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Many magnetic resonance imaging (MRI) measures are being studied longitudinally to explore topics such as biomarker detection and clinical staging. A pertinent concern to longitudinal work is MRI scanner upgrades. When upgrades occur during the course of a longitudinal MRI neuroimaging investigation, there may be an impact on the compatibility of pre- and post-upgrade measures. Similarly, subject motion is another issue that may be detrimental to MRI work and embedding volumetric navigators (vNavs) within acquisition sequences has emerged as a technique that allows for prospective motion correction. Our research group recently underwent an upgrade from a Siemens MAGNETOM 3T Tim Trio system to a Siemens MAGNETOM 3T Prisma Fit system. The goals of the current work were to: 1) investigate the impact of this upgrade on commonly used structural imaging measures and proton magnetic resonance spectroscopy indices (“Prisma Upgrade protocol”) and 2) examine structural imaging measures in a sequence with vNavs alongside a standard acquisition sequence (“vNav protocol”). While high reliability was observed for most of the investigated MRI outputs, suboptimal reliability was observed for certain indices. Across the scanner upgrade, increases in frontal, temporal, and cingulate cortical thickness (CT) and thalamus volume, along with decreases in parietal CT, amygdala, globus pallidus, hippocampus, and striatum volumes were observed across the upgrade. No significant impact of the upgrade was found in 1H-MRS analyses. Further, CT estimates were found to be larger in MPRAGE acquisitions compared to vNav-MPRAGE acquisitions mainly within temporal areas, while the opposite was found mostly in parietal brain regions. The results from this work should be considered in longitudinal study designs and comparable prospective motion correction investigations are warranted in cases of marked head movement.

The hippocampus has been extensively studied in various neuropsychiatric disorders throughout the lifespan. However, inconsistent results have been reported with respect to which subfield volumes are most related to age. Here, we investigate whether these discrepancies may be explained by experimental design differences that exist between studies. Multiple datasets were used to collect 1690 magnetic resonance scans from healthy individuals aged 18-95 years old. Standard T1-weighted (T1w; MPRAGE sequence, 1 mm3 voxels), high-resolution T2-weighted (T2w; SPACE sequence, 0.64 mm3 voxels) and slab T2-weighted (Slab; 2D turbo spin echo, 0.4 x 0.4 x 2 mm3 voxels) images were acquired. The MAGeT Brain algorithm was used for segmentation of the hippocampal grey matter (GM) subfields and peri-hippocampal white matter (WM) subregions. Linear mixed-effect models and Akaike information criterion were used to examine linear, second or third order natural splines relationship between hippocampal volumes and age. We demonstrated that stratum radiatum/lacunosum/moleculare and fornix subregions expressed the highest relative volumetric decrease, while the cornus ammonis 1 presented a relative volumetric preservation of its volume with age. We also found that volumes extracted from slab images were often underestimated and demonstrated different age-related relationships compared to volumes extracted from T1w and T2w images. The current work suggests that although T1w, T2w and slab derived subfield volumetric outputs are largely homologous, modality choice plays a meaningful role in the volumetric estimation of the hippocampal subfields.

Over the last two decades, numerous human MRI studies of neuroplasticity have shown compelling evidence for extensive and rapid experience-induced brain plasticity in vivo. To date, most of these studies have consisted of simply detecting a difference in structural or functional images with little concern for their lack of biological specificity. Recent reviews and public debates have stressed the need for advanced imaging techniques to gain a better understanding of the nature of these differences - characterizing their extent in time and space, their underlying biological and network dynamics. The purpose of this article is to give an overview of advanced imaging techniques for an audience of cognitive neuroscientists that can assist them in the design and interpretation of future MRI studies of neuroplasticity. The review encompasses MRI methods that probe the morphology, microstructure, function, and connectivity of the brain with improved specificity. We underline the possible physiological underpinnings of these techniques and their recent applications within the framework of learning- and experience-induced plasticity in healthy adults. Finally, we discuss the advantages of a multi-modal approach to gain a more nuanced and comprehensive description of the process of learning.

Magnetic resonance imaging at ultra high field opens the door to quantitative brain imaging at sub-millimeter isotropic resolutions. However, novel image processing tools to analyze these new rich datasets are lacking. In this article, we introduce the Open Science CBS Neuroimaging Repository: a unique repository of high-resolution and quantitative images acquired at 7 T. The motivation for this project is to increase interest for high-resolution and quantitative imaging and stimulate the development of image processing tools developed specifically for high-field data. Our growing repository currently includes datasets from MP2RAGE and multi-echo FLASH sequences from 28 and 20 healthy subjects respectively. These datasets represent the current state-of-the-art in in-vivo relaxometry at 7 T, and are now fully available to the entire neuroimaging community.

The position of cortical areas can be approximately predicted from cortical surface folding patterns. However, there is extensive inter-subject variability in cortical folding patterns, prohibiting a one-to-one mapping of cortical folds in certain areas. In addition, the relationship between cortical area boundaries and the shape of the cortex is variable, and weaker for higher-order cortical areas. Current surface registration techniques align cortical folding patterns using sulcal landmarks or cortical curvature, for instance. The alignment of cortical areas by these techniques is thus inherently limited by the sole use of geometric similarity metrics. Magnetic resonance imaging T1 maps show intra-cortical contrast that reflects myelin content, and thus can be used to improve the alignment of cortical areas. In this article, we present a new symmetric diffeomorphic multi-contrast multi-scale surface registration (MMSR) technique that works with partially inflated surfaces in the level-set framework. MMSR generates a more precise alignment of cortical surface curvature in comparison to two widely recognized surface registration algorithms. The resulting overlap in gyrus labels is comparable to FreeSurfer. Most importantly, MMSR improves the alignment of cortical areas further by including T1 maps. As a first application, we present a group average T1 map at a uniquely high-resolution and multiple cortical depths, which reflects the myeloarchitecture of the cortex. MMSR can also be applied to other MR contrasts, such as functional and connectivity data.

Computational anatomy studies typically use T1-weighted magnetic resonance imaging contrast to look at local differences in cortical thickness or grey matter volume across time or subjects. This type of analysis is a powerful and non-invasive tool to probe anatomical changes associated with neurodevelopment, aging, disease or experience-induced plasticity. However, these comparisons could suffer from biases arising from vascular and metabolic subject- or time-dependent differences. Differences in blood flow and volume could be caused by vasodilation or differences in vascular density, and result in a larger signal contribution of the blood compartment within grey matter voxels. Metabolic changes could lead to differences in dissolved oxygen in brain tissue, leading to T1 shortening. Here, we analyze T1 maps and T1-weighted images acquired during different breathing conditions (ambient air, hypercapnia (increased CO2) and hyperoxia (increased O2)) to evaluate the effect size that can be expected from changes in blood flow, volume and dissolved O2 concentration in computational anatomy studies. Results show that increased blood volume from vasodilation during hypercapnia is associated with an overestimation of cortical thickness (1.85%) and grey matter volume (3.32%), and that both changes in O2 concentration and blood volume lead to changes in the T1 value of tissue. These results should be taken into consideration when interpreting existing morphometry studies and in future study design. Furthermore, this study highlights the overlap in structural and physiological MRI, which are conventionally interpreted as two independent modalities.

Structural magnetic resonance imaging can now resolve laminar features within the cerebral cortex in vivo. A variety of intracortical contrasts have been used to study the cortical myeloarchitecture with the purpose of mapping cortical areas in individual subjects. In this article, we first briefly review recent advances in MRI analysis of cortical microstructure to portray the potential and limitations of the current state-of-the-art. We then present an integrated framework for the analysis of intracortical structure, composed of novel image processing tools designed for high resolution cortical images. The main features of our framework are the segmentation of quantitative T1 maps to delineate the cortical boundaries (Bazin et al., 2014), and the use of an equivolume layering model to define an intracortical coordinate system that follows the anatomical layers of the cortex (Waehnert et al., 2014). We evaluate the framework with 150μm isotropic post mortem T2(∗)-weighted images and 0.5mm isotropic in vivo T1 maps, a quantitative index of myelin content. We study the laminar structure of the primary visual cortex (Brodmann area 17) in the post mortem and in vivo data, as well as the central sulcus region in vivo, in particular Brodmann areas 1, 3b and 4. We also investigate the impact of the layering models on the relationship between T1 and cortical curvature. Our experiments demonstrate that the equivolume intracortical surfaces and transcortical profiles best reflect the laminar structure of the cortex in areas of curvature in comparison to the state-of-the-art equidistant and Laplace implementations. This framework generates a subject specific intracortical coordinate system, the basis for subsequent architectonic analyses of the cortex. Any structural or functional contrast co-registered to the T1 maps, used to segment the cortex, can be sampled on the curved grid for analysis. This work represents an important step towards in vivo structural brain mapping of individual subjects.