T1Effects in Sequential Dynamic Susceptibility Contrast Experiments

Residual effects of an initial bolus of gadolinium contrast agent have been previously demonstrated in sequential dynamic susceptibility contrast MR experiments. While these residual effects quickly reach a saturation steady state, their etiology is uncertain, and they can lead to spurious estimates of hemodynamic parameters in activation experiments. The possible influence ofT₁effects is now investigated with experiments in whichT₁weighting is varied as well as with serial regionalT₁measurements. Little evidence for significant residualT₁effects is found, suggesting instead that susceptibility effects underlie these observations. An initial saturation dose of contrast agent minimizes this effect.     

A template of rat brain based on fMRI T*2 imaging

The development of functional magnetic resonance imaging (fMRI) technology has made it possible to carry out functional brain imaging experiments in small animals. Usually, group data is required to form the assessment of population, which can not only increase the sensitivity of the overall experiment, but also allow the generalization of the conclusion to the whole population. In order to average the signals of functional brain images from different subjects, it is necessary to put all the mapping images into the same standard space (template image). However, up to now, most animal brain templates remain unavailable and it must be done by ourselves. In this study, a template image based on the brains of eight male Wistar rats is obtained, and it is successfully used in our present Alzheimer disease (AD)-like rat model studies as template for spatially normalizing images to the same stereotaxical space. The fMRI results processed with statistical parametric mapping (SPM99) software are in agreement with the results from immunohistochemical experiment, which proves that this method is universally applicable to the pathologic models of other small animals and to human brain lesion studies.     

Maximum likelihood estimation for second level fMRI data analysis with expectation trust region algorithm

The trust region method which originated from the Levenberg–Marquardt (LM) algorithm for mixed effect model estimation are considered in the context of second level functional magnetic resonance imaging (fMRI) data analysis. We first present the mathematical and optimization details of the method for the mixed effect model analysis, then we compare the proposed methods with the conventional expectation-maximization (EM) algorithm based on a series of datasets (synthetic and real human fMRI datasets). From simulation studies, we found a higher damping factor for the LM algorithm is better than lower damping factor for the fMRI data analysis. More importantly, in most cases, the expectation trust region algorithm is superior to the EM algorithm in terms of accuracy if the random effect variance is large. We also compare these algorithms on real human datasets which comprise repeated measures of fMRI in phased-encoded and random block experiment designs. We observed that the proposed method is faster in computation and robust to Gaussian noise for the fMRI analysis. The advantages and limitations of the suggested methods are discussed.     

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.     

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.     

The anxiolytic effects of midazolam during anticipation to pain revealed using fMRI

BACKGROUND AND PURPOSE: Functional neuroimaging can distinguish components of the pain experience associated with anticipation to pain from those associated with the experience of pain itself. Anticipation to pain is thought to increase the suffering of chronic pain patients. Inappropriate anxiety, of which anticipation is a component, is also a cause of disability. We present a pharmacological functional magnetic resonance imaging (fMRI) study in which we investigate the selective modulation by midazolam of brain activity associated with anticipation to pain compared to pain itself. METHODS: Eight right-handed male volunteers underwent fMRI combined with a thermal pain conditioning paradigm and midazolam (30 mug/kg) or saline administration on different occasions, with order randomized across volunteers. Volunteers learned to associate a colored light with either painful, hot stimulation or nonpainful, warm stimulation to the back of the left hand. RESULTS: Comparison of the period during thermal stimulation (pain-warm) revealed a network of brain activity commonly associated with noxious stimulation, including activities in the anterior cingulate cortex (ACC), the bilateral insular cortices (anterior and posterior), the thalamus, S1, the motor cortex, the brainstem, the prefrontal cortex and the cerebellum. Comparison of the periods preceding thermal stimulation (anticipation to pain-anticipation to warm) revealed activity principally in the ACC, the contralateral anterior insular cortex and the ipsilateral S2/posterior insula. Detected by a region-of-interest analysis, midazolam reduced the activity associated specifically with anticipation to pain while controlling for anticipation to warm. This was most significant in the contralateral anterior insula (P<.05). There were no significant drug effects on the activity associated with pain itself. CONCLUSION: In identifying a pharmacological effect on activity preceding but not during pain, we have successfully demonstrated an fMRI assay that can be used to study the action of anxiolytic agents in a relatively small cohort of humans.     

BOLD sensitivity to cortical activation induced by microstimulation: comparison to visual stimulation

Electrical microstimulation via intracortical electrodes is a widely used method for deducing functions of the brain. In this study, we compared the spatial extent and amplitude of BOLD responses evoked by intracortical electrical stimulation in primary visual cortex with BOLD activations evoked by visual stimulation. The experiments were performed in anesthetized rhesus monkeys. Visual stimulation yielded activities larger than predicted from the well-established visual magnification factor. However, electrical microstimulation yielded an even greater spread of the BOLD response. Our results confirm that the effects of electrical microstimulation extend beyond the brain region expected to be excited by direct current spread.     

Functional neuroimaging of inner fields-of-view with 2D-selective RF excitations

Echo-planar imaging is widely used in functional neuroimaging but suffers from its pronounced sensitivity to field inhomogeneities that cause geometric distortions and image blurring which both limit the effective in-plane resolution achievable. In this work, it is shown how inner-field-of-view techniques based on 2D-selective RF excitations (2DRF) can be applied to reduce the field-of-view in the phase-encoding direction without aliasing and increase the in-plane resolution accordingly. Free-induction-decay (FID) EPI and echo-train-shifted (T2*-weighted) and standard (T2-weighted) spin-echo (SE) EPI with in-plane resolutions of up to 0.5×1.0 mm² (slice thickness 5 mm) were acquired at 3 T. Unwanted signal contributions of 2DRF side excitations were shifted out of the object (FID-EPI) or of the refocusing plane by tilting the excitation plane (SE-EPI). Brain activation in healthy volunteers was investigated with checkerboard and finger-tapping block-design paradigms. Brain activation could be detected with all sequences and contrasts, most reliably with FID-EPI due to its higher signal amplitude and the longer 2DRF excitation that are more sensitive to magnetic field inhomogeneities. In conclusion, inner-FOV EPI based on 2DRF excitations could help to improve the spatial resolution of fMRI of focal target regions, e.g. for applications in the spinal cord.     

Derivative temporal clustering analysis: detecting prolonged neuronal activity

Temporal clustering analysis (TCA) and independent component analysis (ICA) are promising data-driven techniques in functional magnetic resonance imaging (fMRI) experiments to obtain brain activation maps in conditions with unknown temporal information regarding the neuronal activity. Although comparable to ICA in detecting transient neuronal activities, TCA fails to detect prolonged plateau brain activations. To eliminate this pitfall, a novel derivative TCA (DTCA) method was introduced and its algorithms with different subtraction intervals were tested on simulated data with a pattern of prolonged plateau brain activation. It was found that the best performance of DTCA method in generating functional maps could be obtained if the subtraction interval is equal to or larger than the length of the rising time of the fMRI response. The DTCA method and its theoretical predication were further investigated and validated using in vivo fMRI data sets. By removing the limitations in the previous TCA, DTCA has shown its powerful capability in detecting prolonged plateau neuronal activities.     

Neural activity-induced modulation of BOLD poststimulus undershoot independent of the positive signal

Despite intense research on the blood oxygenation level-dependent (BOLD) signal underlying functional magnetic resonance imaging, our understanding of its physiological basis is far from complete. In this study, it was investigated whether the so-called poststimulus BOLD signal undershoot is solely a passive vascular effect or actively induced by neural responses. Prolonged static and flickering black-white checkerboard stimulation with isoluminant grey screen as baseline condition were employed on eight human subjects. Within the same region of interest, the positive BOLD time courses for static and flickering stimuli were identical over the entire stimulus duration. In contrast, the static stimuli exhibited no poststimulus BOLD signal undershoot, whereas the flickering stimuli caused a strong BOLD poststimulus undershoot. To ease the interpretation, we performed an additional study measuring both BOLD signal and cerebral blood flow (CBF) using arterial spin labeling. Also for CBF, a difference in the poststimulus period was found for the two stimuli. Thus, a passive blood volume effect as the only contributor to the poststimulus undershoot comes short in explaining the BOLD poststimulus undershoot phenomenon for this particular experiment. Rather, an additional active neuronal activation or deactivation can strongly modulate the BOLD poststimulus behavior. In summary, the poststimulus time course of BOLD signal could potentially be used to differentiate neuronal activity patterns that are otherwise indistinguishable using the positive evoked response.