maze working memory tasks were acquired. Then the coupling differences between delta rhythm phase, theta rhythm phase and gamma rhythm amplitude of rats in different parameter stimulation groups and control group were compared. The experimental results showed that the coupling intensity of delta and gamma rhythm in stimulation groups was significantly lower than that in the control group ( P<0.05), while the coupling intensity of theta and gamma rhythm was significantly higher than that in the control group ( P<0.05). With the increase of stimulation parameters, the degree of coupling between delta and gamma rhythm showed a decreasing trend, while the degree of coupling between theta and gamma rhythm tended to increase. The preliminary results of this paper indicated that transcranial magneto-acoustic-electrical stimulation inhibited delta rhythmic neuronal activity and enhanced the oscillation of theta and gamma rhythm in the prefrontal cortex, thus promoted the exchange and transmission of information between neuronal clusters in different spatial scales. This lays the foundation for further exploring the mechanism of transcranial magneto-acoustic-electrical stimulation in regulating brain memory function.

Effects of transcranial magneto-acoustic electrical stimulation on calcium signals in prefrontal nerve clusters / 生物医学工程学杂志

Transcranial magneto-acoustic electrical stimulation (TMAES) is a novel method of brain nerve regulation and research, which uses induction current generated by the coupling of ultrasound and magnetic field to regulate neural electrical activity in different brain regions. As the second special envoy of nerve signal, calcium plays a key role in nerve signal transmission. In order to investigate the effect of TMAES on prefrontal cortex electrical activity, 15 mice were divided into control group, ultrasound stimulation (TUS) group and TMAES group. The TMAES group received 2.6 W/cm 2 and 0.3 T of magnetic induction intensity, the TUS group received only ultrasound stimulation, and the control group received no ultrasound and magnetic field for one week. The calcium ion concentration in the prefrontal cortex of mice was recorded in real time by optical fiber photometric detection technology. The new object recognition experiment was conducted to compare the behavioral differences and the time-frequency distribution of calcium signal in each group. The results showed that the mean value of calcium transient signal in the TMAES group was (4.84 ± 0.11)% within 10 s after the stimulation, which was higher than that in the TUS group (4.40 ± 0.10)% and the control group (4.22 ± 0.08)%, and the waveform of calcium transient signal was slower, suggesting that calcium metabolism was faster. The main energy band of the TMAES group was 0-20 Hz, that of the TUS group was 0-12 Hz and that of the control group was 0-8 Hz. The cognitive index was 0.71 in the TMAES group, 0.63 in the TUS group, and 0.58 in the control group, indicating that both ultrasonic and magneto-acoustic stimulation could improve the cognitive ability of mice, but the effect of the TMAES group was better than that of the TUS group. These results suggest that TMAES can change the calcium homeostasis of prefrontal cortex nerve clusters, regulate the discharge activity of prefrontal nerve clusters, and promote cognitive function. The results of this study provide data support and reference for further exploration of the deep neural mechanism of TMAES.

Research progress on the effect of transcranial magnetic stimulation on learning, memory and plasticity of brain synaptic / 生物医学工程学杂志

Transcranial magnetic stimulation (TMS) as a noninvasive neuromodulation technique can improve the impairment of learning and memory caused by diseases, and the regulation of learning and memory depends on synaptic plasticity. TMS can affect plasticity of brain synaptic. This paper reviews the effects of TMS on synaptic plasticity from two aspects of structural and functional plasticity, and further reveals the mechanism of TMS from synaptic vesicles, neurotransmitters, synaptic associated proteins, brain derived neurotrophic factor and related pathways. Finally, it is found that TMS could affect neuronal morphology, glutamate receptor and neurotransmitter, and regulate the expression of synaptic associated proteins through the expression of brain derived neurotrophic factor, thus affecting the learning and memory function. This paper reviews the effects of TMS on learning, memory and plasticity of brain synaptic, which provides a reference for the study of the mechanism of TMS.

Effects of parameters selection with transcranial direct current stimulation based on real head model / 生物医学工程学杂志

Transcranial direct current stimulation (tDCS) is a brain stimulation intervention technique, which has the problem of different criteria for the selection of stimulation parameters. In this study, a four-layer real head model was constructed. Based on this model, the changes of the electric field distribution in the brain with the current intensity, electrode shape, electrode area and electrode spacing were analyzed by using finite element simulation technology, and then the optimal scheme of electrical stimulation parameters was discussed. The results showed that the effective stimulation region decreased and the focusing ability increased with the increase of current intensity. The normal current density of the quadrilateral electrode was obviously larger than that of the circular electrode, which indicated that the quadrilateral electrode was more conducive to current stimulation of neurons. Moreover, the effective stimulation region of the quadrilateral electrode was more concentrated and the focusing ability was stronger. The focusing ability decreased with the increase of electrode area. Specifically, the focusing tended to increase first and then decrease with the increase of electrode spacing and the optimal electrode spacing was 64.0-67.2 mm. These results could provide some basis for the selection of electrical stimulation parameters.

Research on characteristics of brain functional network in stroke patients during convalescent period under transcranial direct current stimulation / 生物医学工程学杂志

Transcranial direct current stimulation (tDCS) is an emerging non-invasive brain stimulation technique. However, the rehabilitation effect of tDCS on stroke disease is unclear. In this paper, based on electroencephalogram (EEG) and complex network analysis methods, the effect of tDCS on brain function network of stroke patients during rehabilitation was investigated. The resting state EEG signals of 31 stroke rehabilitation patients were collected and divided into stimulation group (16 cases) and control group (15 cases). The Pearson correlation coefficients were calculated between the channels, brain functional network of two groups were constructed before and after stimulation, and five characteristic parameters were analyzed and compared such as node degree, clustering coefficient, characteristic path length, global efficiency, and small world attribute. The results showed that node degree, clustering coefficient, global efficiency, and small world attributes of brain functional network in the tDCS group were significantly increased, characteristic path length was significantly reduced, and the difference was statistically significant (

Cross-subject electroencephalogram emotion recognition based on maximum classifier discrepancy / 生物医学工程学杂志

Affective brain-computer interfaces (aBCIs) has important application value in the field of human-computer interaction. Electroencephalogram (EEG) has been widely concerned in the field of emotion recognition due to its advantages in time resolution, reliability and accuracy. However, the non-stationary characteristics and individual differences of EEG limit the generalization of emotion recognition model in different time and different subjects. In this paper, in order to realize the recognition of emotional states across different subjects and sessions, we proposed a new domain adaptation method, the maximum classifier difference for domain adversarial neural networks (MCD_DA). By establishing a neural network emotion recognition model, the shallow feature extractor was used to resist the domain classifier and the emotion classifier, respectively, so that the feature extractor could produce domain invariant expression, and train the decision boundary of classifier learning task specificity while realizing approximate joint distribution adaptation. The experimental results showed that the average classification accuracy of this method was 88.33% compared with 58.23% of the traditional general classifier. It improves the generalization ability of emotion brain-computer interface in practical application, and provides a new method for aBCIs to be used in practice.

A review of brain-like spiking neural network and its neuromorphic chip research / 生物医学工程学杂志

Under the current situation of the rapid development of brain-like artificial intelligence and the increasingly complex electromagnetic environment, the most bionic and anti-interference spiking neural network has shown great potential in computing speed, real-time information processing, and spatiotemporal data processing. Spiking neural network is the core part of brain-like artificial intelligence, which realizes brain-like computing by simulating the structure of biological neural network and the way of information transmission. This article first summarizes the advantages and disadvantages of the five models, and analyzes the characteristics of several network topologies. Then, it summarizes the spiking neural network algorithms. The unsupervised learning based on spike timing dependent plasticity (STDP) rules and four types of supervised learning algorithms are analyzed. Finally, the research on brain-like neuromorphic chips at home and abroad are reviewed. This paper aims to provide learning ideas and research directions for new colleagues in the field of spiking neural network.

Effects of magnetic stimulation at different frequencies on neuronal excitability and voltage-gated potassium channels / 生物医学工程学杂志

As a noninvasive neuromodulation technique, transcranial magnetic stimulation (TMS) is widely used in the clinical treatment of neurological and psychiatric diseases, but the mechanism of its action is still unclear. The purpose of this paper is to investigate the effects of different frequencies of magnetic stimulation (MS) on neuronal excitability and voltage-gated potassium channels in the

Research on the application of convolution neural network in the diagnosis of Alzheimer's disease / 生物医学工程学杂志

With the wide application of deep learning technology in disease diagnosis, especially the outstanding performance of convolutional neural network (CNN) in computer vision and image processing, more and more studies have proposed to use this algorithm to achieve the classification of Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal cognition (CN). This article systematically reviews the application progress of several classic convolutional neural network models in brain image analysis and diagnosis at different stages of Alzheimer's disease, and discusses the existing problems and gives the possible development directions in order to provide some references.

Effects of virtual reality visual experience on brain functional network / 生物医学工程学杂志

With the wide application of virtual reality technology and the rapid popularization of virtual reality devices, the problem of brain fatigue caused by prolonged use has attracted wide attention. Sixteen healthy subjects were selected in this study. And electroencephalogram (EEG) signals were acquired synchronously while the subjects watch videos in similar types presented by traditional displayer and virtual reality separately. Two questionnaires were conducted by all subjects to evaluate the state of fatigue before and after the experiment. The mutual correlation method was selected to construct the mutual correlation brain network of EEG signals before and after watching videos in two modes. We also calculated the mutual correlation coefficient matrix and the mutual correlation binary matrix and compared the average of degree, clustering coefficient, path length, global efficiency and small world attribute during two experiments. The results showed that the subjects were easier to get fatigue by watching virtual reality video than watching video presented by traditional displayer in a certain period of time. By comparing the characteristic parameters of brain network before and after watching videos, it was found that the average degree value, the average clustering coefficient, the average global efficiency and the small world attribute decreases while the average path length value increased significantly. In addition, compared to traditional plane video, the characteristic parameters of brain network changed more greatly after watching the virtual reality video with a significant difference ( < 0.05). This study can provide theoretical basis and experimental reference for analyzing and evaluating brain fatigue induced by virtual reality visual experience.

Repetitive transcranial magnetic stimulation significantly improves cognitive impairment and neuronal excitability during aging in mice / 生物医学工程学杂志

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain stimulation technique that has been paid attention to with increasing interests as a therapeutic neural rehabilitative tool. Studies confirmed that high-frequency rTMS could improve the cognitive performance in behavioral test as well as the excitability of the neuron in animals. This study aimes to investigate the effects of rTMS on the cognition and neuronal excitability of Kunming mice during the natural aging. Twelve young mice, 12 adult mice, and 12 aged mice were used, and each age group were randomly divided into rTMS group and control group. rTMS-treated groups were subjected to high-frequency rTMS treatment for 15 days, and control groups were treated with sham stimulation for 15 days. Then, novel object recognition and step-down tests were performed to examine cognition of learning and memory. Whole-cell patch clamp technique was used to record and analyze resting membrane potential, action potential (AP), and related electrical properties of AP of hippocampal dentate gyrus (DG) granule neurons. Data analysis showed that cognition of mice and neuronal excitability of DG granule neurons were degenerated significantly as the age increased. Cognitive damage and degeneration of some electrical properties were alleviated under the condition of high-frequency rTMS. It may be one of the mechanisms of rTMS to alleviate cognitive damage and improve cognitive ability by changing the electrophysiological properties of DG granule neurons and increasing neuronal excitability.

Research progress on multiscale entropy algorithm and its application in neural signal analysis / 生物医学工程学杂志

Changes in the intrinsic characteristics of brain neural activities can reflect the normality of brain functions. Therefore, reliable and effective signal feature analysis methods play an important role in brain dysfunction and relative diseases early stage diagnosis. Recently, studies have shown that neural signals have nonlinear and multi-scale characteristics. Based on this, researchers have developed the multi-scale entropy (MSE) algorithm, which is considered more effective when analyzing multi-scale nonlinear signals, and is generally used in neuroinformatics. The principles and characteristics of MSE and several improved algorithms base on disadvantages of MSE were introduced in the article. Then, the applications of the MSE algorithm in disease diagnosis, brain function analysis and brain-computer interface were introduced. Finally, the challenges of these algorithms in neural signal analysis will face to and the possible further investigation interests were discussed.

Analysis of time-frequency characteristics and coherence of local field potentials during working memory task of rats after high-frequency repeated transcranial magnetic stimulation / 生物医学工程学杂志

Repetitive transcranial magnetic stimulation(rTMS) is a painless and non-invasive method for stimulation and modulation in the field of cognitive neuroscience research and clinical neurological regulation. In this paper, adult Wistar rats were divided into the rTMS group and control group randomly. Rats in the rTMS group were stimulated with 5 Hz rTMS for 14 days, while the rats in the control group did not accept any stimulation. Then, the behavior and local field potentials (LFPs) were recorded synchronously when the rats perform a working memory (WM) task with T-maze. Finally, the time-frequency distribution and coherence characteristics of the LFPs signal in the prefrontal cortex (PFC) during working memory task were analyzed. The results showed that the rats in the rTMS group needed less training days to reach the task correction criterion than the control group (

A TrAdaBoost-based method for detecting multiple subjects' P300 potentials / 生物医学工程学杂志

Individual differences of P300 potentials lead to that a large amount of training data must be collected to construct pattern recognition models in P300-based brain-computer interface system, which may cause subjects' fatigue and degrade the system performance. TrAdaBoost is a method that transfers the knowledge from source area to target area, which improves learning effect in the target area. Our research purposed a TrAdaBoost-based linear discriminant analysis and a TrAdaBoost-based support vector machine to recognize the P300 potentials across multiple subjects. This method first trains two kinds of classifiers separately by using the data deriving from a small amount of data from same subject and a large amount of data from different subjects. Then it combines all the classifiers with different weights. Compared with traditional training methods that use only a small amount of data from same subject or mixed different subjects' data to directly train, our algorithm improved the accuracies by 19.56% and 22.25% respectively, and improved the information transfer rate of 14.69 bits/min and 15.76 bits/min respectively. The results indicate that the TrAdaBoost-based method has the potential to enhance the generalization ability of brain-computer interface on the individual differences.

Long term power frequency electromagnetic fields exposure influences the causal network connection pattern of local field potentials during working memory / 生物医学工程学杂志

The possible influence of electromagnetic field (EMF) on the function of neural systems has been widely concerned. In this article, we intend to investigate the effects of long term power frequency EMF exposure on brain cognitive functions and it's mechanism. The Sprague-Dawley (SD) rats were randomly divided into 3 groups: the rats in EMF Ⅰ group were placed in the 2 mT power frequency EMF for 24 days. The rats in EMF Ⅱ group were placed in the 2 mT power frequency EMF for 48 days. The rats in control group were not exposed to the EMF. Then, the 16 channel local field potentials (LFPs) were recorded from rats' prefrontal cortex (PFC) in each group during the working memory (WM) tasks. The causal networks of LFPs were also established by applying the directed transfer function (DTF). Based on that, the differences of behavior and the LFPs network connection patterns between different groups were compared in order to investigate the influence of long term power frequency EMF exposure on working memory. The results showed the rats in the EMF Ⅱ group needed more training to reach the task correction criterion (over 80%). Moreover, the causal network connection strength and the global efficiency of the rats in EMF Ⅰ and EMF Ⅱ groups were significantly lower than the corresponding values of the control group. Meanwhile, significant differences of causal density values were found between EMF Ⅱ group and the other two groups. These results indicate that long term exposure to 2 mT power frequency EMF will reduce the connection strength and the information transfer efficiency of the LFPs causal network in the PFC, as well as the behavior performance of the rats. These results may explain the effect of EMF exposure on working memory from the view of neural network connectivity and provide a support for further studies on the mechanism of the effect of EMF on cognition.

Research on classification of brain functional network features during mental fatigue / 生物医学工程学杂志

This study is aimed to investigate objective indicators of mental fatigue evaluation to improve the accuracy of mental fatigue evaluation. Mental fatigue was induced by a sustained cognitive task. The brain functional networks in two states (normal state and mental fatigue state) were constructed based on electroencephalogram (EEG) data. This study used complex network theory to calculate and analyze nodal characteristics parameters (degree, betweenness centrality, clustering coefficient and average path length of node), and served them as the classification features of support vector machine (SVM). Parameters of the SVM model were optimized by gird search based on 6-fold cross validation. Then, the subjects were classified. The results show that characteristic parameters of node of brain function networks can be divided into normal state and mental fatigue state, which can be used in the objective evaluation of mental fatigue state.