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
The precise classification for the electroencephalogram(EEG)in different mental tasks in the research on braincomputer interface(BCI)is the key for the design and clinical application of the system.In this paper,a ne...The precise classification for the electroencephalogram(EEG)in different mental tasks in the research on braincomputer interface(BCI)is the key for the design and clinical application of the system.In this paper,a new combination classification algorithm is presented and tested using the EEG data of right and left motor imagery experiments.First,to eliminate the low frequency noise in the original EEGs,the signals were decomposed by empirical mode decomposition(EMD)and then the optimal kernel parameters for support vector machine(SVM)were determined,the energy features of thefirst three intrinsic mode functions(IMFs)of every signal were extracted and used as input vectors of the employed SVM.The output of the SVM will be classification result for different mental task EEG signals.The study shows that mean identification rate of the proposed algorithm is 95%,which is much better than the present traditional algorithms.展开更多
Today,electroencephalography is used to measure brain activity by creating signals that are viewed on a monitor.These signals are frequently used to obtain information about brain neurons and may detect disorders that...Today,electroencephalography is used to measure brain activity by creating signals that are viewed on a monitor.These signals are frequently used to obtain information about brain neurons and may detect disorders that affect the brain,such as epilepsy.Electroencephalogram(EEG)signals are however prone to artefacts.These artefacts must be removed to obtain accurate and meaningful signals.Currently,computer-aided systems have been used for this purpose.These systems provide high computing power,problem-specific development,and other advantages.In this study,a new clinical decision support system was developed for individuals to detect epileptic seizures using EEG signals.Comprehensive classification results were obtained for the extracted filtered features from the time-frequency domain.The classification accuracies of the time-frequency features obtained from discrete continuous transform(DCT),fractional Fourier transform(FrFT),and Hilbert transform(HT)are compared.Artificial neural networks(ANN)were applied,and back propagation(BP)was used as a learning method.Many studies in the literature describe a single BP algorithm.In contrast,we looked at several BP algorithms including gradient descent with momentum(GDM),scaled conjugate gradient(SCG),and gradient descent with adaptive learning rate(GDA).The most successful algorithm was tested using simulations made on three separate datasets(DCT_EEG,FrFT_EEG,and HT_EEG)that make up the input data.The HT algorithm was the most successful EEG feature extractor in terms of classification accuracy rates in each EEG dataset and had the highest referred accuracy rates of the algorithms.As a result,HT_EEG gives the highest accuracy for all algorithms,and the highest accuracy of 87.38%was produced by the SCG algorithm.展开更多
Since the advent of imaging studies such as magnetic resonance imaging (MRI), the role of electroencephalograms (EEGs) has diminished. Simultaneously, computerized scanning and miniaturization of the EEG and its compo...Since the advent of imaging studies such as magnetic resonance imaging (MRI), the role of electroencephalograms (EEGs) has diminished. Simultaneously, computerized scanning and miniaturization of the EEG and its components have allowed us to obtain lengthier recordings in an ambulatory setting. We report on 261 ambulatory electroencephalograms performed consecutively in the two year period of 2011 and 2012 in a busy neurology and neuropsychiatry practice with predominantly geriatric patient population. 23% of these patients had abnormal AEEGs demonstrating clear-cut epileptogenic discharges. The role of these findings in clinical practice, especially in geriatric and psychiatric populations is discussed.展开更多
Since the advent of imaging studies such as magnetic resonance imaging (MRI), the role of electroencephalograms (EEGs) has diminished. Simultaneously, computerized scanning and miniaturization of the EEG and its compo...Since the advent of imaging studies such as magnetic resonance imaging (MRI), the role of electroencephalograms (EEGs) has diminished. Simultaneously, computerized scanning and miniaturization of the EEG and its components have allowed us to obtain lengthier recordings in an ambulatory setting. We report on 261 ambulatory electroencephalograms performed consecutively in the two year period of 2011 and 2012 in a busy neurology and neuropsychiatry practice with predominantly geriatric patient population. 23% of these patients had abnormal AEEGs demonstrating clear-cut epileptogenic discharges. The role of these findings in clinical practice, especially in geriatric and psychiatric populations is discussed.展开更多
Attempts have been made to modulate motor sequence learning(MSL)through repetitive transcranial magnetic stimulation,targeting different sites within the sensorimotor network.However,the target with the optimum modula...Attempts have been made to modulate motor sequence learning(MSL)through repetitive transcranial magnetic stimulation,targeting different sites within the sensorimotor network.However,the target with the optimum modulatory effect on neural plasticity associated with MSL remains unclarified.This study was therefore designed to compare the role of the left primary motor cortex and the left supplementary motor area proper(SMAp)in modulating MSL across different complexity levels and for both hands,as well as the associated neuroplasticity by applying intermittent theta burst stimulation together with the electroencephalogram and concurrent transcranial magnetic stimulation.Our data demonstrated the role of SMAp stimulation in modulating neural communication to support MSL,which is achieved by facilitating regional activation and orchestrating neural coupling across distributed brain regions,particularly in interhemispheric connections.These findings may have important clinical implications,particularly for motor rehabilitation in populations such as post-stroke patients.展开更多
Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,n...Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.展开更多
General anesthesia,pivotal for surgical procedures,requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments.Traditional assessment methods,relyin...General anesthesia,pivotal for surgical procedures,requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments.Traditional assessment methods,relying on physiological indicators or behavioral responses,fall short of accurately capturing the nuanced states of unconsciousness.This study introduces a machine learning-based approach to decode anesthesia depth,leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats.Our findings demonstrate the model’s robust predictive accuracy,underscored by a novel intrasubject dataset partitioning and a 5-fold cross-validation method.The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states,highlighting distinct EEG patterns and enhancing prediction accuracy.Moreover,the model’s ability to generalize across individuals suggests its potential for broad clinical application,distinguishing between anesthetic agents and their depths.Despite relying on rat EEG data,which poses questions about real-world applicability,our approach marks a significant advance in anesthesia monitoring.展开更多
The global incidence of Alzheimer's Disease(AD)is on a swift rise.The Electroencephalogram(EEG)signals is an effective tool for the identification of AD and its initial Mild Cognitive Impairment(MCI)stage using ma...The global incidence of Alzheimer's Disease(AD)is on a swift rise.The Electroencephalogram(EEG)signals is an effective tool for the identification of AD and its initial Mild Cognitive Impairment(MCI)stage using machine learning models.Analysis of AD using EEG involves multi-channel analysis.However,the use of multiple channels may impact the classification performance due to data redundancy and complexity.In this work,a hybrid EEG channel selection is proposed using a combination of Reptile Search Algorithm and Snake Optimizer(RSO)for AD and MCI detection based on decomposition methods.Empirical Mode Decomposition(EMD),Low-Complexity Orthogonal Wavelet Filter Banks(LCOWFB),Variational Mode Decomposition,and discrete-wavelet transform decomposition techniques have been employed for subbands-based EEG analysis.We extracted thirty-four features from each subband of EEG signals.Finally,a hybrid RSO optimizer is compared with five individual metaheuristic algorithms for effective channel selection.The effectiveness of this model is assessed by two publicly accessible AD EEG datasets.An accuracy of 99.22% was achieved for binary classification from RSO with EMD using 4(out of 16)EEG channels.Moreover,the RSO with LCOWFBs obtained 89.68%the average accuracy for three-class classification using 7(out of 19)channels.The performance reveals that RSO performs better than individual Metaheuristic algorithms with 60%fewer channels and improved accuracy of 4%than existing AD detection techniques.展开更多
Abuse of amphetamine-based stimulants is a primary public health concern.Recent studies have underscored a troubling escalation in the inappropriate use of prescription amphetamine-based stimulants.However,the neuroph...Abuse of amphetamine-based stimulants is a primary public health concern.Recent studies have underscored a troubling escalation in the inappropriate use of prescription amphetamine-based stimulants.However,the neurophysiological mechanisms underlying the impact of acute methamphetamine exposure(AME)on sleep homeostasis remain to be explored.This study employed non-human primates and electroencephalogram(EEG)sleep staging to evaluate the influence of AME on neural oscillations.The primary focus was on alterations in spindles,delta oscillations,and slow oscillations(SOs)and their interactions as conduits through which AME influences sleep stability.AME predominantly diminishes sleep-spindle waves in the non-rapid eye movement 2(NREM2)stage,and impacts SOs and delta waves differentially.Furthermore,the competitive relationships between SO/delta waves nesting with sleep spindles were selectively strengthened by methamphetamine.Complexity analysis also revealed that the SO-nested spindles had lost their ability to maintain sleep depth and stability.In summary,this finding could be one of the intrinsic electrophysiological mechanisms by which AME disrupted sleep homeostasis.展开更多
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
Recent deep neural network(DNN)based blind image quality assessment(BIQA)approaches take mean opinion score(MOS)as ground-truth labels,which would lead to cross-datasets biases and limited generalization ability of th...Recent deep neural network(DNN)based blind image quality assessment(BIQA)approaches take mean opinion score(MOS)as ground-truth labels,which would lead to cross-datasets biases and limited generalization ability of the DNN-based BIQA model.This work validates the natural instability of MOS through investigating the neuropsychological characteristics inside the human visual system during quality perception.By combining persistent homology analysis with electroencephalogram(EEG),the physiologically meaningful features of the brain responses to different distortion levels are extracted.The physiological features indicate that although volunteers view exactly the same image content,their EEG features are quite varied.Based on the physiological results,we advocate treating MOS as noisy labels and optimizing the DNN based BIQA model with earlystop strategies.Experimental results on both innerdataset and cross-dataset demonstrate the superiority of our optimization approach in terms of generalization ability.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
BACKGROUND Electroconvulsive therapy(ECT)is both an effective treatment for patients with major depressive disorder(MDD)and a noxious stimulus.Although some studies have explored the effect of sedation depth on seizur...BACKGROUND Electroconvulsive therapy(ECT)is both an effective treatment for patients with major depressive disorder(MDD)and a noxious stimulus.Although some studies have explored the effect of sedation depth on seizure parameters in ECT,there is little research on the noxious stimulation response to ECT.In this study,we used two electroencephalography(EEG)-derived indices,the quantitative consci-ousness(qCON)index and quantitative nociceptive(qNOX)index,to monitor sedation,hypnosis,and noxious stimulation response in patients with MDD undergoing acute ECT.METHODS Patients with MDD(n=24)underwent acute bilateral temporal ECT under propofol anesthesia.Before ECT,the patients were randomly divided into three groups according to qCON scores(qCON60-70,qCON50-60,and qCON40-50).Continuous qCON monitoring was performed 3 minutes before and during ECT,and the qCON,qNOX,vital signs,EEG seizure parameters,and complications during the recovery period were recorded.The 24-item Hamilton Rating Scale for Depression,Zung’s Self-rating Depression Scale,and Montreal Cognitive Asse-ssment scores were evaluated before the first ECT session,after the fourth ECT session,and after the full course of ECT.RESULTS A total of 193 ECT sessions were performed on 24 participants.The qCON index significantly affected the EEG seizure duration,peak mid-ictal amplitude,and maximum heart rate during ECT(P<0.05).The qNOX index significantly affected the post-ictal suppression index(P<0.05).Age,number of ECT sessions,and anesthetic-ECT time intervals also had a significant effect on EEG seizure parameters(P<0.05).However,there were no significant differences in complications,24-item Hamilton Rating Scale for Depression scores,Zung’s Self-rating Depression Scale scores,or Montreal Cognitive Assessment scores among the three groups(P>0.05).CONCLUSION Electrical stimulation at a qCON index of 60-70 resulted in better EEG seizure parameters without increasing complications in patients with MDD undergoing bilateral temporal ECT under propofol anesthesia.展开更多
With cutting-edge technologies and considering airline human-resource-saving,a single pilot in commercial jets could be technically feasible.Investigating changes in captains’natural behaviours are initially required...With cutting-edge technologies and considering airline human-resource-saving,a single pilot in commercial jets could be technically feasible.Investigating changes in captains’natural behaviours are initially required to comprehend the specific safe human performance envelope for safeguarding single-pilot flight,particularly in high-risk situations.This paper investigates how captains’performance transforms for fixing emergencies when operating from Dual-Pilot Operations(DPO)to Single-Pilot Operations(SPO)through a physiological-based approach.Twenty pilots flew an emergency-included flight with/without first officers’assistance.The neural activities and scanning behaviours were recorded using a 32-channel Electroencephalogram(EEG)and glasses-based eye tracker,with the observation and post-experiment questionnaires to evaluate the flight operations and pilots’perception.Flying alone,there was a significantly increased cortical activity in h and b waves over the frontal,parietal,and temporal lobes during the more complicated emergencies,and pilots focused less on the primary flight display while spending significantly more time scanning the other interfaces.The physiological fluctuating patterns associated with risky operations in SPO were highlighted by cross-correlating multimodal data.The experimental-based noteworthy insights may wish to inform commercial SPO measures to lessen the persistent physiological fluctuation,assisting airlines in creating SPO-oriented intelligent flight systems to give captains adequate support for assuring safer air transportation.展开更多
Obstructive sleep apnea-hypopnea syndrome(OSAHS)significantly impairs children's growth and cognition.This study aims to elucidate the pathophysiological mechanisms underlying OSAHS in children,with a particular f...Obstructive sleep apnea-hypopnea syndrome(OSAHS)significantly impairs children's growth and cognition.This study aims to elucidate the pathophysiological mechanisms underlying OSAHS in children,with a particular focus on the alterations in cortical information interaction during respiratory events.We analyzed sleep electroencephalography before,during,and after events,utilizing Symbolic Transfer Entropy(STE)for brain network construction and information flow assessment.The results showed a significant increase in STE after events in specific frequency bands during N2 and rapid eye movement(REM)stages,along with increased STE during N3 stage events.Moreover,a noteworthy rise in the information flow imbalance within and between hemispheres was found after events,displaying unique patterns in central sleep apnea and hypopnea.Importantly,some of these alterations were correlated with symptom severity.These findings highlight significant changes in brain region coordination and communication during respiratory events,offering novel insights into OSAHS pathophysiology in children.展开更多
Bai et al investigate the predictive value of T lymphocyte proportion in Alzheimer's disease(AD)prognosis.Through a retrospective study involving 62 AD patients,they found that a decrease in T lymphocyte proportio...Bai et al investigate the predictive value of T lymphocyte proportion in Alzheimer's disease(AD)prognosis.Through a retrospective study involving 62 AD patients,they found that a decrease in T lymphocyte proportion correlated with a poorer prognosis,as indicated by higher modified Rankin scale scores.While the study highlights the potential of T lymphocyte proportion as a prognostic marker,it suggests the need for larger,multicenter studies to enhance generalizability and validity.Additionally,future research could use cognitive exams when evaluating prognosis and delve into immune mechanisms underlying AD progression.Despite limitations inherent in retrospective designs,Bai et al's work contributes to understanding the immune system's role in AD prognosis,paving the way for further exploration in this under-researched area.展开更多
Sensory conflict impacts postural control,yet its effect on cortico-muscular interaction remains underexplored.We aimed to investigate sensory conflict's influence on the cortico-muscular network and postural stab...Sensory conflict impacts postural control,yet its effect on cortico-muscular interaction remains underexplored.We aimed to investigate sensory conflict's influence on the cortico-muscular network and postural stability.We used a rotating platform and virtual reality to present subjects with congruent and incongruent sensory input,recorded EEG(electroencephalogram)and EMG(electromyogram)data,and constructed a directed connectivity network.The results suggest that,compared to sensory congruence,during sensory conflict:(1)connectivity among the sensorimotor,visual,and posterior parietal cortex generally decreases,(2)cortical control over the muscles is weakened,(3)feedback from muscles to the cortex is strengthened,and(4)the range of body sway increases and its complexity decreases.These results underline the intricate effects of sensory conflict on cortico-muscular networks.During the sensory conflict,the brain adaptively decreases the integration of conflicting information.Without this integrated information,cortical control over muscles may be lessened,whereas the muscle feedback may be enhanced in compensation.展开更多
Rationale:Subacute sclerosing panencephalitis(SSPE)is a progressive neurological disorder caused by persistent measles virus infection.SSPE predominantly affects children and adolescents.The symptoms usually develop 6...Rationale:Subacute sclerosing panencephalitis(SSPE)is a progressive neurological disorder caused by persistent measles virus infection.SSPE predominantly affects children and adolescents.The symptoms usually develop 6-15 years after measles infection and ultimately leading to death in many cases.Patient concerns:Patient 1 presented with cognitive decline and myoclonus and the Patient 2 presented with diminution of vision with myoclonic jerks.Diagnosis:Based on the clinical features with a characteristic electroencephalogram pattern and the presence of a high titer of anti-measles IgG in serum and cerebrospinal fluid,these patients were diagnosed as SSPE.Interventions:Antiepileptics were started for controlling myoclonus along with supportive treatment.Outcomes:Both patients were discharged on antiepileptics and supportive care.Lessons:Whenever there are unusual clinical manifestations with unknown vaccination status,SSPE can be suspected and the cerebrospinal fluid should be examined for anti-measles antibodies.Our case study also highlights the importance of universal coverage of measles vaccination.To reduce the incidence of measles and associated deaths,it is important to maintain a high level of immunization coverage for the measles vaccine and to strengthen all the integral components of the national immunization program.展开更多
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This work is supported by National Natural Science Foundation of China under Grant No.81071221.
文摘The precise classification for the electroencephalogram(EEG)in different mental tasks in the research on braincomputer interface(BCI)is the key for the design and clinical application of the system.In this paper,a new combination classification algorithm is presented and tested using the EEG data of right and left motor imagery experiments.First,to eliminate the low frequency noise in the original EEGs,the signals were decomposed by empirical mode decomposition(EMD)and then the optimal kernel parameters for support vector machine(SVM)were determined,the energy features of thefirst three intrinsic mode functions(IMFs)of every signal were extracted and used as input vectors of the employed SVM.The output of the SVM will be classification result for different mental task EEG signals.The study shows that mean identification rate of the proposed algorithm is 95%,which is much better than the present traditional algorithms.
基金This study was supported by The Scientific Technological Research Council of Turkey(TÜBITAK)under the Project No.118E682.
文摘Today,electroencephalography is used to measure brain activity by creating signals that are viewed on a monitor.These signals are frequently used to obtain information about brain neurons and may detect disorders that affect the brain,such as epilepsy.Electroencephalogram(EEG)signals are however prone to artefacts.These artefacts must be removed to obtain accurate and meaningful signals.Currently,computer-aided systems have been used for this purpose.These systems provide high computing power,problem-specific development,and other advantages.In this study,a new clinical decision support system was developed for individuals to detect epileptic seizures using EEG signals.Comprehensive classification results were obtained for the extracted filtered features from the time-frequency domain.The classification accuracies of the time-frequency features obtained from discrete continuous transform(DCT),fractional Fourier transform(FrFT),and Hilbert transform(HT)are compared.Artificial neural networks(ANN)were applied,and back propagation(BP)was used as a learning method.Many studies in the literature describe a single BP algorithm.In contrast,we looked at several BP algorithms including gradient descent with momentum(GDM),scaled conjugate gradient(SCG),and gradient descent with adaptive learning rate(GDA).The most successful algorithm was tested using simulations made on three separate datasets(DCT_EEG,FrFT_EEG,and HT_EEG)that make up the input data.The HT algorithm was the most successful EEG feature extractor in terms of classification accuracy rates in each EEG dataset and had the highest referred accuracy rates of the algorithms.As a result,HT_EEG gives the highest accuracy for all algorithms,and the highest accuracy of 87.38%was produced by the SCG algorithm.
文摘Since the advent of imaging studies such as magnetic resonance imaging (MRI), the role of electroencephalograms (EEGs) has diminished. Simultaneously, computerized scanning and miniaturization of the EEG and its components have allowed us to obtain lengthier recordings in an ambulatory setting. We report on 261 ambulatory electroencephalograms performed consecutively in the two year period of 2011 and 2012 in a busy neurology and neuropsychiatry practice with predominantly geriatric patient population. 23% of these patients had abnormal AEEGs demonstrating clear-cut epileptogenic discharges. The role of these findings in clinical practice, especially in geriatric and psychiatric populations is discussed.
文摘Since the advent of imaging studies such as magnetic resonance imaging (MRI), the role of electroencephalograms (EEGs) has diminished. Simultaneously, computerized scanning and miniaturization of the EEG and its components have allowed us to obtain lengthier recordings in an ambulatory setting. We report on 261 ambulatory electroencephalograms performed consecutively in the two year period of 2011 and 2012 in a busy neurology and neuropsychiatry practice with predominantly geriatric patient population. 23% of these patients had abnormal AEEGs demonstrating clear-cut epileptogenic discharges. The role of these findings in clinical practice, especially in geriatric and psychiatric populations is discussed.
基金supported by grants from the Zhejiang Provincial Natural Science Foundation(LGJ22H180001)Zhejiang Medical and Health Science and Technology Project(2021KY249)the National Key R&D Program of China(2017YFC1310000).
文摘Attempts have been made to modulate motor sequence learning(MSL)through repetitive transcranial magnetic stimulation,targeting different sites within the sensorimotor network.However,the target with the optimum modulatory effect on neural plasticity associated with MSL remains unclarified.This study was therefore designed to compare the role of the left primary motor cortex and the left supplementary motor area proper(SMAp)in modulating MSL across different complexity levels and for both hands,as well as the associated neuroplasticity by applying intermittent theta burst stimulation together with the electroencephalogram and concurrent transcranial magnetic stimulation.Our data demonstrated the role of SMAp stimulation in modulating neural communication to support MSL,which is achieved by facilitating regional activation and orchestrating neural coupling across distributed brain regions,particularly in interhemispheric connections.These findings may have important clinical implications,particularly for motor rehabilitation in populations such as post-stroke patients.
文摘Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.
基金supported by grants from the Shanghai Municipal Health Commission(2023ZDFC0203)the National Natural Science Foundation of China(32171044).
文摘General anesthesia,pivotal for surgical procedures,requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments.Traditional assessment methods,relying on physiological indicators or behavioral responses,fall short of accurately capturing the nuanced states of unconsciousness.This study introduces a machine learning-based approach to decode anesthesia depth,leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats.Our findings demonstrate the model’s robust predictive accuracy,underscored by a novel intrasubject dataset partitioning and a 5-fold cross-validation method.The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states,highlighting distinct EEG patterns and enhancing prediction accuracy.Moreover,the model’s ability to generalize across individuals suggests its potential for broad clinical application,distinguishing between anesthetic agents and their depths.Despite relying on rat EEG data,which poses questions about real-world applicability,our approach marks a significant advance in anesthesia monitoring.
文摘The global incidence of Alzheimer's Disease(AD)is on a swift rise.The Electroencephalogram(EEG)signals is an effective tool for the identification of AD and its initial Mild Cognitive Impairment(MCI)stage using machine learning models.Analysis of AD using EEG involves multi-channel analysis.However,the use of multiple channels may impact the classification performance due to data redundancy and complexity.In this work,a hybrid EEG channel selection is proposed using a combination of Reptile Search Algorithm and Snake Optimizer(RSO)for AD and MCI detection based on decomposition methods.Empirical Mode Decomposition(EMD),Low-Complexity Orthogonal Wavelet Filter Banks(LCOWFB),Variational Mode Decomposition,and discrete-wavelet transform decomposition techniques have been employed for subbands-based EEG analysis.We extracted thirty-four features from each subband of EEG signals.Finally,a hybrid RSO optimizer is compared with five individual metaheuristic algorithms for effective channel selection.The effectiveness of this model is assessed by two publicly accessible AD EEG datasets.An accuracy of 99.22% was achieved for binary classification from RSO with EMD using 4(out of 16)EEG channels.Moreover,the RSO with LCOWFBs obtained 89.68%the average accuracy for three-class classification using 7(out of 19)channels.The performance reveals that RSO performs better than individual Metaheuristic algorithms with 60%fewer channels and improved accuracy of 4%than existing AD detection techniques.
基金supported by the National Natural Science Foundation of China(No.82271515)the SJTU Trans-Med Awards Research(No.2019015)+4 种基金the Scientific and Technological Innovation Action Plan of Shanghai(No.KY20211478)the Shanghai Municipal Science and Technology Major Project(No.2021SHZDZX)the Nursing Development Program of Shanghai Jiao Tong University School of Medicine(No.SJTUHLXK2022)the 2024 Shanghai Ruijin Hospital Nursing Research Fund(No.RJHK-2024-001)the Shanghai Nursing Association Funding(No.2024MS-B13),China。
文摘Abuse of amphetamine-based stimulants is a primary public health concern.Recent studies have underscored a troubling escalation in the inappropriate use of prescription amphetamine-based stimulants.However,the neurophysiological mechanisms underlying the impact of acute methamphetamine exposure(AME)on sleep homeostasis remain to be explored.This study employed non-human primates and electroencephalogram(EEG)sleep staging to evaluate the influence of AME on neural oscillations.The primary focus was on alterations in spindles,delta oscillations,and slow oscillations(SOs)and their interactions as conduits through which AME influences sleep stability.AME predominantly diminishes sleep-spindle waves in the non-rapid eye movement 2(NREM2)stage,and impacts SOs and delta waves differentially.Furthermore,the competitive relationships between SO/delta waves nesting with sleep spindles were selectively strengthened by methamphetamine.Complexity analysis also revealed that the SO-nested spindles had lost their ability to maintain sleep depth and stability.In summary,this finding could be one of the intrinsic electrophysiological mechanisms by which AME disrupted sleep homeostasis.
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.
基金supported by the Medium and Long-term Science and Technology Plan for Radio,Television,and Online Audiovisuals(2023AC0200)the Public Welfare Technology Application Research Project of Zhejiang Province,China(No.LGF21F010001).
文摘Recent deep neural network(DNN)based blind image quality assessment(BIQA)approaches take mean opinion score(MOS)as ground-truth labels,which would lead to cross-datasets biases and limited generalization ability of the DNN-based BIQA model.This work validates the natural instability of MOS through investigating the neuropsychological characteristics inside the human visual system during quality perception.By combining persistent homology analysis with electroencephalogram(EEG),the physiologically meaningful features of the brain responses to different distortion levels are extracted.The physiological features indicate that although volunteers view exactly the same image content,their EEG features are quite varied.Based on the physiological results,we advocate treating MOS as noisy labels and optimizing the DNN based BIQA model with earlystop strategies.Experimental results on both innerdataset and cross-dataset demonstrate the superiority of our optimization approach in terms of generalization ability.
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the National Natural Science Foundation of China,No.81873798 and No.81901377Chongqing Science and Technology Bureau Under Grant,No.cstc2019jcyj-msxmX0839.
文摘BACKGROUND Electroconvulsive therapy(ECT)is both an effective treatment for patients with major depressive disorder(MDD)and a noxious stimulus.Although some studies have explored the effect of sedation depth on seizure parameters in ECT,there is little research on the noxious stimulation response to ECT.In this study,we used two electroencephalography(EEG)-derived indices,the quantitative consci-ousness(qCON)index and quantitative nociceptive(qNOX)index,to monitor sedation,hypnosis,and noxious stimulation response in patients with MDD undergoing acute ECT.METHODS Patients with MDD(n=24)underwent acute bilateral temporal ECT under propofol anesthesia.Before ECT,the patients were randomly divided into three groups according to qCON scores(qCON60-70,qCON50-60,and qCON40-50).Continuous qCON monitoring was performed 3 minutes before and during ECT,and the qCON,qNOX,vital signs,EEG seizure parameters,and complications during the recovery period were recorded.The 24-item Hamilton Rating Scale for Depression,Zung’s Self-rating Depression Scale,and Montreal Cognitive Asse-ssment scores were evaluated before the first ECT session,after the fourth ECT session,and after the full course of ECT.RESULTS A total of 193 ECT sessions were performed on 24 participants.The qCON index significantly affected the EEG seizure duration,peak mid-ictal amplitude,and maximum heart rate during ECT(P<0.05).The qNOX index significantly affected the post-ictal suppression index(P<0.05).Age,number of ECT sessions,and anesthetic-ECT time intervals also had a significant effect on EEG seizure parameters(P<0.05).However,there were no significant differences in complications,24-item Hamilton Rating Scale for Depression scores,Zung’s Self-rating Depression Scale scores,or Montreal Cognitive Assessment scores among the three groups(P>0.05).CONCLUSION Electrical stimulation at a qCON index of 60-70 resulted in better EEG seizure parameters without increasing complications in patients with MDD undergoing bilateral temporal ECT under propofol anesthesia.
基金supported by the Research Committee and the Department of Aeronautical and Aviation Engineering,The Hong Kong Polytechnic University,Hong Kong SAR,China(RH1W,ZVS9,RJX2,RLPA and CE1G)Cho Yin Yiu is a recipient of the Hong Kong PhD Fellowship(Reference number:PF21-62058)This study has been granted human ethics approval from the PolyU Institutional Review Board of The Hong Kong Polytechnic University(IRB Reference Number:HSEARS20210318002).
文摘With cutting-edge technologies and considering airline human-resource-saving,a single pilot in commercial jets could be technically feasible.Investigating changes in captains’natural behaviours are initially required to comprehend the specific safe human performance envelope for safeguarding single-pilot flight,particularly in high-risk situations.This paper investigates how captains’performance transforms for fixing emergencies when operating from Dual-Pilot Operations(DPO)to Single-Pilot Operations(SPO)through a physiological-based approach.Twenty pilots flew an emergency-included flight with/without first officers’assistance.The neural activities and scanning behaviours were recorded using a 32-channel Electroencephalogram(EEG)and glasses-based eye tracker,with the observation and post-experiment questionnaires to evaluate the flight operations and pilots’perception.Flying alone,there was a significantly increased cortical activity in h and b waves over the frontal,parietal,and temporal lobes during the more complicated emergencies,and pilots focused less on the primary flight display while spending significantly more time scanning the other interfaces.The physiological fluctuating patterns associated with risky operations in SPO were highlighted by cross-correlating multimodal data.The experimental-based noteworthy insights may wish to inform commercial SPO measures to lessen the persistent physiological fluctuation,assisting airlines in creating SPO-oriented intelligent flight systems to give captains adequate support for assuring safer air transportation.
基金supported by the National Natural Science Foundation of China (82001919)the Guangdong Basic and Applied Basic Research Foundation (2022A1515010050)+2 种基金the China Postdoctoral Science Foundation (2022M711219)the Key Realm R&D Program of Guangdong Province (2019B03035001)the Foundation of Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instruments (2020B1212060077).
文摘Obstructive sleep apnea-hypopnea syndrome(OSAHS)significantly impairs children's growth and cognition.This study aims to elucidate the pathophysiological mechanisms underlying OSAHS in children,with a particular focus on the alterations in cortical information interaction during respiratory events.We analyzed sleep electroencephalography before,during,and after events,utilizing Symbolic Transfer Entropy(STE)for brain network construction and information flow assessment.The results showed a significant increase in STE after events in specific frequency bands during N2 and rapid eye movement(REM)stages,along with increased STE during N3 stage events.Moreover,a noteworthy rise in the information flow imbalance within and between hemispheres was found after events,displaying unique patterns in central sleep apnea and hypopnea.Importantly,some of these alterations were correlated with symptom severity.These findings highlight significant changes in brain region coordination and communication during respiratory events,offering novel insights into OSAHS pathophysiology in children.
文摘Bai et al investigate the predictive value of T lymphocyte proportion in Alzheimer's disease(AD)prognosis.Through a retrospective study involving 62 AD patients,they found that a decrease in T lymphocyte proportion correlated with a poorer prognosis,as indicated by higher modified Rankin scale scores.While the study highlights the potential of T lymphocyte proportion as a prognostic marker,it suggests the need for larger,multicenter studies to enhance generalizability and validity.Additionally,future research could use cognitive exams when evaluating prognosis and delve into immune mechanisms underlying AD progression.Despite limitations inherent in retrospective designs,Bai et al's work contributes to understanding the immune system's role in AD prognosis,paving the way for further exploration in this under-researched area.
基金supported by the National Defense Foundation Strengthening Program Technology Field Fund Project of China(2021-JCJQ-JJ-1029)the Science Technology Plan Project of Zhejiang Province(2023C03159)+1 种基金the Science Foundation of National Health and Family Planning Commission-Medical Health Science and Technology Project of Zhejiang Provincial Health(WKJ-ZJ-2334)the key projects of major health science and technology plan of Zhejiang Province(WKJ-ZJ-2129).
文摘Sensory conflict impacts postural control,yet its effect on cortico-muscular interaction remains underexplored.We aimed to investigate sensory conflict's influence on the cortico-muscular network and postural stability.We used a rotating platform and virtual reality to present subjects with congruent and incongruent sensory input,recorded EEG(electroencephalogram)and EMG(electromyogram)data,and constructed a directed connectivity network.The results suggest that,compared to sensory congruence,during sensory conflict:(1)connectivity among the sensorimotor,visual,and posterior parietal cortex generally decreases,(2)cortical control over the muscles is weakened,(3)feedback from muscles to the cortex is strengthened,and(4)the range of body sway increases and its complexity decreases.These results underline the intricate effects of sensory conflict on cortico-muscular networks.During the sensory conflict,the brain adaptively decreases the integration of conflicting information.Without this integrated information,cortical control over muscles may be lessened,whereas the muscle feedback may be enhanced in compensation.
文摘Rationale:Subacute sclerosing panencephalitis(SSPE)is a progressive neurological disorder caused by persistent measles virus infection.SSPE predominantly affects children and adolescents.The symptoms usually develop 6-15 years after measles infection and ultimately leading to death in many cases.Patient concerns:Patient 1 presented with cognitive decline and myoclonus and the Patient 2 presented with diminution of vision with myoclonic jerks.Diagnosis:Based on the clinical features with a characteristic electroencephalogram pattern and the presence of a high titer of anti-measles IgG in serum and cerebrospinal fluid,these patients were diagnosed as SSPE.Interventions:Antiepileptics were started for controlling myoclonus along with supportive treatment.Outcomes:Both patients were discharged on antiepileptics and supportive care.Lessons:Whenever there are unusual clinical manifestations with unknown vaccination status,SSPE can be suspected and the cerebrospinal fluid should be examined for anti-measles antibodies.Our case study also highlights the importance of universal coverage of measles vaccination.To reduce the incidence of measles and associated deaths,it is important to maintain a high level of immunization coverage for the measles vaccine and to strengthen all the integral components of the national immunization program.
