Functional MRI changes in the central motor system in myotonic dystrophy type 1

Myotonic dystrophy type 1 (DM1) is a multisystemic disease involving multiple organ systems including central nervous system (CNS) and muscles. Few studies have focused on the central motor system in DM1, pointing to a subclinical abnormality in the CNS. The aim of our study was to investigate patterns of cerebral activation in DM1 during a motor task using functional MRI (fMRI). Fifteen DM1 patients, aged 20 to 59 years, and 15 controls of comparable age were scanned during a self-paced sequential finger-to-thumb opposition task of their dominant right hand. Functional MRI images were analyzed using SPM99. Patients underwent clinical and genetic assessment; all subjects underwent a conventional MR study. Myotonic dystrophy type 1 patients showed greater activation than controls in bilateral sensorimotor areas and inferior parietal lobules, basal ganglia and thalami, in the ipsilateral premotor area, insula and supplementary motor area (corrected P<.05). Analysis of the interaction between disease and age showed that correlation with age was significantly greater in patients than in controls in bilateral sensorimotor areas and in contralateral parietal areas. Other clinical and MR characteristics did not correlate with fMRI. Functional changes in DM1 may represent compensatory mechanisms such as reorganization and redistribution of functional networks to compensate for ultrastructural and neurochemical changes occurring as part of the accelerated aging process.     

Retinotopic mapping with spin echo BOLD at 7T

For blood oxygenation level-dependent (BOLD) functional MRI experiments, contrast-to-noise ratio (CNR) increases with increasing field strength for both gradient echo (GE) and spin echo (SE) BOLD techniques. However, susceptibility artifacts and nonuniform coil sensitivity profiles complicate large field-of-view fMRI experiments (e.g., experiments covering multiple visual areas instead of focusing on a single cortical region). Here, we use SE BOLD to acquire retinotopic mapping data in early visual areas, testing the feasibility of SE BOLD experiments spanning multiple cortical areas at 7T. We also use a recently developed method for normalizing signal intensity in T₁-weighted anatomical images to enable automated segmentation of the cortical gray matter for scans acquired at 7T with either surface or volume coils. We find that the CNR of the 7T GE data (average single-voxel, single-scan stimulus coherence: 0.41) is almost twice that of the 3T GE BOLD data (average coherence: 0.25), with the CNR of the SE BOLD data (average coherence: 0.23) comparable to that of the 3T GE data. Repeated measurements in individual subjects find that maps acquired with 1.8-mm resolution at 3T and 7T with GE BOLD and at 7T with SE BOLD show no systematic differences in either the area or the boundary locations for V1, V2 and V3, demonstrating the feasibility of high-resolution SE BOLD experiments with good sensitivity throughout multiple visual areas.     

Reversal of myo-inositol metabolic level in the left dorsolateral prefrontal cortex of rats exposed to forced swimming test following desipramine treatment: an in vivo localized H-MRS study at 4.7 T

The forced swimming test (FST) is a useful paradigm that is relatively quick and simple to perform and has been utilized to predict antidepressant activity based on learned helplessness as a model of depression. To date, few studies have used proton magnetic resonance spectroscopy (¹H-MRS) to assess antidepressant effects in rats. The purpose of this study was to assess desipramine (DMI) effects on the left dorsolateral prefrontal cortex (DLPFC) of the rats, which were randomly assigned to three groups (control, n=10; FST+saline, n=10; FST+DMI, n=10), using single-voxel localization technique. All ¹H-MRS experiments were performed on a Bruker 4.7-T scanner with 400 mm bore magnet, allowing for acquisition of in vivo ¹H point-resolved spectroscopy spectra (TR/TE=3000/30 ms, number of data points=2048, NEX=512, voxel volume=27 μl, scan time=25 min). Proton metabolites were quantified automatically using LCModel software and were expressed as ratios to total creatine (Cr+PCr). Major target metabolites such as N-acetyl aspartate (NAA)+N-acetylaspartylglutamate (NAAG), glutamate+glutamine (Glu+Gln), glycerophosphorylcholine+phosphorylcholine (GPC+PCho), myo-inositol (mIns) and taurine (Tau) were successfully quantified with Cramer–Rao lower boundary ≤10%. There were significantly higher mIns/(Cr+PCr) and mIns/(NAA+NAAG) ratios in the FST+saline group compared to the control group. In the FST+DMI group, both mIns/(Cr+PCr) and mIns/(NAA+NAAG) ratios were significantly decreased to the level similar to those in the control group. No other metabolite ratios were significantly different among the three groups. Our findings suggest a possible role of altered mIns level within the left DLPFC of the rat model for depression.     

Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA

Functional magnetic resonance imaging (fMRI) based on the so-called blood oxygen level-dependent (BOLD) contrast is a powerful tool for studying brain function not only locally but also on the large scale. Most studies assume a simple relationship between neural and BOLD activity, in spite of the fact that it is important to elucidate how the “when” and “what” components of neural activity are correlated to the “where” of fMRI data. Here we conducted simultaneous recordings of neural and BOLD signal fluctuations in primary visual (V1) cortex of anesthetized monkeys. We explored the neurovascular relationship during periods of spontaneous activity by using temporal kernel canonical correlation analysis (tkCCA). tkCCA is a multivariate method that can take into account any features in the signals that univariate analysis cannot. The method detects filters in voxel space (for fMRI data) and in frequency–time space (for neural data) that maximize the neurovascular correlation without any assumption of a hemodynamic response function (HRF). Our results showed a positive neurovascular coupling with a lag of 4–5 s and a larger contribution from local field potentials (LFPs) in the γ range than from low-frequency LFPs or spiking activity. The method also detected a higher correlation around the recording site in the concurrent spatial map, even though the pattern covered most of the occipital part of V1. These results are consistent with those of previous studies and represent the first multivariate analysis of intracranial electrophysiology and high-resolution fMRI.