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Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research. [Display omitted]

•Dopaminergic neurons dominate effective transverse relaxation in nigrosome 1.•Ion beam microscopy reveals highest iron concentrations in dopaminergic neurons.•Developed biophysical model links MRI parameters to cellular iron content.•Ferritin- and neuromelanin-bound iron impact MRI parameters differently.•Quantitative MRI provides a potential biomarker of iron in dopaminergic neurons. In Parkinson’s disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 of the substantia nigra precedes motor symptoms by two decades. Methods capable of monitoring this neuronal depletion, at an early disease stage, are needed for early diagnosis and treatment monitoring. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to tissue microstructure and in particular, to iron. However, the exact mechanisms of MRI contrast in the substantia nigra are not well understood, hindering the development of powerful biomarkers. In the present report, we illuminate the contrast mechanisms in gradient and spin echo MR images in human nigrosome 1 by combining quantitative 3D iron histology and biophysical modeling with quantitative MRI on post mortem human brain tissue. We show that the dominant contribution to the effective transverse relaxation rate (R2*) in nigrosome 1 originates from iron accumulated in the neuromelanin of dopaminergic neurons. This contribution is appropriately described by a static dephasing approximation of the MRI signal. We demonstrate that the R2* contribution from dopaminergic neurons reflects the product of cell density and cellular iron concentration. These results demonstrate that the in vivo monitoring of neuronal density and iron in nigrosome 1 may be feasible with MRI and provide directions for the development of biomarkers for an early detection of dopaminergic neuron depletion in Parkinson’s disease.

Cortical layer-dependent high (sub-millimeter) resolution functional magnetic resonance imaging (fMRI) in human or animal brain can be used to address questions regarding the functioning of cortical circuits, such as the effect of different afferent and efferent connectivities on activity in specific cortical layers. The sensitivity of gradient echo (GE) blood oxygenation level-dependent (BOLD) responses to large draining veins reduces its local specificity and can render the interpretation of the underlying laminar neural activity impossible. The application of the more spatially specific cerebral blood volume (CBV)-based fMRI in humans has been hindered by the low sensitivity of the noninvasive modalities available. Here, a vascular space occupancy (VASO) variant, adapted for use at high field, is further optimized to capture layer-dependent activity changes in human motor cortex at sub-millimeter resolution. Acquired activation maps and cortical profiles show that the VASO signal peaks in gray matter at 0.8–1.6mm depth, and deeper compared to the superficial and vein-dominated GE-BOLD responses. Validation of the VASO signal change versus well-established iron-oxide contrast agent based fMRI methods in animals showed the same cortical profiles of CBV change, after normalization for lamina-dependent baseline CBV. In order to evaluate its potential of revealing small lamina-dependent signal differences due to modulations of the input-output characteristics, layer-dependent VASO responses were investigated in the ipsilateral hemisphere during unilateral finger tapping. Positive activation in ipsilateral primary motor cortex and negative activation in ipsilateral primary sensory cortex were observed. This feature is only visible in high-resolution fMRI where opposing sides of a sulcus can be investigated independently because of a lack of partial volume effects. Based on the results presented here, we conclude that VASO offers good reproducibility, high sensitivity and lower sensitivity than GE-BOLD to changes in larger vessels, making it a valuable tool for layer-dependent fMRI studies in humans. [Display omitted] •A CBV-sensitive fMRI method is developed for high-resolution fMRI in humans.•Lamina-dependent CBV fMRI responses are shown in humans.•VASO cortical profiles are validated with Fe-contrast agent fMRI in animals.•Sensitivity to large veins can be minimized using VASO-CBV instead of BOLD fMRI.•Ipsilateral fMRI responses to finger tapping are positive in M1 and negative in S1.

Cortical layer-dependent high (sub-millimeter) resolution functional magnetic resonance imaging (fMRI) in human or animal brain can be used to address questions regarding the functioning of cortical circuits, such as the effect of different afferent and efferent connectivities on activity in specific cortical layers. The sensitivity of gradient echo (GE) blood oxygenation level-dependent (BOLD) responses to large draining veins reduces its local specificity and can render the interpretation of the underlying laminar neural activity impossible. The application of the more spatially specific cerebral blood volume (CBV)-based fMRI in humans has been hindered by the low sensitivity of the noninvasive modalities available. Here, a vascular space occupancy (VASO) variant, adapted for use at high field, is further optimized to capture layer-dependent activity changes in human motor cortex at sub-millimeter resolution. Acquired activation maps and cortical profiles show that the VASO signal peaks in gray matter at 0.8-1.6mm depth, and deeper compared to the superficial and vein-dominated GE-BOLD responses. Validation of the VASO signal change versus well-established iron-oxide contrast agent based fMRI methods in animals showed the same cortical profiles of CBV change, after normalization for lamina-dependent baseline CBV. In order to evaluate its potential of revealing small lamina-dependent signal differences due to modulations of the input-output characteristics, layer-dependent VASO responses were investigated in the ipsilateral hemisphere during unilateral finger tapping. Positive activation in ipsilateral primary motor cortex and negative activation in ipsilateral primary sensory cortex were observed. This feature is only visible in high-resolution fMRI where opposing sides of a sulcus can be investigated independently because of a lack of partial volume effects. Based on the results presented here, we conclude that VASO offers good reproducibility, high sensitivity and lower sensitivity than GE-BOLD to changes in larger vessels, making it a valuable tool for layer-dependent fMRI studies in humans.

The amygdala plays an important role in emotion, learning, and memory. It would be highly advantageous to understand more precisely its internal structure and connectivity for individual human subjects in vivo. Earlier cytoarchitectural research in post-mortem human and animal brains has revealed multiple subdivisions and connectivity patterns, probably related to different functions. With standard magnetic resonance imaging (MRI) techniques, however, the amygdala appears as an undifferentiated area of grey matter. Using high-quality diffusion tensor imaging (DTI) at 3 Tesla, we show diffusion anisotropy in this grey matter area. Such data allowed us to subdivide the amygdala for the first time in vivo. In 15 living subjects, we applied a spectral clustering algorithm to the principal diffusion direction in each amygdala voxel and found a consistent subdivision of the amygdala into a medial and a lateral region. The topography of these regions is in good agreement with the fibre architecture visible in myelin-stained sections through the amygdala of a human post-mortem brain. From these in vivo results we derived a probabilistic map of amygdalar fibre orientations. This segmentation technique has important implications for functional studies in the processing of emotions, cognitive function, and psychiatric disorders and in studying morphometry and volumetry of amygdala subdivisions.

Histological studies show that human amygdala is subdivided into several nuclei with specific connections to other brain areas. One such study has been recently used as the basis of a probabilistic amygdala map, to enable in vivo identification of specifically located functions within the amygdala and connections to it. The involvement of the amygdala in cognition, emotion and action, which may underlie several psychiatric disorders, points to a need for discrimination of these nuclei in living human brains using different techniques. Structural MRI scans of the human amygdala at standard field strengths (≤3T) have shown a region of generally featureless gray matter. Apparently homogeneous regions may reveal internal structure, however, when improved imaging strategies and better SNR are available. The goal of this study is the in vivo anatomical segmentation of the amygdala using high resolution structural MR data. The use of different MRI tissue contrast mechanisms at high field strengths has been little explored so far. Combining two different contrasts, and using cutting-edge image analysis, the following study provides a robust clustering of three amygdala components in vivo using 7T structural imaging. ► The high CNR available at 7 T enables the segmentation of the amygdala in vivo. ► MR contrast combination provides a more precise tissue segmentation. ► Spectral clustering provided three sets of robustly distinguishable areas on structural images. ► Consistency is checked across subjects, coils used and image intensities. ► These segments have been compared to previous in vivo and ex vivo amygdala maps.

Histological studies show that human amygdala is subdivided into several nuclei with specific connections to other brain areas. One such study has been recently used as the basis of a probabilistic amygdala map, to enablein vivoidentification of specifically located functions within the amygdala and connections to it. The involvement of the amygdala in cognition, emotion and action, which may underlie several psychiatric disorders, points to a need for discrimination of these nuclei in living human brains using different techniques. Structural MRI scans of the human amygdala at standard field strengths (<=3T) have shown a region of generally featureless gray matter. Apparently homogeneous regions may reveal internal structure, however, when improved imaging strategies and better SNR are available. The goal of this study is thein vivoanatomical segmentation of the amygdala using high resolution structural MR data. The use of different MRI tissue contrast mechanisms at high field strengths has been little explored so far. Combining two different contrasts, and using cutting-edge image analysis, the following study provides a robust clustering of three amygdala componentsin vivousing 7T structural imaging.

In Parkinson’s disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 of the substantia nigra precedes motor symptoms by two decades. Monitoring this neuronal depletion, at an early disease stage, is needed for early diagnosis. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to iron. However, the exact mechanisms of MRI contrast in nigrosome 1 are not well understood, hindering the development of powerful biomarkers. We demonstrate that the dominant contribution to the effective transverse MRI relaxation rate in nigrosome 1 originates from iron accumulated in dopaminergic neurons. We link quantitatively to the product of cell density and local iron concentration in dopaminergic neurons, combining quantitative 3D iron histology, biophysical modeling, and quantitative MRI on post mortem brain tissue. It is now theoretically possible to monitor dopaminergic neuron depletion, in vivo, as an early diagnostic tool for Parkinson’s disease.

In Parkinson's disease, the depletion of iron-rich dopaminergic neurons in substantia nigra's nigrosome 1 precedes first motor symptoms by two decades. Monitoring this neuronal depletion at an early disease stage is needed for diagnosis and treatment monitoring. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to tissue iron. However, the mechanisms of MRI contrast in substantia nigra are not well understood, hindering the development of specific biomarkers. We showed that the dominant contribution to the effective transverse MRI relaxation rate R2* in nigrosome 1 originates from iron accumulated in the neuromelanin of dopaminergic neurons. We linked R2* quantitatively to the product of cell density and local iron concentration in dopaminergic neurons, combining quantitative 3D iron histology, biophysical modeling, and quantitative MRI on post mortem brain tissue. This knowledge opens an avenue for monitoring neuronal iron and density in vivo and may be applied to detect early neurodegeneration in Parkinson's disease. Competing Interest Statement The Max Planck Institute for Human Cognitive and Brain Sciences has an institutional research agreement with Siemens Healthcare. NW was a speaker at an event organized by Siemens Healthcare and was reimbursed for the travel expenses.

Viruses manipulate cellular signalling by inducing the degradation of crucial signal transducers, usually via the ubiquitin–proteasome pathway. Here, we show that the murine cytomegalovirus (Murid herpesvirus 1) M45 protein induces the degradation of two cellular signalling proteins, the nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) essential modulator (NEMO) and the receptor-interacting protein kinase 1 (RIPK1), via a different mechanism: it induces their sequestration as insoluble protein aggregates and subsequently facilitates their degradation by autophagy. Aggregation of target proteins requires a distinct sequence motif in M45, which we termed ‘induced protein aggregation motif’. In a second step, M45 recruits the retromer component vacuolar protein sorting 26B (VPS26B) and the microtubule-associated protein light chain 3 (LC3)-interacting adaptor protein TBC1D5 to facilitate degradation of aggregates by selective autophagy. The induced protein aggregation motif is conserved in M45-homologous proteins of several human herpesviruses, including herpes simplex virus, Epstein–Barr virus and Kaposi’s sarcoma-associated herpesvirus, but is only partially conserved in the human cytomegalovirus UL45 protein. We further show that the HSV-1 ICP6 protein induces RIPK1 aggregation and degradation in a similar fashion to M45. These data suggest that induced protein aggregation combined with selective autophagy of aggregates (aggrephagy) represents a conserved viral immune-evasion mechanism. Herpesviruses are shown to specifically block innate antiviral responses by inducing the aggregation of key signalling molecules nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) essential modulator (NEMO) and receptor-interacting protein kinase 1 (RIPK1) and their degradation by selective autophagy, thereby blocking the activation of NF-κB and the induction of necroptosis, respectively.