BACKGROUND Mild cognitive impairment(MCI)is a high-risk precursor to Alzheimer’s disease characterized by declining memory or other progressive cognitive functions without compromising daily living abilities.AIM To i...BACKGROUND Mild cognitive impairment(MCI)is a high-risk precursor to Alzheimer’s disease characterized by declining memory or other progressive cognitive functions without compromising daily living abilities.AIM To investigate the efficacy of repetitive transcranial magnetic stimulation(rTMS)in patients with MCI.METHODS This retrospective analysis involved 180 patients with MCI who were admitted to The First Hospital of Shanxi Medical University from January 2021 to June 2023.Participants were allocated into the research(n=98,receiving rTMS)and control groups(n=82,receiving sham stimulation).Memory tests,cognitive function assessments,event-related potential–P300 tests,and electroencephalogram(EEG)examinations were conducted pre-treatment and post-treatment.Further,memory quotient(MQ),cognitive function scores,and EEG grading results were compared,along with adverse reaction incidences.RESULTS Pre-treatment MQ scores,long-term and short-term memory,as well as immediate memory scores,demonstrated no notable differences between the groups.Post-treatment,the research group exhibited significant increases in MQ scores,long-term memory,and short-term memory compared to baseline(P<0.05),with these improvements being statistically superior to those in the control group.However,immediate memory scores exhibited no significant change(P>0.05).Further,the research group demonstrated statistically better post-treatment scores on the Revised Wechsler Memory Scale than the control group.Furthermore,post-treatment P300 latency and amplitude improved significantly in the research group,surpassing the control group.EEG grading in the research group improved,and the incidence of adverse reactions was significantly lower than in the control group.CONCLUSION Patients with MCI receiving rTMS therapy demonstrated improved memory and cognitive functions and EEG grading and exhibited high safety with fewer adverse reactions.展开更多
Physiological signals such as electroencephalogram(EEG)signals are often corrupted by artifacts during the acquisition and processing.Some of these artifacts may deteriorate the essential properties of the signal that...Physiological signals such as electroencephalogram(EEG)signals are often corrupted by artifacts during the acquisition and processing.Some of these artifacts may deteriorate the essential properties of the signal that pertains to meaningful information.Most of these artifacts occur due to the involuntary movements or actions the human does during the acquisition process.So,it is recommended to eliminate these artifacts with signal processing approaches.This paper presents two mechanisms of classification and elimination of artifacts.In the first step,a customized deep network is employed to classify clean EEG signals and artifact-included signals.The classification is performed at the feature level,where common space pattern features are extracted with convolutional layers,and these features are later classified with a support vector machine classifier.In the second stage of the work,the artifact signals are decomposed with empirical mode decomposition,and they are then eliminated with the proposed adaptive thresholding mechanism where the threshold value changes for every intrinsic mode decomposition in the iterative mechanism.展开更多
BACKGROUND Post-stroke epilepsy is a common and easily overlooked complication of acute cerebrovascular disease.Long-term seizures can seriously affect the prognosis and quality of life of patients.Electroencephalogra...BACKGROUND Post-stroke epilepsy is a common and easily overlooked complication of acute cerebrovascular disease.Long-term seizures can seriously affect the prognosis and quality of life of patients.Electroencephalogram(EEG)is the simplest way to diagnose epilepsy,and plays an important role in predicting seizures and guiding medication.AIM To explore the EEG characteristics of patients with post-stroke epilepsy and improve the detection rate of inter-seizure epileptiform discharges.METHODS From January 2017 to June 2020,10 patients with post-stroke epilepsy in our hospital were included.The clinical,imaging,and EEG characteristics were collected.The stroke location,seizure type,and ictal and interictal EEG manifestations of the patients with post-stroke epilepsy were then retrospectively analyzed.RESULTS In all 10 patients,epileptiform waves occurred in the side opposite to the stroke lesion during the interictal stage;these manifested as sharp wave,sharp-wave complex,or spike discharges in the anterior head lead of the side opposite to the lesion.CONCLUSION In EEG,epileptiform waves can occur in the side opposite to the stroke lesion in patients with post-stroke epilepsy.展开更多
Early and timely diagnosis of stroke is critical for effective treatment,and the electroencephalogram(EEG)offers a low-cost,non-invasive solution.However,the shortage of high-quality patient EEG data often hampers the...Early and timely diagnosis of stroke is critical for effective treatment,and the electroencephalogram(EEG)offers a low-cost,non-invasive solution.However,the shortage of high-quality patient EEG data often hampers the accuracy of diagnostic classification methods based on deep learning.To address this issue,our study designed a deep data amplification model named Progressive Conditional Generative Adversarial Network with Efficient Approximating Self Attention(PCGAN-EASA),which incrementally improves the quality of generated EEG features.This network can yield full-scale,fine-grained EEG features from the low-scale,coarse ones.Specially,to overcome the limitations of traditional generative models that fail to generate features tailored to individual patient characteristics,we developed an encoder with an effective approximating self-attention mechanism.This encoder not only automatically extracts relevant features across different patients but also reduces the computational resource consumption.Furthermore,the adversarial loss and reconstruction loss functions were redesigned to better align with the training characteristics of the network and the spatial correlations among electrodes.Extensive experimental results demonstrate that PCGAN-EASA provides the highest generation quality and the lowest computational resource usage compared to several existing approaches.Additionally,it significantly improves the accuracy of subsequent stroke classification tasks.展开更多
BACKGROUND： Low-frequency repetitive transcranial magnetic stimulation （rTMS） has been shown to significantly reduce epileptiform discharges and control clinical seizures in intractable epilepsy patients. The locat...BACKGROUND： Low-frequency repetitive transcranial magnetic stimulation （rTMS） has been shown to significantly reduce epileptiform discharges and control clinical seizures in intractable epilepsy patients. The location of epileptic foci and magnetic stimulation sites remain uncertain. The effects of rTMS on electroencephalogram and seizure remain unclear in epileptic patients following dipole source localization. OBJECTIVE： To investigate the effects of low-frequency rTMS on electroencephalogram and seizure in temporal lobe epilepsy patients after dipole source localization. DESIGN, TIME AND SETTING： The randomized, controlled study was performed at the outpatient clinic Department of Neurology, Hospital Affiliated to North Sichuan Medical College from December 2003 to February 2007. PARTICIPANTS： A total of 30 temporal lobe epilepsy patients, comprising 19 males and 11 females, aged 1749 years, presented with epileptiform discharges and were enrolled for this study. Disease course ranged between 1-6 years, with 1-5 seizures per month. Imaging examinations revealed 11 patients with structural changes in the brain. The patients were randomly and equally assigned into drug treatment and transcranial magnetic stimulation （TMS） groups. METHODS： Patients in the drug treatment group were orally treated with carbamazepine. Patients in the TMS group received oral carbamazepine treatment of and TMS. A Maglite-r25 magnetic stimulator （Dantec Dynamics, Denmark） was used to stimulate epileptic foci in the temporal lobe following electroencephalogram dipole localization （1 Hz, 90% threshold intensity, at a stimulation frequency of 500 times, once a day, for 7 days）. MAIN OUTCOME MEASURES： At 30 days after TMS, seizure frequency and rate of epileptiform discharges were observed in patients from both groups. Therapeutic safety was investigated during treatment. RESULTS： Within 30 days of treatment, there were no significant differences in seizure frequency between the TMS group （1.5 ± 0.3） seizures and the drug treatment group [（1.9± 0.4） seizures] （P 〉 0.05）. The rate of epileptiform discharges [27% （4/15）] was significantly less in the TMS group than in the drug treatment group [73% （11/15）] （P 〈 0.05）. During TMS, five patients suffered from transient mild headache, but were completely relieved within 2 hours. CONCLUSION： Low-frequency rTMS exhibited inhibitory effects on epileptiform discharges over a short period of time, and decreased seizure frequency to some degree. Results from the present study suggested that low-frequency rTMS is safe.展开更多
BACKGROUND： It has proved that dynamic electroencephalogram （EEG） is definite in judging the outcome of ischemic hypoxic comatose patients, EEG is more sensitive to the cortical affection, but not sensitive to the ...BACKGROUND： It has proved that dynamic electroencephalogram （EEG） is definite in judging the outcome of ischemic hypoxic comatose patients, EEG is more sensitive to the cortical affection, but not sensitive to the subcortical and brainstem affections, thus it is necessary to clarify the indications of this technique in the clinical application.OBJECTIVE： To observe and compare the prognostic value of dynamic EEG and Glasgow coma score in comatose patients with different diseased region.DESIGN： A clinical case-controlled observation.SETTING： Union Hospital of Fujian Medical University.PARTICIPANTS： Sixty-eight comatose patients were selected from the Union Hospital affiliated to Fujian Medical University from June 1998 to January 2005. The diseased regions were identified using cranial CT （n =43） or MR （n =25）. According to different primarily diseased regions, the comatose patients were divided into two groups： ① brainstem affection group （n =23）： 13 males and 10 females, 14 - 62 years of age; ②diffuse cortical affection group （n =45）： 28 males and 17 females, 23 - 75 years of age.METHODS： The dynamic EEG and Glasgow coma score were examined in the 45 comatose patients with primarily cortical affection and 22 comatose patients with primarily brainstem affection at acute phase. The patients were followed-up for 3 months to observe the outcome, The termination of outcome judgment was 3 months after attack or the death. The clinical outcome was classified as complete rehabilitation, survived with disability, death or vegetative state. Correlations of dynamic EEG and Glasgow coma score with the outcome of patients were analyzed. The correlations of dynamic EEG grades and Glasgow coma scores with the outcome were analyzed, and the prognostic value of dynamic EEG grades was compared between the two groups.MAIN OUTCOME MEASURES： ① Correlations of dynamic EEG and Glasgow coma score with the outcome of patients; ② Comparison of the prognostic value of dynamic EEG grades between the two groups.RESULTS： All the 68 patients were involved in the analysis of results. ① Correlations of dynamic EEG grades and Glasgow scores and their correlation analysis： EEG grades had significant negative correlation with Glasgow coma scores in both the cortical affection group and brainstem affection group （r = - 0.743,- 0.564, P 〈 0.01, 0.05）. In the cortical affection group, the Glasgow coma scores and dynamic EEG grades in the patients with the outcome of death or vegetative state were significantly different from those with the outcome of rehabilitation （P 〈 0.05 - 0.01）. In the brainstem affection group, the Glasgow coma scores were only significantly different between the patients with outcome of rehabilitation and death （P 〈 0.05）, and there was no significant difference in dynamic EEG grades among the three prognostic states （P 〉 0.05）. ②Comparison of the prognostic value of dynamic EEG grades between comatose patients with cortical affection and brainstem affection： The sensitivity, specificity and accuracy were all higher （P 〈 0.05）, while the error rate was lower （P〈0.05） in the cortical affection group than in the brainstem affection group.CONCLUSION： Dynamic EEG was valuable in predicting the outcome of comatose patients with primarily cortical affection, but it was not certainly valuable in those with primarily brainstem affection.展开更多
In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads o...In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.展开更多
Central nerve signal evoked by thoughts can be directly used to control a robot or prosthetic devices without the involvement of the peripheral nerve and muscles.This is a new strategy of human-computer interaction.A ...Central nerve signal evoked by thoughts can be directly used to control a robot or prosthetic devices without the involvement of the peripheral nerve and muscles.This is a new strategy of human-computer interaction.A method of electroencephalogram(EEG) phase synchronization combined with band energy was proposed to construct a feature vector for pattern recognition of brain-computer interaction based on EEG induced by motor imagery in this paper,rhythm and beta rhythm were first extracted from EEG by band pass filter and then the frequency band energy was calculated by the sliding time window;the instantaneous phase values were obtained using Hilbert transform and then the phase synchronization feature was calculated by the phase locking value(PLV) and the best time interval for extracting the phase synchronization feature was searched by the distribution of the PLV value in the time domain.Finally,discrimination of motor imagery patterns was performed by the support vector machine(SVM).The results showed that the phase synchronization feature more effective in4s-7s and the correct classification rate was 91.4%.Compared with the results achieved by a single EEG feature related to motor imagery,the correct classification rate was improved by 3.5 and4.3 percentage points by combining phase synchronization with band energy.These indicate that the proposed method is effective and it is expected that the study provides a way to improve the performance of the online real-time brain-computer interaction control system based on EEG related to motor imagery.展开更多
The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate ...The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate entropy and a support vector machine that has strong generalization ability were applied to classify electroencephalogram signals at epileptic interictal and ictal periods. Our aim was to verify whether approximate entropy waves can be effectively applied to the automatic real-time detection of epilepsy in the electroencephalogram, and to explore its generalization ability as a classifier trained using a nonlinear dynamics index. Four patients presenting with partial epileptic seizures were included in this study. They were all diagnosed with neocortex localized epilepsy and epileptic foci were clearly observed by electroencephalogram. The electroencephalogram data form the four involved patients were segmented and the characteristic values of each segment, that is, the approximate entropy, were extracted. The support vector machine classifier was constructed with the approximate entropy extracted from one epileptic case, and then electroencephalogram waves of the other three cases were classified, reaching a 93.33% accuracy rate. Our findings suggest that the use of approximate entropy allows the automatic real-time detection of electroencephalogram data in epileptic cases. The combination of approximate entropy and support vector machines shows good generalization ability for the classification of electroencephalogram signals for epilepsy.展开更多
Here, we administered repeated-pulse transcranial magnetic stimulation to healthy people at the left Guangming （GB37） and a mock point, and calculated the sample entropy of electroencephalo- gram signals using nonli...Here, we administered repeated-pulse transcranial magnetic stimulation to healthy people at the left Guangming （GB37） and a mock point, and calculated the sample entropy of electroencephalo- gram signals using nonlinear dynamics. Additionally, we compared electroencephalogram sample entropy of signals in response to visual stimulation before, during, and after repeated-pulse tran- scranial magnetic stimulation at the Guangming. Results showed that electroencephalogram sample entropy at left （F3） and right （FP2） frontal electrodes were significantly different depending on where the magnetic stimulation was administered. Additionally, compared with the mock point, electroencephalogram sample entropy was higher after stimulating the Guangming point. When visual stimulation at Guangming was given before repeated-pulse transcranial magnetic stimula- tion, significant differences in sample entropy were found at five electrodes （C3, Cz, C4, P3, T8） in parietal cortex, the central gyrus, and the right temporal region compared with when it was given after repeated-pulse transcranial magnetic stimulation, indicating that repeated-pulse transcranial magnetic stimulation at Guangming can affect visual function. Analysis of electroencephalogram revealed that when visual stimulation preceded repeated pulse transcranial magnetic stimulation, sample entropy values were higher at the C3, C4, and P3 electrodes and lower at the Cz and T8 electrodes than visual stimulation followed preceded repeated pulse transcranial magnetic stimula- tion. The findings indicate that repeated-pulse transcranial magnetic stimulation at the Guangming evokes different patterns of electroencephalogram signals than repeated-pulse transcranial mag- netic stimulation at other nearby points on the body surface, and that repeated-pulse transcranial magnetic stimulation at the Guangrning is associated with changes in the complexity of visually evoked electroencephalogram signals in parietal regions, central gyrus, and temporal regions.展开更多
As the relevance between left and right brain neurons when transmitting electrical signals of umami taste is unknown,the aim of this work was to investigate responsive regions of the brain to the umami tastant monosod...As the relevance between left and right brain neurons when transmitting electrical signals of umami taste is unknown,the aim of this work was to investigate responsive regions of the brain to the umami tastant monosodium glutamate(MSG)by using scalp-electroencephalogram(EEG)to identify the most responsive brain regions to MSG.Three concentrations of MSG(0.05,0.12,0.26 g/100 mL)were provided to participants for tasting while recoding their responsive reaction times and brain activities.The results indicated that the most responsive frequency to MSG was at 2 Hz,while the most responsive brain regions were T4 CzA2,F8 CzA2,and Fp2 CzA2.Moreover,the sensitivity of the brain to MSG was significantly higher in the right brain region.This study shows the potential of using EEG to investigate the relevance between different brains response to umami taste,which contributes to better understanding the mechanism of umami perception.展开更多
BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great s...BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great significance for improving the patients’intellectual development and quality of life.Electroencephalograms(EEG)can predict an accelerated decline in cognitive function.AIM To determine the clinical and EEG characteristics and treatment results of benign epilepsy in spiking children.METHODS A total of 106 cases of benign epilepsy in children with myocardial spines treated at our hospital from January 2017 to January 2020 were selected.Differences in clinical data and EGG characteristics between treatment-effective/-ineffective patients were analyzed,and children’s intellectual development before and after treatment evaluated using the Gesell Development Diagnostic Scale.RESULTS EEG showed that the discharge proportion in the awake and sleep periods was 66.04%,and the peak/peak discharge was mainly single-sided,accounting for 81.13%,while the discharge generalization accounted for 31.13%.There was no significant difference in any of these variables between sexes and ages(P>0.05).The proportion of patients with early onset(<5 years old)and seizure frequency>3 times/half a year was 40.00%and 60.00%,respectively;the incidence rate and seizure frequency in the younger age group(<5 years old)were significantly higher than those in the treatment-effective group(P<0.05),while the discharge index was significantly lower than that in the treatment-effective group(P<0.05).The discharge index was negatively correlated with fine motor skill and language development(r=-0.274 and-0.247,respectively;P<0.05),but not with the rest(P>0.05).Logistic regression analysis showed that low age onset(<5 years old)and seizure frequency were the factors affecting ineffective-treatment of benign epilepsy in children(odds ratio=11.304 and 5.784,respectively;P<0.05).The discharge index of the responsive group after treatment was significantly lower than that of the unresponsive group(P<0.05).However,there was no significant difference between groups after treatment in gross and fine motor skills,adaptability,language,and personal social development(P>0.05).CONCLUSION The EEG of children with benign epilepsy due to spinal wave in central time zone has characteristic changes,and the therapeutic effect is influenced by age of onset and attack frequency.展开更多
Combination of the wavelet transform and independent component analysis （ICA） was employed for blind source separation （BSS） of multichannel electroencephalogram （EEG）. After denoising the original signals by di...Combination of the wavelet transform and independent component analysis （ICA） was employed for blind source separation （BSS） of multichannel electroencephalogram （EEG）. After denoising the original signals by discrete wavelet transform, high frequency components of some noises and artifacts were removed from the original signals. The denoised signals were reconstructed again for the purpose of ICA, such that the drawback that ICA cannot distinguish noises from source signals can be overcome effectively. The practical processing results showed that this method is an effective way to BSS of multichannel EEG. The method is actually a combination of wavelet transform with adaptive neural network, so it is also useful for BBS of other complex signals.展开更多
Previous studies have demonstrated that hand shadows may activate the motor cortex associated with the mirror neuron system in human brain. However, there is no evidence of activity of the human mirror neuron system d...Previous studies have demonstrated that hand shadows may activate the motor cortex associated with the mirror neuron system in human brain. However, there is no evidence of activity of the human mirror neuron system during the observation of intransitive movements by shadows and line drawings of hands. This study examined the suppression of electroencephalography mu waves （8-13 Hz） induced by observation of stimuli in 18 healthy students. Three stimuli were used： real hand actions, hand shadow actions and actions made by line drawings of hands. The results showed significant desynchronization of the mu rhythm （＂mu suppression＂） across the sensodmotor cortex （recorded at C3, Cz and C4）, the frontal cortex （recorded at F3, Fz and F4） and the central and right posterior parietal cortex （recorded at Pz and P4） under all three conditions. Our experimental findings suggest that the observation of ＂impoverished hand actions＂, such as intransitive movements of shadows and line drawings of hands, is able to activate widespread cortical areas related to the putative human mirror neuron system.展开更多
Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)techniques.Especially,the EEG signals associated with seizure epilepsy can be detected to distinguish betwee...Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)techniques.Especially,the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions.From this perspective,an automated AI technique with a digital processing method can be used to improve these signals.This paper proposes two classifiers:long short-term memory(LSTM)and support vector machine(SVM)for the classification of seizure and non-seizure EEG signals.These classifiers are applied to a public dataset,namely the University of Bonn,which consists of 2 classes–seizure and non-seizure.In addition,a fast Walsh-Hadamard Transform(FWHT)technique is implemented to analyze the EEG signals within the recurrence space of the brain.Thus,Hadamard coefficients of the EEG signals are obtained via the FWHT.Moreover,the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings.Also,a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers.The LSTM classifier provides the best performance,with a testing accuracy of 99.00%.The training and testing loss rates for the LSTM are 0.0029 and 0.0602,respectively,while the weighted average precision,recall,and F1-score for the LSTM are 99.00%.The results of the SVM classifier in terms of accuracy,sensitivity,and specificity reached 91%,93.52%,and 91.3%,respectively.The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s,respectively.The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals.Eventually,the proposed classifiers provide high classification accuracy compared to previously published classifiers.展开更多
Objective To evaluate the usefulness of quantitative electroencephalogram （QEEG）, flash visual evoked potential （F-VEP） and auditory brainstem responses （ABR） as indicators of general neurological status. Method...Objective To evaluate the usefulness of quantitative electroencephalogram （QEEG）, flash visual evoked potential （F-VEP） and auditory brainstem responses （ABR） as indicators of general neurological status. Methods Comparison was conducted on healthy controls （N=30） and patients with brain concussion （N=60） within 24 h after traumatic brain injury. Follow-up study of patient group was completed with the same standard paradigm 3 months later. All participants were recorded in multi-modality related potential testing in both early and late concussion at the same clinical setting. Glasgow coma scale, CT scanning, and physical examinations of neuro-psychological function, optic and auditory nervous system were performed before electroencephalogram （EEG） and evoked potential （EEG-EP） testing. Any participants showed abnormal changes of clinical examinations were excluded from the study. Average power of frequency spectrum and power ratios were selected for QEEG testing, and latency and amplitude of F-VEP and ABR were recorded. Results Between patients and normal controls, the results indicated： （1） Highly significance （P 〈 0.01） in average power of α1 and power ratios of θ/α1, 0/α2, α1/α2 of EEG recording; （2） N70-P 100 amplitude of F-VEP in significant difference at early brain concussion; and （3） apparent prolongation of Ⅰ～Ⅲ inter-peak latency of ABR appeared in some individuals at early stage after concussion. The follow-up study showed that some patients with concussion were also afflicted with characteristic changes of EEG components for both increments of α1 average power and θ/α2 power ratio after 3 months recording. Conclusion EEG testing has been shown to be more effective and sensitive than evoked potential tests alone on detecting functional state of patients with mild traumatic brain injury （MTBI）. Increments of α1 average power and θ/α2 power ratio are the sensitive EEG parameters to determining early concussion and evaluating outcome of postconcussion symptoms （PCS）. Follow-up study associated with persistent PCS may be consistent with the postulate of substantial biological, rather than psychological origin. The study suggests that combination of EEG and EP parameters can contribute to the evaluation of brain function as a whole for clinical and forensic applications.展开更多
With the fast-accelerating pace of life,most of the population is troubled by anxious feelings,or they even developed anxiety disorders,which affect their life qualities viciously.The current treatment is not without ...With the fast-accelerating pace of life,most of the population is troubled by anxious feelings,or they even developed anxiety disorders,which affect their life qualities viciously.The current treatment is not without drawbacks,such as exhibiting slow or acute effects only.Music therapy has shown promising outcomes in significantly reducing tension and anxiety in many studies.To explore the underlying mechanism,we recruited 12 undergraduate student volunteers from Shanghai Jiao Tong University with habits of music listening.We explored the changes in the electroencephalogram(EEG)power spectrum both during and after listening to self-select favorite music,and the relation between EEG signals and anxiety-relieving during music listening.The results showed that the power of the band in the right parietal area was significantly higher in those who were self-report able to relax during music listening compared with those who could not get relaxed.We observed power increased in the right parietal area of self-reports,not able to relax while music playing.Also,a significant difference inband power in the left frontal area and band in the right frontal area before and after music listening was observed between high anxiety group and low anxiety group.These results imply that band activity in the left frontal area is associated with the anxiety-relieving capability of anxiety,which provides evidence for further elucidating the mechanism underlying anxiety-relieving during music listening.展开更多
An observation on the changes of immune function(serum immunoglobulin, lymphocyte transformation ) and electroencephalogram were carried out when the explorers were residing in Antarctica for a long time.Serum IgM, Ig...An observation on the changes of immune function(serum immunoglobulin, lymphocyte transformation ) and electroencephalogram were carried out when the explorers were residing in Antarctica for a long time.Serum IgM, IgG decreased by the end of twelve months residing in Antarctica. It were only 40%; 38% (P<0.01) of the previous value before leaving for Antarctica. Serum IgA increased first and then returned to its previous value before leaving for Antarctica. When they returned back to Beijing for 2 months serum IgA was lower than that before leaving (P<0. 05). Lymphocyte transformation rate decreased to 45% (P<0. 05 ) of its previous level before leaving for Antarctica. The low lymphocyte transformation rate lasted for 2 months after return. But the variation of Ig level and lymphocyte transformation rate were small in the control group at different seasons. It is obviously that the significant change of ig level and lymphocyte transformation rate of explorers residing in Antarctica is the result of special environment.The desynchronization process on electroencephalogram (EEG) increased. The frequency and index of β-wave band increased during their stay in Antarctica. There is a close relationship between the decrease of lymphocyte transformation rate and the increase of the index and amplitude of β-band on EEG. It indicated that the decrease of immunity (especially cell mediated immunity) resulted from living under stress for a long time.展开更多
To listen to brain activity as a piece of music,we previously proposed scale-free brainwave music（SFBM）technology,which translated the scalp electroencephalogram（EEG）into musical notes according to the power law o...To listen to brain activity as a piece of music,we previously proposed scale-free brainwave music（SFBM）technology,which translated the scalp electroencephalogram（EEG）into musical notes according to the power law of both the EEG and music.In this study,the methodology was further extended to ensemble music on two channels from the two hemispheres.EEG data from two channels symmetrically located on the left and right hemispheres were translated into MIDI sequences by SFBM,and the EEG parameters modulated the pitch,duration and volume of each note.Then,the two sequences were filtered into an ensemble with two voices：the pentatonic scale（traditional Chinese music）or the heptatonic scale（standard Western music）.We demonstrated differences in harmony between the two scales generated at different sleep stages,with the pentatonic scale being more harmonious.The harmony intervals of this brain ensemble at various sleep stages followed the power law.Compared with the heptatonic scale,it was easier to distinguish the different stages using the pentatonic scale.These results suggested that the hemispheric ensemble can represent brain activity by variations in pitch,tempo and harmony.The ensemble with the pentatonic scale sounds more consonant,and partially reflects the relations of the two hemispheres.This can be used to distinguish the different states of brain activity and provide a new perspective on EEG analysis.展开更多
BACKGROUND Cognitive dysfunction in epileptic patients is a high-incidence complication.Its mechanism is related to nervous system damage during seizures,but there is no effective diagnostic biomarker.Neuronal pentrax...BACKGROUND Cognitive dysfunction in epileptic patients is a high-incidence complication.Its mechanism is related to nervous system damage during seizures,but there is no effective diagnostic biomarker.Neuronal pentraxin 2(NPTX2)is thought to play a vital role in neurotransmission and the maintenance of synaptic plasticity.This study explored how serum NPTX2 and electroencephalogram(EEG)slow wave/fast wave frequency ratio relate to cognitive dysfunction in patients with epilepsy.AIM To determine if serum NPTX2 could serve as a potential biomarker for diagnosing cognitive impairment in epilepsy patients.METHODS The participants of this study,conducted from January 2020 to December 2021,comprised 74 epilepsy patients with normal cognitive function(normal group),37 epilepsy patients with cognitive dysfunction[epilepsy patients with cognitive dysfunction(ECD)group]and 30 healthy people(control group).The minimental state examination(MMSE)scale was used to evaluate cognitive function.We determined serum NPTX2 levels using an enzyme-linked immunosorbent kit and calculated the signal value of EEG regions according to the EEG recording.Pearson correlation coefficient was used to analyze the correlation between serum NPTX2 and the MMSE score.RESULTS The serum NPTX2 level in the control group,normal group and ECD group were 240.00±35.06 pg/mL,235.80±38.01 pg/mL and 193.80±42.72 pg/mL,respectively.The MMSE score was lowest in the ECD group among the three,while no significant difference was observed between the control and normal groups.In epilepsy patients with cognitive dysfunction,NPTX2 level had a positive correlation with the MMSE score(r=0.367,P=0.0253)and a negative correlation with epilepsy duration(r=−0.443,P=0.0061)and the EEG slow wave/fast wave frequency ratio value in the temporal region(r=−0.339,P=0.039).CONCLUSION Serum NPTX2 was found to be related to cognitive dysfunction and the EEG slow wave/fast wave frequency ratio in patients with epilepsy.It is thus a potential biomarker for the diagnosis of cognitive impairment in patients with epilepsy.展开更多
文摘BACKGROUND Mild cognitive impairment(MCI)is a high-risk precursor to Alzheimer’s disease characterized by declining memory or other progressive cognitive functions without compromising daily living abilities.AIM To investigate the efficacy of repetitive transcranial magnetic stimulation(rTMS)in patients with MCI.METHODS This retrospective analysis involved 180 patients with MCI who were admitted to The First Hospital of Shanxi Medical University from January 2021 to June 2023.Participants were allocated into the research(n=98,receiving rTMS)and control groups(n=82,receiving sham stimulation).Memory tests,cognitive function assessments,event-related potential–P300 tests,and electroencephalogram(EEG)examinations were conducted pre-treatment and post-treatment.Further,memory quotient(MQ),cognitive function scores,and EEG grading results were compared,along with adverse reaction incidences.RESULTS Pre-treatment MQ scores,long-term and short-term memory,as well as immediate memory scores,demonstrated no notable differences between the groups.Post-treatment,the research group exhibited significant increases in MQ scores,long-term memory,and short-term memory compared to baseline(P<0.05),with these improvements being statistically superior to those in the control group.However,immediate memory scores exhibited no significant change(P>0.05).Further,the research group demonstrated statistically better post-treatment scores on the Revised Wechsler Memory Scale than the control group.Furthermore,post-treatment P300 latency and amplitude improved significantly in the research group,surpassing the control group.EEG grading in the research group improved,and the incidence of adverse reactions was significantly lower than in the control group.CONCLUSION Patients with MCI receiving rTMS therapy demonstrated improved memory and cognitive functions and EEG grading and exhibited high safety with fewer adverse reactions.
文摘Physiological signals such as electroencephalogram(EEG)signals are often corrupted by artifacts during the acquisition and processing.Some of these artifacts may deteriorate the essential properties of the signal that pertains to meaningful information.Most of these artifacts occur due to the involuntary movements or actions the human does during the acquisition process.So,it is recommended to eliminate these artifacts with signal processing approaches.This paper presents two mechanisms of classification and elimination of artifacts.In the first step,a customized deep network is employed to classify clean EEG signals and artifact-included signals.The classification is performed at the feature level,where common space pattern features are extracted with convolutional layers,and these features are later classified with a support vector machine classifier.In the second stage of the work,the artifact signals are decomposed with empirical mode decomposition,and they are then eliminated with the proposed adaptive thresholding mechanism where the threshold value changes for every intrinsic mode decomposition in the iterative mechanism.
基金Research Fund for Lin He’s Academician Workstation of New Medicine and Clinical Translation in Jining Medical University,No.JYHL2019FMS25and The Key Research and Development Program of Jining,No.2022YXNS028.
文摘BACKGROUND Post-stroke epilepsy is a common and easily overlooked complication of acute cerebrovascular disease.Long-term seizures can seriously affect the prognosis and quality of life of patients.Electroencephalogram(EEG)is the simplest way to diagnose epilepsy,and plays an important role in predicting seizures and guiding medication.AIM To explore the EEG characteristics of patients with post-stroke epilepsy and improve the detection rate of inter-seizure epileptiform discharges.METHODS From January 2017 to June 2020,10 patients with post-stroke epilepsy in our hospital were included.The clinical,imaging,and EEG characteristics were collected.The stroke location,seizure type,and ictal and interictal EEG manifestations of the patients with post-stroke epilepsy were then retrospectively analyzed.RESULTS In all 10 patients,epileptiform waves occurred in the side opposite to the stroke lesion during the interictal stage;these manifested as sharp wave,sharp-wave complex,or spike discharges in the anterior head lead of the side opposite to the lesion.CONCLUSION In EEG,epileptiform waves can occur in the side opposite to the stroke lesion in patients with post-stroke epilepsy.
基金supported by the General Program under grant funded by the National Natural Science Foundation of China(NSFC)(No.62171307)the Basic Research Program of Shanxi Province under grant funded by the Department of Science and Technology of Shanxi Province(China)(No.202103021224113).
文摘Early and timely diagnosis of stroke is critical for effective treatment,and the electroencephalogram(EEG)offers a low-cost,non-invasive solution.However,the shortage of high-quality patient EEG data often hampers the accuracy of diagnostic classification methods based on deep learning.To address this issue,our study designed a deep data amplification model named Progressive Conditional Generative Adversarial Network with Efficient Approximating Self Attention(PCGAN-EASA),which incrementally improves the quality of generated EEG features.This network can yield full-scale,fine-grained EEG features from the low-scale,coarse ones.Specially,to overcome the limitations of traditional generative models that fail to generate features tailored to individual patient characteristics,we developed an encoder with an effective approximating self-attention mechanism.This encoder not only automatically extracts relevant features across different patients but also reduces the computational resource consumption.Furthermore,the adversarial loss and reconstruction loss functions were redesigned to better align with the training characteristics of the network and the spatial correlations among electrodes.Extensive experimental results demonstrate that PCGAN-EASA provides the highest generation quality and the lowest computational resource usage compared to several existing approaches.Additionally,it significantly improves the accuracy of subsequent stroke classification tasks.
基金the Youth Foundation Program of Sichuan Province,No.04ZQ026-010
文摘BACKGROUND： Low-frequency repetitive transcranial magnetic stimulation （rTMS） has been shown to significantly reduce epileptiform discharges and control clinical seizures in intractable epilepsy patients. The location of epileptic foci and magnetic stimulation sites remain uncertain. The effects of rTMS on electroencephalogram and seizure remain unclear in epileptic patients following dipole source localization. OBJECTIVE： To investigate the effects of low-frequency rTMS on electroencephalogram and seizure in temporal lobe epilepsy patients after dipole source localization. DESIGN, TIME AND SETTING： The randomized, controlled study was performed at the outpatient clinic Department of Neurology, Hospital Affiliated to North Sichuan Medical College from December 2003 to February 2007. PARTICIPANTS： A total of 30 temporal lobe epilepsy patients, comprising 19 males and 11 females, aged 1749 years, presented with epileptiform discharges and were enrolled for this study. Disease course ranged between 1-6 years, with 1-5 seizures per month. Imaging examinations revealed 11 patients with structural changes in the brain. The patients were randomly and equally assigned into drug treatment and transcranial magnetic stimulation （TMS） groups. METHODS： Patients in the drug treatment group were orally treated with carbamazepine. Patients in the TMS group received oral carbamazepine treatment of and TMS. A Maglite-r25 magnetic stimulator （Dantec Dynamics, Denmark） was used to stimulate epileptic foci in the temporal lobe following electroencephalogram dipole localization （1 Hz, 90% threshold intensity, at a stimulation frequency of 500 times, once a day, for 7 days）. MAIN OUTCOME MEASURES： At 30 days after TMS, seizure frequency and rate of epileptiform discharges were observed in patients from both groups. Therapeutic safety was investigated during treatment. RESULTS： Within 30 days of treatment, there were no significant differences in seizure frequency between the TMS group （1.5 ± 0.3） seizures and the drug treatment group [（1.9± 0.4） seizures] （P 〉 0.05）. The rate of epileptiform discharges [27% （4/15）] was significantly less in the TMS group than in the drug treatment group [73% （11/15）] （P 〈 0.05）. During TMS, five patients suffered from transient mild headache, but were completely relieved within 2 hours. CONCLUSION： Low-frequency rTMS exhibited inhibitory effects on epileptiform discharges over a short period of time, and decreased seizure frequency to some degree. Results from the present study suggested that low-frequency rTMS is safe.
基金the NaturalScience Foundation of Fujian Province, No. C0310021
文摘BACKGROUND： It has proved that dynamic electroencephalogram （EEG） is definite in judging the outcome of ischemic hypoxic comatose patients, EEG is more sensitive to the cortical affection, but not sensitive to the subcortical and brainstem affections, thus it is necessary to clarify the indications of this technique in the clinical application.OBJECTIVE： To observe and compare the prognostic value of dynamic EEG and Glasgow coma score in comatose patients with different diseased region.DESIGN： A clinical case-controlled observation.SETTING： Union Hospital of Fujian Medical University.PARTICIPANTS： Sixty-eight comatose patients were selected from the Union Hospital affiliated to Fujian Medical University from June 1998 to January 2005. The diseased regions were identified using cranial CT （n =43） or MR （n =25）. According to different primarily diseased regions, the comatose patients were divided into two groups： ① brainstem affection group （n =23）： 13 males and 10 females, 14 - 62 years of age; ②diffuse cortical affection group （n =45）： 28 males and 17 females, 23 - 75 years of age.METHODS： The dynamic EEG and Glasgow coma score were examined in the 45 comatose patients with primarily cortical affection and 22 comatose patients with primarily brainstem affection at acute phase. The patients were followed-up for 3 months to observe the outcome, The termination of outcome judgment was 3 months after attack or the death. The clinical outcome was classified as complete rehabilitation, survived with disability, death or vegetative state. Correlations of dynamic EEG and Glasgow coma score with the outcome of patients were analyzed. The correlations of dynamic EEG grades and Glasgow coma scores with the outcome were analyzed, and the prognostic value of dynamic EEG grades was compared between the two groups.MAIN OUTCOME MEASURES： ① Correlations of dynamic EEG and Glasgow coma score with the outcome of patients; ② Comparison of the prognostic value of dynamic EEG grades between the two groups.RESULTS： All the 68 patients were involved in the analysis of results. ① Correlations of dynamic EEG grades and Glasgow scores and their correlation analysis： EEG grades had significant negative correlation with Glasgow coma scores in both the cortical affection group and brainstem affection group （r = - 0.743,- 0.564, P 〈 0.01, 0.05）. In the cortical affection group, the Glasgow coma scores and dynamic EEG grades in the patients with the outcome of death or vegetative state were significantly different from those with the outcome of rehabilitation （P 〈 0.05 - 0.01）. In the brainstem affection group, the Glasgow coma scores were only significantly different between the patients with outcome of rehabilitation and death （P 〈 0.05）, and there was no significant difference in dynamic EEG grades among the three prognostic states （P 〉 0.05）. ②Comparison of the prognostic value of dynamic EEG grades between comatose patients with cortical affection and brainstem affection： The sensitivity, specificity and accuracy were all higher （P 〈 0.05）, while the error rate was lower （P〈0.05） in the cortical affection group than in the brainstem affection group.CONCLUSION： Dynamic EEG was valuable in predicting the outcome of comatose patients with primarily cortical affection, but it was not certainly valuable in those with primarily brainstem affection.
基金supported by the Science Foundation of Jiangsu Province of China (Grant No.BK2011759)
文摘In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.
基金supported by the National Natural Science Foundation of China(81470084,61463024)the Research Project for Application Foundation of Yunnan Province(2013FB026)+2 种基金the Cultivation Program of Talents of Yunnan Province(KKSY201303048)the Focal Program for Education Department of Yunnan Province(2013Z130)the Brain Information Processing and Brain-computer Interaction Fusion Control of Kunming University Scienceand Technology(Fund of Discipline Direction Team)
文摘Central nerve signal evoked by thoughts can be directly used to control a robot or prosthetic devices without the involvement of the peripheral nerve and muscles.This is a new strategy of human-computer interaction.A method of electroencephalogram(EEG) phase synchronization combined with band energy was proposed to construct a feature vector for pattern recognition of brain-computer interaction based on EEG induced by motor imagery in this paper,rhythm and beta rhythm were first extracted from EEG by band pass filter and then the frequency band energy was calculated by the sliding time window;the instantaneous phase values were obtained using Hilbert transform and then the phase synchronization feature was calculated by the phase locking value(PLV) and the best time interval for extracting the phase synchronization feature was searched by the distribution of the PLV value in the time domain.Finally,discrimination of motor imagery patterns was performed by the support vector machine(SVM).The results showed that the phase synchronization feature more effective in4s-7s and the correct classification rate was 91.4%.Compared with the results achieved by a single EEG feature related to motor imagery,the correct classification rate was improved by 3.5 and4.3 percentage points by combining phase synchronization with band energy.These indicate that the proposed method is effective and it is expected that the study provides a way to improve the performance of the online real-time brain-computer interaction control system based on EEG related to motor imagery.
基金financially supported by the National Natural Science Foundation of China,No.61263011,81000554Program in Sun Yat-sen University supported by Fundamental Research Funds for the Central Universities,No.11ykpy07+1 种基金Natural Science Foundation of Guangdong Province,No.S2011010005309Innovation Fund of Xinjiang Medical University,No.XJC201209
文摘The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate entropy and a support vector machine that has strong generalization ability were applied to classify electroencephalogram signals at epileptic interictal and ictal periods. Our aim was to verify whether approximate entropy waves can be effectively applied to the automatic real-time detection of epilepsy in the electroencephalogram, and to explore its generalization ability as a classifier trained using a nonlinear dynamics index. Four patients presenting with partial epileptic seizures were included in this study. They were all diagnosed with neocortex localized epilepsy and epileptic foci were clearly observed by electroencephalogram. The electroencephalogram data form the four involved patients were segmented and the characteristic values of each segment, that is, the approximate entropy, were extracted. The support vector machine classifier was constructed with the approximate entropy extracted from one epileptic case, and then electroencephalogram waves of the other three cases were classified, reaching a 93.33% accuracy rate. Our findings suggest that the use of approximate entropy allows the automatic real-time detection of electroencephalogram data in epileptic cases. The combination of approximate entropy and support vector machines shows good generalization ability for the classification of electroencephalogram signals for epilepsy.
基金supported by the National Natural Science Foundation of China,No.31100711,51377045,31300818the Natural Science Foundation of Hebei Province,No.H2013202176
文摘Here, we administered repeated-pulse transcranial magnetic stimulation to healthy people at the left Guangming （GB37） and a mock point, and calculated the sample entropy of electroencephalo- gram signals using nonlinear dynamics. Additionally, we compared electroencephalogram sample entropy of signals in response to visual stimulation before, during, and after repeated-pulse tran- scranial magnetic stimulation at the Guangming. Results showed that electroencephalogram sample entropy at left （F3） and right （FP2） frontal electrodes were significantly different depending on where the magnetic stimulation was administered. Additionally, compared with the mock point, electroencephalogram sample entropy was higher after stimulating the Guangming point. When visual stimulation at Guangming was given before repeated-pulse transcranial magnetic stimula- tion, significant differences in sample entropy were found at five electrodes （C3, Cz, C4, P3, T8） in parietal cortex, the central gyrus, and the right temporal region compared with when it was given after repeated-pulse transcranial magnetic stimulation, indicating that repeated-pulse transcranial magnetic stimulation at Guangming can affect visual function. Analysis of electroencephalogram revealed that when visual stimulation preceded repeated pulse transcranial magnetic stimulation, sample entropy values were higher at the C3, C4, and P3 electrodes and lower at the Cz and T8 electrodes than visual stimulation followed preceded repeated pulse transcranial magnetic stimula- tion. The findings indicate that repeated-pulse transcranial magnetic stimulation at the Guangming evokes different patterns of electroencephalogram signals than repeated-pulse transcranial mag- netic stimulation at other nearby points on the body surface, and that repeated-pulse transcranial magnetic stimulation at the Guangrning is associated with changes in the complexity of visually evoked electroencephalogram signals in parietal regions, central gyrus, and temporal regions.
基金supported by the National Natural Science Foundation of China(31972198,31622042)the National Key R&D Program of China(2016YFD0400803,2016YFD0401501)。
文摘As the relevance between left and right brain neurons when transmitting electrical signals of umami taste is unknown,the aim of this work was to investigate responsive regions of the brain to the umami tastant monosodium glutamate(MSG)by using scalp-electroencephalogram(EEG)to identify the most responsive brain regions to MSG.Three concentrations of MSG(0.05,0.12,0.26 g/100 mL)were provided to participants for tasting while recoding their responsive reaction times and brain activities.The results indicated that the most responsive frequency to MSG was at 2 Hz,while the most responsive brain regions were T4 CzA2,F8 CzA2,and Fp2 CzA2.Moreover,the sensitivity of the brain to MSG was significantly higher in the right brain region.This study shows the potential of using EEG to investigate the relevance between different brains response to umami taste,which contributes to better understanding the mechanism of umami perception.
文摘BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great significance for improving the patients’intellectual development and quality of life.Electroencephalograms(EEG)can predict an accelerated decline in cognitive function.AIM To determine the clinical and EEG characteristics and treatment results of benign epilepsy in spiking children.METHODS A total of 106 cases of benign epilepsy in children with myocardial spines treated at our hospital from January 2017 to January 2020 were selected.Differences in clinical data and EGG characteristics between treatment-effective/-ineffective patients were analyzed,and children’s intellectual development before and after treatment evaluated using the Gesell Development Diagnostic Scale.RESULTS EEG showed that the discharge proportion in the awake and sleep periods was 66.04%,and the peak/peak discharge was mainly single-sided,accounting for 81.13%,while the discharge generalization accounted for 31.13%.There was no significant difference in any of these variables between sexes and ages(P>0.05).The proportion of patients with early onset(<5 years old)and seizure frequency>3 times/half a year was 40.00%and 60.00%,respectively;the incidence rate and seizure frequency in the younger age group(<5 years old)were significantly higher than those in the treatment-effective group(P<0.05),while the discharge index was significantly lower than that in the treatment-effective group(P<0.05).The discharge index was negatively correlated with fine motor skill and language development(r=-0.274 and-0.247,respectively;P<0.05),but not with the rest(P>0.05).Logistic regression analysis showed that low age onset(<5 years old)and seizure frequency were the factors affecting ineffective-treatment of benign epilepsy in children(odds ratio=11.304 and 5.784,respectively;P<0.05).The discharge index of the responsive group after treatment was significantly lower than that of the unresponsive group(P<0.05).However,there was no significant difference between groups after treatment in gross and fine motor skills,adaptability,language,and personal social development(P>0.05).CONCLUSION The EEG of children with benign epilepsy due to spinal wave in central time zone has characteristic changes,and the therapeutic effect is influenced by age of onset and attack frequency.
基金Project supported by the National Natural Science Foundation of China （Grant No 10234070） and by the Science Foundation of Educational Commission of Fujian Province of China （Grant No JA004238）.
文摘Combination of the wavelet transform and independent component analysis （ICA） was employed for blind source separation （BSS） of multichannel electroencephalogram （EEG）. After denoising the original signals by discrete wavelet transform, high frequency components of some noises and artifacts were removed from the original signals. The denoised signals were reconstructed again for the purpose of ICA, such that the drawback that ICA cannot distinguish noises from source signals can be overcome effectively. The practical processing results showed that this method is an effective way to BSS of multichannel EEG. The method is actually a combination of wavelet transform with adaptive neural network, so it is also useful for BBS of other complex signals.
基金supported by the grants from the National Natural Science Foundation of China,No.60775019,60970062 and 61173116the Research Fund for the Doctoral Program of Higher Education of China,No.201100702110014
文摘Previous studies have demonstrated that hand shadows may activate the motor cortex associated with the mirror neuron system in human brain. However, there is no evidence of activity of the human mirror neuron system during the observation of intransitive movements by shadows and line drawings of hands. This study examined the suppression of electroencephalography mu waves （8-13 Hz） induced by observation of stimuli in 18 healthy students. Three stimuli were used： real hand actions, hand shadow actions and actions made by line drawings of hands. The results showed significant desynchronization of the mu rhythm （＂mu suppression＂） across the sensodmotor cortex （recorded at C3, Cz and C4）, the frontal cortex （recorded at F3, Fz and F4） and the central and right posterior parietal cortex （recorded at Pz and P4） under all three conditions. Our experimental findings suggest that the observation of ＂impoverished hand actions＂, such as intransitive movements of shadows and line drawings of hands, is able to activate widespread cortical areas related to the putative human mirror neuron system.
基金The authors would like to thank the support of the Taif University Researchers Supporting Project TURSP 2020/34,Taif University,Taif Saudi Arabia for supporting this work.
文摘Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)techniques.Especially,the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions.From this perspective,an automated AI technique with a digital processing method can be used to improve these signals.This paper proposes two classifiers:long short-term memory(LSTM)and support vector machine(SVM)for the classification of seizure and non-seizure EEG signals.These classifiers are applied to a public dataset,namely the University of Bonn,which consists of 2 classes–seizure and non-seizure.In addition,a fast Walsh-Hadamard Transform(FWHT)technique is implemented to analyze the EEG signals within the recurrence space of the brain.Thus,Hadamard coefficients of the EEG signals are obtained via the FWHT.Moreover,the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings.Also,a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers.The LSTM classifier provides the best performance,with a testing accuracy of 99.00%.The training and testing loss rates for the LSTM are 0.0029 and 0.0602,respectively,while the weighted average precision,recall,and F1-score for the LSTM are 99.00%.The results of the SVM classifier in terms of accuracy,sensitivity,and specificity reached 91%,93.52%,and 91.3%,respectively.The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s,respectively.The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals.Eventually,the proposed classifiers provide high classification accuracy compared to previously published classifiers.
基金This work was supported in part by grants from National Natural Science Foundation of China （No. 30571909） China Postdoctoral Science Foundation （No. 32134006） Foundation of Soozhow University （No. Q4134405）.
文摘Objective To evaluate the usefulness of quantitative electroencephalogram （QEEG）, flash visual evoked potential （F-VEP） and auditory brainstem responses （ABR） as indicators of general neurological status. Methods Comparison was conducted on healthy controls （N=30） and patients with brain concussion （N=60） within 24 h after traumatic brain injury. Follow-up study of patient group was completed with the same standard paradigm 3 months later. All participants were recorded in multi-modality related potential testing in both early and late concussion at the same clinical setting. Glasgow coma scale, CT scanning, and physical examinations of neuro-psychological function, optic and auditory nervous system were performed before electroencephalogram （EEG） and evoked potential （EEG-EP） testing. Any participants showed abnormal changes of clinical examinations were excluded from the study. Average power of frequency spectrum and power ratios were selected for QEEG testing, and latency and amplitude of F-VEP and ABR were recorded. Results Between patients and normal controls, the results indicated： （1） Highly significance （P 〈 0.01） in average power of α1 and power ratios of θ/α1, 0/α2, α1/α2 of EEG recording; （2） N70-P 100 amplitude of F-VEP in significant difference at early brain concussion; and （3） apparent prolongation of Ⅰ～Ⅲ inter-peak latency of ABR appeared in some individuals at early stage after concussion. The follow-up study showed that some patients with concussion were also afflicted with characteristic changes of EEG components for both increments of α1 average power and θ/α2 power ratio after 3 months recording. Conclusion EEG testing has been shown to be more effective and sensitive than evoked potential tests alone on detecting functional state of patients with mild traumatic brain injury （MTBI）. Increments of α1 average power and θ/α2 power ratio are the sensitive EEG parameters to determining early concussion and evaluating outcome of postconcussion symptoms （PCS）. Follow-up study associated with persistent PCS may be consistent with the postulate of substantial biological, rather than psychological origin. The study suggests that combination of EEG and EP parameters can contribute to the evaluation of brain function as a whole for clinical and forensic applications.
基金the National Natural Science Founda-tion of China(No.81871064),and the Cross Foundation of Arts and Science of Shanghai Jiao Tong University(No.14JCRZ01)。
文摘With the fast-accelerating pace of life,most of the population is troubled by anxious feelings,or they even developed anxiety disorders,which affect their life qualities viciously.The current treatment is not without drawbacks,such as exhibiting slow or acute effects only.Music therapy has shown promising outcomes in significantly reducing tension and anxiety in many studies.To explore the underlying mechanism,we recruited 12 undergraduate student volunteers from Shanghai Jiao Tong University with habits of music listening.We explored the changes in the electroencephalogram(EEG)power spectrum both during and after listening to self-select favorite music,and the relation between EEG signals and anxiety-relieving during music listening.The results showed that the power of the band in the right parietal area was significantly higher in those who were self-report able to relax during music listening compared with those who could not get relaxed.We observed power increased in the right parietal area of self-reports,not able to relax while music playing.Also,a significant difference inband power in the left frontal area and band in the right frontal area before and after music listening was observed between high anxiety group and low anxiety group.These results imply that band activity in the left frontal area is associated with the anxiety-relieving capability of anxiety,which provides evidence for further elucidating the mechanism underlying anxiety-relieving during music listening.
文摘An observation on the changes of immune function(serum immunoglobulin, lymphocyte transformation ) and electroencephalogram were carried out when the explorers were residing in Antarctica for a long time.Serum IgM, IgG decreased by the end of twelve months residing in Antarctica. It were only 40%; 38% (P<0.01) of the previous value before leaving for Antarctica. Serum IgA increased first and then returned to its previous value before leaving for Antarctica. When they returned back to Beijing for 2 months serum IgA was lower than that before leaving (P<0. 05). Lymphocyte transformation rate decreased to 45% (P<0. 05 ) of its previous level before leaving for Antarctica. The low lymphocyte transformation rate lasted for 2 months after return. But the variation of Ig level and lymphocyte transformation rate were small in the control group at different seasons. It is obviously that the significant change of ig level and lymphocyte transformation rate of explorers residing in Antarctica is the result of special environment.The desynchronization process on electroencephalogram (EEG) increased. The frequency and index of β-wave band increased during their stay in Antarctica. There is a close relationship between the decrease of lymphocyte transformation rate and the increase of the index and amplitude of β-band on EEG. It indicated that the decrease of immunity (especially cell mediated immunity) resulted from living under stress for a long time.
基金supported by the National Natural Science Foundation of China(81201159,90820301 and 60835005)the Fundamental Research Funds for the Central Universitiesthe Neuro Information ‘111’ project,China
文摘To listen to brain activity as a piece of music,we previously proposed scale-free brainwave music（SFBM）technology,which translated the scalp electroencephalogram（EEG）into musical notes according to the power law of both the EEG and music.In this study,the methodology was further extended to ensemble music on two channels from the two hemispheres.EEG data from two channels symmetrically located on the left and right hemispheres were translated into MIDI sequences by SFBM,and the EEG parameters modulated the pitch,duration and volume of each note.Then,the two sequences were filtered into an ensemble with two voices：the pentatonic scale（traditional Chinese music）or the heptatonic scale（standard Western music）.We demonstrated differences in harmony between the two scales generated at different sleep stages,with the pentatonic scale being more harmonious.The harmony intervals of this brain ensemble at various sleep stages followed the power law.Compared with the heptatonic scale,it was easier to distinguish the different stages using the pentatonic scale.These results suggested that the hemispheric ensemble can represent brain activity by variations in pitch,tempo and harmony.The ensemble with the pentatonic scale sounds more consonant,and partially reflects the relations of the two hemispheres.This can be used to distinguish the different states of brain activity and provide a new perspective on EEG analysis.
基金Supported by 2022 Educational Research Program for Young and Middle-aged Teachers in Fujian Province(Science and Technology),No.JAT220107.
文摘BACKGROUND Cognitive dysfunction in epileptic patients is a high-incidence complication.Its mechanism is related to nervous system damage during seizures,but there is no effective diagnostic biomarker.Neuronal pentraxin 2(NPTX2)is thought to play a vital role in neurotransmission and the maintenance of synaptic plasticity.This study explored how serum NPTX2 and electroencephalogram(EEG)slow wave/fast wave frequency ratio relate to cognitive dysfunction in patients with epilepsy.AIM To determine if serum NPTX2 could serve as a potential biomarker for diagnosing cognitive impairment in epilepsy patients.METHODS The participants of this study,conducted from January 2020 to December 2021,comprised 74 epilepsy patients with normal cognitive function(normal group),37 epilepsy patients with cognitive dysfunction[epilepsy patients with cognitive dysfunction(ECD)group]and 30 healthy people(control group).The minimental state examination(MMSE)scale was used to evaluate cognitive function.We determined serum NPTX2 levels using an enzyme-linked immunosorbent kit and calculated the signal value of EEG regions according to the EEG recording.Pearson correlation coefficient was used to analyze the correlation between serum NPTX2 and the MMSE score.RESULTS The serum NPTX2 level in the control group,normal group and ECD group were 240.00±35.06 pg/mL,235.80±38.01 pg/mL and 193.80±42.72 pg/mL,respectively.The MMSE score was lowest in the ECD group among the three,while no significant difference was observed between the control and normal groups.In epilepsy patients with cognitive dysfunction,NPTX2 level had a positive correlation with the MMSE score(r=0.367,P=0.0253)and a negative correlation with epilepsy duration(r=−0.443,P=0.0061)and the EEG slow wave/fast wave frequency ratio value in the temporal region(r=−0.339,P=0.039).CONCLUSION Serum NPTX2 was found to be related to cognitive dysfunction and the EEG slow wave/fast wave frequency ratio in patients with epilepsy.It is thus a potential biomarker for the diagnosis of cognitive impairment in patients with epilepsy.
