Quantitative analysis of asymmetrical cortical activity in motor areas during sequential finger movement

Brain asymmetry is a phenomenon well known for handedness and has been studied in motor cortices. However, few quantitative studies on asymmetrical cortical activity in motor areas have been conducted. In this study, we systematically investigated asymmetrical cortical activity in motor areas during sequential finger movement by quantitatively analyzing functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) responses. The norm of BOLD signal percentage of change was introduced to quantitatively measure the BOLD signal intensity change difference between the left and right motor areas. The results of the data collected from six subjects show that the norm of BOLD signal percentage of change in the right motor area is higher than that in the left motor area for two-hand movement (P=.0059) and single-hand movement (P=.0279) with right-handedness. These results from fMRI show the asymmetry of motor areas and may suggest that the left hemisphere motor area comes into being as an adaptation system that needs few neuron cells only to finish any movement task for right-handedness. The activation intensity in the left motor area is reduced with normal right finger movement. The activation intensity in the right motor area is obviously higher than that in the left motor area.     

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.     

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.     

Biophysical and neural basis of resting state functional connectivity: Evidence from non-human primates

Functional MRI (fMRI) has evolved from simple observations of regional changes in MRI signals caused by cortical activity induced by a task or stimulus, to task-free acquisitions of images in a resting state. Such resting state signals contain low frequency fluctuations which may be correlated between voxels, and strongly correlated regions are deemed to reflect functional connectivity within synchronized circuits. Resting state functional connectivity (rsFC) measures have been widely adopted by the neuroscience community, and are being used and interpreted as indicators of intrinsic neural circuits and their functional states in a broad range of applications, both basic and clinical. However, there has been relatively little work reported that validates whether inter-regional correlations in resting state fluctuations of fMRI (rsfMRI) signals actually measure functional connectivity between brain regions, or to establish how MRI data correlate with other metrics of functional connectivity. In this mini-review, we summarize recent studies of rsFC within mesoscopic scale cortical networks (100 μm–10 mm) within a well defined functional region of primary somatosensory cortex (S1), as well as spinal cord and brain white matter in non-human primates, in which we have measured spatial patterns of resting state correlations and validated their interpretation with electrophysiological signals and anatomic connections. Moreover, we emphasize that low frequency correlations are a general feature of neural systems, as evidenced by their presence in the spinal cord as well as white matter. These studies demonstrate the valuable role of high field MRI and invasive measurements in an animal model to inform the interpretation of human imaging studies.     

Post-stimulus response in hemodynamics observed by functional magnetic resonance imaging--difference between the primary sensorimotor area and the supplementary motor area

The blood oxygen level dependency (BOLD) contrast is a useful tool for functional neuroimaging based on the hemodynamic response to neuronal activation. We observed different hemodynamic responses in the BOLD signal between the primary sensorimotor area (SM1) and the supplementary motor area (SMA) in the sequential finger movement task. In the SMA, a stronger initial overshoot and a post-stimulus overshoot were observed. It was hypothesized from the time course analysis that the stronger initial overshoot reflected the activation of the SMA for motor control programming in the initial phase. Although the post-stimulus overshoot may be partially explained by cerebral blood flow (CBF) cerebral blood volume (CBV) uncoupling, its mechanism remained unknown. In the SM1, only the initial overshoot was observed and the level of BOLD signal was almost constant after the initial overshoot during the task period. These observations suggested that the BOLD signal is characterized by both CBF-CBV uncoupling and the neuronal activation characteristics in each region.     

Origins of intersubject variability of blood oxygenation level dependent and arterial spin labeling fMRI: implications for quantification of brain activity

Accurate localization of brain activity using blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been challenged because of the large BOLD signal within distal veins. Arterial spin labeling (ASL) techniques offer greater sensitivity to the microvasculature but possess low temporal resolution and limited brain coverage. In this study, we show that the physiological origins of BOLD and ASL depend on whether percent change or statistical significance is being considered. For BOLD and ASL fMRI data collected during a simple unilateral hand movement task, we found that in the area of the contralateral motor cortex the centre of gravity (CoG) of the intersubject coefficient of variation (CV) of BOLD fMRI was near the brain surface for percent change in signal, whereas the CoG of the intersubject CV for Z-score was in close proximity of sites of brain activity for both BOLD and ASL. These findings suggest that intersubject variability of BOLD percent change is vascular in origin, whereas the origin of inter-subject variability of Z-score is neuronal for both BOLD and ASL. For longer duration tasks (12 s or greater), however, there was a significant correlation between BOLD and ASL percent change, which was not evident for short duration tasks (6 s). These findings suggest that analyses directly comparing percent change in BOLD signal between pre-defined regions of interest using short duration stimuli, as for example in event-related designs, may be heavily weighted by large-vessel responses rather than neuronal responses.     

Brain oscillatory activity during motor imagery in EEG-fMRI coregistration

The purpose of the present work was to investigate the correlation between topographical changes in brain oscillatory activity and the blood oxygenation level-dependent (BOLD) signal during a motor imagery (MI) task using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) coregistration.     

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.     

Functional MRI and multivariate autoregressive models

Connectivity refers to the relationships that exist between different regions of the brain. In the context of functional magnetic resonance imaging (fMRI), it implies a quantifiable relationship between hemodynamic signals from different regions. One aspect of this relationship is the existence of small timing differences in the signals in different regions. Delays of 100 ms or less may be measured with fMRI, and these may reflect important aspects of the manner in which brain circuits respond as well as the overall functional organization of the brain. The multivariate autoregressive time series model has features to recommend it for measuring these delays and is straightforward to apply to hemodynamic data. In this review, we describe the current usage of the multivariate autoregressive model for fMRI, discuss the issues that arise when it is applied to hemodynamic time series and consider several extensions. Connectivity measures like Granger causality that are based on the autoregressive model do not always reflect true neuronal connectivity; however, we conclude that careful experimental design could make this methodology quite useful in extending the information obtainable using fMRI.     

Regional homogeneity of resting-state fMRI contributes to both neurovascular and task activation variations

The task induced blood oxygenation level dependent signal changes observed using functional magnetic resonance imaging (fMRI) are critically dependent on the relationship between neuronal activity and hemodynamic response. Therefore, understanding the nature of neurovascular coupling is important when interpreting fMRI signal changes evoked via task. In this study, we used regional homogeneity (ReHo), a measure of local synchronization of the BOLD time series, to investigate whether the similarities of one voxel with the surrounding voxels are a property of neurovascular coupling. FMRI scans were obtained from fourteen subjects during bilateral finger tapping (FTAP), digit–symbol substitution (DSST) and periodic breath holding (BH) paradigm. A resting-state scan was also obtained for each of the subjects for 4 min using identical imaging parameters. Inter-voxel correlation analyses were conducted between the resting-state ReHo, resting-state amplitude of low frequency fluctuations (ALFF), BH responses and task activations within the masks related to task activations. There was a reliable mean voxel-wise spatial correlation between ReHo and other neurovascular variables (BH responses and ALFF). We observed a moderate correlation between ReHo and task activations (FTAP: r = 0.32; DSST: r = 0.22) within the task positive network and a small yet reliable correlation within the default mode network (DSST: r = − 0.08). Subsequently, a linear regression was used to estimate the contribution of ReHo, ALFF and BH responses to the task activated voxels. The unique contribution of ReHo was minimal. The results suggest that regional synchrony of the BOLD activity is a property that can explain the variance of neurovascular coupling and task activations; but its contribution to task activations can be accounted for by other neurovascular factors such as the ALFF.     

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.     

Non-neural BOLD variability in block and event-related paradigms

Block and event-related stimulus designs are typically used in fMRI studies depending on the importance of detection power or estimation efficiency. The extent of vascular contribution to variability in block and event-related fMRI-BOLD response is not known. With scaling, the extent of vascular variability in the fMRI-BOLD response during block and event-related design tasks was investigated. Blood oxygen level-dependent (BOLD) contrast data from healthy volunteers performing a block design motor task and an event-related memory task requiring performance of a motor response were analyzed from the regions of interest (ROIs) surrounding the primary and supplementary motor cortices. Average BOLD signal change was significantly larger during the block design compared to the event-related design. In each subject, BOLD signal change across voxels in the ROIs had higher variation during the block design task compared to the event-related design task. Scaling using the resting state fluctuation of amplitude (RSFA) and breath-hold (BH), which minimizes BOLD variation due to vascular origins, reduced the within-subject BOLD variability in every subject during both tasks but significantly reduced BOLD variability across subjects only during the block design task. The strong non-neural source of intra- and intersubject variability of BOLD response during the block design compared to event-related task indicates that study designs optimizing for statistical power through enhancement of the BOLD contrast (for, e.g., block design) can be affected by enhancement of non-neural sources of BOLD variability.     

BOLD signal and vessel dynamics: a hierarchical cluster analysis

The aim of the present study was to analyze blood oxygenation level-dependent (BOLD) signal variation during an apnea-based task in order to assess the capability of a functional magnetic resonance imaging (fMRI) procedure to estimate cerebral vascular dynamic effects. We measured BOLD contrast by hierarchical cluster analysis in healthy subjects undergoing an fMRI experiment, in which the task paradigm was one phase of inspirational apnea (IA). By processing the time courses of the fMRI experiment, analysis was performed only on a subclass of all the possible signal patterns; basically, root mean square and absolute variation differences have been calculated. Considering the baseline value obtained by computing the mean value of the initial rest period as reference, particular voxels showed relative important variations during the IA task and during the recovery phase following the IA. We focused our interest on the signal response of voxels that would correspond mainly to white and gray matter regions and that also may be affected by the proximity of large venous vessels. The results are presented as maps of space-temporal distribution of time series variations with two levels of hierarchical clustering among voxels with low to high initial response. Furthermore, we have presented a clustering of the signal response delay, conducting to a partition and identification of specified brain sites.     

Functional MRI of the motor cortex using a conventional gradient system: comparison of FLASH and EPI techniques

Gradient echo (GE) and echo planar imaging (EPI) techniques are two different approaches to functional MRI (fMRI). In contrast to GE sequences, the ultra short EPI technique facilitates fMRI experiments with high spatial and temporal resolution or mapping of the whole brain. Although it has become the method of choice for fMRI, EPI is generally restricted to modern scanners with a strong gradient system. The aim of our study was to evaluate the applicability of EPI for fMRI of the motor cortex using a 1.5 T scanner with a conventional gradient system of 10 mT/m (rise time: 1 ms). Therefore, EPI was compared with a well-established high resolution fast low angle shot (FLASH) technique (matrix size 128²). The FLASH technique was applied additionally with a 64² matrix size to exclude influences caused by different spatial resolution, because the EPI sequence was restricted to a 64² matrix size. A total of 35 healthy volunteers were included in this study. The task consisted of clenching and spreading of the right hand. FLASH and EPI techniques were compared regarding geometric distortions as well as qualitative and quantitative fMRI criteria: Mean signal increase between activation and rest and the area of activation were measured within the contralateral, ipsilateral, and supplementary motor cortex. The quality of subtraction images between activation and rest, as well as the quality of z-maps and time course within activated regions of interest, was evaluated visually. EPI revealed significant distortions of the anterior and postior brain margins; lateral distortions (relevant for the motor cortex) could be neglected in most cases. The mean signal increase was significantly higher using FLASH 128² compared to FLASH 64² and EPI 64², whereas the activated areas proved to be smaller in FLASH 128² functional images. Both results can be explained by well-documented partial volume effects, caused by different voxel size. Similar quality of the subtraction images and of the time courses in different regions of interest were found for all techniques under investigation, but slightly reduced quality of z-map in FLASH 128². Within the limits of reproducibility and measurement accuracy, the location of contralateral activation was similar using FLASH and EPI sequences. In conclusion, EPI proved to be a reliable technique for fMRI of the motor cortex, even on an MR scanner with a conventional gradient system.     

Activation volume vs BOLD signal change as measures of fMRI activation – Its impact on GABA – fMRI activation correlation

PurposeTo explore the relative robustness of functional MRI (fMRI) activation volume and blood oxygen level-dependent (BOLD) signal change as fMRI metric, and to study the effect of relative robustness on the correlation between fMRI activation and cortical gamma amino butyric acid (GABA) in healthy controls and patients with multiple sclerosis (MS).MethodsfMRI data were acquired from healthy controls and patients with MS, with the subjects peforming self paced bilateral finger tapping in block design. GABA spectroscopy was performed with voxel placed on the area of maximum activation during fMRI. Activation volume and BOLD signal changes at primary motor cortex (M1), as well as GABA concentration were calculated for each patient.ResultsActivation volume correlated with BOLD signal change in healthy controls, but no such correlation was observed in patients with MS. This difference was likely the result of higher intersubject noise variance in the patient population. GABA concentration correlated with M1 activation volume in patients but not in controls, and did not correlate with any fMRI metric in patients or controls.ConclusionOur data suggest that activation volume is a more robust measure than BOLD signal change in a group with high intersubject noise variance as in patients with MS. Additionally, this study demonstrated difference in correlation behavior between GABA concentration and the 2 fMRI metrics in patients with MS, suggesting that GABA - activation volume correlation is more appropriate measure in the patient group.     

Neural and vascular variability and the fMRI-BOLD response in normal aging

Neural, vascular and structural variables contributing to the blood oxygen level-dependent (BOLD) signal response variability were investigated in younger and older humans. Twelve younger healthy human subjects (six male and six female; mean age: 24 years; range: 19–27 years) and 12 older healthy subjects (five male and seven female; mean age: 58 years; range: 55–71 years) with no history of head trauma and neurological disease were scanned. Functional magnetic resonance imaging measurements using the BOLD contrast were made when participants performed a motor, cognitive or a breath hold (BH) task. Activation volume and the BOLD response amplitude were estimated for the younger and older at both group and subject levels. Mean activation volume was reduced by 45%, 40% and 38% in the elderly group during the motor, cognitive and BH tasks, respectively, compared to the younger. Reduction in activation volume was substantially higher compared to the reduction in the gray matter volume of 14% in the older compared to the younger. A significantly larger variability in the intersubject BOLD signal change occurred during the motor task, compared to the cognitive task. BH-induced BOLD signal change between subjects was significantly less-variable in the motor task-activated areas in the younger compared to older whereas such a difference between age groups was not observed during the cognitive task. Hemodynamic scaling using the BH signal substantially reduced the BOLD signal variability during the motor task compared to the cognitive task. The results indicate that the origin of the BOLD signal variability between subjects was predominantly vascular during the motor task while being principally a consequence of neural variability during the cognitive task. Thus, in addition to gray matter differences, the type of task performed can have different vascular variability weighting that can influence age-related differences in brain functional response.     

Effects of mild hypoxic hypoxia on poststimulus undershoot of blood-oxygenation-level-dependent fMRI signal in the human visual cortex

Characteristics of the blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal poststimulus undershoot in the visual cortex were studied at varying levels of arterial blood oxygen saturation (Ysat). Undershoot with an amplitude of -0.6+/-0.2% appeared after positive BOLD response (+1.7+/-0.5%) under control conditions. Cerebral blood volume (CBV), as determined with vascular-space-occupancy-dependent fMRI, increased by 26-43% during the positive BOLD peak, but the CBV proceeded at baseline level during the BOLD poststimulus undershoot. Mild hypoxic hypoxia (Ysat ranging from 0.82 to 0.89) had no effect on the amplitude or duration of poststimulus undershoot in activated BOLD pixels. Hypoxia did not influence CBV during the BOLD poststimulus undershoot. In contrast, the positive BOLD signal at the level of all activated pixels was smaller in hypoxia than in normoxia. The present results show that the BOLD poststimulus undershoot is not influenced by curtailed oxygen availability and that, during the undershoot, CBV is not different from resting state.     

A comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response

Blood oxygenation level-dependent (BOLD) contrast-based functional magnetic resonance imaging (fMRI) has been widely utilized to detect brain neural activities and great efforts are now stressed on the hemodynamic processes of different brain regions activated by a stimulus. The focus of this paper is the comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response. The convolutions are between the perfusion function of the neural response to a stimulus and a Gaussian or Gamma function. The parameters of the two models are estimated by a nonlinear least-squares optimal algorithm for the fMRI data of eight subjects collected in a visual stimulus experiment. The results show that the Gaussian model is better than the Gamma model in fitting the data. The model parameters are different in the left and right occipital regions, which indicate that the dynamic processes seem different in various cerebral functional regions.     

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.     

An investigation of the relationship between BOLD and perfusion signal changes during epileptic generalised spike wave activity

In pathological conditions interpretation of functional magnetic resonance imaging (fMRI) results can be difficult. This is due to a reliance on the assumed coupling between neuronal activity and changes in cerebral blood flow (CBF) and oxygenation. We wanted to investigate the coupling between blood oxygen level dependant contrast (BOLD) and CBF time courses in epilepsy patients with generalised spike wave activity (GSW) to better understand the underlying mechanisms behind the EEG-fMRI signal changes observed, especially in regions of negative BOLD response (NBR). Four patients with frequent GSW were scanned with simultaneous electroencephalographic (EEG)-fMRI with BOLD and arterial spin labeling (ASL) sequences. We examined the relationship between simultaneous CBF and BOLD measurements by looking at the correlation of the two signals in terms of percentage signal change on a voxel-by-voxel basis. This method is not reliant on coincident activation. BOLD and CBF were positively correlated in patients with epilepsy during background EEG activity and GSW. The subject average value of the Delta CBF/Delta BOLD slope lay between +19 and +36 and also showed spatial variation which could indicate areas with altered vascular response. There was not a significant difference between Delta CBF/Delta BOLD during GSW, suggesting that neurovascular coupling to BOLD signal is generally maintained between states and, in particular, within areas of NBR.