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 and , proton density and magnetisation transfer 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.

Highlights: 21• A CBV-sensitive fMRI method is developed for high resolution fMRI in humans. 22• Lamina-dependent CBV fMRI responses are shown in humans. 23• VASO cortical profiles are validated with Fe-contrast agent fMRI in animals. 24• Sensitivity to large veins can be minimized using VASO-CBV instead of BOLD fMRI. 25• Ipsilateral fMRI responses to finger-tapping are positive in M1 and negative in S1. 26 27 Abstract 28Cortical layer-dependent high (sub-millimeter) resolution functional magnetic resonance imaging 29 (fMRI) in human or animal brain can be used to address questions regarding the functioning of 30 cortical circuits, such as the effect of different afferent and efferent connectivity on activity in 31 specific cortical layers. The sensitivity of gradient echo (GE) blood oxygenation level dependent 32 (BOLD) responses to large draining veins reduces its local specificity and can render the 33 interpretation of the underlying laminar neural activity impossible. Application of the more spatially 34 specific cerebral blood volume (CBV) based fMRI in humans has been hindered by the low sensitivity 35 of the non-invasive modalities available. Here, a Vascular Space Occupancy (VASO) variant, adapted 36 for use at high field, is further optimized to capture layer-dependent activity changes in human 37 motor cortex at sub-millimeter resolution. Acquired activation maps and cortical profiles show that 38 the VASO signal peaks in grey matter at 0.8 -1.6 mm depth, and deeper compared to the superficial 39 and vein-dominated GE-BOLD responses. Validation of the VASO signal change versus well-40 established iron-oxide contrast agent based fMRI methods in animals showed the same cortical 41 profiles of CBV change, after normalization for lamina-dependent baseline CBV. In order to evaluate 42 its potential of revealing small lamina-dependent signal differences due to modulations of the input-43 output characteristics, layer-dependent VASO responses were investigated in the ipsilateral 44 hemisphere during unilateral finger tapping. Positive activation in ipsilateral primary motor cortex 45 *7. Manuscript Click here to view linked References 2 and negative activation in ipsilateral primary sensory cortex were observed. This feature is only 1 visible in high-resolution fMRI where opposing sides of a sulcus can be investigated independently 2 because of a lack of partial volume effects. Based on the results presented here we conclude that 3 VASO offers good reproducibility, high sensitivity, and lower sensitivity than GE-BOLD to changes in 4 larger vessels, making it a valuable tool for layer-dependent fMRI studies in humans. 5Abbreviations: BOLD = blood oxygenation level dependent; CBV = cerebral blood volume; CNR = 6 contrast-to-noise ratio; CSF = cerebrospinal fluid; ΔCBV = change in CBV; EPI = echo planar imaging; 7 Fe = iron; fMRI = functional magnetic resonance imaging; GE = gradient echo; GM = grey matter; ROI 8 = region of interest; SNR = signal-to-noise ratio; SS-SI-VASO = slice-selective slab-inversion VASO...

Using a novel method for validating the effectiveness of in vivo prospective motion correction, we have demonstrated that prospective motion correction using motion data from the embedded tracking system considerably improved image quality.

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.

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