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.     

脑卒中后完全性失语症患者功能连接模式的功能性近红外光谱成像研究

目的:采用功能性近红外光谱技术(functional near-infrared spectroscopy,f NIRS)观察脑卒中后完全性失语症患者功能连接模式的特征。方法:选取脑卒中后完全性失语症患者10例,脑卒中后非失语症患者10例为非失语症对照组,健康中老年人21例为健康对照组。采用f NIRS采集8min的静息态数据,并选择与语言相关的关键脑区,包括背外侧前额叶(dorsolateral prefrontal cortex,DLPFC)、Broca区、颞上回(superior temporal gyrus,STG)、颞中回(middle temporal gyrus,MTG)、Wernicke区、角回、辅助运动区(supplementary motor area,SMA)作为感兴趣区,分别与全脑做相关分析,获得各组的脑功能连接图。结果:与健康对照组比较,完全性失语症组全脑语言网络功能连通性和连接比下降,其中连接比下降有显著性意义(P0.05),同时在左侧DLPFC-右侧SMA、左侧DLPFC-右侧Wernicke、左侧MTG-右侧MTG、左侧SMA-右侧Wernicke、左侧DLPFC-左侧SMA、右侧DLPFC-左侧SMA、左侧SMA-右侧SMA间的功能连接差异有显著性意义(P0.05)。相较于非失语症组,完全性失语症组表现出左侧MTG-左侧角回间功能连接下降且差异有显著性意义(P0.05)。结论:脑卒中后完全性失语症患者全脑语言网络的功能连通性与连接比以及关键语言区之间的功能连接模式存在异常,相关脑区之间的功能连接减弱可能是引起脑卒中后语言功能减弱的原因之一。其中左侧MTG-左侧角回间的功能连接可能为关键功能连接,左侧MTG和角回有望成为针对脑卒中后完全性失语症患者的新的神经调控靶点。     

失眠患者杏仁核功能连接的静息态功能磁共振成像

目的分析静息状态下失眠患者杏仁核与其他脑功能连接的改变。方法失眠患者39例为失眠组,体检健康者23例为对照组,2组均进行临床匹兹堡睡眠质量指数量表(Pittsburgh Sleep Quality Index, PSQI)、汉密尔顿抑郁量表(Hamilton Depression Scale, HAMD)、汉密尔顿焦虑量表(Hamilton Anxiety Scale, HAMA)、世界卫生组织-加利福尼亚听觉词语学习测验(World Health Organization University of California Los Angeles Auditory Verbal Learning Test, WHO-UCLA AVLT)评估睡眠、认知、情绪情况,2组均行磁共振常规扫描和静息态功能MRI扫描(resting-state functional MRI, rs-fMRI),以双侧杏仁核为种子点,比较2组脑功能连接的差异;采用Pearson相关分析失眠组长时记忆评分与左侧杏仁核-左侧海马旁回、左侧杏仁核-右侧海马旁回的功能连接强度的相关性。结果失眠组PSQI[(13.46±2.74)分]、HAMA[(10.10±3.97)分]、HAMD[(9.56±3.48)分]评分及认知障碍评分[(1.23±0.67)分]明显高于对照组[(2.52±1.75)、(1.57±1.90)、(0.78±1.24)、(0.08±0.07)分](P<0.05),WHO-UCLA学习记忆量表中长时记忆[(10.67±2.35)分]和再认记忆[(12.36±2.40)分]评分低于对照组[(11.96±1.85)、(13.39±1.31)分](P<0.05);与对照组比较,失眠组左侧杏仁核与后扣带回、双侧海马旁回、双侧海马、颞叶、舌回和枕叶的功能连接增强(P<0.05),右侧杏仁核与边缘叶、右侧海马旁回、舌回、枕叶、右侧距状皮层、后扣带回、前额叶功能连接增强(P<0.05);失眠组长时记忆评分与左侧杏仁核-左侧海马旁回、左侧杏仁核-右侧海马旁回的功能连接强度呈正相关(r=0.556,P<0.001;r=0.150,P=0.032)。结论失眠患者双侧杏仁核与多个脑区的功能连接出现异常,可能是失眠患者出现情绪调节障碍、认知障碍等的机制之一。     

基于功能性近红外光谱技术的脑卒中后运动功能障碍患者脑网络功能连接研究

摘要 目的：采用功能性近红外光谱技术（fNIRS）对比观察运动功能障碍的脑卒中患者与健康人的静息态脑功能连接差异。 方法：应用fNIRS分析20例左侧、20例右侧脑卒中后运动功能障碍患者及20例健康对照组静息状态下各脑区之间功能连接强度,并在前额叶（prefrontal cortex,PFC）、第一躯体运动区（M1）、初级躯体感觉皮层区（primary somatosensory cortex,PSC）中比较组间差异。 结果：基于氧合血红蛋白情况下,左右脑卒中组的全脑功能连接平均强度均低于健康组;同源比较中左侧脑卒中组与左侧M1区（患侧）的功能连接强度与健康组有显著性差异（P＜0.05）,其余兴趣区（ROI）与健康组无明显差异。右脑卒中组的左侧PFC、左侧M1区（健侧）的功能连接强度与健康组有显著性差异（P＜0.05）,其余ROI与健康组无明显差异。异源比较中左脑卒中组和右脑卒中组与健康组相比左侧M1与右侧M1区间的功能连接强度差异有显著性意义（P<0.05）,提示与健康组相比,左右脑卒中组的患者的双侧大脑半球间即健侧和患侧半球间M1区间的功能连接强度有明显减弱。另外,相较于健康组,右脑卒中组在左右半球PFC间的功能连接强度也有显著性意义（P<0.05）;而左脑卒中组则没有显著性差异（P＞0.05）。其他ROI功能区间功能连接均无显著性差异（P＞0.05）。左右脑卒中组的PFC区、M1区与FMA评分以及Brunnstrom分期之间的相关性没有显著性差异（P＞0.05）。 结论：在采用功能性近红外脑功能成像的静息态脑功能连接研究中,左右脑卒中组的全脑功能连接平均强度均低于健康组;其中左脑卒中组的患侧M1区功能连接低于健康组,而在左右半球间的功能连接中左右脑卒中组的两侧半球M1区间的功能连接均减少,右脑卒中组的两侧半球PFC区间的功能连接减少。     

Resting state functional connectivity of the whole head with near-infrared spectroscopy

Resting state connectivity aims to identify spontaneous cerebral hemodynamic fluctuations that reflect neuronal activity at rest. In this study, we investigated the spatial-temporal correlation of hemoglobin concentration signals over the whole head during the resting state. By choosing a source-detector pair as a seed, we calculated the correlation value between its time course and the time course of all other source-detector combinations, and projected them onto a topographic map. In all subjects, we found robust spatial interactions in agreement with previous fMRI and NIRS findings. Strong correlations between the two opposite hemispheres were seen for both sensorimotor and visual cortices. Correlations in the prefrontal cortex were more heterogeneous and dependent on the hemodynamic contrast. HbT provided robust, well defined maps, suggesting that this contrast may be used to better localize functional connectivity. The effects of global systemic physiology were also investigated, particularly low frequency blood pressure oscillations which give rise to broad regions of high correlation and mislead interpretation of the results. These results confirm the feasibility of using functional connectivity with optical methods during the resting state, and validate its use to investigate cortical interactions across the whole head.     

Mapping resting-state functional connectivity using perfusion MRI

Resting-state, low-frequency (<0.08 Hz) fluctuations of blood oxygenation level-dependent (BOLD) magnetic resonance signal have been shown to exhibit high correlation among functionally connected regions. However, correlations of cerebral blood flow (CBF) fluctuations during the resting state have not been extensively studied. The main challenges of using arterial spin labeling perfusion magnetic resonance imaging to detect CBF fluctuations are low sensitivity, low temporal resolution, and contamination from BOLD. This work demonstrates CBF-based quantitative functional connectivity mapping by combining continuous arterial spin labeling (CASL) with a neck labeling coil and a multi-channel receiver coil to achieve high perfusion sensitivity. In order to reduce BOLD contamination, the CBF signal was extracted from the CASL signal time course by high frequency filtering. This processing strategy is compatible with sinc interpolation for reducing the timing mismatch between control and label images and has the flexibility of choosing an optimal filter cutoff frequency to minimize BOLD fluctuations. Most subjects studied showed high CBF correlation in bilateral sensorimotor areas with good suppression of BOLD contamination. Root-mean-square CBF fluctuation contributing to bilateral correlation was estimated to be 29+/-19% (N=13) of the baseline perfusion, while BOLD fluctuation was 0.26+/-0.14% of the mean intensity (at 3 T and 12.5 ms echo time).     

Exploring resting-state functional connectivity with total interdependence

Resting-state fMRI has become a powerful tool for studying network mechanisms of normal brain functioning and its impairments by neurological and psychiatric disorders. Analytically, independent component analysis and seed-based cross correlation are the main methods for assessing the connectivity of resting-state fMRI time series. A feature common to both methods is that they exploit the covariation structures of contemporaneously (zero-lag) measured data but ignore temporal relations that extend beyond the zero-lag. To examine whether data covariations across different lags can contribute to our understanding of functional brain networks, a measure that can uncover the overall temporal relationship between two resting-state BOLD signals is needed. In this paper we propose such a measure referred as total interdependence (TI). Comparing TI with zero-lag cross correlation (CC) we report three results. First, when combined with a random permutation procedure, TI can reveal the amount of temporal relationship between two resting-state BOLD time series that is not captured by CC. Second, comparing resting-state data with task-state data recorded in the same scanning session, we demonstrate that the resting-state functional networks constructed with TI match more precisely the networks activated by the task. Third, TI is shown to be more statistically sensitive than CC and provides better feature vectors for network clustering analysis.     

MRI观察精神分裂症静息态下小脑功能连接和解剖连接

目的 应用静息态功能磁共振成像(fMRI)和扩散张量成像(DTI)观察精神分裂症患者与正常人小脑功能连接与解剖连接的差异。方法 分别对10例精神分裂症患者(精神分裂组)及14名健康对照者(正常对照组)行静息态脑fMRI和DTI。对数据进行后处理后得到功能连接的相关系数r值及小脑中脚的平均FA值,应用双样本t检验比较组间差异,并对两种数据进行相关性检验。结果 ①精神分裂组与左侧小脑功能连接改变显著的区域为双侧舌回、右侧额中回、双侧缘上回和左侧小脑(P<0.001,未校正);与右侧小脑功能连接改变显著的区域为双侧舌回、左侧中央前回和左侧缘上回(P<0.001,未校正);②精神分裂组左侧小脑中脚的FA值显著降低(P<0.05);③精神分裂组右侧小脑-右侧舌回的连接强度与右侧小脑中脚的FA值呈显著正相关(r=0.84,P<0.05)。结论 联合运用多种成像方式可能为理解小脑在精神分裂症病理生理学中的作用提供新的方向;精神分裂症患者静息态下小脑与大脑皮层某些区域的连接降低和小脑中脚局部白质纤维完整性受损的同时出现以及二者之间的相关性提示功能连接与解剖解剖之间存在密切关系。     

Anticorrelated resting-state functional connectivity in awake rat brain

Resting-state functional connectivity (RSFC) measured by functional magnetic resonance imaging has played an essential role in understanding neural circuitry and brain diseases. The vast majority of RSFC studies have been focused on positive RSFC, whereas our understanding about its conceptual counterpart - negative RSFC (i.e. anticorrelation) - remains elusive. To date, anticorrelated RSFC has yet been observed without the commonly used preprocessing step of global signal correction. However, this step can induce artifactual anticorrelation (Murphy et al., 2009), making it difficult to determine whether the observed anticorrelation in humans is a processing artifact (Fox et al., 2005). In this report we demonstrated robust anticorrelated RSFC in a well characterized frontolimbic circuit between the infralimbic cortex (IL) and amygdala in the awake rat. This anticorrelation was anatomically specific, highly reproducible and independent of preprocessing methods. Interestingly, this anticorrelated relationship was absent in anesthetized rats even with global signal correction, further supporting its functional significance. Establishing negative RSFC independent of data preprocessing methods will significantly enhance the applicability of RSFC in better understanding neural circuitries and brain networks. In addition, combining the neurobiological data of the IL-amygdala circuit in rodents, the finding of the present study will enable further investigation of the neurobiological basis underlying anticorrelation.     

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.     

Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer's disease

Statistical interdependencies between magnetoencephalographic signals recorded over different brain regions may reflect the functional connectivity of the resting-state networks. We investigated topographic characteristics of disturbed resting-state networks in Alzheimer's disease patients in different frequency bands. Whole-head 151-channel MEG was recorded in 18 Alzheimer patients (mean age 72.1 years, SD 5.6; 11 males) and 18 healthy controls (mean age 69.1 years, SD 6.8; 7 males) during a no-task eyes-closed resting state. Pair-wise interdependencies of MEG signals were computed in six frequency bands (delta, theta, alpha1, alpha2, beta and gamma) with the synchronization likelihood (a nonlinear measure) and coherence and grouped into long distance (intra- and interhemispheric) and short distance interactions. In the alpha1 and beta band, Alzheimer patients showed a loss of long distance intrahemispheric interactions, with a focus on left fronto-temporal/parietal connections. Functional connectivity was increased in Alzheimer patients locally in the theta band (centro-parietal regions) and the beta and gamma band (occipito-parietal regions). In the Alzheimer group, positive correlations were found between alpha1, alpha2 and beta band synchronization likelihood and MMSE score. Resting-state functional connectivity in Alzheimer's disease is characterized by specific changes of long and short distance interactions in the theta, alpha1, beta and gamma bands. These changes may reflect loss of anatomical connections and/or reduced central cholinergic activity and could underlie part of the cognitive impairment.     

Role of local network oscillations in resting-state functional connectivity

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain.     

Modeling the outcome of structural disconnection on resting-state functional connectivity

A growing body of experimental evidence suggests that functional connectivity at rest is shaped by the underlying anatomical structure. Furthermore, the organizational properties of resting-state functional networks are thought to serve as the basis for an optimal cognitive integration. A disconnection at the structural level, as occurring in some brain diseases, would then lead to functional and presumably cognitive impairments. In this work, we propose a computational model to investigate the role of a structural disconnection (encompassing putative local/global and axonal/synaptic mechanisms) on the organizational properties of emergent functional networks. The brain's spontaneous neural activity and the corresponding hemodynamic response were simulated using a large-scale network model, consisting of local neural populations coupled through white matter fibers. For a certain coupling strength, simulations reproduced healthy resting-state functional connectivity with graph properties in the range of the ones reported experimentally. When the structural connectivity is decreased, either globally or locally, the resultant simulated functional connectivity exhibited a network reorganization characterized by an increase in hierarchy, efficiency and robustness, a decrease in small-worldness and clustering and a narrower degree distribution, in the same way as recently reported for schizophrenia patients. Theoretical results indicate that most disconnection-related neuropathologies should induce the same qualitative changes in resting-state brain activity.     

基于静息态功能连接模式的正常人脑扣带皮层亚区划分

基于静息态功能连接(rsFC)模式对正常人脑扣带皮层进行亚区划分,并分析不同亚区的功能连接模式。方法 收集47名右利手健康志愿者。采集结构磁共振图像及静息态功能磁共振图像。在蒙特利尔脑研究所标准空间勾画扣带皮层ROI。基于个体计算ROI中每个体素与全脑其他体素时间序列的Pearson线性相关系数,得到互相关矩阵,采用K-均值聚类算法自动聚类。采用交互验证的方法选择合适分割数。最终计算最大概率图谱。通过单样本t检验确定与每个亚区具有正功能连接的脑区。结果 扣带皮层被分为6个亚区:前扣带皮层、背侧中前扣带皮层、腹侧中前扣带皮层、中后扣带皮层、背侧后扣带皮层及腹侧后扣带皮层亚区。每个亚区有特异的静息态功能连接模式。结论 人脑扣带皮层依据不同的静息态功能连接模式分为6个亚区,每个亚区分属不同的脑功能网络,参与不同的功能。     

Bedside optical imaging of occipital resting-state functional connectivity in neonates

Resting-state networks derived from temporal correlations of spontaneous hemodynamic fluctuations have been extensively used to elucidate the functional organization of the brain in adults and infants. We have previously developed functional connectivity diffuse optical tomography methods in adults, and we now apply these techniques to study functional connectivity in newborn infants at the bedside. We present functional connectivity maps in the occipital cortices obtained from healthy term-born infants and premature infants, including one infant with an occipital stroke. Our results suggest that functional connectivity diffuse optical tomography has potential as a valuable clinical tool for the early detection of functional deficits and for providing prognostic information on future development.     

功能性近红外光谱应用于脑认知领域的可视化分析

目的：对功能性近红外光谱技术应用于脑认知相关研究的现状、热点及前沿行可视化分析。方法：检索Web of Science（WOS）数据库2012年1月1日～2022年12月31日功能性近红外光谱技术应用于脑认知研究的文献,使用CiteSpace 5.7软件进行可视化分析。结果：最终纳入文献1685篇,文献年发表量呈增长趋势。Ann-Christine Ehlis是发文最多的作者（36篇）,美国是发文量最多的国家（480篇）,德国图宾根大学是发文量最多的机构（47篇）,发文机构间合作较密切。研究热点集中于认知障碍及儿童脑发育障碍等认知疾病的神经机制研究、认知水平测量及认知疾病治疗评价等方面。结论：功能性近红外光谱技术在脑认知领域的应用处于发展阶段,国内机构应继续强化合作,近年研究开始结合多模态检测数据,研究者可进一步将多模态大数据结合人工智能建立各类认知疾病的认知评估、疗效评价等模型,实现脑认知疾病的客观化精准医疗。     

Antidepressant medications reduce subcortical-cortical resting-state functional connectivity in healthy volunteers

Studies have revealed abnormalities in resting-state functional connectivity in those with major depressive disorder specifically in areas such as the dorsal anterior cingulate, thalamus, amygdala, the pallidostriatum and subgenual cingulate. However, the effect of antidepressant medications on human brain function is less clear and the effect of these drugs on resting-state functional connectivity is unknown. Forty volunteers matched for age and gender with no previous psychiatric history received either citalopram (SSRI; selective serotonergic reuptake inhibitor), reboxetine (SNRI; selective noradrenergic reuptake inhibitor) or placebo for 7 days in a double-blind design. Using resting-state functional magnetic resonance imaging and seed based connectivity analysis we selected the right nucleus accumbens, the right amygdala, the subgenual cingulate and the dorsal medial prefrontal cortex as seed regions. Mood and subjective experience were also measured before and after drug administration using self-report scales. Despite no differences in mood across the three groups, we found reduced connectivity between the amygdala and the ventral medial prefrontal cortex in the citalopram group and the amygdala and the orbitofrontal cortex for the reboxetine group. We also found reduced striatal-orbitofrontal cortex connectivity in the reboxetine group. These data suggest that antidepressant medications can decrease resting-state functional connectivity independent of mood change and in areas known to mediate reward and emotional processing in the brain. We conclude that hypothesis-driven seed based analysis of resting-state fMRI supports the proposition that antidepressant medications might work by normalising the elevated resting-state functional connectivity seen in depressed patients.     

Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI

Most studies of resting-state functional magnetic resonance imaging (fMRI) have applied the temporal correlation in the time courses to investigate the functional connectivity between brain regions. Alternatively, the power of low frequency fluctuation (LFF) may also be used as a biomarker to assess spontaneous activity. The purpose of the current study is to evaluate whether the amplitude of the LFF (ALFF) relates to cerebral physiological states. Ten healthy subjects underwent four resting-state fMRI scanning sessions, two for eyes-open (EO) and two for eyes-closed (EC) conditions, with two sets of parameters (TR=400 ms and 2 s, respectively). After data preprocessing, ALFF was obtained by calculating the square root of the power spectrum in the frequency range of 0.01-0.08 Hz. Our results showed that the ALFF in EO was significantly higher than that in EC (P<0.05, corrected) in the bilateral visual cortices. Furthermore, the ALFF in EO was significantly reduced in the right paracentral lobule (PCL) than in EC (P<0.05, corrected). Region of interest (ROI) analysis showed that the ALFF differences between EO and EC were consistent for each subject. In contrast, no significant ALFF differences were found between EO and EC (P<0.381) in the posterior cingulate cortex. All these results agree well with previous studies comparing EO and EC states. Our finding of the distinct ALFF difference between EO and EC in the visual cortex implies that the ALFF may be a novel biomarker for physiological states of the brain.     

生理性进食之后静息态fMRI脑功能连接的变化

目的探讨生理性进食之后静息态脑功能连接的变化。材料与方法 42名健康被试按照人口统计学特征平衡分为三组。为了增加胃肠活动的差异,三组分别服用多潘立酮、奥替溴铵、安慰剂。所有被试均给予标准实验早餐,于空腹、早餐后、餐后2h及午餐前行静息态功能磁共振(functional MRI,fMRI)检查。数据分析采用扣带回后部-楔前叶作为种子点,计算全脑功能连接,并采用重复测量ANOVA分析在时间与药物因素上具有显著差异的脑区,并提取其功能连接Z值,进行事后检验。结果时间主效应:右侧眶额回/壳核/丘脑、右侧缘上回和右侧岛盖的功能连接在时间因素上有显著差异(P0.05)。药物主效应:右侧楔前叶、左侧颞中回、左侧舌回、右侧颞中回、右侧额上回、双侧眶额回、左侧额中回的功能连接在药物因素上有显著差异(P0.05)。结论静息态fMRI健康被试生理性进食前后,奖赏系统、右侧丘脑和躯体感觉区的功能连接会发生变化,并且呈现右侧偏侧化优势;胃动力药物对上述脑区的变化无影响。为常规fMRI实验中被试进食状态对实验结果的潜在影响提供了分析依据。