Vulnerable brain regions in adolescent major depressive disorder:A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis

BACKGROUND Adolescent major depressive disorder(MDD)is a significant mental health concern that often leads to recurrent depression in adulthood.Resting-state functional magnetic resonance imaging(rs-fMRI)offers unique insights into the neural mechanisms underlying this condition.However,despite previous research,the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.AIM To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation(ALE)meta-analysis.METHODS We performed a comprehensive literature search through July 12,2023,for studies investigating brain functional changes in adolescent MDD patients.We utilized regional homogeneity(ReHo),amplitude of low-frequency fluctuations(ALFF)and fractional ALFF(fALFF)analyses.We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls(HCs)using ALE.RESULTS Ten studies(369 adolescent MDD patients and 313 HCs)were included.Combining the ReHo and ALFF/fALFF data,the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs(voxel size:648 mm3,P<0.05),and no brain region exhibited increased activity.Based on the ALFF data,we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients(voxel size:736 mm3,P<0.05),with no regions exhibiting increased activity.CONCLUSION Through ALE meta-analysis,we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients,increasing our understanding of the neuropathology of affected adolescents.

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

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.

Electroencephalogram findings in 10 patients with post-stroke epilepsy:A retrospective study

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.

The development of brain functional connectivity networks revealed by resting-state functional magnetic resonance imaging

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.

Resting-state network complexity and magnitude changes in neonates with severe hypoxic ischemic encephalopathy

Resting-state functional magnetic resonance imaging has revealed disrupted brain network connectivity in adults and teenagers with cerebral palsy. However, the specific brain networks implicated in neonatal cases remain poorly understood. In this study, we recruited 14 termborn infants with mild hypoxic ischemic encephalopathy and 14 term-born infants with severe hypoxic ischemic encephalopathy from Changzhou Children's Hospital, China. Resting-state functional magnetic resonance imaging data showed efficient small-world organization in whole-brain networks in both the mild and severe hypoxic ischemic encephalopathy groups. However, compared with the mild hypoxic ischemic encephalopathy group, the severe hypoxic ischemic encephalopathy group exhibited decreased local efficiency and a low clustering coefficient. The distribution of hub regions in the functional networks had fewer nodes in the severe hypoxic ischemic encephalopathy group compared with the mild hypoxic ischemic encephalopathy group. Moreover, nodal efficiency was reduced in the left rolandic operculum, left supramarginal gyrus, bilateral superior temporal gyrus, and right middle temporal gyrus. These results suggest that the topological structure of the resting state functional network in children with severe hypoxic ischemic encephalopathy is clearly distinct from that in children with mild hypoxic ischemic encephalopathy, and may be associated with impaired language, motion, and cognition. These data indicate that it may be possible to make early predictions regarding brain development in children with severe hypoxic ischemic encephalopathy, enabling early interventions targeting brain function. This study was approved by the Regional Ethics Review Boards of the Changzhou Children's Hospital(approval No. 2013-001) on January 31, 2013. Informed consent was obtained from the family members of the children. The trial was registered with the Chinese Clinical Trial Registry(registration number: ChiCTR1800016409) and the protocol version is 1.0.

Global Functional Network Connectivity Disturbances in Parkinson’s Disease with Mild Cognitive Impairment by Resting-State Functional MRI

Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels:functional connectivity analysis within resting state networks(RSNs)and functional network connectivity(FNC)analysis.Using group independent component analysis(ICA)on rs-fMRI data acquired from 30 participants(14 healthy controls and 16 PD patients with MCI),16 RSNs were identified,and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups.Compared to controls,patients with PD showed decreased functional connectivity within putamen network,thalamus network,cerebellar network,attention network,and self-referential network,and increased functional connectivity within execution network.Globally disturbed,mostly increased functional connectivity of FNC was observed in PD group,and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs.Cerebellar network showed decreased functional connectivity with caudate network,insular network,and self-referential network.In general,decreased functional connectivity within RSNs and globally disturbed,mostly increased functional connectivity of FNC may be characteristics of PD.Increased functional connectivity within execution network may be an early marker of PD.The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN,contributing to the understanding of the neural mechanism of PD.

Modulatory effect of International standard Scalp Acupuncture on brain activation in the elderly as revealed by resting-state fMRI

The specific mechanisms by which acupuncture affects the central nervous system are unclear. In the International Standard Scalp Acupuncture system, acupuncture needles are applied at the middle line of the vertex, anterior parietal-temporal oblique line, and the posterior parietal-temporal oblique line. We conducted a single-arm prospective clinical trial in which seven healthy elderly volunteers (three men and four women;50–70 years old) received International Standard Scalp Acupuncture at MS5 (the mid-sagittal line between Baihui (DU20) and Qianding (DU21)), the left MS6 (line joining Sishencong (EX-HN1) and Xuanli (GB6)), and the left MS7 (line joining DU20 and Qubin (GB7)). After acupuncture, resting-state functional magnetic resonance imaging demonstrated changes in the fractional amplitude of low frequency fluctuations and regional homogeneity in various areas, showing remarkable enhancement of regional homogeneity in the bilateral anterior cingulate, left medial frontal gyrus, supramarginal gyrus, right middle frontal gyrus, and inferior frontal gyrus. Functional connectivity based on a seed region at the right middle frontal gyrus (42, 51, 9) decreased at the bilateral medial superior frontal gyrus. Our data preliminarily indicates that the international standard scalp acupuncture in healthy elderly participants specifcally enhances the correlation between the brain regions involved in cognition and implementation of the brain network regulation system and the surrounding adjacent brain regions. The study was approved by the Ethics Committee of the China-Japan Union Hospital at Jilin University, China, on July 18, 2016 (approval No. 2016ks043).

Human Mirror Neuron System (hMNS) Specific Differences in Resting-State Functional Connectivity in Self-Reported Democrats and Republicans: A Pilot Study

In light of ever-present partisan division in the US political system, it is critical that researchers gain a better under-standing of potential biological differences that exist between self-professed Democrats and Republicans. In the current pilot experiment, we examined differences within the human mirror neuron system (hMNS), a network linked to a host of social and emotional abilities, in a small group of self-identified Republicans and Democrats. We found clear differences between these two groups with respect to resting-state brain connectivity within the hMNS. These neural differences were not systematically related to differences in empathy. Our findings are consistent with the idea that other factors, such as one’s preferential type of social connectivity (broad vs. tight), may have driven the reported findings. These data provide novel insights regarding our knowledge of the biological basis of party identification, and suggest specific directions for future research.

Brain activation and inhibition after acupuncture at Taichong and Taixi: resting-state functional magnetic resonance imaging

Acupuncture can induce changes in the brain. However, the majority of studies to date have focused on a single acupoint at a time. In the present study, we observed activity changes in the brains of healthy volunteers before and after acupuncture atTaichong （LR3） andTaixi （KI3） using resting-state functional magnetic resonance imaging. Fifteen healthy volunteers underwent resting-state functional magnetic resonance imaging of the brain 15 minutes before acupuncture, then received acupuncture atTaichong andTaixi using the nail-pressing needle insertion method, after which the needle was retained in place for 30 minutes. Fifteen minutes after withdrawal of the needle, the volunteers underwent a further session of resting-state functional magnetic res-onance imaging, which revealed that the amplitude of low-frequency lfuctuation, a measure of spontaneous neuronal activity, increased mainly in the cerebral occipital lobe and middle occipital gyrus （Brodmann area 18/19）, inferior occipital gyrus （Brodmann area 18） and cuneus （Brodmann area 18）, but decreased mainly in the gyrus rectus of the frontal lobe （Brodmann area 11）, inferi-or frontal gyrus （Brodmann area 44） and the center of the posterior lobe of the cerebellum. The present ifndings indicate that acupuncture atTaichong andTaixi speciifcally promote blood lfow and activation in the brain areas related to vision, emotion and cognition, and inhibit brain areas related to emotion, attention, phonological and semantic processing, and memory.

Resting-state connectivity in the default mode network and insula during experimental low back pain

Functional magnetic resonance imaging studies have shown that the insular cortex has a signif- icant role in pain identification and information integration, while the default mode network is associated with cognitive and memory-related aspects of pain perception. However, changes in the functional connectivity between the defauk mode network and insula during pain remain unclear. This study used 3.0 T functional magnetic resonance imaging scans in 12 healthy sub- jects aged 24.8 ± 3.3 years to compare the differences in the functional activity and connectivity of the insula and default mode network between the baseline and pain condition induced by intramuscular injection of hypertonic saline. Compared with the baseline, the insula was more functionally connected with the medial prefrontal and lateral temporal cortices, whereas there was lower connectivity with the posterior cingulate cortex, precuneus and inferior parietal lobule in the pain condition. In addition, compared with baseline, the anterior cingulate cortex exhibited greater connectivity with the posterior insula, but lower connectivity with the anterior insula, during the pain condition. These data indicate that experimental low back pain led to dysfunction in the connectivity between the insula and default mode network resulting from an impairment of the regions of the brain related to cognition and emotion, suggesting the impor- tance of the interaction between these regions in pain processing.

Classification of Electroencephalogram Signals Using LSTM and SVM Based on Fast Walsh-Hadamard Transform

Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)techniques.Especially,the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions.From this perspective,an automated AI technique with a digital processing method can be used to improve these signals.This paper proposes two classifiers:long short-term memory(LSTM)and support vector machine(SVM)for the classification of seizure and non-seizure EEG signals.These classifiers are applied to a public dataset,namely the University of Bonn,which consists of 2 classes–seizure and non-seizure.In addition,a fast Walsh-Hadamard Transform(FWHT)technique is implemented to analyze the EEG signals within the recurrence space of the brain.Thus,Hadamard coefficients of the EEG signals are obtained via the FWHT.Moreover,the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings.Also,a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers.The LSTM classifier provides the best performance,with a testing accuracy of 99.00%.The training and testing loss rates for the LSTM are 0.0029 and 0.0602,respectively,while the weighted average precision,recall,and F1-score for the LSTM are 99.00%.The results of the SVM classifier in terms of accuracy,sensitivity,and specificity reached 91%,93.52%,and 91.3%,respectively.The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s,respectively.The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals.Eventually,the proposed classifiers provide high classification accuracy compared to previously published classifiers.

Age-related connectivity differences between attention deficit and hyperactivity disorder patients and typically developing subjects：a resting-state functional MRI study

Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing（TD） subjects using resting state f MRI（rs-f MRI） for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals（27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults）.The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status（i.e.,ADHD or TD） and age（i.e.,child,adolescent,or adult）（P 0.001）.Additional regions were identified at a relaxed threshold（P 0.05）.Many of the identified regions（the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus） were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.

Functional role of frontal electroencephalogram alpha asymmetry in the resting state in patients with depression:A review

Depression is a psychological disorder that affects the general public worldwide.It is particularly important to make an objective and accurate diagnosis of depression,and the measurement methods of brain activity have gradually received increasing attention.Resting electroencephalogram(EEG)alpha asymmetry in patients with depression shows changes in activation of the alpha frequency band of the left and right frontal cortices.In this paper,we review the findings of the relationship between frontal EEG alpha asymmetry in the resting state and depression.Based on worldwide studies,we found the following:(1)Compared with individuals without depression,those with depression showed greater right frontal EEG alpha asymmetry in the resting state.However,the pattern of frontal EEG alpha asymmetry in the resting state in depressive individuals seemed to disappear with age;(2)Compared with individuals without maternal depression,those with maternal depression showed greater right frontal EEG alpha asymmetry in the resting state,which indicated that genetic or experience-based influences have an impact on frontal EEG alpha asymmetry at rest;and(3)Frontal EEG alpha asymmetry in the resting state was stable,and little or no change occurred after antidepressant treatment.Finally,we concluded that the contrasting results may be due to differences in methodology,clinical characteristics,and participant characteristics.

Serum neuronal pentraxin 2 is related to cognitive dysfunction and electroencephalogram slow wave/fast wave frequency ratio in epilepsy

BACKGROUND Cognitive dysfunction in epileptic patients is a high-incidence complication.Its mechanism is related to nervous system damage during seizures,but there is no effective diagnostic biomarker.Neuronal pentraxin 2(NPTX2)is thought to play a vital role in neurotransmission and the maintenance of synaptic plasticity.This study explored how serum NPTX2 and electroencephalogram(EEG)slow wave/fast wave frequency ratio relate to cognitive dysfunction in patients with epilepsy.AIM To determine if serum NPTX2 could serve as a potential biomarker for diagnosing cognitive impairment in epilepsy patients.METHODS The participants of this study,conducted from January 2020 to December 2021,comprised 74 epilepsy patients with normal cognitive function(normal group),37 epilepsy patients with cognitive dysfunction[epilepsy patients with cognitive dysfunction(ECD)group]and 30 healthy people(control group).The minimental state examination(MMSE)scale was used to evaluate cognitive function.We determined serum NPTX2 levels using an enzyme-linked immunosorbent kit and calculated the signal value of EEG regions according to the EEG recording.Pearson correlation coefficient was used to analyze the correlation between serum NPTX2 and the MMSE score.RESULTS The serum NPTX2 level in the control group,normal group and ECD group were 240.00±35.06 pg/mL,235.80±38.01 pg/mL and 193.80±42.72 pg/mL,respectively.The MMSE score was lowest in the ECD group among the three,while no significant difference was observed between the control and normal groups.In epilepsy patients with cognitive dysfunction,NPTX2 level had a positive correlation with the MMSE score(r=0.367,P=0.0253)and a negative correlation with epilepsy duration(r=−0.443,P=0.0061)and the EEG slow wave/fast wave frequency ratio value in the temporal region(r=−0.339,P=0.039).CONCLUSION Serum NPTX2 was found to be related to cognitive dysfunction and the EEG slow wave/fast wave frequency ratio in patients with epilepsy.It is thus a potential biomarker for the diagnosis of cognitive impairment in patients with epilepsy.

视频脑电图与常规脑电图诊断癫痫的早期效能比较

目的比较视频脑电图(VEEG)与常规脑电图(REEG)诊断癫痫的早期效能。方法回顾性分析2019年5月至2023年5月长春市中心医院收治的104例拟诊癫痫患者的临床资料,所有患者均进行VEEG与REEG监测,比较VEEG与REEG监测效果、检出情况及分型、定位诊断。以病史、临床表现及其他辅助检查结果为金标准,比较VEEG与REEG诊断癫痫的早期效能。结果VEEG监测到的痫样放电率、临床发作率均高于REEG,差异有统计学意义(P<0.05)。VEEG癫痫、非癫痫发作检出率均高于REEG,暂不诊断癫痫检出率低于REEG,差异有统计学意义(P<0.05)。41例癫痫患者中,强直阵挛性发作8例,肌阵挛发作7例,复杂部分性发作8例,全面性发作5例,单纯部分性发作6例,失神发作7例;睡眠期出现异常放电24例,清醒期出现异常放电7例,睡眠期和清醒期均出现异常放电10例;明确痫样放电部位32例,包括颞区发作8例,额区发作7例,额颞区发作6例,中央区发作4例,枕区发作4例,颞枕后区发作3例。根据病史、临床表现以及其他辅助检查结果诊断,104例拟诊癫痫患者中,确诊癫痫患者58例,非癫痫患者46例,VEEG早期诊断癫痫的准确度、灵敏度、特异度、阳性预测值、阴性预测值均高于REEG,差异有统计学意义(P<0.05)。结论VEEG可提高痫样放电和临床发作检出率,还能用于癫痫分型和痫灶定位,在癫痫早期诊断中具有较高准确度,值得临床应用推广。

基于多频带路径签名特征的癫痫脑电图信号分类方法

基于脑电图(EEG)信号的癫痫自动检测对癫痫的临床诊断和治疗有很大的帮助。由于大部分癫痫识别算法忽略了EEG信号的时序关系,为此,文中提出了一种基于多频带路径签名特征的癫痫EEG信号分类方法。此方法首先将EEG信号分解成5个不同频段的频带信号,再通过路径签名算法进行特征提取,然后采用局部主成分分析去除特征相关性并进行特征融合,最后将融合特征送入集成分类器中进行预测分类。由于路径签名可以更深入地挖掘EEG信号的相关关系,结合局部主成分分析后,文中方法可以获取更有鉴别性的癫痫分类特征。分别在时长超过2 000 s癫痫发作片段的本地医院私有数据集和开源的CHB-MIT癫痫数据集上,选用10折交叉进行实验验证,结果表明:在私有数据集上,文中方法的平均分类准确率达到97.25%,比经典的基于经验模态分解(EMD)的方法提高了3.44个百分点,比最新的基于长短期记忆网络(LSTM)+卷积神经网络(CNN)的方法提高了1.35个百分点;在CHB-MIT数据集上,文中方法的平均分类准确率达到98.11%,比经典的基于EMD的方法提高了5.20个百分点,比最新的基于LSTM+CNN的方法提高了2.64个百分点;在两个数据集上文中方法的分类准确率均优于其他对比方法。

基于听觉刺激的意识障碍患者脑功能连通性研究

目的目前对意识障碍(DOC)患者的分级评估仍是相关领域的重点和难点。因效性网络可以通过时间序列间的因果关系直观地反映信息传递方向,帮助人们更好地理解患者大脑不同区域之间的信息交互作用。本文结合脑电图和因效性网络探讨听觉刺激下无反应觉醒综合征(VS)患者与最低意识状态(MCS)患者的脑功能连通性差异。方法共纳入23例DOC患者,采集并分析唤名刺激下的脑电信号,通过多元格兰杰因果方法构建脑功能网络,利用脑网络节点度、聚类系数、全局效率以及因果流向性等参量从脑区之间协同工作的角度对比研究听觉刺激下不同意识水平患者的网络特征。结果唤名刺激下MCS患者的脑功能连通性强于VS患者,且呈现出因果流向差异,MCS与VS患者四个脑区的信息传递方向均不相同。结论唤名听觉刺激下MCS患者的信息传递能力强于VS患者;与VS患者相比MCS患者为因果源的电极通道数增多,对其他脑区的信息输出增多。本研究可为DOC患者意识水平的分级评估提供一定的理论依据。

髋或膝关节置换术患者术后苏醒期谵妄的前额脑电特征

目的分析髋或膝关节置换术后发生苏醒期谵妄(ED)患者的前额脑电特征。方法选择择期行髋或膝关节置换术的患者64例,男12例,女52例,年龄≥60岁,BMI 18.5~30.0 kg/m^(2),ASAⅡ或Ⅲ级。术后麻醉苏醒期间,采用重症监护室意识模糊评估方法(CAM-ICU)和Richmond躁动-镇静评分(RASS)量表判断ED发生。根据苏醒期是否发生谵妄将患者分为两组:苏醒期谵妄组(ED组)和苏醒期非谵妄组(非ED组)。收集脑电监测仪中患者苏醒期原始脑电图数据,并截取苏醒前(停药后5~10 min)和完全苏醒后(拔喉罩后15~20 min)两个时间段的数据进行频谱分析。结果有28例(44%)患者发生ED。两组苏醒前与完全苏醒时脑电变化一致:频谱边缘频率(SEF)上升,β、γ波功率升高,α波峰值频率降低。与苏醒前比较,非ED组完全苏醒时θ波、α波功率明显降低(P<0.05),α波峰值功率明显降低(P<0.05),ED组完全清醒时α波功率和α波峰值功率差异无统计学意义。与非ED组比较,ED组苏醒前和完全苏醒时样本熵与排列熵均明显升高(P<0.05)。结论非ED患者在麻醉苏醒期间θ波、α波功率及α波峰值功率均明显降低,而ED患者在麻醉苏醒期间α波功率及α波峰值功率均无明显变化,同时伴有样本熵与排列熵的升高。

基于多尺度卷积和自注意力特征融合的多模态情感识别方法

基于生理信号的情感识别受噪声等因素影响,存在准确率低和跨个体泛化能力弱的问题。对此,提出一种基于脑电(EEG)、心电(ECG)和眼动信号的多模态情感识别方法。首先,对生理信号进行多尺度卷积,获取更高维度的信号特征并减少参数量;其次,在多模态信号特征的融合中使用自注意力机制,以提升关键特征的权重并减少模态之间的特征干扰;最后,使用双向长短期记忆(Bi-LSTM)网络提取融合特征的时序信息并进行分类。实验结果表明,所提方法在效价、唤醒度和效价/唤醒度四分类任务上分别取得90.29%、91.38%和83.53%的识别准确率,相较于脑电单模态和脑电/心电双模态方法,准确率上提升了3.46~7.11和0.92~3.15个百分点。所提方法能够准确识别情感,在个体间的识别稳定性更好。

不同剂量右美托咪定口腔黏膜喷雾或滴鼻用于小儿脑电图检查的镇静效果

目的观察不同剂量右美托咪定(Dex)口腔黏膜喷雾或滴鼻用于小儿脑电图(EEG)检查的镇静效果。方法151例患儿根据Dex口腔黏膜喷雾2.5 ug/kg、3 ug/kg,Dex滴鼻2.5 ug/kg、3 ug/kg,随机分为D1组(38例)、D2组(38例)、D3组(37例)和D4组(38例)。记录患儿给药前(T_(0)),给药后10 min(T_(1))、20 min(T_(2))、30 min(T_(3))、40 min(T_(4))警觉镇静量表(OAA/S)评分、MAP、HR、SpO_(2)。观察患儿镇静一次成功率、诱导时间、检查时间、苏醒时间、不良反应和不同时间点4组患儿的镇静效果和MAP、HR、SpO_(2)。结果D1与D3组、D1与D2组起效时间和D3与D4组的苏醒时间差异有统计学意义(P<0.05);T_(2)时的D1与D2组、D3与D4组和T_(4)时的D3与D4组的OAA/S评分差异有统计学意义(P<0.05);T_(2)时的D1与D2组的MAP差异有统计学意义(P<0.05);T_(1)时的D1与D2组、T_(3)时的D1与D2组和D3与D4组的HR差异有统计学意义(P<0.05)。结论小儿EEG检查前应用Dex 3ug/kg滴鼻,诱导时间快、成功率高、镇静效果好,是一种安全有效的EEG检查前的镇静方法。