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MR Imaging the spinal cord of non-human primates (NHP), such as squirrel monkey, is important since the injuries in NHP resemble those that afflict human spinal cords. Our previous studies have reported a multi-parametric MRI protocol, including functional MRI, diffusion tensor imaging, quantitative magnetization transfer and chemical exchange saturation transfer, which allows non-invasive detection and monitoring of injury-associated structural, functional and molecular changes over time. High signal-to-noise ratio (SNR) is critical for obtaining high-resolution images and robust estimates of MRI parameters. In this work, we describe our construction and use of a single channel coil designed to maximize the SNR for imaging the squirrel monkey cervical spinal cord in a 21 cm bore magnet at 9.4 T. We first numerically optimized the coil dimension of a single loop coil and then evaluated the benefits of a quadrature design. We then built an optimized coil based on the simulation results and compared its SNR performance with a non-optimized single coil in both phantoms and in vivo.
Copyright © 2020 Elsevier Inc. All rights reserved.
PURPOSE - This study aims to systematically evaluate the accuracy and precision of pool size ratio (PSR) measurements from quantitative magnetization transfer (qMT) acquisitions using simplified models in the context of assessing injury-associated spatiotemporal changes in spinal cords of non-human primates. This study also aims to characterize changes in the spinal tissue pathology in individual subjects, both regionally and longitudinally, in order to demonstrate the relationship between regional tissue compositional changes and sensorimotor behavioral recovery after cervical spinal cord injury (SCI).
METHODS - MRI scans were recorded on anesthetized monkeys at 9.4 T, before and serially after a unilateral section of the dorsal column tract. Images were acquired following saturating RF pulses at different offset frequencies. Models incorporating two pools of protons but with differing numbers of variable parameters were used to fit the data to derive qMT parameters. The results using different amounts of measured data and assuming different numbers of variable model parameters were compared. Behavioral impairments and recovery were assessed by a food grasping-retrieving task. Histological sections were obtained post mortem for validation of the injury.
RESULTS - QMT fitting provided maps of pool size ratio (PSR), the relative amounts of immobilized protons exchanging magnetization compared to the "free" water. All the selected modeling approaches detected a lesion/cyst at the site of injury as significant reductions in PSR values. The regional contrasts in the PSR maps obtained using the different fittings varied, but the 2-parameter fitting results showed strong positive correlations with results from 5-parameter modeling. 2-parameter fitting results with modest (>3) RF offsets showed comparable sensitivity for detecting demyelination in white matter and loss of macromolecules in gray matter around lesion sites compared to 5-parameter fitting with fully-sampled data acquisitions. Histology confirmed that decreases of PSR corresponded to regional demyelination around lesion sites, especially when demyelination occurred along the dorsal column on the injury side. Longitudinally, PSR values of injured dorsal column tract and gray matter horns exhibited remarkable recovery that associated with behavioral improvement.
CONCLUSION - Simplified qMT modeling approaches provide efficient and sensitive means to detect and characterize injury-associated demyelination in white matter tracts and loss of macromolecules in gray matter and to monitor its recovery over time.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.
Correlations between fluctuations in resting state BOLD fMRI signals are interpreted as measures of functional connectivity (FC), but the neural basis of their origins and their relationships to specific features of underlying electrophysiologic activity, have not been fully established. In particular, the dependence of FC metrics on different frequency bands of local field potentials (LFPs), and the relationship of dynamic changes in BOLD FC to underlying temporal variations of LFP correlations, are not known. We compared the spatial profiles of resting state coherences of different frequency bands of LFP signals, with high resolution resting state BOLD FC measurements. We also compared the probability distributions of temporal variations of connectivity in both modalities using a Markov chain model-based approach. We analyzed data obtained from the primary somatosensory (S1) cortex of monkeys. We found that in areas 3b and 1 of S1 cortex, low frequency LFP signal fluctuations were the main contributions to resting state LFP coherence. Additionally, the dynamic changes of BOLD FC behaved most similarly to the LFP low frequency signal coherence. These results indicate that, within the S1 cortex meso-scale circuit studied, resting state FC measures from BOLD fMRI mainly reflect contributions from low frequency LFP signals and their dynamic changes.
Understanding the relationship between the diffusion-weighted MRI signal and the arrangement of white matter fibers is fundamental for accurate voxel-wise reconstruction of the fiber orientation distribution (FOD) and subsequent fiber tractography. Spherical deconvolution reconstruction techniques model the diffusion signal as the convolution of the FOD with a response function that represents the signal profile of a single fiber orientation. Thus, given the signal and a fiber response function, the FOD can be estimated in every imaging voxel by deconvolution. However, the selection of the appropriate response function remains relatively under-studied, and requires further validation. In this work, using 3D histologically defined FODs and the corresponding diffusion signal from three ex vivo squirrel monkey brains, we derive the ground truth response functions. We find that the histologically derived response functions differ from those conventionally used. Next, we find that response functions statistically vary across brain regions, which suggests that the practice of using the same kernel throughout the brain is not optimal. We show that different kernels lead to different FOD reconstructions, which in turn can lead to different tractography results depending on algorithmic parameters, with large variations in the accuracy of resulting reconstructions. Together, these results suggest there is room for improvement in estimating and understanding the relationship between the diffusion signal and the underlying FOD.
© 2019 John Wiley & Sons, Ltd.
Whereas resting state blood oxygenation-level dependent (BOLD) functional MRI has been widely used to assess functional connectivity between cortical regions, the laminar specificity of such measures is poorly understood. This study aims to determine: (a) whether the resting state functional connectivity (rsFC) between two functionally related cortical regions varies with cortical depth, (b) the relationship between layer-resolved tactile stimulus-evoked activation pattern and interlayer rsFC pattern between two functionally distinct but related somatosensory areas 3b and 1, and (c) the effects of spatial resolution on rsFC measures. We examined the interlayer rsFC between areas 3b and 1 of squirrel monkeys under anesthesia using tactile stimulus-driven and resting state BOLD acquisitions at submillimeter resolution. Consistent with previous observations in the areas 3b and 1, we detected robust stimulus-evoked BOLD activations with foci were confined mainly to the upper layers (centered at 21% of the cortical depth). By carefully placing seeds in upper, middle, and lower layers of areas 3b and 1, we observed strong rsFC between upper and middle layers of these two areas. The layer-resolved activation patterns in areas 3b and 1 agree with their interlayer rsFC patterns, and are consistent with the known anatomical connections between layers. In summary, using BOLD rsFC pattern, we identified an interlayer interareal microcircuit that shows strong intrinsic functional connections between upper and middle layer areas 3b and 1. RsFC can be used as a robust invasive tool to probe interlayer corticocortical microcircuits.
© 2018 Wiley Periodicals, Inc.
For two decades diffusion fiber tractography has been used to probe both the spatial extent of white matter pathways and the region to region connectivity of the brain. In both cases, anatomical accuracy of tractography is critical for sound scientific conclusions. Here we assess and validate the algorithms and tractography implementations that have been most widely used - often because of ease of use, algorithm simplicity, or availability offered in open source software. Comparing forty tractography results to a ground truth defined by histological tracers in the primary motor cortex on the same squirrel monkey brains, we assess tract fidelity on the scale of voxels as well as over larger spatial domains or regional connectivity. No algorithms are successful in all metrics, and, in fact, some implementations fail to reconstruct large portions of pathways or identify major points of connectivity. The accuracy is most dependent on reconstruction method and tracking algorithm, as well as the seed region and how this region is utilized. We also note a tremendous variability in the results, even though the same MR images act as inputs to all algorithms. In addition, anatomical accuracy is significantly decreased at increased distances from the seed. An analysis of the spatial errors in tractography reveals that many techniques have trouble properly leaving the gray matter, and many only reveal connectivity to adjacent regions of interest. These results show that the most commonly implemented algorithms have several shortcomings and limitations, and choices in implementations lead to very different results. This study should provide guidance for algorithm choices based on study requirements for sensitivity, specificity, or the need to identify particular connections, and should serve as a heuristic for future developments in tractography.
Copyright © 2018 Elsevier Inc. All rights reserved.
Numerous studies have used functional magnetic resonance imaging (fMRI) to characterize functional connectivity between cortical regions by analyzing correlations in blood oxygenation level dependent (BOLD) signals in a resting state. However, to date, there have been only a handful of studies reporting resting state BOLD signals in white matter. Nonetheless, a growing number of reports has emerged in recent years suggesting white matter BOLD signals can be reliably detected, though their biophysical origins remain unclear. Moreover, recent studies have identified robust correlations in a resting state between signals from cortex and specific white matter tracts. In order to further validate and interpret these findings, we studied a non-human primate model to investigate resting-state connectivity patterns between parcellated cortical volumes and specific white matter bundles. Our results show that resting-state connectivity patterns between white and gray matter structures are not randomly distributed but share notable similarities with diffusion- and histology-derived anatomic connectivities. This suggests that resting-state BOLD correlations between white matter fiber tracts and the gray matter regions to which they connect are directly related to the anatomic arrangement and density of WM fibers. We also measured how different levels of baseline neural activity, induced by varying levels of anesthesia, modulate these patterns. As anesthesia levels were raised, we observed weakened correlation coefficients between specific white matter tracts and gray matter regions while key features of the connectivity pattern remained similar. Overall, results from this study provide further evidence that neural activity is detectable by BOLD fMRI in both gray and white matter throughout the resting brain. The combined use of gray and white matter functional connectivity could also offer refined full-scale functional parcellation of the entire brain to characterize its functional architecture.
Published by Elsevier Inc.
The squirrel monkey (Saimiri sciureus) is a commonly-used surrogate for humans in biomedical research. In the neuroimaging community, MRI and histological atlases serve as valuable resources for anatomical, physiological, and functional studies of the brain; however, no digital MRI/histology atlas is currently available for the squirrel monkey. This paper describes the construction of a web-based multi-modal atlas of the squirrel monkey brain. The MRI-derived information includes anatomical MRI contrast (i.e., T2-weighted and proton-density-weighted) and diffusion MRI metrics (i.e., fractional anisotropy and mean diffusivity) from data acquired both in vivo and ex vivo on a 9.4 Tesla scanner. The histological images include Nissl and myelin stains, co-registered to the corresponding MRI, allowing identification of cyto- and myelo-architecture. In addition, a bidirectional neuronal tracer, biotinylated dextran amine (BDA) was injected into the primary motor cortex, enabling highly specific identification of regions connected to the injection location. The atlas integrates the results of common image analysis methods including diffusion tensor imaging glyphs, labels of 57 white-matter tracts identified using DTI-tractography, and 18 cortical regions of interest identified from Nissl-revealed cyto-architecture. All data are presented in a common space, and all image types are accessible through a web-based atlas viewer, which allows visualization and interaction of user-selectable contrasts and varying resolutions. By providing an easy to use reference system of anatomical information, our web-accessible multi-contrast atlas forms a rich and convenient resource for comparisons of brain findings across subjects or modalities. The atlas is called the Combined Histology-MRI Integrated Atlas of the Squirrel Monkey (CHIASM). All images are accessible through our web-based viewer ( https://chiasm.vuse.vanderbilt.edu /), and data are available for download at ( https://www.nitrc.org/projects/smatlas/ ).
This study addresses one long-standing question of whether functional separations are preserved for somatosensory modalities of touch, heat, and cold nociception within primate primary somatosensory (S1) cortex. This information is critical for understanding how the nature of pain is represented in the primate brain. Using a combination of submillimeter-resolution fMRI and microelectrode local field potential (LFP) and spike recordings, we identified spatially segregated cortical zones for processing touch and nociceptive heat and cold stimuli in somatotopically appropriate areas 3a, 3b, 1, and 2 of S1 in male monkeys. The distances between zones were comparable (∼3.4 mm) across stimulus modalities (heat, cold, and tactile), indicating the existence of uniform, modality-specific modules. Stimulus-evoked LFP maps validated the fMRI maps in areas 3b and 1. Isolation of heat and cold nociceptive neurons from the fMRI zones confirmed the validity of using fMRI to probe nociceptive regions and circuits. Resting-state fMRI analysis revealed distinct intrinsic functional circuits among functionally related zones. We discovered distinct modular structures and networks for thermal nociception within S1 cortex, a finding that has significant implications for studying chronic pain syndromes and guiding the selection of neuromodulation targets for chronic pain management. Primate S1 subregions contain discrete heat and cold nociceptive modules. Modules with the same properties exhibit strong functional connection. Nociceptive fMRI response coincides with LFP and spike activities of nociceptive neurons. Functional separation of heat and cold pain is retained within primate S1 cortex.
Copyright © 2018 the authors 0270-6474/18/381774-14$15.00/0.
Diffusion magnetic resonance imaging (dMRI) is widely used to probe tissue microstructure, and is currently the only non-invasive way to measure the brain's fiber architecture. While a large number of approaches to recover the intra-voxel fiber structure have been utilized in the scientific community, a direct, 3D, quantitative validation of these methods against relevant histological fiber geometries is lacking. In this study, we investigate how well different high angular resolution diffusion imaging (HARDI) models and reconstruction methods predict the ground-truth histologically defined fiber orientation distribution (FOD), as well as investigate their behavior over a range of physical and experimental conditions. The dMRI methods tested include constrained spherical deconvolution (CSD), Q-ball imaging (QBI), diffusion orientation transform (DOT), persistent angular structure (PAS), and neurite orientation dispersion and density imaging (NODDI) methods. Evaluation criteria focus on overall agreement in FOD shape, correct assessment of the number of fiber populations, and angular accuracy in orientation. In addition, we make comparisons of the histological orientation dispersion with the fiber spread determined from the dMRI methods. As a general result, no HARDI method outperformed others in all quality criteria, with many showing tradeoffs in reconstruction accuracy. All reconstruction techniques describe the overall continuous angular structure of the histological FOD quite well, with good to moderate correlation (median angular correlation coefficient > 0.70) in both single- and multiple-fiber voxels. However, no method is consistently successful at extracting discrete measures of the number and orientations of FOD peaks. The major inaccuracies of all techniques tend to be in extracting local maxima of the FOD, resulting in either false positive or false negative peaks. Median angular errors are ∼10° for the primary fiber direction and ∼20° for the secondary fiber, if present. For most methods, these results did not vary strongly over a wide range of acquisition parameters (number of diffusion weighting directions and b value). Regardless of acquisition parameters, all methods show improved successes at resolving multiple fiber compartments in a voxel when fiber populations cross at near-orthogonal angles, with no method adequately capturing low to moderate angle (<60°) crossing fibers. Finally, most methods are limited in their ability to capture orientation dispersion, resulting in low to moderate, yet statistically significant, correlation with histologically-derived dispersion with both HARDI and NODDI methodologies. Together, these results provide quantitative measures of the reliability and limitations of dMRI reconstruction methods and can be used to identify relative advantages of competing approaches as well as potential strategies for improving accuracy.
Copyright © 2017 Elsevier Inc. All rights reserved.