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.     

Abnormal dynamics of cortical resting state functional connectivity in chronic headache patients

The goals of this study are to characterize the temporal dynamics of inter-regional connectivity of the brain in chronic headache (CH) patients versus their age/gender matched controls (CON_CH, n = 28 pairs), and to determine whether dynamic measures reveal additional features to static functional connectivity and correlate with psychometric scores. Cortical thickness and inter-regional resting state fMRI connectivity were quantified and compared between CH and CON_CH groups. Six cortical regions of interest (ROI) pairs that exhibited correlated cortical thickness and static functional connectivity abnormalities were selected for temporal dynamic analysis. Two methods were used: temporal sliding-window (SW) and wavelet transformation coherence (WTC). SW analyses using three temporal windows of 30, 60, 120 s revealed that all six ROI pairs of CH exhibited higher percentage of strong connectivity (high r values), and smaller fast Fourier transform (FFT) amplitudes at a very low frequency range (i.e., 0.002–0.01 Hz), compared to those of CON_CH. These features were particularly prevalent in the 120 s window analysis. Less variable dynamic fluctuation (i.e., smaller standard deviation of r values) was identified in two out of six ROI pairs in CH. WTC analysis revealed that time-averaged coherence was generally greater in CH than CON_CH between wavelet decomposition scales 20 to 55 (0.018–0.05 Hz), and was statistically significant in three out of six ROI pairs. Together, the most robust and significant differences in temporal dynamics between CH and CON_CH were detected in two ROI pairs: left medial-orbitofrontal–left posterior-cingulate and left medial-orbitofrontal–left inferior-temporal. The high degrees of sleep disturbance (high PSQI score), depression (high HRSD score) and fatigue (low SF-36 score) were associated with high degree of inter-regional temporal coherence in CH. In summary, these dynamic functional connectivity (dFC) measures uncovered a temporal “lock-down” condition in a subset of ROI pairs, showing static functional connectivity changes in CH patients. This study provides important evidence for the presence of associated psychological wellbeing and abnormal temporal dynamics in between specific cortical regions in CH patients.     

Asymmetrical hippocampal connectivity in mesial temporal lobe epilepsy: evidence from resting state fMRI

Background

Recent studies have shown that the human right-hemispheric auditory cortex is particularly sensitive to reduction in sound quality, with an increase in distortion resulting in an amplification of the auditory N1m response measured in the magnetoencephalography (MEG). Here, we examined whether this sensitivity is specific to the processing of acoustic properties of speech or whether it can be observed also in the processing of sounds with a simple spectral structure. We degraded speech stimuli (vowel /a/), complex non-speech stimuli (a composite of five sinusoidals), and sinusoidal tones by decreasing the amplitude resolution of the signal waveform. The amplitude resolution was impoverished by reducing the number of bits to represent the signal samples. Auditory evoked magnetic fields (AEFs) were measured in the left and right hemisphere of sixteen healthy subjects.

Results

We found that the AEF amplitudes increased significantly with stimulus distortion for all stimulus types, which indicates that the right-hemispheric N1m sensitivity is not related exclusively to degradation of acoustic properties of speech. In addition, the P1m and P2m responses were amplified with increasing distortion similarly in both hemispheres. The AEF latencies were not systematically affected by the distortion.

Conclusions

We propose that the increased activity of AEFs reflects cortical processing of acoustic properties common to both speech and non-speech stimuli. More specifically, the enhancement is most likely caused by spectral changes brought about by the decrease of amplitude resolution, in particular the introduction of periodic, signal-dependent distortion to the original sound. Converging evidence suggests that the observed AEF amplification could reflect cortical sensitivity to periodic sounds.     

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.     

Investigating the neural basis for fMRI-based functional connectivity in a blocked design: application to interregional correlations and psycho-physiological interactions

This paper investigates how well different kinds of fMRI functional connectivity analysis reflect the underlying interregional neural interactions. This is hard to evaluate using real experimental data where such relationships are unknown. Rather, we use a biologically realistic neural model to simulate both neuronal activities and multiregional fMRI data from a blocked design. Because we know how every element in the model is related to every other element, we can compare functional connectivity measurements across different spatial and temporal scales. We focus on (1) psycho-physiological interaction (PPI) analysis, which is a simple brain connectivity method that characterizes the activity in one brain region by the interaction between another region's activity and a psychological factor, and (2) interregional correlation analysis. We investigated the neurobiological underpinnings of PPI using simulated neural activities and fMRI signals generated by a large-scale neural model that performs a visual delayed match-to-sample task. Simulated fMRI data are generated by convolving integrated synaptic activities (ISAs) with a hemodynamic response function. The simulation was done under three task conditions: high-attention, low-attention and a control task ('passive viewing'). We investigated how biological and scanning parameters affect PPI and compared these with functional connectivity measures obtained using correlation analysis. We performed correlational and PPI analyses with three types of time-series data: ISA, fMRI and deconvolved fMRI (which yields estimated neural signals) obtained using a deconvolution algorithm. The simulated ISA can be considered as the 'gold standard' because it represents the underlying neural activity. Our main findings show (1) that evaluating the change in an interregional functional connection using the difference in regression coefficients (as is essentially done in the PPI method) produces results that better reflect the underlying changes in neural interrelationships than does evaluating the functional connectivity difference as a change in correlation coefficient; (2) that using fMRI and deconvolved fMRI data led to similar conclusions in the PPI-based functional connectivity results, and these generally agreed with the nature of the underlying neural interactions; and (3) the functional connectivity correlation measures often led to different conclusions regarding significance for different scanning and hemodynamic parameters, but the significances of the PPI regression parameters were relatively robust. These results highlight the way in which neural modeling can be used to help validate the inferences one can make about functional connectivity based on fMRI data.     

Single-subject manual independent component analysis and resting state fMRI connectivity outcomes in patients with juvenile absence epilepsy

The quality of fMRI data impacts functional connectivity measures and consequently, the decisions that clinicians and researchers make regarding functional connectivity interpretation. The present study used resting state fMRI to investigate resting state network connectivity in a sample of patients with Juvenile Absence Epilepsy. Single-subject manual independent component analysis was used in two levels, whereby all noise components were removed, and cerebrospinal fluid pulsation components only were isolated and removed. Improved temporal signal to noise ratios and functional connectivity metrics were observed in each of the cleaning levels for both epilepsy and control cohorts. Results showed full, single-subject manual independent component analysis reduced the number of functional connectivity correlations and increased the strength of these correlations. Similar effects were also observed for the cerebrospinal fluid pulsation only cleaned data relative to the uncleaned, and fully cleaned data. Single-subject manual independent component analysis coupled with short TR multiband acquisition can significantly improve the validity of findings derived from fMRI data sets.     

Pharmacokinetic analysis and drug delivery efficiency of the focused ultrasound-induced blood-brain barrier opening in non-human primates

PurposeFocused Ultrasound (FUS) in conjunction with systemically administered microbubbles has been shown to open the Blood-Brain Barrier (BBB) locally, non-invasively and reversibly in rodents and non-human primates (NHP), suggesting the immense potential of this technique. The objective of this study entailed the investigation of the physiologic changes in the brain following the FUS-induced BBB opening and their relationship with the underlying anatomy.Materials and methodsPharmacokinetic analysis was implemented in NHP's that received FUS at various acoustic pressures. Relaxivity mapping enabled the robust quantitative detection of the BBB opening as well as grey and white matter segmentation. Drug delivery efficiency was measured for pre-clinical validation of the technique.ResultsBased on our results, the opening volume and the amount of the gadolinium delivered were found mostly contained in the grey matter, while FUS-induced permeability and drug concentration varied depending upon the underlying brain inhomogeneity, and increased with the acoustic pressure.ConclusionsOverall, apart from the in vivo protocols for BBB analysis developed here, this study also suggests the important role that FUS can have in efficient drug delivery via localized and transient BBB opening.     

基于模糊近似熵的抑郁症患者静息态功能磁共振成像信号复杂度分析

提出采用模糊近似熵的方法对功能磁共振成像(functional magnetic resonance imaging,fMRI)复杂度量化分析,并与样本熵进行比较.采用的22个成年抑郁症患者中,11位男性,年龄在18—65岁之间.我们期望测量的静息态fMRI信号复杂度与Goldberger/Lipsitz模型一致,越健康、越稳健其生理表现的复杂度越大,且复杂度随年龄的增大而降低.全脑平均模糊近似熵与年龄之间差异性显著(r=-0.512,p0.001).相比之下,样本熵与年龄之间差异性不显著(r=-0.102,p=0.482).模糊近似熵同样与年龄相关脑区(额叶、顶叶、边缘系统、颞叶、小脑顶叶)之间差异性显著(p0.05),样本熵与年龄相关脑区之间差异性不显著性.这些结果与Goldberger/Lipsitz模型一致,说明采用模糊近似熵分析fMRI数据复杂度是一个有效的新方法.     

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.     

Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

Background

Minocycline, a second-generation tetracycline with anti-inflammatory and anti-apoptotic properties, has been shown to promote therapeutic benefits in experimental stroke. However, equally compelling evidence demonstrates that the drug exerts variable and even detrimental effects in many neurological disease models. Assessment of the mechanism underlying minocycline neuroprotection should clarify the drug's clinical value in acute stroke setting.

Results

Here, we demonstrate that minocycline attenuates both in vitro (oxygen glucose deprivation) and in vivo (middle cerebral artery occlusion) experimentally induced ischemic deficits by direct inhibition of apoptotic-like neuronal cell death involving the anti-apoptotic Bcl-2/cytochrome c pathway. Such anti-apoptotic effect of minocycline is seen in neurons, but not apparent in astrocytes. Our data further indicate that the neuroprotection is dose-dependent, in that only low dose minocycline inhibits neuronal cell death cascades at the acute stroke phase, whereas the high dose exacerbates the ischemic injury.

Conclusion

The present study advises our community to proceed with caution to use the minimally invasive intravenous delivery of low dose minocycline in order to afford neuroprotection that is safe for stroke.     

Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

Background  

The present work was performed to investigate the ability of two different embryonic stem (ES) cell-derived neural precursor populations to generate functional neuronal networks in vitro. The first ES cell-derived neural precursor population was cultivated as free-floating neural aggregates which are known to form a developmental niche comprising different types of neural cells, including neural precursor cells (NPCs), progenitor cells and even further matured cells. This niche provides by itself a variety of different growth factors and extracellular matrix proteins that influence the proliferation and differentiation of neural precursor and progenitor cells. The second population was cultivated adherently in monolayer cultures to control most stringently the extracellular environment. This population comprises highly homogeneous NPCs which are supposed to represent an attractive way to provide well-defined neuronal progeny. However, the ability of these different ES cell-derived immature neural cell populations to generate functional neuronal networks has not been assessed so far.     

Dynamics of a neural network model with finite connectivity and cycle stored patterns

The spatiotemporal evolution and memory retrieval properties of a Hopfield-like neural network with cycle-stored patterns and finite connectivity are studied. The analytical studies on a mean-field version show that, given the number of stored patterns p, there is a critical connectivity k_c such that the retrieval states are stable fixed points if and only if k > k_c. The dependence of k_c on the number of stored patterns is also present. The numerical simulations are applied to the short-ranged model with local interaction. It is revealed that, given p, the memory retrieval function is kept if the connectivity is high enough while the dynamics of the system is in the frozen phase. However when the connectivity k is less than a critical value k_c the system is in the chaotic phase and loses its memory retrieval ability. The critical points of both the dynamical phase transition and memory-loss phase transition are obtained by simulation data.     

Evidence for mixed-charge state from the normal-phase transport properties of cuprate superconductors

We derive the expressions for the resistivity, Hall coefficient and Hall angle for a cuprate superconductor crystal having semi-metal normal state characteristics and show that the normal-state transport properties can be explained in terms of the mixed-charge behavior of the system which, for highly mobile hole systems, leads to a R_H scaling rule [Phys. Rev. Lett. 72 (1994) 2636]. This is consistent with the mixed charge condensation model proposed earlier [Phys. Lett. A 208 (1995) 171].     

fMRI of the auditory system: understanding the neural basis of auditory gestalt

Functional magnetic resonance imaging (fMRI) has rapidly become the most widely used imaging method for studying brain functions in humans. This is a result of its extreme flexibility of use and of the astonishingly detailed spatial and temporal information it provides. Nevertheless, until very recently, the study of the auditory system has progressed at a considerably slower pace compared to other functional systems. Several factors have limited fMRI research in the auditory field, including some intrinsic features of auditory functional anatomy and some peculiar interactions between fMRI technique and audition. A well known difficulty arises from the high intensity acoustic noise produced by gradient switching in echo-planar imaging (EPI), as well as in other fMRI sequences more similar to conventional MR sequences. The acoustic noise interacts in an unpredictable way with the experimental stimuli both from a perceptual point of view and in the evoked hemodynamics. To overcome this problem, different approaches have been proposed recently that generally require careful tailoring of the experimental design and the fMRI methodology to the specific requirements posed by the auditory research. The novel methodological approaches can make the fMRI exploration of auditory processing much easier and more reliable, and thus may permit filling the gap with other fields of neuroscience research. As a result, some fundamental neural underpinnings of audition are being clarified, and the way sound stimuli are integrated in the auditory gestalt are beginning to be understood.     

Projections from the posterolateral olfactory amygdala to the ventral striatum: neural basis for reinforcing properties of chemical stimuli

Background  

Vertebrates sense chemical stimuli through the olfactory receptor neurons whose axons project to the main olfactory bulb. The main projections of the olfactory bulb are directed to the olfactory cortex and olfactory amygdala (the anterior and posterolateral cortical amygdalae). The posterolateral cortical amygdaloid nucleus mainly projects to other amygdaloid nuclei; other seemingly minor outputs are directed to the ventral striatum, in particular to the olfactory tubercle and the islands of Calleja.     

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.     

Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting' brain

Functional magnetic resonance imaging techniques using the blood oxygenation level-dependent (BOLD) contrast are widely used to map human brain function by relating local hemodynamic responses to neuronal stimuli compared to control conditions. There is increasing interest in spontaneous cerebral BOLD fluctuations that are prominent in the low-frequency range (<0.1 Hz) and show intriguing spatio-temporal correlations in functional networks. The nature of these signal fluctuations remains unclear, but there is accumulating evidence for a neural basis opening exciting new avenues to study human brain function and its connectivity at rest. Moreover, an increasing number of patient studies report disease-dependent variation in the amplitude and spatial coherence of low-frequency BOLD fluctuations (LFBF) that may afford greater diagnostic sensitivity and easier clinical applicability than standard fMRI. The main disadvantage of this emerging tool relates to physiological (respiratory, cardiac and vasomotion) and motion confounds that are challenging to disentangle requiring thorough preprocessing. Technical aspects of functional connectivity fMRI analysis and the neuroscientific potential of spontaneous LFBF in the default mode and other resting-state networks have been recently reviewed. This review will give an update on the current knowledge of the nature of LFBF, their relation to physiological confounds and potential for clinical diagnostic and pharmacological studies.     

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.     

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.