Magnetic resonance spectroscopy in migraine: what have we learned so far?

Objective: To summarize and evaluate proton (H-1) and phosphorus (P-31) magnetic resonance spectroscopy (MRS) findings in migraine. Methods: A thorough review of H-1 and/or P-31-MRS studies in any form of migraine published up to September 2011. Results: Some findings were consistent in all studies, such as a lack of ictal/interictal brain pH change and a disturbed energy metabolism, the latter of which is reflected in a drop in phosphocreatine content, both in the resting brain and in muscle following exercise. In a recent interictal study ATP was found to be significantly decreased in the occipital lobe of migraine with aura patients, reinforcing the concept of a mitochondrial component to the migraine threshold, at least in a subgroup of patients. In several studies a correlation between the extent of the energy disturbance and the clinical phenotype severity was apparent. Less consistent but still congruent with a disturbed energy metabolism is an observed lactate increase in the occipital cortex of several migraine subtypes (MwA, migraine with prolonged aura). No increases in brain glutamate levels were found. Conclusion: The combined abnormalities found in MRS studies imply a mitochondrial component in migraine neurobiology. This could be due to a primary mitochondrial dysfunction or be secondary to, for example, alterations in brain excitability. The extent of variation in the data can be attributed to both the variable clinical inclusion criteria used and the variation in applied methodology. Therefore it is necessary to continue to optimize MRS methodology to gain further insights, especially concerning lactate and glutamate

Image Aquisition Order and Input Order of BOLD-fMRI Data for Slice Time Correction in fMRI Data Processing Tools

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Mental rotation meets the motion aftereffect: the role of hV5/MT+ in visual mental imagery

A growing number of studies show that visual mental imagery recruits the same brain areas as visual perception. Although the necessity of hV5/MT+ for motion perception has been revealed by means of TMS, its relevance for motion imagery remains unclear. We induced a direction-selective adaptation in hV5/MT+ by means of an MAE while subjects performed a mental rotation task that elicits imagined motion. We concurrently measured behavioral performance and neural activity with fMRI, enabling us to directly assess the effect of a perturbation of hV5/MT+ on other cortical areas involved in the mental rotation task. The activity in hV5/MT+ increased as more mental rotation was required, and the perturbation of hV5/MT+ affected behavioral performance as well as the neural activity in this area. Moreover, several regions in the posterior parietal cortex were also affected by this perturbation. Our results show that hV5/MT+ is required for imagined visual motion and engages in an interaction with parietal cortex during this cognitive process

Overlapping neural systems represent cognitive effort and reward anticipation

Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior

SCSA based MATLAB pre-processing toolbox for 1H MR spectroscopic water suppression and denoising

In vivo 1H Magnetic Resonance Spectroscopy (MRS) is a useful tool in assessing neurological and metabolic disease, and to improve tumor treatment. Different pre-processing pipelines have been developed to obtain optimal results from the acquired data with sophisticated data fitting, peak suppression, and denoising protocols. We introduce a Semi-Classical Signal Analysis (SCSA) based Spectroscopy pre-processing toolbox for water suppression and data denoising, which allows researchers to perform water suppression using SCSA with phase correction and apodization filters and denoising of MRS data, and data fitting has been included as an additional feature, but it is not the main aim of the work. The fitting module can be passed on to other software. The toolbox is easy to install and to use: 1) import water unsuppressed MRS data acquired in Siemens, Philips and .mat file format and allow visualization of spectroscopy data, 2) allow pre-processing of single voxel and multi-voxel spectra, 3) perform water suppression and denoising using SCSA, 4) incorporate iterative nonlinear least squares fitting as an extra feature. This article provides information about how the above features have been included, along with details of the graphical user interface using these features in MATLAB

Reduction of Acquisition time by Partition of the signal Decay in Spectroscopic Imaging (RAPID-SI) technique : preliminary In-vivo results and comparison with CSI

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Modeling brain dynamics in brain tumor patients using the virtual brain

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance

Reduction of acquisition time using partition of the signal decay in spectroscopic imaging technique (RAPID-SI)

To overcome long acquisition times of Chemical Shift Imaging (CSI), a new Magnetic Resonance Spectroscopic Imaging (MRSI) technique called Reduction of Acquisition time by Partition of the signal Decay in Spectroscopic Imaging (RAPID-SI) using blipped phase encoding gradients inserted during signal acquisition was developed. To validate the results using RAPID-SI and to demonstrate its usefulness in terms of acquisition time and data quantification; simulations, phantom and in vivo studies were conducted, and the results were compared to standard CSI. The method was based upon the partition of a magnetic resonance spectroscopy (MRS) signal into sequential sub-signals encoded using blipped phase encoding gradients inserted during signal acquisition at a constant time interval. The RAPID-SI technique was implemented on a clinical 3 T Siemens scanner to demonstrate its clinical utility. Acceleration of data collection was performed by inserting R (R= acceleration factor) blipped gradients along a given spatial direction during data acquisition. Compared to CSI, RAPID-SI reduced acquisition time by the acceleration factor R. For example, a 2D 16x16 data set acquired in about 17 min with CSI, was reduced to approximately 2 min with the RAPID-SI (R= 8). While the SNR of the acquired RAPID-SI signal was lower compared to CSI by approximately the factor root R, it can be improved after data pre-processing and reconstruction. Compared to CSI, RAPID-SI reduces acquisition time, while preserving metabolites information. Furthermore, the method is flexible and could be combined with other acceleration methods such as Parallel Imaging