A study on small-world brain functional networks altered by postherpetic neuralgia

Understanding the effect of postherpetic neuralgia (PHN) pain on brain activity is important for clinical strategies. This is the first study, to our knowledge, to relate PHN pain to small-world properties of brain functional networks. Functional magnetic resonance imaging (fMRI) was used to construct functional brain networks of the subjects during the resting state. Sixteen patients with PHN pain and 16 (8 males, 8 females for both groups) age-matched controls were studied. The PHN patients exhibited decreased local efficiency along with non-significant changes of global efficiency in comparison with the healthy controls. Moreover, regional nodal efficiency was found to be significantly affected by PHN pain in the areas related to sense (postcentral gyrus, inferior parietal gyrus and thalamus), memory/affective processes (parahippocampal gyrus) and emotional activities (putamen). Significant correlation (p < 0.05) was also found between the nodal efficiency of putamen and pain intensity in PHN patients. Our results suggest that PHN modulates the local efficiency, and the small-world properties of brain networks may have potentials to objectively evaluate pain information in clinic.     

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.     

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.     

Activation of Visuomotor Systems during Visually Guided Movements: A Functional MRI Study

The dorsal stream is a dominant visuomotor pathway that connects the striate and extrastriate cortices to posterior parietal areas. In turn, the posterior parietal areas send projections to the frontal primary motor and premotor areas. This cortical pathway is hypothesized to be involved in the transformation of a visual input into the appropriate motor output. In this study we used functional magnetic resonance imaging (fMRI) of the entire brain to determine the patterns of activation that occurred while subjects performed a visually guided motor task. In nine human subjects, fMRI data were acquired on a 4-T whole-body MR system equipped with a head gradient coil and a birdcage RF coil using aT^*₂-weighted EPI sequence. Functional activation was determined for three different tasks: (1) a visuomotor task consisting of moving a cursor on a screen with a joystick in relation to various targets, (2) a hand movement task consisting of moving the joystick without visual input, and (3) a eye movement task consisting of moving the eyes alone without visual input. Blood oxygenation level-dependent (BOLD) contrast-based activation maps of each subject were generated using period cross-correlation statistics. Subsequently, each subject's brain was normalized to Talairach coordinates, and the individual maps were compared on a pixel by pixel basis. Significantly activated pixels common to at least four out of six subjects were retained to construct the final functional image. The pattern of activation during visually guided movements was consistent with the flow of information from striate and extrastriate visual areas, to the posterior parietal complex, and then to frontal motor areas. The extensive activation of this network and the reproducibility among subjects is consistent with a role for the dorsal stream in transforming visual information into motor behavior. Also extensively activated were the medial and lateral cerebellar structures, implicating the cortico–ponto–cerebellar pathway in visually guided movements. Thalamic activation, particularly of the pulvinar, suggests that this nucleus is an important subcortical target of the dorsal stream.     

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.     

Changes in cerebral activity after decreased upper-limb hypertonus: an EMG-fMRI study

Objective

Whereas several studies have used functional magnetic resonance imaging (fMRI) to investigate motor recovery, whether therapy to decrease post-stroke hypertonus alters central motor patterns remains unclear. In this study, we used continuous electromyography (EMG)-fMRI to investigate possible changes in movement-related brain activation in patients receiving Botulinum toxin (BoNT-A) for hand-muscle hypertonus after chronic stroke.

Methods

We studied eight stroke patients all of whom had hemiparesis and associated upper-limb hypertonus. All patients underwent an fMRI-EMG recording and clinical-neurological assessment before BoNT-A and 5 weeks thereafter. The handgrip motor task during imaging was fixed across both patients and controls. The movements were metronome paced, movement amplitude and force were controlled with a plastic orthosis, dynamometer and EMG recording. An age-matched control group was recruited from among healthy volunteers underwent the same fMRI-EMG recording.

Results

Before BoNT-A, while patients moved the paretic hand, fMRI detected wide bilateral activation in the sensorymotor areas (SM1), in the supplementary motor area (SMA) and cerebellum. After BoNT-A blood oxygenation level-dependent (BOLD) activation decreased in ipsilateral and contralateral motor areas and became more lateralized. BOLD activation decreased also in ipsilateral cerebellar regions and in the SMA.

Conclusion

Changes in peripheral upper-limb hypertonus after BoNT-A were associated to an improvement in active movements and more lateralized and focalized activation of motor areas. The clinical and EMG-fMRI coregistration technique we used to study hand-muscle hypertonus in patients receiving BoNT-A after chronic stroke should be useful in future studies seeking improved strategies for post-stroke neurorehabilitation.     

Bayesian wavelet-based analysis of functional magnetic resonance time series

Wavelet methods for image regularization offer a data-driven alternative to Gaussian smoothing in functional magnetic resonance (fMRI) analysis. Their impact has been limited by the difficulties in integrating regularization in the wavelet domain and inference in the image domain, precluding the probabilistic decision on which areas are activated by a task. Here we present an integrated framework for Bayesian estimation and regularization in wavelet space that allows the usual voxelwise hypothesis testing. This framework is flexible, being an adaptation to fMRI time series of a more general wavelet-based functional mixed-effect model. Through testing on a combination of simulated and real fMRI data, we show evidence of improved signal recovery, without compromising test accuracy in image space.     

Nonlinear blood oxygen level-dependent responses for transient activations and deactivations in V1 - insights into the hemodynamic response function with the balloon model

We report studies of the nonlinear nature of blood oxygen level-dependent (BOLD) responses to short transient deactivations in human visual cortex. Both functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) have been used to compare and contrast the hemodynamic response functions (HRFs) associated with transient activation and deactivation in primary visual cortex. We show that signal decreases for short duration deactivations are smaller than corresponding signal increases in activation studies. Moreover, the standard balloon model of BOLD effects may be modified to account for the observed nonlinear nature of deactivations by appropriate changes to simple hemodynamic parameters without recourse to new assumptions about the nature of the coupling between activity and oxygen use.     

Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA

In functional magnetic resonance imaging (fMRI) analysis, although the univariate general linear model (GLM) is currently the dominant approach to brain activation detection, there is growing interest in multivariate approaches such as principal component analysis, canonical variate analysis (CVA), independent component analysis and cluster analysis, which have the potential to reveal neural networks and functional connectivity in the brain. To understand the effect of processing options on performance of multivariate model-based fMRI processing pipelines with real fMRI data, we investigated the impact of commonly used fMRI preprocessing steps and optimized the associated multivariate CVA-based, single-subject processing pipelines with the NPAIRS (nonparametric prediction, activation, influence and reproducibility resampling) performance metrics [prediction accuracy and statistical parametric image (SPI) reproducibility] on the Fiswidgets platform. We also compared the single-subject SPIs of univariate GLM with multivariate CVA-based processing pipelines from SPM, FSL.FEAT, NPAIRS.GLM and NPAIRS.CVA software packages (or modules) using a novel second-level CVA. We found that for the block-design data, (a) slice timing correction and global intensity normalization have little consistent impact on the fMRI processing pipeline, but spatial smoothing, temporal detrending or high-pass filtering, and motion correction significantly improved pipeline performance across all subjects; (b) the combined optimization of spatial smoothing, temporal detrending and CVA model parameters on average improved between-subject reproducibility; and (c) the most important pipeline choices include univariate or multivariate statistical models and spatial smoothing. This study suggests that considering options other than simply using GLM with a fixed spatial filter may be of critical importance in determining activation patterns in BOLD fMRI studies.     

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.