Fractional amplitude of low-frequency fluctuation changes in functional dyspepsia: A resting-state fMRI study

Recently, there is an increasing interest in the study of the role of brain dysfunction in the pathogenesis of symptoms of functional dyspepsia (FD). More specifically, abnormal brain activities in patients with FD during the resting state have been proven by several positron emission tomography (PET) studies. Resting-state functional magnetic resonance imaging (fMRI) is also a valuable tool in investigating spontaneous brain activity abnormalities in pathological conditions. In the present study, we examined the amplitude of low-frequency fluctuations (ALFF) and fractional (f)ALFF changes in patients with FD by using fMRI. Twenty-nine patients with FD and sixteen healthy controls participated in this study. Between-group differences in ALFF/fALFF were examined using a permutation-based nonparametric test after accounting for the gender and age effects. The results revealed a significant between-group difference in fALFF but not in ALFF in multiple brain regions including the right insula, brainstem and cerebellum. Seed-based resting-state functional connectivity analysis revealed that FD patients have increased correlations between the right cerebellum and multiple brain regions including the bilateral brainstem, bilateral cerebellum, bilateral thalamus, left para-/hippocampus, left pallidum and left putamen. Furthermore, fLAFF values in the right insula were positively correlated with the severity of the disease. These findings have provided further evidence of spontaneous brain activity abnormalities in FD patients which might contribute to our understanding of the pathophysiology of the disease.     

Assessing functional connectivity in the human brain by fMRI

Functional magnetic resonance imaging (fMRI) is widely used to detect and delineate regions of the brain that change their level of activation in response to specific stimuli and tasks. Simple activation maps depict only the average level of engagement of different regions within distributed systems. FMRI potentially can reveal additional information about the degree to which components of large-scale neural systems are functionally coupled together to achieve specific tasks. In order to better understand how brain regions contribute to functionally connected circuits, it is necessary to record activation maps either as a function of different conditions, at different times or in different subjects. Data obtained under different conditions may then be analyzed by a variety of techniques to infer correlations and couplings between nodes in networks. Several multivariate statistical methods have been adapted and applied to analyze variations within such data. An approach of particular interest that is suited to studies of connectivity within single subjects makes use of acquisitions of runs of MRI images obtained while the brain is in a so-called steady state, either at rest (i.e., without any specific stimulus or task) or in a condition of continuous activation. Interregional correlations between fluctuations of MRI signal potentially reveal functional connectivity. Recent studies have established that interregional correlations between different components of circuits in each of the visual, language, motor and working memory systems can be detected in the resting state. Correlations at baseline are changed during the performance of a continuous task. In this review, various methods available for assessing connectivity are described and evaluated.     

Detecting functional connectivity in the resting brain: a comparison between ICA and CCA

Independent component analysis (ICA) and cross-correlation analysis (CCA) are general tools for detecting resting-state functional connectivity. In this study, we jointly evaluated these two approaches based on simulated data and in vivo functional magnetic resonance imaging data acquired from 10 resting healthy subjects. The influence of the number of independent components (maps) on the results of ICA was investigated. The influence of the selection of the seeds on the results of CCA was also examined. Our results reveal that significant differences between these two approaches exist. The performance of ICA is superior as compared with that of CCA; in addition, the performance of ICA is not significantly affected by structured noise over a relatively large range. The results of ICA could be affected by the number of independent components if this number is too small, however. Converting the spatially independent maps of ICA into z maps for thresholding tends to overestimate the false-positive rate. However, the overestimation is not very severe and may be acceptable in most cases. The results of CCA are dependent on seeds location. Seeds selected based on different criteria will significantly affect connectivity maps.     

Functional connectivity in the rat brain: a complex network approach

Functional connectivity analyses of fMRI data can provide a wealth of information on the brain functional organization and have been widely applied to the study of the human brain. More recently, these methods have been extended to preclinical species, thus providing a powerful translational tool. Here, we review methods and findings of functional connectivity studies in the rat. More specifically, we focus on correlation analysis of pharmacological MRI (phMRI) responses, an approach that has enabled mapping the patterns of connectivity underlying major neurotransmitter systems in vivo. We also review the use of novel statistical approaches based on a network representation of the functional connectivity and their application to the study of the rat brain functional architecture.     

Fractional amplitude of low-frequency fluctuation changes in monkeys with spinal cord injury: A resting-state fMRI study

Purpose

Although functional magnetic resonance imaging (fMRI) has revealed that spinal cord injury (SCI) causes anomalous changes in task-induced brain activation, its effect during the resting state remains unclear. The aim of this study is to explore the changes of the brain resting-state function in non-human primates with unilateral SCI.

Materials and methods

Eleven adult female rhesus monkeys were subjected to resting-state fMRI: five with unilateral thoracic SCI and six healthy monkeys, to obtain the fractional amplitude of low-frequency fluctuations (fALFF) of the blood oxygenation level-dependent (BOLD) contrast signal to determine the influence of SCI on the cerebral resting-state function.

Results

The SCI-induced fALFF vary significantly in several encephalic regions, including the left cerebellum, the left thalamus, the right lateral geniculate nucleus, the right superior parietal lobule, and the posterior cingulate gyrus.

Conclusion

Analysis of the resting-state fMRI provides evidence of abnormal spontaneous brain activations in primates with SCI, which may help us understand the pathophysiologic mechanisms underlying the changes in neural plasticity in the central nervous system after SCI.     

FMRI connectivity analysis of acupuncture effects on the whole brain network in mild cognitive impairment patients

The increased risk for the elderly with mild cognitive impairment (MCI) to progress to Alzheimer's disease makes it an appropriate condition for investigation. While the use of acupuncture as a complementary therapeutic method for treating MCI is popular in certain parts of the world, the underlying mechanism is still elusive. We sought to investigate the acupuncture effects on the functional connectivity throughout the entire brain in MCI patients compared to healthy controls (HC). The functional magnetic resonance imaging experiment was performed with two different paradigms, namely, deep acupuncture (DA) and superficial acupuncture (SA), at acupoint KI3. We first identified regions showing abnormal functional connectivity in the MCI group compared to HC during the resting state and subsequently tested whether these regions could be modulated by acupuncture. Then, we made the comparison of MCI vs. HC to test whether there were any specific modulatory patterns in the poststimulus resting brain between the two groups. Finally, we made the comparisons of DA vs. SA in each group to test the effect of acupuncture with different needling depths. We found the temporal regions (hippocampus, thalamus, fusiform gyrus) showing abnormal functional connectivity during the resting state. These regions are implicated in memory encoding and retrieving. Furthermore, we found significant changes in functional connectivity related with the abnormal regions in MCI patients following acupuncture. Compared to HC, the correlations related with the temporal regions were enhanced in the poststimulus resting brain in MCI patients. Compared to SA, significantly increased correlations related with the temporal regions were found for the DA condition. The enhanced correlations in the memory-related brain regions following acupuncture may be related to the purported therapeutically beneficial effects of acupuncture for the treatment of MCI. The heterogeneous modulatory patterns between DA and SA may suggest that deep muscle insertion of acupuncture is necessary to achieve the appreciable clinical effect.     

A serial functional connectivity MRI study in healthy individuals assessing the variability of connectivity measures: reduced interhemispheric connectivity in the motor network during continuous performance

To date, little data is available on the reproducibility of functional connectivity MRI (fcMRI) studies. Here, we tested the variability and reproducibility of both the functional connectivity itself and different statistical methods to analyze this phenomenon. In the main part of our study, we repeatedly examined two healthy subjects in 10 sessions over 6 months with fcMRI. Cortical areas involved in motor function were examined under two different cognitive states: during continuous performance (CP) of a flexion/extension task of the fingers of the right hand and while subjects were at rest. Connectivity to left primary motor cortex (lSM1) was calculated by correlation analysis. The resulting correlation coefficients were transformed to z-scores of the standard normal distribution. For each subject, multisession statistical analyses were carried out with the z-score maps of the resting state (RS) and the CP experiments. First, voxel based t tests between the two groups of fcMRI experiments were performed. Second, ROI analyses were carried out for contralateral right SM1 and for supplementary motor area (SMA). For both ROI, mean and maximum z-score were calculated for each experiment. Also, the fraction of significantly (P<.05) correlated voxels (FCV) in each ROI was calculated. To evaluate the differences between the RS and the CP condition, paired t tests were performed for the mean and maximum z-scores, and Wilcoxon signed ranks tests for matched pairs were carried out for the FCV. All statistical methods and connectivity measures under investigation yielded a distinct loss in left–right SM1 connectivity under the CP condition. For SMA, interindividual differences were apparent. We therefore repeated the fcMRI experiments and the ROI analyses in a group of seven healthy subjects (including the two subjects of the main study). In this substudy, we were able to verify the reduction of left–right SM1 connectivity during unilateral performance. Still, the direction of SMA to lSM1 connectivity change during the CP condition remained undefined as four subjects showed a connectivity increase and three showed a decrease. In summary, we were able to demonstrate a distinct reduction in left–right SM1 synchrony in the CP condition compared to the RS both in the longitudinal and in the multisubject study. This effect was reproducible with all statistical methods and all measures of connectivity under investigation. We conclude that despite intra- and interindividual variability, serial and cross-sectional assessment of functional connectivity reveals stable and reliable results.     

Images-based suppression of unwanted global signals in resting-state functional connectivity studies

Correlated fluctuations of low-frequency fMRI signal have been suggested to reflect functional connectivity among the involved regions. However, large-scale correlations are especially prone to spurious global modulations induced by coherent physiological noise. Cardiac and respiratory rhythms are the most offending component, and a tailored preprocessing is needed in order to reduce their impact. Several approaches have been proposed in the literature, generally based on the use of physiological recordings acquired during the functional scans, or on the extraction of the relevant information directly from the images. In this paper, the performances of the denoising approach based on general linear fitting of global signals of noninterest extracted from the functional scans were assessed. Results suggested that this approach is sufficiently accurate for the preprocessing of functional connectivity data.     

On the low-frequency limit of the Schönfeld pulse 1/f law

On the basis of propositions of the common fluctuation theory, peculiarities of small fluctuations in real physical systems with limited sizes are analyzed. It is established that small fluctuations should necessarily be divided into two types of fluctuations: “small” and “very small”. It is shown that the damping process of “small” fluctuations has relaxation character, while the damping process of “very small” fluctuations is of random character, i.e., it represents a random rectangular signal. The probability density of “very small” fluctuations is shown to be Gaussian. The agreement of the obtained results with experimental data acquired from semiconductor-based devices is analyzed. A relation between the generation–recombination noise and phonon number fluctuations in semiconductors is studied. On the basis of this consideration it is shown that the Schönfeld pulse spectrum preserves its well-known 1/f form only in the range of intermediate frequencies; at lower frequencies the spectrum gets saturated. An expression for the low-frequency limit of Schönfeld pulse 1/f law is obtained.     

Modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case studying

Manual acupuncture is widely used for pain treatment and stress control. Previous studies on acupuncture have shown its modulatory effects on functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of threshold, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas characteristic path length is shorter. We provide further support for the presence of "small-world" network characteristics in functional networks by acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of acupuncture effects on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.     

静息态脑电信号动态功能连接分析

静息态脑功能连接分析是近年来脑研究的一个热点问题, 对于某些脑疾病的诊断及成因理解具有重要意义. 已有的脑功能连接研究基本上都假设功能连接网络在一段时间内是稳定不变的, 但越来越多的证据表明它应该是随时间动态变化的. 对25名被试睁眼和闭眼状态的64电极脑电生理信号, 采用独立成分分析、滑动时间窗、低分辨率脑电断层溯源、图论等方法和技术进行动态功能连接分析, 展现了睁眼和闭眼两种基线状态下视觉网络、默认网络等功能连接网络随时间的动态变化, 并对动态连接矩阵进行主成分分析得到了在整个时间段内具有代表意义的功能连接模式. 该结论支持和补充了传统稳态脑功能连接的研究, 也将为相关实验设计以及脑电信号临床研究提供基线选择依据.     

The modulation of brain functional connectivity with manual acupuncture in healthy subjects:An electroencephalograph case study

Manual acupuncture is widely used for pain relief and stress control.Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions.To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level,we acupuncture at ST36 of a right leg to obtain electroencephalograph(EEG) signals.By coherence estimation,we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states.The resulting synchronization matrices are converted into functional networks by applying a threshold,and the clustering coefficients and path lengths are computed as a function of threshold.The results show that acupuncture can increase functional connections and synchronizations between different brain areas.For a wide range of thresholds,the clustering coefficient during acupuncture and postacupuncture period is higher than that during the pre-acupuncture control period,whereas the characteristic path length is shorter.We provide further support for the presence of "small-world" network characteristics in functional networks by using acupuncture.These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture,which could contribute to the understanding of the effects of acupuncture on the entire brain,as well as the neurophysiological mechanisms underlying acupuncture.Moreover,the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.     

Investigation of the large-scale functional brain networks modulated by acupuncture

Previous neuroimaging studies have primarily focused on the neural activities involving the acute effects of acupuncture. Considering that acupuncture can induce long-lasting effects, several researchers have begun to pay attention to the sustained effects of acupuncture on the resting brain. Most of these researchers adopted functional connectivity analysis based on one or a few preselected brain regions and demonstrated various function-guided brain networks underlying the specific effect of acupuncture. Few have investigated how these brain networks interacted at the whole-brain level. In this study, we sought to investigate the functional correlations throughout the entire brain following acupuncture at acupoint ST36 (ACUP) in comparison with acupuncture at nearby nonacupoint (SHAM). We divided the whole brain into 90 regions and constructed functional brain network for each condition. Then we examined the network hubs and identified statistically significant differences in functional correlations between the two conditions. Following ACUP, but not SHAM, the limbic/paralimbic regions such as the amygdala, hippocampus and anterior cingulate gyrus emerged as network hubs. For direct comparisons, increased correlations for ACUP compared to SHAM were primarily related with the limbic/paralimbic and subcortical regions such as the insula, amygdala, anterior cingulate gyrus, and thalamus, whereas decreased correlations were mainly related with the sensory and frontal cortex. The heterogeneous modulation patterns between the two conditions may relate to the functional specific modulatory effects of acupuncture. The preliminary findings may help us to better understand the long-lasting effects of acupuncture on the entire resting brain, as well as the neurophysiological mechanisms underlying acupuncture.     

Understanding the radiation-induced amorphization of zirconolite using molecular dynamics and connectivity topology analysis

Connectivity topology analysis is a powerful method for describing both crystalline structures and their metamict or amorphous analogues, because it places no reliance on symmetry operators or periodic translation, which vanish upon introduction of disorder to a material. Topological analysis represents atomic systems as graphs, and analysis of closed circuit connectivity (rings) is used to search for shortest non-degenerable connectivity paths that define the structure. A connectivity topology analysis is presented of crystalline zirconolite, a potential actinide-accommodating nuclear waste material. Characteristic topological differences are established in the connectivities of radiation-damaged and melt-quenched zirconolite structures generated by molecular dynamics simulations. Amorphization induced by alpha-recoil displacement cascades still retains certain short- and intermediate-range ordered configurations, particularly for Ti atoms. [TiO _x ] polyhedral edge-sharing chains are observed in the metamict state, which may act to stabilize the radiation-damaged structure and prevent recovery of the initial crystalline phase. An assessment of the predicted amorphizability of zirconolite, based on the topological constraints imposed by its structure, reveals that the varying structural rigidity of the layers in the zirconolite structure is crucial to its amorphizability behavior. The hexagonal tungsten bronze structure [TiO _x ] layer in particular provides weak constraints that are responsible for zirconolite's comparative ease of amorphization.     

Theoretical analysis and experimental scheme of QND measurement for intensity difference fluctuations

A feasible experimental scheme of QND measurement for intensity difference fluctuations is presented, in which a nondegenerate optical parametric amplifier is used as the nonlinear coupling device. Optimum behavior is obtained by appropriately choosing the operating parameters, which can provide design references for the measurement.     

Analyzing topological characteristics of neuronal functional networks in the rat brain

In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats.     

振幅和相位涨落对锁模脉冲列特性的影响

 用傅里叶变换的方法分析了锁模激光器中模式间的相位和振幅涨落对锁模脉冲列特性的影响。将锁模激光器中各模式的相位和振幅涨落作傅里叶展开，再通过增益谱抽样的傅里叶变化得到其时域行为。分析结果表明振幅系统涨落及随机涨落均不引起脉宽的明显变化，只引起脉冲间背景的加大，但相位涨落随机会使脉冲列强度产生波动。所用物理图像简明，结果对获得稳定的锁模脉冲列的实验研究有参考意义。     

振幅和相位涨落对锁模脉冲列特性的影响

用傅里叶变换的方法分析了锁模激光器中模式间的相位和振幅涨落对锁模脉冲列特性的影响。将锁模激光器中各模式的相位和振幅涨落作傅里叶展开,再通过增益谱抽样的傅里叶变化得到其时域行为。分析结果表明振幅系统涨落及随机涨落均不引起脉宽的明显变化,只引起脉冲间背景的加大,但相位涨落随机会使脉冲列强度产生波动。所用物理图像简明,结果对获得稳定的锁模脉冲列的实验研究有参考意义。     

Comparison of the small-world topology between anatomical and functional connectivity in the human brain

We applied graph analysis to both anatomical and functional connectivity in the human brain. Anatomical connectivity was acquired from diffusion tensor imaging data by probabilistic fiber tracking, and functional connectivity was extracted from resting-state functional magnetic resonance imaging data by calculating correlation maps of time series. For the same subject, anatomical networks seemed to be disassortative, while functional networks were significantly assortative. Anatomical networks showed higher efficiency and smaller diameters than functional networks. It can be proposed that anatomical connectivity, as a major constraint of functional connectivity, has a relatively stable and efficient structure to support functional connectivity that is more changeable and flexible.