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The anatomical complexity and location of the human subcortex render it difficult to study by MRI in vivo . Here, Forstmann et al . argue that understanding subcortex function may be facilitated by combining in vivo and post-mortem ultra-high field MRI, post-mortem histology and modelling approaches. The human subcortex is a densely populated part of the brain, of which only 7% of the individual structures are depicted in standard MRI atlases. In vivo MRI of the subcortex is challenging owing to its anatomical complexity and its deep location in the brain. The technical advances that are needed to reliably uncover this 'terra incognita' call for an interdisciplinary human neuroanatomical approach. We discuss the emerging methods that could be used in such an approach and the incorporation of the data that are generated from these methods into model-based cognitive neuroscience frameworks.

The subthalamic nucleus and the directly adjacent substantia nigra are small and important structures in the basal ganglia. Functional magnetic resonance imaging studies have shown that the subthalamic nucleus and substantia nigra are selectively involved in response inhibition, conflict processing, and adjusting global and selective response thresholds. However, imaging these nuclei is complex, because they are in such close proximity, they can vary in location, and are very small relative to the resolution of most fMRI sequences. Here, we investigated the consistency in localization of these nuclei in BOLD fMRI studies, comparing reported coordinates with probabilistic atlas maps of young human participants derived from ultra-high resolution 7T MRI scanning. We show that the fMRI signal reported in previous studies is likely not unequivocally arising from the subthalamic nucleus but represents a mixture of subthalamic nucleus, substantia nigra, and surrounding tissue. Using a simulation study, we also tested to what extent spatial smoothing, often used in fMRI preprocessing pipelines, influences the mixture of BOLD signals. We propose concrete steps how to analyze fMRI BOLD data to allow inferences about the functional role of small subcortical nuclei like the subthalamic nucleus and substantia nigra.

Magnetic resonance imaging studies typically use standard anatomical atlases for identification and analyses of (patho-)physiological effects on specific brain areas; these atlases often fail to incorporate neuroanatomical alterations that may occur with both age and disease. The present study utilizes Parkinson's disease and age-specific anatomical atlases of the subthalamic nucleus for diffusion tractography, assessing tracts that run between the subthalamic nucleus and a-priori defined cortical areas known to be affected by Parkinson's disease. The results show that the strength of white matter fiber tracts appear to remain structurally unaffected by disease. Contrary to that, Fractional Anisotropy values were shown to decrease in Parkinson's disease patients for connections between the subthalamic nucleus and the pars opercularis of the inferior frontal gyrus, anterior cingulate cortex, the dorsolateral prefrontal cortex and the pre-supplementary motor, collectively involved in preparatory motor control, decision making and task monitoring. While the biological underpinnings of fractional anisotropy alterations remain elusive, they may nonetheless be used as an index of Parkinson's disease. Moreover, we find that failing to account for structural changes occurring in the subthalamic nucleus with age and disease reduce the accuracy and influence the results of tractography, highlighting the importance of using appropriate atlases for tractography.

How, and to what extent do size and shape of a voxel measured with magnetic resonance imaging (MRI) affect the ability to visualize small brain nuclei? Despite general consensus that voxel geometry affects volumetric properties of regions of interest, particularly those of small brain nuclei, no quantitative data on the influence of voxel size and shape on labeling accuracy is available. Using simulations, we investigated the selective influence of voxel geometry by reconstructing simulated ellipsoid structures with voxels varying in shape and size. For each reconstructed ellipsoid, we calculated differences in volume and similarity between the labeled volume and the predefined dimensions of the ellipsoid. Probability functions were derived from one or two individual raters and a simulated ground truth for reference. As expected, larger voxels (i.e., coarser resolution) and increasing anisotropy results in increased deviations of both volume and shape measures, which is of particular relevance for small brain structures. Our findings clearly illustrate the anatomical inaccuracies introduced by the application of large and/or anisotropic voxels. To ensure deviations occur within the acceptable range (Dice coefficient scores; DCS > 0.75, corresponding to < 57% volume deviation), the volume of isotropic voxels should not exceed 5% of the total volume of the region of interest. When high accuracy is required (DCS > 0.90, corresponding to a < 19% volume deviation), the volumes of isotropic voxels should not exceed 0.08%, of the total volume. Finally, when large anisotropic factors (>3) are used, and the ellipsoid is orthogonal to the slice axes, having its long axis in the imaging plane, the voxel volume should not exceed 0.005% of the total volume. This allows sufficient compensation of anisotropy effects, in order to reach accuracy in the acceptable range (DCS > 0.75, corresponding to >57% volume deviation).

The subthalamic nucleus (STN) plays a crucial role in the surgical treatment of Parkinson's disease (PD). Studies investigating optimal protocols for STN visualization using state of the art magnetic resonance imaging (MRI) techniques have shown that susceptibility weighted images, which display the magnetic susceptibility distribution, yield better results than T1-weighted, T2-weighted, and T2*-weighted contrasts. However, these findings are based on young healthy individuals, and require validation in elderly individuals and persons suffering from PD. Using 7T MRI, the present study set out to investigate which MRI contrasts yielded the best results for STN visualization in 12 PD patients and age-matched healthy controls (HC). We found that STNs were more difficult to delineate in PD as reflected by a lower inter-rater agreement when compared to HCs. No STN size differences were observed between the groups. Analyses of quantitative susceptibility mapping (QSM) images showed a higher inter-rater agreement reflected by increased Dice-coefficients. The location of the center of mass of the STN was not affected by contrast. Overall, contrast-to-noise ratios (CNR) were higher in QSM than in T2*-weighted images. This can at least partially, explain the higher inter-rater agreement in QSM. The current results indicate that the calculation of QSM contrasts contributes to an improved visualization of the entire STN. We conclude that QSM contrast is the preferred choice for the visualization of the STN in persons with PD as well as in aging HC.

The locus coeruleus is a small brainstem nucleus which contains neuromelanin cells and is involved in a number of cognitive functions such as attention, arousal and stress, as well as several neurological and psychiatric disorders. Locus coeruleus imaging in vivo is generally performed using a T1-weighted turbo spin echo MRI sequence at 3 Tesla (T). However, imaging at high magnetic field strength can increase the signal-to-noise ratio and offers the possibility of imaging at higher spatial resolution. Therefore, in the present study we explored the possibility of visualizing the locus coeruleus at 7T. To this end, twelve healthy volunteers participated in three scanning sessions: two with 3T MRI and one with 7T MRI. The volumes of the first 3T session were used to segment the locus coeruleus, whereas the volumes of the second 3T and the 7T session were used to quantify the contrast of the locus coeruleus with several reference regions across eight different structural sequences. The results indicate that several of the 7T sequences provide detectable contrast between the locus coeruleus and surrounding tissue. Of the tested sequences, a T1-weighted sequence with spectral presaturation inversion recovery (SPIR) seems the most promising method for visualizing the locus coeruleus at ultra-high field MRI. While there is insufficient evidence to prefer the 7T SPIR sequence over the 3T TSE sequence, the isotropic voxels at 7T are an important advantage when visualizing small structures such as the locus coeruleus.

The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.

The subthalamic nucleus (STN) is a small but vitally important structure in the basal ganglia. Because of its small volume, and its localization in the basal ganglia, the STN can best be visualized using ultra-high resolution 7 Tesla (T) magnetic resonance imaging (MRI). In the present study, first we individually segmented 7T MRI STN masks to generate atlas probability maps. Secondly, the individually segmented STN masks and the probability maps were used to derive cortico-subthalamic white matter tract strength. Tract strength measures were then taken to test two functional STN hypotheses which account for the efficiency in stopping a motor response: the right inferior fronto-subthalamic (rIFC-STN) hypothesis and the posterior medial frontal cortex-subthalamic (pMFC-STN) hypothesis. Results of two independent experiments show that increased white matter tract strength between the pMFC and STN results in better stopping behaviour. •Created STN atlas probability maps based on ultra-high resolution 7T MRI images.•Individually segmented STN masks and probability maps were used to test cortico-subthalamic white matter strength.•Tract strength measures were taken to test two functional STN hypotheses to account for the efficacy to withhold a motor response.•Results of two independent experiments show that increased white matter tract strength between the pMFC and STN results in better stopping behaviour. [Display omitted] ► Created STN atlas probability maps based on ultra-high resolution 7T MRI images. ► Individually segmented STN masks and probability maps were used to test cortico-subthalamic white matter strength. ► Tract strength measures were taken to investigate the efficacy to withhold a motor response. ► Results show increased white matter tract strength between the pFMC and STN to account for better stopping behaviour.

Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency. •We describe a new multimodal method for subcortical segmentation and apply it to the striatum and globus pallidus.•The method does not require multiple manual segmentations for training.•The method improves upon exiting methods that only use a T1‐weighted image (FIRST and FreeSurfer).•Multimodal segmentation is particularly advantageous for the globus pallidus, which has poor contrast on T1‐weighted scans.

Currently little is known about structure-function mappings in the human subcortex. Here we present a large-scale automated meta-analysis on the literature to understand the structure-function mapping in the human subcortex. The results provide converging evidence into unique large scale structure-function mappings of the human subcortex based on their functional and anatomical similarity.