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.     

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.     

Brain modifications after acute alcohol consumption analyzed by resting state fMRI

Resting-state functional magnetic resonance imaging (fMRI) is a recent breakthrough in neuroimaging research able to describe “in vivo” the spontaneous baseline neuronal activity characterized by blood oxygen level dependent (BOLD) signal fluctuations at slow frequency (0.01–0.1 Hz) that, in the absence of any task, forms spatially distributed functional connectivity networks, called resting state networks (RSNs). The aim of this study was to investigate, in the young and healthy population, the changing of the RSNs after acute ingestion of an alcohol dose able to determine a blood concentration (0.5 g/L) that barely exceeds the legal limits for driving in the majority of European Countries. Fifteen healthy volunteers underwent two fMRI sessions using a 1.5 T MR scanner before and after alcohol oral consumption. The main sequence acquired was EPI 2D BOLD, one per each session. To prevent the excessive alcohol consumption the subjects underwent the estimation of blood rate by breath test and after the stabilization of blood alcohol level (BAL) at 0.5 g/L the subjects underwent the second fMRI session. Functional data elaboration was carried out using the probabilistic independent component analysis (PICA). Spatial maps so obtained were further organized, with MELODIC multisession temporal concatenation FSL option, in a cluster representing the group of pre-alcohol sessions and the group of post-alcohol sessions, followed by the dual regression approach in order to evaluate the increase or decrease in terms of connectivity in the RSNs between the two sessions at group level.The results we obtained reveal that acute consumption of alcohol reduces in a significant way the BOLD signal fluctuations in the resting brain selectively in the sub-callosal cortex (SCC), in left temporal fusiform cortex (TFC) and left inferior temporal gyrus (ITG), which are cognitive regions known to be part of the reward brain network and the ventral visual system.     

静息状态下脑功能连接的磁共振成像研究

静息状态下脑功能连接的磁共振成像研究近年来取得了迅猛发展. 通过对fMRI信号低频涨落成分的同步性分析,可以得到大脑静息态任意脑区的功能连接和多套网络系统,其中“默认网络”的发现可能为人脑固有网络的研究提供新的思路. 而静息态网络与解剖连接之间可能存在的对应,以及在神经精神疾病患者脑中性质和连接的异常改变,使其具有重要的研究和临床应用价值. 该文总结了静息状态功能磁共振成像的主要研究成果,对静息状态脑功能网络的发现和发展、研究方法、各网络及其特点以及在临床方面的应用进行简单的介绍和分析.     

Hierarchical clustering to measure connectivity in fMRI resting-state data

Low frequency oscillations, which are temporally correlated in functionally related brain regions, characterize the mammalian brain, even when no explicit cognitive tasks are performed. Functional connectivity MR imaging is used to map regions of the resting brain showing synchronous, regional and slow fluctuations in cerebral blood flow and oxygenation. In this study, we use a hierarchical clustering method to detect similarities of low-frequency fluctuations. We describe one measure of correlations in the low frequency range for classification of resting-state fMRI data. Furthermore, we investigate the contribution of motion and hardware instabilities to resting-state correlations and provide a method to reduce artifacts. For all cortical regions studied and clusters obtained, we quantify the degree of contamination of functional connectivity maps by the respiratory and cardiac cycle. Results indicate that patterns of functional connectivity can be obtained with hierarchical clustering that resemble known neuronal connections. The corresponding voxel time series do not show significant correlations in the respiratory or cardiac frequency band.     

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.     

The effect of sensorimotor activation on functional connectivity mapping with MRI

The correlations in the fluctuations in the blood oxygenation level-dependent (BOLD) MRI signal between anatomically distinct regions of the cortex that are known components of functional systems have been previously studied as possible indicators of functional connectivity. The objective of this study was to examine the effect of sensorimotor brain activity, as assessed by task-based functional magnetic resonance imaging (fMRI), on functional connectivity indices in the same region. Regions of activation for sequential finger motion were determined using a task-based, block-design fMRI study. Functional connectivity measurements based on interregional correlations were acquired at rest and during continuous, sequential finger motion. Connectivity indices were determined using normalized mean correlations within and between three regions of interest activated for the finger motion task. Connectivity indices were also determined for a control region that was not activated for the task. Continuous motor tasks performed during BOLD measurements did not significantly affect the functional connectivity as compared to the connectivity at rest within or between regions known to be activated by the task. However, there appeared to be a trend suggesting a slight reduction in connectivity indices during the motor task. The connectivity within and between those areas not activated for the task remained unchanged between conditions. These results suggest that in the motor system investigated, the recruitment of neurons to perform a specific task may moderately reduce the degree of hemodynamic coupling within and between regions.     

Acute and chronic MRI changes in the spine and spinal cord after surgical stem cell grafting in patients with definite amyotrophic lateral sclerosis: Post-infusion injuries are unrelated with clinical impairment

ObjectiveTo report MRI spinal changes after surgical infusion of bone marrow stem cells (BMSc) in ALS patients and assess their correlation with clinical events and functional performance.MethodsBMSc were surgically injected in the thoracic spinal cord of 11 ALS patients (6/5 male/female; median age 46 years). We performed first-week and third, sixth, ninth and twelfth post-surgical months spinal MRIs. The spinal changes in the postsurgical week and follow-up MRIs, as well as clinical events, functional scales and respiratory and electromyography data, were longitudinally monitored. Correlations between the imaging and clinical data were evaluated with the Spearman's test.ResultsTransient extradural fluid collections (100%), transient spinal cord T2 hyperintensity (81.8%), and chronic spinal cord deformities (63.6%) were the dominating MRI changes. Spinal cord hemorrhages (27.3%) and cystic myelomalacia (1/11 patients) were important although unusual findings. During the follow-up, minor adverse events of mild to moderate intensity eventually improved. Initial and follow-up imaging scores showed a strongly positive correlation (r 0.879, P < 0.001). The initial and delayed clinical scores did not correlate. There was no significant correlation between any of the imaging scores and clinical data.ConclusionsInfusion of BMSc produces a variety of spinal changes apparently unrelated with clinical events and disease worsening.     

Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets

A new approach in studying interregional functional connectivity using functional magnetic resonance imaging (fMRI) is presented. Functional connectivity may be detected by means of cross correlating time course data from functionally related brain regions. These data exhibit high temporal coherence of low frequency fluctuations due to synchronized blood flow changes. In the past, this fMRI technique for studying functional connectivity has been applied to subjects that performed no prescribed task ("resting" state). This paper presents the results of applying the same method to task-related activation datasets. Functional connectivity analysis is first performed in areas not involved with the task. Then a method is devised to remove the effects of activation from the data using independent component analysis (ICA) and functional connectivity analysis is repeated. Functional connectivity, which is demonstrated in the "resting brain," is not affected by tasks which activate unrelated brain regions. In addition, ICA effectively removes activation from the data and may allow us to study functional connectivity even in the activated regions.     

Characterization of cardiac-related noise in fMRI of the cervical spinal cord

Magnetic resonance imaging (MRI) has recently been applied to study spinal cord function in humans. However, spinal functional MRI (fMRI) encounters major technical challenges with cardiac noise being considered a major source of noise. The present study relied on echo-planar imaging of the cervical cord at short TR (TR=250 ms; TE=40 ms; flip=45 degrees), combined with plethysmographic recordings to characterize the spatiotemporal properties of cardiac-induced signal changes in spinal fMRI. Frequency-based analyses examining signal change at the cardiac frequency confirmed mean fluctuations of about 10% (relative to the mean signal) in the spinal cord and surrounding cerebrospinal fluid (CSF), with maximal responses reaching up to 66% in some voxels. A spatial independent component analysis (sICA) confirmed that cardiac noise is an important source of variance in spinal fMRI with several components showing a response coherent with the cardiac frequency spectrum. The time course of the main cardiac components approximated a sinusoidal function tightly coupled to the cardiac systole with at least one component showing a comparable temporal profile across runs and subjects. Spatially, both the frequency-domain analysis and the sICA demonstrated cardiac noise distributed irregularly along the full rostrocaudal extent of the segments scanned with peaks concentrated in the ventral part of the lateral slices in all scans and subjects, consistent with the major channels of CSF flow. These results confirm that cardiac-induced changes are a significant source of noise likely to affect the detection of spinal Blood Oxygen Level Dependent (BOLD) responses. Most importantly, the complex spatiotemporal structure of cardiac noise is unlikely to be accounted for adequately by ad hoc linear methods, especially in data acquired using long TR (i.e. aliasing the cardiac frequency). However, the reliable spatiotemporal distribution of cardiac noise across scanning runs and within subjects may provide a valid means to identify and extract cardiac noise based on sICA methods.     

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.     

Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG

Different brain imaging devices are presently available to provide images of the human functional cortical activity, based on hemodynamic, metabolic or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions are interconnected. The concept of brain connectivity plays a central role in the neuroscience, and different definitions of connectivity, functional and effective, have been adopted in literature. While the functional connectivity is defined as the temporal coherence among the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally among cortical sites. The structural equation modeling (SEM) is the most used method to estimate effective connectivity in neuroscience, and its typical application is on data related to brain hemodynamic behavior tested by functional magnetic resonance imaging (fMRI), whereas the directed transfer function (DTF) method is a frequency-domain approach based on both a multivariate autoregressive (MVAR) modeling of time series and on the concept of Granger causality.

This study presents advanced methods for the estimation of cortical connectivity by applying SEM and DTF on the cortical signals estimated from high-resolution electroencephalography (EEG) recordings, since these signals exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. To estimate correctly the cortical signals, we used a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual MRI, a distributed source model and a regularized linear inverse source estimates of cortical current density. Before the application of SEM and DTF methodology to the cortical waveforms estimated from high-resolution EEG data, we performed a simulation study, in which different main factors (signal-to-noise ratio, SNR, and simulated cortical activity duration, LENGTH) were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). The statistical analysis returned that during simulations, both SEM and DTF estimators were able to correctly estimate the imposed connectivity patterns under reasonable operative conditions, that is, when data exhibit an SNR of at least 3 and a LENGTH of at least 75 s of nonconsecutive EEG recordings at 64 Hz of sampling rate.

Hence, effective and functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in any practical EEG recordings, by combining high-resolution EEG techniques and linear inverse estimation with SEM or DTF methods. We conclude that the estimation of cortical connectivity can be performed not only with hemodynamic measurements, but also with EEG signals treated with advanced computational techniques.     

Issues about the fMRI of the human spinal cord

Noninvasive functional studies on human spinal cord by means of magnetic resonance imaging (MRI) are gaining attention because of the promising applications in the study of healthy and injured central nervous system. The findings obtained are generally consistent with the anatomic knowledge based on invasive methods, but the origin and specificity of functional contrast is still debated. In this paper, a review of current knowledge and major issues about functional MRI (fMRI) in the human spinal cord is presented, with emphasis on the main methodological and technical problems and on forthcoming applications as clinical tool.     

Fine-scale functional connectivity in somatosensory cortex revealed by high-resolution fMRI

High-resolution functional magnetic resonance imaging (fMRI) at high field (9.4 T) has been used to measure functional connectivity between subregions within the primary somatosensory (SI) cortex of the squirrel monkey brain. The hand-face region within the SI cortex of the squirrel monkey has been previously well mapped with functional imaging and electrophysiological and anatomical methods, and the orderly topographic map of the hand region is characterized by a lateral to medial representation of individual digits in four subregions of areas 3a, 3b, 1 and 2. With submillimeter resolution, we are able to detect not only the separate islands of activation corresponding to vibrotactile stimulations of single digits but also, in subsequent acquisitions, the degree of correlation between voxels within the SI cortex in the resting state. The results suggest that connectivity patterns are very similar to stimulus-driven distributions of activity and that connectivity varies on the scale of millimeters within the same primary region. Connectivity strength is not a reflection of global larger-scale changes in blood flow and is not directly dependent on distance between regions. Preliminary electrophysiological recordings agree well with the fMRI data. In human studies at 7 T, high-resolution fMRI may also be used to identify the same subregions and assess responses to sensory as well as painful stimuli, and to measure connectivity dynamically before and after such stimulations.     

Influence of attention focus on neural activity in the human spinal cord during thermal sensory stimulation

Perceptions of sensation and pain in healthy people are believed to be the net result of sensory input and descending modulation from brainstem and cortical regions depending on emotional and cognitive factors. Here, the influence of attention on neural activity in the spinal cord during thermal sensory stimulation of the hand was investigated with functional magnetic resonance imaging by systematically varying the participants' attention focus across and within repeated studies. Attention states included (1) attention to the stimulus by rating the sensation and (2) attention away from the stimulus by performing various mental tasks of watching a movie and identifying characters, detecting the direction of coherently moving dots within a randomly moving visual field and answering mentally-challenging questions. Functional MRI results spanning the cervical spinal cord and brainstem consistently demonstrated that the attention state had a significant influence on the activity detected in the cervical spinal cord, as well as in brainstem regions involved with the descending analgesia system. These findings have important implications for the detection and study of pain, and improved characterization of the effects of injury or disease.     

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.     

Diffusion tensor imaging of the cervical spinal cord of patients with Neuromyelitis Optica

BackgroundPrevious studies have demonstrated a correlation between Expanded Disability Status Scale (EDSS) and Diffusion Tensor Imaging (DTI) metrics, but the conclusions were based on evaluations of the entire cervical spinal cord.ObjectivesThe purpose of this study was to quantify the FA and MD values in the spinal cord of NMO patients, separating the lesion sites from the preserved sites, which has not been previously preformed. In addition, we attempted to identify a correlation with EDSS.MethodsDTI was performed in 11 NMO patients and 11 healthy individuals using a 1.5-T MRI scanner. We measured the FA and MD at ROIs positioned along the cervical spinal cord. The mean values of FA and MD at lesion, preserved and spinal cord sites were compared with those of a control group. We tested the correlations between the mean FA and MD with EDSS.ResultsFA in NMO patients was significantly reduced in lesion sites (0.44 vs. 0.55, p = 0.0046), preserved sites (0.46 vs. 0.55, p = 0.0015), and all sites (0.45 vs 0.55, p = 0.0013) while MD increased only in lesion sites (1.03 × 10^− 3 mm²/s vs. 0.90 × 10^− 3 mm²/s, p = 0.009). The FA demonstrated the best correlation with EDSS (r = − 0.7603, p = 0.0086), particularly at lesion sites.ConclusionsThe results reinforce the importance of the FA index and confirm the hypothesis that NMO is a diffuse disease.     

Comparison of α-chloralose,medetomidine and isoflurane anesthesia for functional connectivity mapping in the rat

Functional connectivity measures based upon low-frequency blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) signal fluctuations have become a widely used tool for investigating spontaneous brain activity in humans. Still unknown, however, is the precise relationship between neural activity, the hemodynamic response and fluctuations in the MRI signal. Recent work from several groups had shown that correlated low-frequency fluctuations in the BOLD signal can be detected in the anesthetized rat — a first step toward elucidating this relationship. Building on this preliminary work, through this study, we demonstrate that functional connectivity observed in the rat depends strongly on the type of anesthesia used. Power spectra of spontaneous fluctuations and the cross-correlation-based connectivity maps from rats anesthetized with α-chloralose, medetomidine or isoflurane are presented using a high-temporal-resolution imaging sequence that ensures minimal contamination from physiological noise. The results show less localized correlation in rats anesthetized with isoflurane as compared with rats anesthetized with α-chloralose or medetomidine. These experiments highlight the utility of using different types of anesthesia to explore the fundamental physiological relationships of the BOLD signal and suggest that the mechanisms contributing to functional connectivity involve a complicated relationship between changes in neural activity, neurovascular coupling and vascular reactivity.     

Noninvasive observation of cervical spinal cord activity in children by functional MRI during cold thermal stimulation

Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging tool that indirectly identifies areas of neural activity in the brain and more recently has been applied to the adult spinal cord (spinal fMRI). Spinal fMRI could clearly benefit pediatric populations as well. The purpose of this work was to characterize the response observed with spinal fMRI in the brainstem and cervical (C) spinal cord of awake, healthy children during thermal stimulation (17°C and 27°C) applied to the right hand. Functional MRI detected neuronal activity in the expected region of the spinal cord (C6 and C7) as well as in the brainstem and thalamus. The observed magnitudes of signal change of the responses to 17°C and 27°C were similar; however, the spatial distribution of active pixels was greater during 17°C stimulation. The results of this study indicate that fMRI can be used to assess activity in the spinal cords of children, with good sensitivity and reliability.     

Measurement and characterization of the human spinal cord SEEP response using event-related spinal fMRI

Although event-related fMRI is able to reliably detect brief changes in brain activity and is now widely used throughout systems and cognitive neuroscience, there have been no previous reports of event-related spinal cord fMRI. This is likely attributable to the various technical challenges associated with spinal fMRI (e.g., imaging a suitable length of the cord, reducing image artifacts from the vertebrae and intervertebral discs, and dealing with physiological noise from spinal cord motion). However, with many of these issues now resolved, the largest remaining impediment for event-related spinal fMRI is a deprived understanding of the spinal cord fMRI signal time course. Therefore, in this study, we used a proton density-weighted HASTE sequence, with functional contrast based on signal enhancement by extravascular water protons (SEEP), and a motion-compensating GLM analysis to (i) characterize the SEEP response function in the human cervical spinal cord and (ii) demonstrate the feasibility of event-related spinal fMRI. This was achieved by applying very brief (1 s) epochs of 22°C thermal stimulation to the palm of the hand and measuring the impulse response function. Our results suggest that the spinal cord SEEP response (time to peak ≈8 s; FWHM ≈4 s; and probably lacking pre- and poststimulus undershoots) is slower than previous estimates of SEEP or BOLD responses in the brain, but faster than previously reported spinal cord BOLD responses. Finally, by detecting and mapping consistent signal-intensity changes within and across subjects, and validating these regions with a block-designed experiment, this study represents the first successful demonstration of event-related spinal fMRI.