Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: a simultaneous recording study

The feasibility of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (RSFC) has already been demonstrated. However the validity of fNIRS-based RSFC has rarely been studied. In the present study, fNIRS and fMRI data were simultaneously acquired from 21 subjects during the resting state. After the spatial correspondence was established between the two imaging modalities by transforming the fMRI data into fNIRS measurements space, the index of Between-Modality-Similarity (BMS) of RSFC was evaluated across multiple spatial scales. First, the RSFC between the bilateral primary motor ROI was quite similar between fNIRS and fMRI for all the subjects (BMS(ROI) = 0.95 ± 0.04 for HbO and BMS(ROI) = 0.86 ± 0.13 for HbR). Second, group-level sensorimotor RSFC maps (0.79 for HbO and 0.74 for HbR) showed higher between-modality similarity than individual-level RSFC maps (0.48 ± 0.16 for HbO and 0.41 ± 0.15 for HbR). Finally, for the first time, we combined fNIRS and graph theory to investigate topological properties of resting-state brain networks. The clustering coefficient (C(p)) and characteristic path length (L(p)) which are the most important network topological parameters, both showed high between-modality similarities (BMS(Cp) = 0.90 ± 0.03 for HbO and 0.90 ± 0.06 for HbR; BMS(Lp) = 0.92 ± 0.04 for HbO and 0.91 ± 0.05 for HbR). In summary, the converged results across all the spatial scales demonstrated that fNIRS is capable of providing comparable RSFC measures to fMRI, and thus provide direct evidence for the validity of the optical brain connectivity and the optical brain network approaches to functional brain integration during resting state.     

Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches

The cognitive activity of the human brain benefits from the functional connectivity of multiple brain regions that form specific, functional brain networks. Recent studies have indicated that the relationship between brain regions can be investigated by examining the temporal interaction (known as functional connectivity) of spontaneous blood oxygen level-dependent (BOLD) signals derived from resting-state functional MRI. Most of these studies plausibly assumed that inter-regional interactions were temporally stationary. However, little is known about the dynamic characteristics of resting-state functional connectivity (RSFC). In this study, we thoroughly examined this question within and between multiple functional brain networks. Twenty-two healthy subjects were scanned in a resting state. Several of the RSFC networks observed, including the default-mode, motor, attention, memory, auditory, visual, language and subcortical networks, were first identified using a conventional voxel-wise correlation analysis with predefined region of interests (ROIs). Then, a variable parameter regression model combined with the Kalman filtering method was employed to detect the dynamic interactions between each ROI and all other brain voxels within each of the RSFC maps extracted above. Experimental results revealed that the functional interactions within each RSFC map showed time-varying properties, and that approximately 10-20% of the voxels within each RSFC map showed significant functional connectivity to each ROI during the scanning session. This dynamic pattern was also observed for the interactions between different functional networks. In addition, the spatial pattern of dynamic connectivity maps obtained from neighboring time points had a high similarity. Overall, this study provides insights into the dynamic properties of resting-state functional networks.     

Static and dynamic functional connectivity in patients with chronic fatigue syndrome: use of arterial spin labelling fMRI

Studies using arterial spin labelling (ASL) have shown that individuals with chronic fatigue syndrome (CFS) have decreased regional cerebral blood flow, which may be associated with changes in functional neural networks. Indeed, recent studies indicate disruptions in functional connectivity (FC) at rest in chronically fatigued patients including perturbations in static FC (sFC), that is average FC at rest between several brain regions subserving neurocognitive, motor and affect‐related networks. Whereas sFC often provides information of functional network reorganization in chronic illnesses, investigations of temporal changes in functional connectivity between multiple brain areas may shed light on the dynamic characteristics of brain network activation associated with such maladies. We used ASL fMRI in 19 patients with CFS and 15 healthy controls (HC) to examine both static and dynamic changes in FC among several a priori selected brain regions during a fatiguing cognitive task. HC showed greater increases than CFS in static FC (sFC) between insula and temporo‐occipital structures and between precuneus and thalamus/striatum. Furthermore, inferior frontal gyrus connectivity to cerebellum, occipital and temporal structures declined in HC but increased in CFS. Patients also showed lower dynamic FC (dFC) between hippocampus and right superior parietal lobule. Both sFC and dFC correlated with task‐related fatigue increases. These data provide the first evidence that perturbations in static and dynamic FC may underlie chronically fatigued patients’ report of task‐induced fatigue. Further research will determine whether such changes in sFC and dFC are also characteristic for other fatigued individuals, including patients with chronic pain, cancer and multiple sclerosis.     

SD-CNN: A static-dynamic convolutional neural network for functional brain networks

Static functional connections (sFCs) and dynamic functional connections (dFCs) have been widely used in the resting-state functional MRI (rs-fMRI) analysis. sFCs, calculated based on entire rs-fMRI scans, can accurately describe the static topology of the brain network. dFCs, estimated by dividing rs-fMRI scans into a series of short sliding windows, are used to reveal time-varying changes in FC patterns. Currently, how to jointly use sFCs and dFCs to identify brain diseases under the framework of deep learning is still a hot issue. To this end, we propose a static-dynamic convolutional neural network for functional brain networks, which involves a static pathway and a dynamic pathway for taking full advantages of sFCs and dFCs. Specifically, the static pathway, using high-resolution convolution filters (i.e., convolution filters with a high number of channels) at a single adjacency matrix of sFCs, is performed to capture static FC patterns. The dynamic pathway, using low-resolution convolution filters at each adjacency matrix of dFCs, is performed to capture time-varying FC patterns. Two types of diffusion connections are used in this model for encouraging the transfer of information between the static pathway and the dynamic pathway, which can make the learned features more discriminative. Furthermore, a static and dynamic combination classifier is introduced to combine features from two pathways for identifying brain diseases. Experiments on two real datasets demonstrate the effectiveness and advantages of our proposed method.     

首发精神分裂症患者大尺度脑网络内及网络间静息态功能连接异常模式

目的 观察首发精神分裂症患者大尺度脑网络内及网络间静息态功能连接（FC）异常模式。方法 前瞻性纳入198例首发精神分裂症患者（精神分裂症组）及199名健康志愿者（正常对照组），采集头部高分辨率结构MRI及静息态功能MRI，基于Yeo七网络模板观察比较组间感觉运动网络（SMN）、背侧注意网络（DAN）、皮层下网络（SC）、默认网络（DMN）、腹侧注意网络（VAN）、额顶网络（FPN）和视觉网络（VN）内部及其间的FC模式。结果 相比正常对照组，精神分裂症组SC内部、SMN内部、SMN与DAN之间、SMN与VAN之间及SMN与DMN之间FC减低（FDR校正P均<0.05）。结论 首发精神分裂症患者多种大尺度脑网络内及其间静息态FC减低。     

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

BackgroundAccumulating studies have indicated a wide range of brain alterations with respect to the structure and function of classic trigeminal neuralgia (CTN). Given the dynamic nature of pain experience, the exploration of temporal fluctuations in interregional activity covariance may enhance the understanding of pain processes in the brain. The present study aimed to characterize the temporal features of functional connectivity (FC) states as well as topological alteration in CTN.MethodsResting-state functional magnetic resonance imaging and three-dimensional T1-weighted images were obtained from 41 CTN patients and 43 matched healthy controls (HCs). After group independent component analysis, sliding window based dynamic functional network connectivity (dFNC) analysis was applied to investigate specific FC states and related temporal properties. Then, the dynamics of the whole brain topological organization were estimated by calculating the coefficient of variation of graph-theoretical properties. Further correlation analyses were performed between all these measurements and clinical data.ResultsTwo distinct states were identified. Of these, the state 2, characterized by complicated coupling between default mode network (DMN) and cognitive control network (CC) and tight connections within DMN, was expressed more in CTN patients and presented as increased fractional windows and dwell time. Moreover, patients switched less frequently between states than HCs. Regarding the dynamic topological analysis, disruptions in global graph-theoretical properties (including network efficiency and small-worldness) were observed in patients, coupled with decreased variability in nodal efficiency of anterior cingulate cortex (ACC) in the salience network (SN) and the thalamus and caudate nucleus in the subcortical network (SC). The variation of topological properties showed negative correlation with disease duration and attack frequency.ConclusionsThe present study indicated disrupted flexibility of brain topological organization under persistent noxious stimulation and further highlighted the important role of “dynamic pain connectome” regions (including DMN/CC/SN) in the pathophysiology of CTN from the temporal fluctuation aspect. Additionally, the findings provided supplementary evidence for current knowledge about the aberrant cortical-subcortical interaction in pain development.Supplementary InformationThe online version contains supplementary material available at 10.1186/s10194-021-01354-z.     

静息态功能磁共振成像观察复发-缓解型多发性硬化壳核功能连接改变

目的 运用fMRI评价复发-缓解型多发性硬化（RRMS）患者静息状态下双侧壳核与全脑功能连接的改变。方法 以20例RRMS患者（RRMS组）及20名健康志愿者（正常对照组）的双侧壳核为ROI进行全脑功能连接分析,并观察其与临床评估参数之间的相关性。结果 与正常对照组相比,RRMS组左侧壳核功能连接增强区域包括左侧额中回、右侧额下回、左侧顶下小叶,减弱区域包括双侧边缘叶、左侧海马旁回、左侧颞中回;右侧壳核功能连接减弱区域包括左侧额上回、左侧颞下回、左侧边缘叶;双侧壳核异常功能连接区域与病程及扩展残疾量表评分、进步式听觉累加测试评分之间均未见明显相关性（P均>0.05）。结论 RRMS患者壳核与全脑功能连接存在异常,其功能连接改变可能是临床常见运动及认知功能障碍的原因之一。     

静息态磁共振功能连接方法的多模态应用

目的 探讨度中心度(DC)、镜像组织功能连接(VMHC)和基于感兴趣区的功能连接(ROI-FC)3种多模态静息态磁共振功能连接类数据处理方法在反映脑功能信息中的价值.方法 采集10名正常志愿者和10例亚急性期脑桥梗死患者的静息态fMRI数据.首先采用DC和VMHC对数据进行预分析,获得梗死患者脑功能显著改变的脑区作为ROI,然后采用ROI-FC分析梗死患者脑功能网络的改变.结果 采用DC未得到有意义的结果,VMHC发现患者左右顶下小叶/角回功能连接显著降低,以此为ROI,ROI-FC发现患者右楔前叶、左顶下小叶、左右颞中回、左右额中回功能连接降低,左额中回/中央前回、左额上回和右扣带回后部/楔前叶的功能连接增强.结论 综合应用DC、VMHC和ROI-FC 3种静息态fMRI功能连接类数据处理方法,可发现脑桥梗死患者相关的脑功能网络紊乱,为脑梗死的临床研究提供有价值的信息.     

Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain

The brain is a complex dynamic system of functionally connected regions. Graph theory has been successfully used to describe the organization of such dynamic systems. Recent resting-state fMRI studies have suggested that inter-regional functional connectivity shows a small-world topology, indicating an organization of the brain in highly clustered sub-networks, combined with a high level of global connectivity. In addition, a few studies have investigated a possible scale-free topology of the human brain, but the results of these studies have been inconclusive. These studies have mainly focused on inter-regional connectivity, representing the brain as a network of brain regions, requiring an arbitrary definition of such regions. However, using a voxel-wise approach allows for the model-free examination of both inter-regional as well as intra-regional connectivity and might reveal new information on network organization. Especially, a voxel-based study could give information about a possible scale-free organization of functional connectivity in the human brain. Resting-state 3 Tesla fMRI recordings of 28 healthy subjects were acquired and individual connectivity graphs were formed out of all cortical and sub-cortical voxels with connections reflecting inter-voxel functional connectivity. Graph characteristics from these connectivity networks were computed. The clustering-coefficient of these networks turned out to be much higher than the clustering-coefficient of comparable random graphs, together with a short average path length, indicating a small-world organization. Furthermore, the connectivity distribution of the number of inter-voxel connections followed a power-law scaling with an exponent close to 2, suggesting a scale-free network topology. Our findings suggest a combined small-world and scale-free organization of the functionally connected human brain. The results are interpreted as evidence for a highly efficient organization of the functionally connected brain, in which voxels are mostly connected with their direct neighbors forming clustered sub-networks, which are held together by a small number of highly connected hub-voxels that ensure a high level of overall connectivity.     

轻微型肝性脑病患者静息态下双侧楔前叶与全脑其他区域功能连接变化

目的 观察轻微型肝性脑病（MHE）患者静息态下双侧楔前叶与全脑其他区域功能连接（FC）变化。方法 对22例肝硬化伴MHE患者（MHE组）、23例肝硬化无MHE患者（NMHE组）和24名健康志愿者（对照组）行静息态fMRI,选择双侧楔前叶为种子点,采用种子体素相关性脑功能网络分析方法计算并比较各组间双侧楔前叶与全脑其他区域的FC。结果 与对照组比较,MHE组左侧楔前叶与右侧额上回、左侧中扣带回的FC及右侧楔前叶与右侧颞极、左侧颞上回、双侧前额叶和内侧扣带回的FC降低,NMHE组左侧楔前叶与右侧额中回的FC及右侧楔前叶与左侧楔前叶、左侧中扣带回的FC降低（P均<0.05）;与NMHE组比校,MHE组左侧楔前叶与右侧额上回的FC及右侧楔前叶与右侧脑岛、右侧额中/上回的FC降低（P均<0.05）。结论 MHE患者静息态下双侧楔前叶与全脑多个脑区FC存在异常,这可能是其大脑内源性神经功能损伤的机制之一。     

南疆维吾尔族终末期肾病患者的低频振荡振幅与脑功能连接研究

目的运用静息态功能磁共振成像(resting state functional MRI,rs-fMRI)技术探讨新疆南疆维吾尔族终末期肾病(end-stage renal disease,ESRD)患者低频振荡振幅(amplitude of low-frequency fluctuation,ALFF)及脑功能连接(functional connectivity,FC)的特点。材料与方法15例维吾尔族ESRD患者为试验组(ESRD组),20名年龄、性别和受教育年限相匹配的同区域长期居住的健康维吾尔族人为正常对照组,两组均行rs-fMRI检查。采用蒙特利尔认知量表(Montreal Cognitive Assessment,MoCA)评估ESRD患者的认知功能。计算ALFF和基于种子点的FC值,并比较两组间大脑ALFF及FC的差异,采用Pearson相关分析评估ESRD患者异常脑区的ALFF、FC和临床信息的相关关系。结果与对照组比较,南疆维吾尔族ESRD组双侧楔前叶(峰值点在右侧楔前叶)的ALFF(自发活动)减低;通过基于种子点的FC显示ESRD组的右侧楔前叶与右侧楔前叶/双侧中扣带回/双侧后扣带回/右侧内侧眶额叶的功能连接减弱;Pearson相关分析发现患者的右侧楔前叶-右侧内侧眶额叶FC和MoCA认知评分呈显著正相关(r=0.683,P=0.005)。结论南疆维吾尔族ESRD患者的大脑默认网络区域(default mode network,DMN)的自发活动以及功能连接减弱,可能是造成脑功能受损、认知障碍的原因之一。     

静息态功能MRI观察脑梗死后失语症患者功能连接变化

目的 采用静息态功能MRI（rs-fMRI）观察脑梗死后失语患者各脑区功能连接（FC）变化。方法 对10例脑梗死后失语症患者（观察组）及10名健康志愿者（对照组）采集rs-fMRI,以左侧额下回（LIFG）布罗卡（Broca）区为种子点,分析组内和组间ROI与其他脑区FC相关性的差异。结果 对照组双侧枕叶、顶叶、额叶、颞叶、小脑半球、小脑扁桃体及脑干与ROI FC呈正相关（P均<0.05）;观察组双侧额下回,左侧中央后回、中央前回、额中回、扣带回、豆状核、海马、楔叶、枕叶,右侧顶下小叶、缘上回与ROI的FC呈正相关（P均<0.05）;观察组双侧缘上回、颞下回、梭状回、顶下小叶、枕中回,右侧额中回、扣带回、小脑半球,左侧颞中回、颞上回等与ROI的FC的相关性高于对照组（P均<0.05）。结论 静息态下健康人脑内存在语言功能网络;左侧脑梗死后失语症患者多个脑区与LIFG Broca区的FC呈正相关,以左侧大脑半球额叶为主,可能与脑梗死后失语症的发生及恢复机制有关。     

儿童注意缺陷多动障碍脑功能及功能连接研究

目的使用静息态功能磁共振成像技术研究注意缺陷多动障碍(attention deficit hyperactivity disorder,ADHD)儿童的大脑局域自发功能活动及功能连接。材料与方法对10例ADHD患儿及10例正常对照组儿童进行全脑扫描,获取静息态功能图像。计算得到每个被试的低频振幅(amplitude of low-frequence fluctuation,ALFF)参数图,进行基于体素的组间比较。选取ALFF与对照组有显著差异的脑区做种子点,得到该区域与其他脑区之间的功能连接强度参数图,采用相同的方法比较两组被试之间的差别。结果与正常对照组相比,ADHD患儿在前扣带回、前额叶、尾状核等脑区存在显著的ALFF升高,提示自发功能活动更加活跃。与对照组相比,以前扣带为种子点,ADHD儿童在双侧丘脑、岛叶及后扣带区域功能连接显著升高;以右侧前额叶的脑区为种子点,ADHD的右侧中央前回和颞上回的功能连接下降;以尾状核为种子点,ADHD在双侧的额中回功能连接下降。结论 ADHD儿童局域脑区自发功能活动及其功能连接异常,揭示ADHD症状与认知注意网络的发育延迟或缺损有关。     

Hyper-connectivity of functional networks for brain disease diagnosis

Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help discover disease-related biomarkers important for disease diagnosis.     

Test-retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy

Recent studies of resting-state functional near-infrared spectroscopy (fNIRS) have emerged as a hot topic and revealed that resting-state functional connectivity (RSFC) is an inherent characteristic of the resting brain. However, it is currently unclear if fNIRS-based RSFC is test-retest reliable. In this study, we utilized independent component analysis (ICA) as an effective RSFC detection tool to address the reliability question. Sixteen subjects participated in two resting-state fNIRS recording sessions held 1week (6.88±1.09 days) apart. Then, RSFC in the sensorimotor regions was extracted using ICA. Test-retest reliability was assessed for intra- and inter-sessions, at both individual and group levels, and for different hemoglobin concentration signals. Our results clearly demonstrated that map-wise reliability was excellent at the group level (with Pearson's r coefficients up to 0.88) and generally fair at the individual level. Cluster-wise reliability was better at the group level (having reproducibility indices of up to 0.97 for the size and up to 0.80 for the location of the detected RSFC) and was weaker but still fair at the individual level (0.56 and 0.46 for intra- and inter-session reliabilities, respectively). Cluster-wise intra-class correlation coefficients (ICCs) also exhibited fair-to-good reliability (with single-measure ICC up to 0.56), while channel-wise single-measure ICCs indicated lower reliability. We conclude that fNIRS-based, ICA-derived RSFC is an essential and reliable biomarker at the individual and group levels if interpreted in map- and cluster-wise manners. Our results also suggested that channel-wise individual-level RSFC results should be interpreted with caution if no optode co-registration procedure had been conducted and indicated that "cluster" should be treated as a minimal analytical unit in further RSFC studies using fNIRS.     

低频振幅结合功能连接对原发性甲亢患者感觉运动网络的功能MRI研究

目的采用低频振幅(amplitude of low frequency fluctuation,ALFF)与功能连接(functional connectivity,FC)相结合的方法,研究原发性甲状腺功能亢进患者静息状态下脑功能改变。材料与方法 12名未经治疗的甲亢患者为病例组,12名自愿接受扫描的健康人(年龄、性别无显著性差异)为对照组。采集所有被试静息态f MRI数据,采用REST及DPARSF软件分析原始数据,得出全脑ALFF,利用双样本t检验的方法比较病例组和对照组ALFF的变化,并以两组间ALFF值有显著性差异的脑区为感兴趣区(regions of interest,ROI)校正后行FC分析。结果与对照组相比,甲亢患者在双侧尾状核及双侧丘脑ALFF值降低(P0.001)。以上脑区的ALFF值均未发现与T3、T4有显著相关性(P0.05)。FC分析显示,左侧丘脑与双侧感觉运动区(包括中央前回、中央后回)FC增强(P0.001);右侧丘脑与右侧中央前回及中央后回连接增强(P0.001)。结论甲亢患者双侧丘脑的局部活动及其与大脑感觉运动网络的FC模式存在异常,增强的FC可能与代谢损伤所导致运动机能受损而使甲状腺功能异常患者有更强的功能需求有关。     

Changes in regional cerebral blood flow and functional connectivity in the cholinergic pathway associated with cognitive performance in subjects with mild Alzheimer's disease after 12-week donepezil treatment

Acetylcholinesterase inhibitors (AChEIs), such as donepezil, have been shown to improve cognition in mild to moderate Alzheimer's disease (AD) patients. In this paper, our goal is to determine the relationship between altered cerebral blood flow (CBF) and intrinsic functional network connectivity changes in mild AD patients before and after 12-week donepezil treatment. An integrative neuroimaging approach was employed by combining pseudocontinuous arterial spin labeling (pCASL) MRI and resting-state functional MRI (R-fMRI) methods to determine the changes in CBF and functional connectivity (FC) in the cholinergic pathway. Linear regression analyses determined the correlations of the regional CBF alterations and functional connectivity changes with cognitive responses. These were measured with the Mini-Mental Status Examination (MMSE) scores and Alzheimer's disease Assessment Scale-Cognitive subscale (ADAS-cog) scores. Our results show that the regional CBF in mild AD subjects after donepezil treatment was significantly increased in the middle cingulate cortex (MCC) and posterior cingulate cortex (PCC), which are the neural substrates of the medial cholinergic pathway. In both brain regions, the baseline CBF and its changes after treatment were significantly correlated with the behavioral changes in ADAS-cog scores. The intrinsic FC was significantly enhanced in the medial cholinergic pathway network in the brain areas of the parahippocampal, temporal, parietal and prefrontal cortices. Finally, the FC changes in the medial prefrontal areas demonstrated an association with the CBF level in the MCC and the PCC, and also were correlated with ADAS-cog score changes. These findings indicate that regional CBF and FC network changes in the medial cholinergic pathway were associated with cognitive performance. It also is suggested that the combined pCASL-MRI and R-fMRI methods could be used to detect regional CBF and FC changes when using drug treatments in mild AD subjects.     

静息态功能MRI脑网络用于研究帕金森病伴冻结步态进展

冻结步态（FOG）是帕金森病（PD）致残性步态障碍。静息态功能MRI（rs-fMRI）可反映静息态下脑功能连接（FC）,有助于揭示FOG病理生理机制。本文就rs-fMRI脑网络用于研究PD伴FOG进展进行综述。     

手机依赖症大学生静息态fMRI海马功能连接分析

目的 探讨手机依赖症（MPD）大学生静息态双侧海马与大脑皮层功能连接的改变及其与神经心理学指标的相关性。方法 对24例MPD大学生（MPD组）及16名健康志愿者（对照组）采用焦虑自评量表（SAS）、抑郁自评量表（SDS）、Barratt冲动性量表第11版（BIS-11）、罗森伯格自尊量表（RSS）、匹兹堡睡眠质量指数量表（PSQI）、感觉寻求量表（SS）、智能手机成瘾量表（SPAI）、手机成瘾指数量表（MPAI）进行神经心理学评估。在静息态fMRI扫描后,选取双侧海马作为种子点进行全脑功能连接分析,并比较两组的差异性;将功能连接差异脑区的功能连接值与神经心理测评量表评分进行相关性分析。结果 MPD组除SS外,其余量表评分与对照组差异均有统计学意义（P均<0.05）。与对照组相比,MPD组双侧海马与双侧额中回的功能连接降低（P<0.05）;海马与额中回的功能连接值与各神经心理测评量表评分均无相关性（P均>0.05）。结论 MPD大学生较正常大学生存在情绪问题、冲动、低自尊、睡眠质量下降。静息态fMRI显示海马与额中回功能连接异常可能是MPD的神经病理机制之一。     

利用静息态功能磁共振成像研究缺血性脑卒中患者康复治疗后运动功能网络连接的变化

目的利用静息态功能磁共振成像技术研究缺血性脑卒中患者康复治疗前后运动功能网络连接变化的特点。方法对2例符合亚急性缺血性脑卒中影像学诊断标准的患者在功能性电刺激康复治疗前后各进行一次静息态功能磁共振扫描,比较两次扫描的运动脑区功能连接的差异。结果康复后患者上肢运动功能改善;与康复治疗前相比,康复治疗后左侧和右侧的运动皮层功能连接均降低,左侧和右侧的运动皮层功能连接系数降低值与脑卒中患者上肢运动功能以及日常生活能力的改善程度相关。结论缺血性脑卒中患者上肢运动功能改善后,即康复后患侧脑区对健侧脑区依赖性减低,并且功能连接系数的降低与脑卒中患者上肢运动功能的改善相关。