This paper proposes a motor imagery recognition algorithm based on feature fusion and transfer adaptive boosting (TrAdaboost) to address the issue of low accuracy in motor imagery (MI) recognition across subjects, thereby increasing the reliability of MI-based brain-computer interfaces (BCI) for cross-individual use. Using the autoregressive model, power spectral density and discrete wavelet transform, time-frequency domain features of MI can be obtained, while the filter bank common spatial pattern is used to extract spatial domain features, and multi-scale dispersion entropy is employed to extract nonlinear features. The IV-2a dataset from the 4 ^th International BCI Competition was used for the binary classification task, with the pattern recognition model constructed by combining the improved TrAdaboost integrated learning algorithm with support vector machine (SVM), k nearest neighbor (KNN), and mind evolutionary algorithm-based back propagation (MEA-BP) neural network. The results show that the SVM-based TrAdaboost integrated learning algorithm has the best performance when 30% of the target domain instance data is migrated, with an average classification accuracy of 86.17%, a Kappa value of 0.723 3, and an AUC value of 0.849 8. These results suggest that the algorithm can be used to recognize MI signals across individuals, providing a new way to improve the generalization capability of BCI recognition models.
Brain-Computer Interfaces ; Humans ; Support Vector Machine ; Algorithms ; Neural Networks, Computer ; Imagination/physiology* ; Pattern Recognition, Automated/methods* ; Electroencephalography ; Wavelet Analysis

Alzheimer's disease (AD) is the most common degenerative disease of the nervous system. Studies have found that the 40 Hz pulsed magnetic field has the effect of improving cognitive ability in AD, but the mechanism of action is not clear. In this study, APP/PS1 double transgenic AD model mice were used as the research object, the water maze was used to group dementia, and 40 Hz/10 mT pulsed magnetic field stimulation was applied to AD model mice with different degrees of dementia. The behavioral indicators, mitochondrial samples of hippocampal CA1 region and electrocardiogram signals were collected from each group, and the effects of 40 Hz pulsed magnetic field on mouse behavior, mitochondrial kinetic indexes and heart rate variability (HRV) parameters were analyzed. The results showed that compared with the AD group, the loss of mitochondrial crest structure was alleviated and the mitochondrial dynamics related indexes were significantly improved in the AD + stimulated group ( P < 0.001), sympathetic nerve excitation and parasympathetic nerve inhibition were improved, and the spatial cognitive memory ability of mice was significantly improved ( P < 0.05). The preliminary results of this study show that 40 Hz pulsed magnetic field stimulation can improve the mitochondrial structure and mitochondrial kinetic homeostasis imbalance of AD mice, and significantly improve the autonomic neuromodulation ability and spatial cognition ability of AD mice, which lays a foundation for further exploring the mechanism of ultra-low frequency magnetic field in delaying the course of AD disease and realizing personalized neurofeedback therapy for AD.
Animals ; Heart Rate/physiology* ; Mice ; Alzheimer Disease/therapy* ; Mice, Transgenic ; Mitochondrial Dynamics/radiation effects* ; Magnetic Field Therapy/methods* ; Magnetic Fields ; Disease Models, Animal ; Mitochondria ; Male ; Maze Learning ; Cognition ; Dementia/therapy*

In recent years, the ongoing development of transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS) has demonstrated significant potential in the treatment and rehabilitation of various brain diseases. In particular, the combined application of TES and TMS has shown considerable clinical value due to their potential synergistic effects. This paper first systematically reviews the mechanisms underlying TES and TMS, highlighting their respective advantages and limitations. Subsequently, the potential mechanisms of transcranial electromagnetic combined stimulation are explored, with a particular focus on three combined stimulation protocols: Repetitive TMS (rTMS) with transcranial direct current stimulation (tDCS), rTMS with transcranial alternating current stimulation (tACS), and theta burst TMS (TBS) with tACS, as well as their clinical applications in brain diseases. Finally, the paper analyzes the key challenges in transcranial electromagnetic combined stimulation research and outlines its future development directions. The aim of this paper is to provide a reference for the optimization and application of transcranial electromagnetic combined stimulation schemes in the treatment and rehabilitation of brain diseases.
Humans ; Transcranial Magnetic Stimulation/methods* ; Transcranial Direct Current Stimulation/methods* ; Brain Diseases/therapy*

A brain-computer interface (BCI) based on motor imagery (MI) provides additional control pathways by decoding the intentions of the brain. MI ability has great intra-individual variability, and the majority of MI-BCI systems are unable to adapt to this variability, leading to poor training effects. Therefore, prediction of MI ability is needed. In this study, we propose an MI ability predictor based on multi-frequency EEG features. To validate the performance of the predictor, a video-guided paradigm and a traditional MI paradigm are designed, and the predictor is applied to both paradigms. The results demonstrate that all subjects achieved > 85% prediction precision in both applications, with a maximum of 96%. This study indicates that the predictor can accurately predict the individuals' MI ability in different states, provide the scientific basis for personalized training, and enhance the effect of MI-BCI training.
Humans ; Imagination/physiology* ; Electroencephalography/methods* ; Brain-Computer Interfaces ; Male ; Female ; Adult ; Young Adult ; Brain/physiology* ; Movement/physiology* ; Motor Activity/physiology* ; Psychomotor Performance/physiology*

BACKGROUND:Transcranial magneto-acoustical electrical stimulation(TMAES)is a non-invasive,high-precision neurofocused stimulation method based on magneto-acoustic coupling electrical effect,which can regulate the rhythmic oscillation of nerve activity,thereby affecting the brain's movement,cognition and other functions. OBJECTIVE:To explore the effect of TMAES on beta oscillations in the neural circuits of healthy rats and Parkinson's rats. METHODS:(1)Animal experiments:Twenty-four Wistar rats were randomly divided into four groups(n=6 per group).The rats in the normal control group received no intervention,while those in the normal stimulation group received TMAES(the average spatial peak pulse intensity:13.33 W/cm2,fundamental frequency:0.4 MHz,the number of fundamental wave cycles:1000,and pulse frequency:200 Hz).The model control group and model stimulation group were established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine.After successful modeling,the rats in the model control group received sham TMAES stimulation in the prefrontal cortex,and those in the model stimulation group received TMAES in the prefrontal cortex,and the duration of stimulation was 2.0 minutes per day.After an interval of 8-10 minutes,the local field potential signals of rats were collected during the execution of T-maze test and the correct rate of behavior was recorded at the same time to compare and analyze the time-frequency distribution of local field potential signals and behavioral differences among the groups.The stimulation experiment and T-maze test were stopped when the correct rate of rats was higher than 80%for 3 consecutive days.(2)Modeling and simulation experiments:The cortical-basal ganglion circuit model under TMAES was established,and the ultrasonic emission period(5,10,20 ms),ultrasonic emission duty cycle(30%,50%,90%)and induced current density(20,50,100 μA/cm2)were changed respectively to compare the power spectral density values of beta oscillations in healthy rats and Parkinson's rats under different stimulation parameters. RESULTS AND CONCLUSION:(1)Animal experiments:The spatial learning ability of the rats in the normal control group was stronger than that of the model control group(P＜0.001),the spatial learning ability of the rats in the normal stimulation group was stronger than that of the normal control group(P＜0.05),and the spatial learning ability of the rats in the model stimulation group was stronger than that of the model control group(P＜0.01).The distribution of beta oscillation energy in the normal control group was more concentrated,and the beta oscillation signal energy was reduced in the normal stimulation group compared with the normal control group.The beta oscillation energy was widely distributed and the energy value was significantly higher in the model control group and the model stimulation group than the normal control and normal stimulation groups.Moreover,the beta oscillation signal energy in the model stimulation group was significantly lower than that in the model control group.(2)Modeling and simulation experiments:the peak power spectral density of the beta band of healthy rats without stimulation(30 dB)was significantly lower than that of Parkinson's rats(55 dB).The power spectral density value generally decreased after stimulation.The peak power spectral density in the beta band was positively correlated with the ultrasonic emission period and negatively correlated with the induced current density.In addition,the peak power spectral density value was the lowest when the duty cycle of ultrasonic emission was 50%.These findings indicate that TMAES suppresses beta oscillations in healthy and Parkinson's disease rats,thereby improving motor function and decision-making cognitive function in rats.

Objective:To study the infection and epidemiological characteristics of soil borne nematode disease in Sihong County, Suqian City, and to provide scientific basis for further development of prevention and control measures.Methods:In 2022, according to geographic location, Sihong County was divided into east and west areas. Jieji Town, Shiji Township, and Linhuai Town were selected from the east area, and Tianganghu Township, Meihua Town from the west area. One administrative village was selected as a survey point in each township. Using cluster sampling method, 450 permanent residents aged 3 years old and older in the village were selected as the respondents for questionnaire survey and fecal sample collection. The infection status of hookworms, roundworms, whipworms and pinworms in fecal samples were examined, transparent tape anal swab method for detecting pinworm eggs in children, and influencing factors were analyzed.Results:A total of 2 264 survey subjects were included, 18 cases of soil borne nematodes were detected as positive, with an overall positive rate of 0.80%. Among them, 15 cases were positive for hookworms, 1 case was positive for whipworms, and 2 cases were positive for pinworms, with detection rates of 0.66%, 0.04%, and 0.09%, respectively. No ascaris lumbricoides were detected. Transparent tape anal swab method was used to examine 142 children, and the positivity rate of 1.41% (2/142). By township, the detection rate of soil borne nematodes was the highest in Jieji Town, at 2.41% (11/457); the others were Meihua Town, Tianganghu Township, Shiji Township, and Linhuai Town, with detection rates of 0.89% (4/451),0.66% (3/454), 0 (0/451) and 0 (0/451), respectively. There was a statistically significant difference between different townships (χ 2 = 19.21, P < 0.001). Among the 18 positive cases of soil borne nematode, 7 were males and 11 were females, with detection rates of 0.66% (7/1 063) and 0.92% (11/1 201), respectively, the difference was not statistically significant (χ 2 = 0.47, P = 0.491). The age distribution showed the highest detection rate in the 40 - < 60 age group, at 1.42% (9/634), with statistically significant differences between different age groups (χ 2 = 6.41, P = 0.033). The occupational distribution showed the highest detection rate in farmers, at 1.46% (9/617), with statistically significant differences between different professions (χ 2 = 8.00, P = 0.034). The differences in total soil borne nematode and hookworm detection rates were statistically significant among different methods of treating human and animal feces (χ 2 = 11.01, 9.02, P = 0.003, 0.011). Conclusions:The main species of soil borne nematode infections in Sihong County, Suqian City are hookworms, with fewer infections of whipworms and pinworms, and no roundworm infections observed. There are regional differences in detection rate. In the future, it is necessary to strengthen health education for key populations, enhance health knowledge publicity, and effectively intervene to change unhealthy production and lifestyle, further reducing the infection of soil borne nematodes in Suqian City.

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.
Humans ; Scalp ; Brain Mapping/methods* ; Epilepsy/diagnosis* ; Electroencephalography/methods* ; Brain

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.
Humans ; Depressive Disorder, Major/therapy* ; Electroconvulsive Therapy ; Brain ; Algorithms ; Electroencephalography

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.
Electroencephalography ; Brain ; Cognition

Electromagnetic stimulation is an important neuromodulation technique that modulates the electrical activity of neurons and affects cortical excitability for the purpose of modulating the nervous system. The phenomenon of inverse stochastic resonance is a response mechanism of the biological nervous system to external signals and plays an important role in the signal processing of the nervous system. In this paper, a small-world neural network with electrical synaptic connections was constructed, and the inverse stochastic resonance of the small-world neural network under electromagnetic stimulation was investigated by analyzing the dynamics of the neural network. The results showed that: the Levy channel noise under electromagnetic stimulation could cause the occurrence of inverse stochastic resonance in small-world neural networks; the characteristic index and location parameter of the noise had significant effects on the intensity and duration of the inverse stochastic resonance in neural networks; the larger the probability of randomly adding edges and the number of nearest neighbor nodes in small-world networks, the more favorable the anti-stochastic resonance was; by adjusting the electromagnetic stimulation parameters, a dual regulation of the inverse stochastic resonance of the neural network can be achieved. The results of this study provide some theoretical support for exploring the regulation mechanism of electromagnetic nerve stimulation technology and the signal processing mechanism of nervous system.
Action Potentials/physiology* ; Computer Simulation ; Models, Neurological ; Stochastic Processes ; Neurons/physiology* ; Electromagnetic Phenomena