Objective: This study investigates the auxiliary role of resting-state electroencephalography (EEG) in the clinical diagnosis of attention-deficit hyperactivity disorder (ADHD) using machine learning techniques. Metho...Objective: This study investigates the auxiliary role of resting-state electroencephalography (EEG) in the clinical diagnosis of attention-deficit hyperactivity disorder (ADHD) using machine learning techniques. Methods: Resting-state EEG recordings were obtained from 57 children, comprising 28 typically developing children and 29 children diagnosed with ADHD. The EEG signal data from both groups were analyzed. To ensure analytical accuracy, artifacts and noise in the EEG signals were removed using the EEGLAB toolbox within the MATLAB environment. Following preprocessing, a comparative analysis was conducted using various ensemble learning algorithms, including AdaBoost, GBM, LightGBM, RF, XGB, and CatBoost. Model performance was systematically evaluated and optimized, validating the superior efficacy of ensemble learning approaches in identifying ADHD. Conclusion: Applying machine learning techniques to extract features from resting-state EEG signals enabled the development of effective ensemble learning models. Differential entropy and energy features across multiple frequency bands proved particularly valuable for these models. This approach significantly enhances the detection rate of ADHD in children, demonstrating high diagnostic efficacy and sensitivity, and providing a promising tool for clinical application.展开更多
Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indice...Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.展开更多
Background Epilepsy is one of the common clinical disorders with comorbid anxiety and depression that severely afects their quality of life and increases their suicidality,while screening for anxiety and depression cu...Background Epilepsy is one of the common clinical disorders with comorbid anxiety and depression that severely afects their quality of life and increases their suicidality,while screening for anxiety and depression currently lacks objective identifers.This study aimed to analyze the characteristics of the electroencephalogram(EEG)power spectrum in patients with epilepsy with comorbid anxiety and depression,utilizing resting EEG data.Methods Resting EEG data were collected under standard conditions from two groups:patients with epilepsy comorbid with anxiety and depression(n=42)and patients without comorbidities(n=45).EEG power was calculated using data processing with EEGLAB and MATLAB.This study compared the absolute and relative powers of theδ,θ,α,β,andγfrequency bands,as well as the values of(δ+θ)/(α+β),between the two groups.Additionally,the correlation between the EEG power of each frequency band and anxiety and depression scores was analyzed.Results 1)Among individuals with epilepsy comorbid with anxiety and depression,lower absolute power ofδ,α,andθat specifc sites was observed(P<0.05),along with lower relative power ofθat certain sites(P<0.05).Conversely,higher relative power ofβandγat specifc sites was noted in those with comorbidities(P<0.05).2)There was no statistically signifcant diference in the values of(δ+θ)/(α+β)between the two groups(P>0.05).3)Depression scores exhibited a negative correlation withθabsolute power at the T3 and T4 sites(P<0.05),while showing a positive correlation withβrelative power at the C4 and T6 sites(P<0.05).Anxiety scores displayed a positive correlation withβrelative power at the F4,C3,C4 and T6 sites andγrelative power at F8 site(P<0.05).Conclusions The fndings suggest that comorbid anxiety and depression may impact resting EEG power spectra in individuals with epilepsy,particularly in regions exhibiting altered network connectivity.Furthermore,a positive correlation was observed between anxiety and depression scores andβrelative power in the right central and right posterior temporal regions,indicating potential screening utility.展开更多
Electroencephalography(EEG)is a powerful tool for investigating the brain bases of human psychological processes non-invasively.Some important mental functions could be encoded by resting-state EEG activity;that is,th...Electroencephalography(EEG)is a powerful tool for investigating the brain bases of human psychological processes non-invasively.Some important mental functions could be encoded by resting-state EEG activity;that is,the intrinsic neural activity not elicited by a specific task or stimulus.The extraction of informative features from resting-state EEG requires complex signal processing techniques.This review aims to demystify the widely used resting-state EEG signal processing techniques.To this end,we first offer a preprocessing pipeline and discuss how to apply it to resting-state EEG preprocessing.We then examine in detail spectral,connectivity,and microstate analysis,covering the oft-used EEG measures,practical issues involved,and data visualization.Finally,we briefly touch upon advanced techniques like nonlinear neural dynamics,complex networks,and machine learning.展开更多
Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network lev...Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.展开更多
BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explo...BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explore the potential characteristics of the brain network and functional connectivity(FC)of SA.METHODS Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly,which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination(MMSE).The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf,and the brain functional network was conducted by DPABINet.The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.RESULTS The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance.The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score,and the FC of the right supramarginal gyrus and right temporal pole:Middle temporal gyrus was the only one decreased and negatively related to MMSE score.All 17 significantly altered FCs of SA were taken into the support vector machine model,and the area under the curve was 0.895.CONCLUSION The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.展开更多
AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished...AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished by differences in dynamic amplitude of low-frequency fluctuations(dALFF)in specific brain regions.METHODS:The resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls.This method was selected to calculate the corresponding dALFF values of each participant,to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine(SVM)permutation test(5000 repetitions).RESULTS:dALFF was lower in POL than in HCs at the right precentral gyrus and right insula.Classification accuracy of the SVM was 89.1%(P<0.001).CONCLUSION:The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK.SVM can correctly classify POL patients and HCs based on dALFF differences.展开更多
同步经颅磁刺激-脑电图(transcranial magnetic stimulation-electroencephalography,TMS-EEG)是一种将经颅磁刺激与脑电记录同步整合的技术。一方面,EEG能够记录TMS脉冲引起的瞬时神经电生理反应,另一方面,TMS脉冲的施加也能基于所记录...同步经颅磁刺激-脑电图(transcranial magnetic stimulation-electroencephalography,TMS-EEG)是一种将经颅磁刺激与脑电记录同步整合的技术。一方面,EEG能够记录TMS脉冲引起的瞬时神经电生理反应,另一方面,TMS脉冲的施加也能基于所记录的EEG信号来进行状态依赖的精准调控。本文结合这两个特点提出并系统梳理了同步TMS-EEG在心理学研究中的三种主要应用模式:神经生理评估、因果性揭示神经机制以及大脑闭环调控。文章将围绕这三条主线,区分并比较不同模式在工作机制、实验方案与应用目标上的差异,并结合近10年的心理学相关研究,梳理各模式已有研究的主要发现,以期为应用同步TMS-EEG技术提供清晰的理论框架与实践指南。展开更多
BACKGROUND Very late-onset schizophrenia-like psychosis(VLOSLP)is a subtype of schizophrenia spectrum disorders in which individuals experience psychotic symptoms for the first time after the age of 60.The incidence o...BACKGROUND Very late-onset schizophrenia-like psychosis(VLOSLP)is a subtype of schizophrenia spectrum disorders in which individuals experience psychotic symptoms for the first time after the age of 60.The incidence of VLOSLP shows a linear relationship with increasing age.However,no studies have reported alterations in spontaneous brain activity among VLOSLP patients and their correlation with cognitive function and clinical symptoms.AIM To explore VLOSLP brain activity and correlations with cognitive function and clinical symptoms using resting-state functional magnetic resonance imaging.METHODS This study included 33 VLOSLP patients and 34 healthy controls.The cognitive assessment utilized the Mini Mental State Examination,Montreal Cognitive Assessment,and the Repeatable Battery for the Assessment of Neuropsychological Status(RBANS).Clinical characteristic acquisition was performed via the Positive and Negative Syndrome Scale(PANSS).All participants were scanned via resting-state functional magnetic resonance imaging,and the data were processed using amplitude of low-frequency fluctuations(ALFF),fractional ALFF(fALFF),regional homogeneity,and voxelmirrored homotopic connectivity(VMHC).RESULTS The VLOSLP group presented decreased ALFF values in the left cuneus,right precuneus,right precentral gyrus,and left paracentral lobule;increased fALFF values in the left caudate nucleus;decreased fALFF values in the right calcarine fissure and surrounding cortex(CAL)and right precuneus;increased regional homogeneity values in the right putamen;and decreased VMHC values in the bilateral CAL,bilateral superior temporal gyrus,and bilateral cuneus.In the VLOSLP group,ALFF values in the right precuneus were negatively correlated with Mini Mental State Examination score and PANSS positive subscale score,and VMHC values in the bilateral CAL were negatively correlated with the RBANS total score,RBANS delayed memory score,and PANSS positive subscale score.CONCLUSION The changes of brain activity in VLOSLP are concentrated in the right precuneus and bilateral CAL regions,which may be associated with cognitive impairment and clinically positive symptoms.展开更多
Pain,as a common symptom,seriously affects the patient's health.The aim of this work was to study the physiological responses of the brain and identify the features of Electroencephalography(EEG)signals related to...Pain,as a common symptom,seriously affects the patient's health.The aim of this work was to study the physiological responses of the brain and identify the features of Electroencephalography(EEG)signals related to friction pain.The results showed that the primary brain activation evoked by friction pain was located in the Prefrontal Cortex(PFC).The activation area decreased,and the negative activation intensity in the PFC region increased with increasing intensity of pain.The inhibitory interactions between different brain regions,especially between the PFC and primary somatosensory cortex(SI)regions were enhanced,and excitatory-inhibitory connections between the medial and lateral pain pathways were balanced during pain perception.The percentage power spectral density of theαrhythm(Dα),dominant singularity strength(αpeak)and longest vertical line(Vmax)of EEG signals induced by pain significantly decreased,and the percent-age power spectral density of theβrhythm(Dβ)significantly increased.The combination of multiple features of Dα,Dβ,αpeak and Vmax could significantly improve the average recognition accuracy of different pain states.This study elucidated the neural processing mechanisms of friction-induced pain,and EEG features associated with friction pain were extracted and recognized.It was helpful to study the brain feedback mechanisms of pain and control signals of Brain-Computer Interface(BCI)system related to pain.展开更多
Automated detection of Motor Imagery(MI)tasks is extremely useful for prosthetic arms and legs of stroke patients for their rehabilitation.Prediction of MI tasks can be performed with the help of Electroencephalogram(...Automated detection of Motor Imagery(MI)tasks is extremely useful for prosthetic arms and legs of stroke patients for their rehabilitation.Prediction of MI tasks can be performed with the help of Electroencephalogram(EEG)signals recorded by placing electrodes on the scalp of subjects;however,accurate prediction of MI tasks remains a challenge due to noise that is incurred during the EEG signal recording process,the extraction of a feature vector with high interclass variance,and accurate classification.The proposed method consists of preprocessing,feature extraction,and classification.First,EEG signals are denoised using a bandpass filter followed by Independent Component Analysis(ICA).Multiple channels are combined to form a single surrogate channel.Short Time Fourier Transform(STFT)is then applied to convert time domain EEG signals into the frequency domain.Handcrafted and automated features are extracted from EEG signals and then concatenated to form a single feature vector.We propose a customized two-dimensional Convolutional Neural Network(CNN)for automated feature extraction with high interclass variance.Feature selection is performed using Particle Swarm Optimization(PSO)to obtain optimal features.The final feature vector is passed to three different classifiers:Support Vector Machine(SVM),Random Forest(RF),and Long Short-Term Memory(LSTM).The final decision is made using the Model-Agnostic Meta Learning(MAML).The Proposed method has been tested on two datasets,including PhysioNet and BCI Competition IV-2a,and it achieved better results in terms of accuracy and F1 score than existing state-of-the-art methods.The proposed framework achieved an accuracy and F1 score of 96%on the PhysioNet dataset and 95.5%on the BCI Competition IV,dataset 2a.We also present SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM)explainable techniques to enhance model interpretability in a clinical setting.展开更多
Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging（RS-fMRI） is a powerful technique for exploring this activity.With good spatial an...Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging（RS-fMRI） is a powerful technique for exploring this activity.With good spatial and temporal resolution,RS-fMRI is a promising approach for accurate localization of the focus of seizure activity.Although simultaneous electroencephalogram-fMRI has been performed with patients in the resting state,most studies focused on activation.This mini-review focuses on RS-fMRI alone,including its computational methods and its application to epilepsy.展开更多
Tension-type headache（TTH） is the most prevalent type of primary headache. Many studies have shown that the pathogenesis of primary headache is associated with fine structural or functional changes. However, these s...Tension-type headache（TTH） is the most prevalent type of primary headache. Many studies have shown that the pathogenesis of primary headache is associated with fine structural or functional changes. However, these studies were mainly based on migraine. The present study aimed to investigate whether TTH patients show functional disturbances compared with healthy subjects. We used restingstate functional magnetic resonance imaging（f MRI） and regional homogeneity（Re Ho） analysis to identify changes in the local synchronization of spontaneous activity in patients with TTH. Ten patients with TTH and 10 age-, gender-, and education-matched healthy controls participated in the study. After demographic and clinical characteristics were acquired, a 3.0-T MRI system was used to obtain restingstate f MRIs. Compared with healthy controls, the TTH group exhibited significantly lower Re Ho values in the bilateral caudate nucleus, the precuneus, the putamen, the left middle frontal gyrus, and the superior frontal gyrus. There was no correlation between mean Re Ho values in TTH patients and duration of TTH, number of attacks, duration of daily attacks, Visual Analogue Scale score, or Headache Impact Test-6 score. These results suggest that TTHpatients exhibit reduced synchronization of neuronal activity in multiple regions involved in the integration and processing of pain signals.展开更多
Objective Little is known about the brain systems that contribute to vulnerability to post-traumatic stress disorder （PTSD）. Comparison of the resting-state patterns of intrinsic functional synchronization, as measu...Objective Little is known about the brain systems that contribute to vulnerability to post-traumatic stress disorder （PTSD）. Comparison of the resting-state patterns of intrinsic functional synchronization, as measured by functional magnetic resonance imaging （fMRI）, between groups with and without PTSD following a traumatic event can help identify the neural mechanisms of the disorder and targets for intervention. Methods Fifty-four PTSD patients and 72 matched traumatized subjects who experienced the 2008 Sichuan earthquake were imaged with blood oxygen level-dependent （BOLD） fMRI and analyzed using the measure of regional homogeneity （ReHo） during the resting state. Results PTSD patients presented enhanced ReHo in the left inferior parietal lobule and right superior frontal gyrus, and reduced ReHo in the right middle temporal gyrus and lingual gyrus, relative to traumatized individuals without PTSD. Conclusion Our findings showed that abnormal brain activity exists under resting conditions in PTSD patients who had been exposed to a major earthquake. Alterations in the local functional connectivity of cortical regions are likely to contribute to the neural mechanisms underlying PTSD.展开更多
Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the...Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.展开更多
Mood disorders/psychosis have been associated with dysfunctions in the default mode network(DMN).However,the relative contributions of DMN regions to state and trait disturbances in pediatric bipolar disorder(PBD)rema...Mood disorders/psychosis have been associated with dysfunctions in the default mode network(DMN).However,the relative contributions of DMN regions to state and trait disturbances in pediatric bipolar disorder(PBD)remain unclear.The aim of this study was to investigate the possible mechanisms of PBD through brain imaging and explore the influence of psychotic symptoms on functional alterations in PBD patients.Twenty-nine psychotic and 26 non-psychotic PBD patients,as well as 19 age-and sex-matched healthy controls underwent a restingstate functional MRI scan and the data were analyzed by independent component analysis.The DMN component from the fMRI data was extracted for each participant.Spearman's rank correlation analysis was performed between aberrant connectivity and clinical measurements.The results demonstrated that psychotic PBD was characterized by aberrant DMN connectivity in the anterior cingulate cortex/medial prefrontal cortex,bilateral caudate nucleus,bilateral angular gyri,and left middle temporal gyrus,while non-psychotic PBD was not,suggesting further impairment with the development of psychosis.In summary,we demonstrated unique impairment in DMN functional connectivity in the psychotic PBD group.These specific neuroanatomical abnormalities may shed light on the underlying pathophysiology and presentation of PBD.展开更多
Abstract Previous studies have suggested that cortical functional reorganization is associated with motor recovery after stroke and that normal afferent sensory information is very important in that process. In this s...Abstract Previous studies have suggested that cortical functional reorganization is associated with motor recovery after stroke and that normal afferent sensory information is very important in that process. In this study, we selected patients who had a stroke in or under the thalamus, with potentially impaired afferent sensory information and analyzed the differences between these patients and healthy controls at three levels： brain regions, the functional con- nectivity between brain areas, and the whole-brain func- tional network. Compared with healthy controls, regionalhomogeneities in the left middle temporal gyrus decreased and functional connectivity between the left middle tem- poral gyrus and the stroke area increased in the patients. However, there was no significant change in the whole- brain functional network. By focusing on stroke located in or under the thalamus, our study contributes to wider inquiries into understanding and treating stroke.展开更多
基金This study received financial support from the Jilin Province Health and Technology Capacity Enhancement Project(Project Number:222Lc132).
文摘Objective: This study investigates the auxiliary role of resting-state electroencephalography (EEG) in the clinical diagnosis of attention-deficit hyperactivity disorder (ADHD) using machine learning techniques. Methods: Resting-state EEG recordings were obtained from 57 children, comprising 28 typically developing children and 29 children diagnosed with ADHD. The EEG signal data from both groups were analyzed. To ensure analytical accuracy, artifacts and noise in the EEG signals were removed using the EEGLAB toolbox within the MATLAB environment. Following preprocessing, a comparative analysis was conducted using various ensemble learning algorithms, including AdaBoost, GBM, LightGBM, RF, XGB, and CatBoost. Model performance was systematically evaluated and optimized, validating the superior efficacy of ensemble learning approaches in identifying ADHD. Conclusion: Applying machine learning techniques to extract features from resting-state EEG signals enabled the development of effective ensemble learning models. Differential entropy and energy features across multiple frequency bands proved particularly valuable for these models. This approach significantly enhances the detection rate of ADHD in children, demonstrating high diagnostic efficacy and sensitivity, and providing a promising tool for clinical application.
基金supported by the National Natural Science Foundation of China,No.82071909(to GF)the Natural Science Foundation of Liaoning Province,No.2023-MS-07(to HL)。
文摘Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.
基金funded by the National Natural Science Foundation of China(82101527,32160190)the Science and Technology Project in Guizhou Province(Grant No.QKHJC-ZK[2021]No.408)the Science and Technology Foundation of the Guizhou Provincial Health Commission(gzwkj2021-026).
文摘Background Epilepsy is one of the common clinical disorders with comorbid anxiety and depression that severely afects their quality of life and increases their suicidality,while screening for anxiety and depression currently lacks objective identifers.This study aimed to analyze the characteristics of the electroencephalogram(EEG)power spectrum in patients with epilepsy with comorbid anxiety and depression,utilizing resting EEG data.Methods Resting EEG data were collected under standard conditions from two groups:patients with epilepsy comorbid with anxiety and depression(n=42)and patients without comorbidities(n=45).EEG power was calculated using data processing with EEGLAB and MATLAB.This study compared the absolute and relative powers of theδ,θ,α,β,andγfrequency bands,as well as the values of(δ+θ)/(α+β),between the two groups.Additionally,the correlation between the EEG power of each frequency band and anxiety and depression scores was analyzed.Results 1)Among individuals with epilepsy comorbid with anxiety and depression,lower absolute power ofδ,α,andθat specifc sites was observed(P<0.05),along with lower relative power ofθat certain sites(P<0.05).Conversely,higher relative power ofβandγat specifc sites was noted in those with comorbidities(P<0.05).2)There was no statistically signifcant diference in the values of(δ+θ)/(α+β)between the two groups(P>0.05).3)Depression scores exhibited a negative correlation withθabsolute power at the T3 and T4 sites(P<0.05),while showing a positive correlation withβrelative power at the C4 and T6 sites(P<0.05).Anxiety scores displayed a positive correlation withβrelative power at the F4,C3,C4 and T6 sites andγrelative power at F8 site(P<0.05).Conclusions The fndings suggest that comorbid anxiety and depression may impact resting EEG power spectra in individuals with epilepsy,particularly in regions exhibiting altered network connectivity.Furthermore,a positive correlation was observed between anxiety and depression scores andβrelative power in the right central and right posterior temporal regions,indicating potential screening utility.
基金supported by the National Natural Science Foundation of China(Grant No.31822025,No.31671141)
文摘Electroencephalography(EEG)is a powerful tool for investigating the brain bases of human psychological processes non-invasively.Some important mental functions could be encoded by resting-state EEG activity;that is,the intrinsic neural activity not elicited by a specific task or stimulus.The extraction of informative features from resting-state EEG requires complex signal processing techniques.This review aims to demystify the widely used resting-state EEG signal processing techniques.To this end,we first offer a preprocessing pipeline and discuss how to apply it to resting-state EEG preprocessing.We then examine in detail spectral,connectivity,and microstate analysis,covering the oft-used EEG measures,practical issues involved,and data visualization.Finally,we briefly touch upon advanced techniques like nonlinear neural dynamics,complex networks,and machine learning.
基金supported by the National Natural Science Foundation of China,Nos.81871836(to MZ),82172554(to XH),and 81802249(to XH),81902301(to JW)the National Key R&D Program of China,Nos.2018YFC2001600(to JX)and 2018YFC2001604(to JX)+3 种基金Shanghai Rising Star Program,No.19QA1409000(to MZ)Shanghai Municipal Commission of Health and Family Planning,No.2018YQ02(to MZ)Shanghai Youth Top Talent Development PlanShanghai“Rising Stars of Medical Talent”Youth Development Program,No.RY411.19.01.10(to XH)。
文摘Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.
基金Supported by the Wuxi Municipal Health Commission Major Project,No.Z202107。
文摘BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explore the potential characteristics of the brain network and functional connectivity(FC)of SA.METHODS Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly,which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination(MMSE).The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf,and the brain functional network was conducted by DPABINet.The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.RESULTS The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance.The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score,and the FC of the right supramarginal gyrus and right temporal pole:Middle temporal gyrus was the only one decreased and negatively related to MMSE score.All 17 significantly altered FCs of SA were taken into the support vector machine model,and the area under the curve was 0.895.CONCLUSION The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.
基金Supported by National Natural Science Foundation of China(No.82160195No.82460203)Key R&D Program of Jiangxi Province(No.20223BBH80014).
文摘AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished by differences in dynamic amplitude of low-frequency fluctuations(dALFF)in specific brain regions.METHODS:The resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls.This method was selected to calculate the corresponding dALFF values of each participant,to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine(SVM)permutation test(5000 repetitions).RESULTS:dALFF was lower in POL than in HCs at the right precentral gyrus and right insula.Classification accuracy of the SVM was 89.1%(P<0.001).CONCLUSION:The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK.SVM can correctly classify POL patients and HCs based on dALFF differences.
文摘同步经颅磁刺激-脑电图(transcranial magnetic stimulation-electroencephalography,TMS-EEG)是一种将经颅磁刺激与脑电记录同步整合的技术。一方面,EEG能够记录TMS脉冲引起的瞬时神经电生理反应,另一方面,TMS脉冲的施加也能基于所记录的EEG信号来进行状态依赖的精准调控。本文结合这两个特点提出并系统梳理了同步TMS-EEG在心理学研究中的三种主要应用模式:神经生理评估、因果性揭示神经机制以及大脑闭环调控。文章将围绕这三条主线,区分并比较不同模式在工作机制、实验方案与应用目标上的差异,并结合近10年的心理学相关研究,梳理各模式已有研究的主要发现,以期为应用同步TMS-EEG技术提供清晰的理论框架与实践指南。
基金Supported by Wuxi Municipal Health Commission Major Project,No.202107and Wuxi Taihu Talent Project,No.WXTTP 2021.
文摘BACKGROUND Very late-onset schizophrenia-like psychosis(VLOSLP)is a subtype of schizophrenia spectrum disorders in which individuals experience psychotic symptoms for the first time after the age of 60.The incidence of VLOSLP shows a linear relationship with increasing age.However,no studies have reported alterations in spontaneous brain activity among VLOSLP patients and their correlation with cognitive function and clinical symptoms.AIM To explore VLOSLP brain activity and correlations with cognitive function and clinical symptoms using resting-state functional magnetic resonance imaging.METHODS This study included 33 VLOSLP patients and 34 healthy controls.The cognitive assessment utilized the Mini Mental State Examination,Montreal Cognitive Assessment,and the Repeatable Battery for the Assessment of Neuropsychological Status(RBANS).Clinical characteristic acquisition was performed via the Positive and Negative Syndrome Scale(PANSS).All participants were scanned via resting-state functional magnetic resonance imaging,and the data were processed using amplitude of low-frequency fluctuations(ALFF),fractional ALFF(fALFF),regional homogeneity,and voxelmirrored homotopic connectivity(VMHC).RESULTS The VLOSLP group presented decreased ALFF values in the left cuneus,right precuneus,right precentral gyrus,and left paracentral lobule;increased fALFF values in the left caudate nucleus;decreased fALFF values in the right calcarine fissure and surrounding cortex(CAL)and right precuneus;increased regional homogeneity values in the right putamen;and decreased VMHC values in the bilateral CAL,bilateral superior temporal gyrus,and bilateral cuneus.In the VLOSLP group,ALFF values in the right precuneus were negatively correlated with Mini Mental State Examination score and PANSS positive subscale score,and VMHC values in the bilateral CAL were negatively correlated with the RBANS total score,RBANS delayed memory score,and PANSS positive subscale score.CONCLUSION The changes of brain activity in VLOSLP are concentrated in the right precuneus and bilateral CAL regions,which may be associated with cognitive impairment and clinically positive symptoms.
基金National Natural Science Foundation of China(grant number:52375224)Natural Science Foundation of Jiangsu Province(grant number:BK20242086)+2 种基金Priority Academic Program Development of Jiangsu Higher Education Institutions,a project supported by"the Fundamental Research Funds for the Central Universities"(grant number:202410976)Graduate Innovation Program of China University of Mining and Technology(grant number:2024WLKXJ075)Postgraduate Research&Practice Innovation Program of Jiangsu Province(grant number:KYCX24_2719).
文摘Pain,as a common symptom,seriously affects the patient's health.The aim of this work was to study the physiological responses of the brain and identify the features of Electroencephalography(EEG)signals related to friction pain.The results showed that the primary brain activation evoked by friction pain was located in the Prefrontal Cortex(PFC).The activation area decreased,and the negative activation intensity in the PFC region increased with increasing intensity of pain.The inhibitory interactions between different brain regions,especially between the PFC and primary somatosensory cortex(SI)regions were enhanced,and excitatory-inhibitory connections between the medial and lateral pain pathways were balanced during pain perception.The percentage power spectral density of theαrhythm(Dα),dominant singularity strength(αpeak)and longest vertical line(Vmax)of EEG signals induced by pain significantly decreased,and the percent-age power spectral density of theβrhythm(Dβ)significantly increased.The combination of multiple features of Dα,Dβ,αpeak and Vmax could significantly improve the average recognition accuracy of different pain states.This study elucidated the neural processing mechanisms of friction-induced pain,and EEG features associated with friction pain were extracted and recognized.It was helpful to study the brain feedback mechanisms of pain and control signals of Brain-Computer Interface(BCI)system related to pain.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2601).
文摘Automated detection of Motor Imagery(MI)tasks is extremely useful for prosthetic arms and legs of stroke patients for their rehabilitation.Prediction of MI tasks can be performed with the help of Electroencephalogram(EEG)signals recorded by placing electrodes on the scalp of subjects;however,accurate prediction of MI tasks remains a challenge due to noise that is incurred during the EEG signal recording process,the extraction of a feature vector with high interclass variance,and accurate classification.The proposed method consists of preprocessing,feature extraction,and classification.First,EEG signals are denoised using a bandpass filter followed by Independent Component Analysis(ICA).Multiple channels are combined to form a single surrogate channel.Short Time Fourier Transform(STFT)is then applied to convert time domain EEG signals into the frequency domain.Handcrafted and automated features are extracted from EEG signals and then concatenated to form a single feature vector.We propose a customized two-dimensional Convolutional Neural Network(CNN)for automated feature extraction with high interclass variance.Feature selection is performed using Particle Swarm Optimization(PSO)to obtain optimal features.The final feature vector is passed to three different classifiers:Support Vector Machine(SVM),Random Forest(RF),and Long Short-Term Memory(LSTM).The final decision is made using the Model-Agnostic Meta Learning(MAML).The Proposed method has been tested on two datasets,including PhysioNet and BCI Competition IV-2a,and it achieved better results in terms of accuracy and F1 score than existing state-of-the-art methods.The proposed framework achieved an accuracy and F1 score of 96%on the PhysioNet dataset and 95.5%on the BCI Competition IV,dataset 2a.We also present SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM)explainable techniques to enhance model interpretability in a clinical setting.
基金supported by National Natural Science Foundation of Inner Mongolia Autonomous Region(2009MS1163)National Natural Science Foundation of China(81020108022,30770594)
文摘Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging（RS-fMRI） is a powerful technique for exploring this activity.With good spatial and temporal resolution,RS-fMRI is a promising approach for accurate localization of the focus of seizure activity.Although simultaneous electroencephalogram-fMRI has been performed with patients in the resting state,most studies focused on activation.This mini-review focuses on RS-fMRI alone,including its computational methods and its application to epilepsy.
基金supported by the National Natural Science Foundation of China (81071140)
文摘Tension-type headache（TTH） is the most prevalent type of primary headache. Many studies have shown that the pathogenesis of primary headache is associated with fine structural or functional changes. However, these studies were mainly based on migraine. The present study aimed to investigate whether TTH patients show functional disturbances compared with healthy subjects. We used restingstate functional magnetic resonance imaging（f MRI） and regional homogeneity（Re Ho） analysis to identify changes in the local synchronization of spontaneous activity in patients with TTH. Ten patients with TTH and 10 age-, gender-, and education-matched healthy controls participated in the study. After demographic and clinical characteristics were acquired, a 3.0-T MRI system was used to obtain restingstate f MRIs. Compared with healthy controls, the TTH group exhibited significantly lower Re Ho values in the bilateral caudate nucleus, the precuneus, the putamen, the left middle frontal gyrus, and the superior frontal gyrus. There was no correlation between mean Re Ho values in TTH patients and duration of TTH, number of attacks, duration of daily attacks, Visual Analogue Scale score, or Headache Impact Test-6 score. These results suggest that TTHpatients exhibit reduced synchronization of neuronal activity in multiple regions involved in the integration and processing of pain signals.
基金supported by the National Natural Science Foundation of China (30830046,30625024, 81171286)the National Science and Technology Program of China (2007BAI17B02)+2 种基金the National Basic Research Development Program (973 Program) of China(2009CB918303)the Science and Technology Program of the Ministry of Education, China (20090162110011)the National High-Tech Research and Development Program of China (863 program:2008AA02Z408)
文摘Objective Little is known about the brain systems that contribute to vulnerability to post-traumatic stress disorder （PTSD）. Comparison of the resting-state patterns of intrinsic functional synchronization, as measured by functional magnetic resonance imaging （fMRI）, between groups with and without PTSD following a traumatic event can help identify the neural mechanisms of the disorder and targets for intervention. Methods Fifty-four PTSD patients and 72 matched traumatized subjects who experienced the 2008 Sichuan earthquake were imaged with blood oxygen level-dependent （BOLD） fMRI and analyzed using the measure of regional homogeneity （ReHo） during the resting state. Results PTSD patients presented enhanced ReHo in the left inferior parietal lobule and right superior frontal gyrus, and reduced ReHo in the right middle temporal gyrus and lingual gyrus, relative to traumatized individuals without PTSD. Conclusion Our findings showed that abnormal brain activity exists under resting conditions in PTSD patients who had been exposed to a major earthquake. Alterations in the local functional connectivity of cortical regions are likely to contribute to the neural mechanisms underlying PTSD.
基金supported by the Natural Science Foundation of Guangdong Province,No.2016A030313180(to FCJ)
文摘Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.
基金supported by National Natural Science Foundation of China (81171291, 81371531, 81571344, 81871344)the Natural Science Foundation of Jiangsu Province, China (BK20161109)+2 种基金the Key Program for Guangming Lu (BWS11J063, and 10z026)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (18KJB190003)the Postdoctoral Science Foundation of China (2014M552700)
文摘Mood disorders/psychosis have been associated with dysfunctions in the default mode network(DMN).However,the relative contributions of DMN regions to state and trait disturbances in pediatric bipolar disorder(PBD)remain unclear.The aim of this study was to investigate the possible mechanisms of PBD through brain imaging and explore the influence of psychotic symptoms on functional alterations in PBD patients.Twenty-nine psychotic and 26 non-psychotic PBD patients,as well as 19 age-and sex-matched healthy controls underwent a restingstate functional MRI scan and the data were analyzed by independent component analysis.The DMN component from the fMRI data was extracted for each participant.Spearman's rank correlation analysis was performed between aberrant connectivity and clinical measurements.The results demonstrated that psychotic PBD was characterized by aberrant DMN connectivity in the anterior cingulate cortex/medial prefrontal cortex,bilateral caudate nucleus,bilateral angular gyri,and left middle temporal gyrus,while non-psychotic PBD was not,suggesting further impairment with the development of psychosis.In summary,we demonstrated unique impairment in DMN functional connectivity in the psychotic PBD group.These specific neuroanatomical abnormalities may shed light on the underlying pathophysiology and presentation of PBD.
基金supported by grants from the National Natural Science Foundation of China(31230032,31171083, and 31471071)Fundamental Research Funds for the Central Universities of China(WK2070000033)+1 种基金the Natural Science Foundation of Anhui Province,China(1208085MH179)Hefei Science Center,CAS "User with Potential"(2015HSC-UP017)
文摘Abstract Previous studies have suggested that cortical functional reorganization is associated with motor recovery after stroke and that normal afferent sensory information is very important in that process. In this study, we selected patients who had a stroke in or under the thalamus, with potentially impaired afferent sensory information and analyzed the differences between these patients and healthy controls at three levels： brain regions, the functional con- nectivity between brain areas, and the whole-brain func- tional network. Compared with healthy controls, regionalhomogeneities in the left middle temporal gyrus decreased and functional connectivity between the left middle tem- poral gyrus and the stroke area increased in the patients. However, there was no significant change in the whole- brain functional network. By focusing on stroke located in or under the thalamus, our study contributes to wider inquiries into understanding and treating stroke.
