Biology subjects

Roebroeck, A.

Publications and source records attributed to Roebroeck, A..

11 recordsLinked to original sources

bioRxiv2026

Intracortical vessel density mapping at mesoscale reveals regionally specific angioarchitecture in the human brain

The metabolic demands of the human brain are met by a complex vascular architecture, yet our characterization of this network remains incomplete. While we have mapped the macroscopic vessels on the brains surface and the microscopic capillaries within small tissue samples, the mesoscopic scale consisting of the penetrating vessels that plunge through cortex remains an anatomical terra incognita. Mapping the interface between the macroscopic and microscopic scales is essential to understanding the critical vascular supply that sustains brain health. Here, we leveraged the BigBrain dataset and developed custom detection and tracing algorithms to reveal a whole-cortex record of the mesoscopic vascular network. We find that vascular density is not uniform across the cortex, but is a heterogeneous landscape that shows clear relationships to traditional areal boundaries. Our results constitute a reference for human mesoscopic angioarchitecture and demonstrates the power of repurposing high-resolution histological at-lases. Ultimately, this work lays the groundwork for validating recently developed in vivo MRI techniques for imaging the human cerebrovascular system at mesoscale.

neuroscience↗

bioRxiv2024

Investigating microscopic angioarchitecture in the human visual cortex in 3D with angioMASH tissue clearing and labelling

Non-invasive imaging techniques, such as ultra-high field fMRI, are intricately connected to the underlying vasculature and are approaching ever higher resolutions. For the analysis of fMRI signals over cortical depth at such high resolutions, microvascular differences might have to be taken into account. Therefore, a better understanding of the laminar distribution and interareal differences in the cortical vasculature is becoming more important. However, in comparison to cyto- and myeloarchitecture, the study of angioarchitecture has received far less attention and relatively few methods have been described to visualise the vascular network in the human brain. Here we present angioMASH, a method for double labelling angioarchitecture and cytoarchitecture in archival human brain tissue, based on the recently published MASH protocol. The double labelling and optical clearing of thick human brain slices can be accomplished within 16 days. We use this method to acquire multi-resolution 3D datasets of combined cyto- and angioarchitecture in large ([~]30 mm x 10 mm x 3 mm) volumes of human samples covering visual areas V1 and V2. We demonstrate for the first time, that classical angioarchitectonic features can be visualised in the human cortex and in 3D using tissue clearing and light-sheet microscopy. Lastly, we show differences in the vessel density and orientation over cortical depth within and between the two areas. Especially in V1, the vascular density is not homogeneous over cortical depth but shows distinct layering. These layers are also determined by changes in the orientation of the blood vessels from a predominantly radial to a more tangential distribution. In V2, differences in vascular density are less pronounced, but orientation profiles follow a similar trend over cortical depth. We discuss potential consequences of these differences for the interpretation of non-invasive functional imaging modalities such as fMRI or fNIRS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/609648v2_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@f9f841org.highwire.dtl.DTLVardef@1197e29org.highwire.dtl.DTLVardef@a9c9ccorg.highwire.dtl.DTLVardef@ffaefe_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

The Benchtop mesoSPIM: a next-generation open-source light-sheet microscope for large cleared samples

In 2015, we launched the mesoSPIM initiative (www.mesospim.org), an open-source project for making light-sheet microscopy of large cleared tissues more accessible. Meanwhile, the demand for imaging larger samples at higher speed and resolution has increased, requiring major improvements in the capabilities of light-sheet microscopy. Here, we introduce the next-generation mesoSPIM ("Benchtop") with significantly increased field of view, improved resolution, higher throughput, more affordable cost and simpler assembly compared to the original version. We developed a new method for testing objectives, enabling us to select detection objectives optimal for light-sheet imaging with large-sensor sCMOS cameras. The new mesoSPIM achieves high spatial resolution (1.5 {micro}m laterally, 3.3 {micro}m axially) across the entire field of view, a magnification up to 20x, and supports sample sizes ranging from sub-mm up to several centimetres, while being compatible with multiple clearing techniques. The new microscope serves a broad range of applications in neuroscience, developmental biology, and even physics.

neuroscience↗

bioRxiv2022

Reflective multi-immersion microscope objectives inspired by the Schmidt telescope

Rapid advances in tissue clearing protocols have begun to outpace the capabilities of existing microscope objectives: High-resolution imaging inside cm-sized cleared samples is often not possible as it requires multi-immersion objectives with high numerical aperture (NA > 0.7), long working distance (WD > 10 mm) and a large field-of-view (FOV > 1 mm). Here, we introduce a novel mirror-based optical design, the "Schmidt objective", which meets all these criteria despite containing only two optical elements. It consists of a spherical mirror in contact with the immersion medium and an aspherical correction plate. We showcase a multi-photon variant of a Schmidt objective that reaches NA 1.08 at an refractive index of 1.56 and demonstrate its versatility by imaging fixed samples in a wide range of immersion media ranging from air and water to BABB, DBE, and ECI. In addition, we demonstrate in vivo imaging by recording neuronal activity in larval zebrafish.

neuroscience↗

bioRxiv2022

Efficient 3D light-sheet imaging of very large-scale optically cleared human brain and prostate tissue samples.

The ability to image human tissue samples in 3D, with both cellular resolution and a large field of view (FOVs), can improve fundamental and clinical investigations. Here, we demonstrate the feasibility of light-sheet imaging of [~]5 cm3 sized formalin fixed human brain and up to [~]7 cm3 sized formalin fixed paraffin embedded (FFPE) prostate cancer samples, processed with the FFPE-MASH protocol. We present a light-sheet microscopy prototype, the cleared-tissue dual view Selective Plane Illumination Microscope (ct-dSPIM), capable of fast, 3D high-resolution acquisitions, of cubic centimetre sized cleared tissue. We used Mosaic scans for fast 3D overview scans of entire tissue samples or higher resolution overviews of large ROIs with various speeds: a) Mosaic 16 (16.4 {micro}m isotropic resolution, [~] 1.7 hr/cm3), b) Mosaic 4 (4.1 {micro}m isotropic resolution, [~] 5 hr/cm3) and c) Mosaic 0.5 (0.5 {micro}m near isotropic resolution, [~]15.8 hr/cm3). We could visualise ROIs around the border of human brain area V1/V2, and could demonstrate suitable imaging quality for Gleason score grading in prostate cancer samples. We show that ct-dSPIM imaging is an excellent technique to quantitatively assess entire MASH prepared large-scale human tissue samples in 3D, with considerable future clinical potential in prostate cancer.

neuroscience↗

bioRxiv2021

Representational similarity scores of digits in the sensorimotor cortex are associated with behavioral performance

Previous studies aimed to unravel a digit-specific somatotopic organization in the primary sensorimotor (SM1) cortex. It is, however, yet to be determined whether such digit somatotopy is associated with motor performance (i.e., effector selection) and digit enslaving (unintentional co-contraction of fingers) during different types of motor tasks. Here, we adopted multivariate representational similarity analysis, applied to high-field (7T) MRI data, to explore digit activation patterns in response to online finger tapping. Sixteen young adults (7 males, mean age: 24.4 years) underwent MRI, and additionally performed an offline choice reaction time task (CRTT) to assess effector selection. During both the finger tapping task (FTT) and the CRTT, force sensor data of all digits were acquired. This allowed us to assess digit enslaving (obtained from CRTT & FTT), as well as digit interference (i.e., erroneous effector selection; obtained from CRTT) and determine the correlation between these variables and digit representational similarity scores of SM1. Digit enslaving during finger tapping was associated with contralateral SM1 representational similarity scores of both hands. During the CRTT, digit enslaving of the right hand only was associated with representational similarity scores of left SM1. Additionally, right hand digit interference was associated with representational similarity scores of left S1. In conclusion, we demonstrate a cortical origin of digit enslaving, and uniquely reveal that effector selection performance is predicted by digit representations in the somatosensory cortex.

neuroscience↗

bioRxiv2020

MESMERISED: Super-accelerated 7 T STEAM imaging for quantitative multi-contrast and diffusion MRI

There is an increasing interest in quantitative imaging of T1, T2 and diffusion contrast in the brain due to greater robustness against bias fields and artifacts, as well as better biophysical interpretability in terms of microstructure. However, acquisition time constraints are a challenge, particularly when multiple quantitative contrasts are desired and when extensive sampling of diffusion directions, high b-values or long diffusion times are needed for multi-compartment microstructure modeling. Although ultra-high fields of 7 T and above have desirable properties for many MR modalities, the shortening T2 and the high specific absorption rate (SAR) of inversion and refocusing pulses bring great challenges to quantitative T1, T2 and diffusion imaging. Here, we present the MESMERISED sequence (Multiplexed Echo Shifted Multiband Excited and Recalled Imaging of STEAM Encoded Diffusion). MESMERISED removes the dead time in Stimulated Echo Acquisition Mode (STEAM) imaging by an echo-shifting mechanism. The echo-shift (ES) factor is independent of multiband (MB) acceleration and allows for very high multiplicative (ESxMB) acceleration factors, particularly under moderate and long mixing times. This results in super-acceleration and high time efficiency at 7 T for quantitative T1 and diffusion imaging, while also retaining the capacity to perform quantitative T2 and B1 mapping. We demonstrate the super-acceleration of MESMERISED for whole-brain T1 relaxometry with total acceleration factors up to 36 at 1.8 mm isotropic resolution, and up to 54 at 1.25 mm resolution qT1 imaging, corresponding to a 6x and 9x speedup, respectively, compared to MB-only accelerated acquisitions. We then demonstrate highly efficient diffusion MRI with high b-values and long diffusion times in two separate cases. First, we show that super-accelerated multi-shell diffusion acquisitions with 370 whole-brain diffusion volumes over 8 b-value shells up to b = 7000 s/mm2 can be generated at 2 mm isotropic in under 8 minutes, a data rate of almost a volume per second, or at 1.8 mm isotropic in under 11 minutes, achieving up to 3.4x speedup compared to MB-only. A comparison of b = 7000 s/mm2 MESMERISED against standard MB pulsed gradient spin echo (PGSE) diffusion imaging shows 70% higher SNR efficiency and greater effectiveness in supporting complex diffusion signal modeling. Second, we demonstrate time-efficient sampling of different diffusion times with 1.8 mm isotropic diffusion data acquired at four diffusion times up to 290 ms, which supports both Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI) at each diffusion time. Finally, we demonstrate how adding quantitative T2 and B1+ mapping to super-accelerated qT1 and diffusion imaging enables efficient quantitative multi-contrast mapping with the same MESMERISED sequence and the same readout train. MESMERISED extends possibilities to efficiently probe T1, T2 and diffusion contrast for multi-component modeling of tissue microstructure.

neuroscience↗

bioRxiv2019

Monte Carlo Simulation of Diffusion MRI in geometries constructed from two-photon microscopy of cortical gray matter

PurposeNeurodegenerative diseases such as Alzheimers disease cause changes and disruption to cortical microstructure and architecture. Diffusion MRI (dMRI) could potentially be sensitive to such changes. There is a growing interest in modeling of human cortical areas using a combination of quantitative MRI and 3D microscopy. The purpose of this study was to quantitatively characterize the cytoarchitecture of human cortical tissue from 3D fluorescence microscopy to simulate diffusion MRI (dMRI) signal in the cortex to better understand its diffusion signal characteristics.\n\nMethodsDiffusion of water molecules and dMRI signal were simulated by an indirect geometry based method and a direct voxel based method in microstructural details extracted from microscopy of cortex. Additionally, residence times of diffusing spins inside voxel volumes were considered to set effective resolution limits. Mean diffusivity (MD) and kurtosis (MK) were calculated for variable cell and neurite densities, sizes and diffusion times under realistic values for permeability and free diffusion.\n\nResultsBoth simulation methods could efficiently and accurately simulate dMRI signals with fractional anisotropy, diffusion coefficient and kurtosis in agreement with previous reports. Simulated MD and MK showed changes with increasing diffusion times specific to cortical cell density and sizes, with MK showing the highest sensitivity. Intra-voxel residence times with increasing diffusion times showed that the effective dMRI resolution approaches the thickness of cortical layers.\n\nConclusionsMonte Carlo simulations based on 3D microscopy data enable estimating changes in MD and MK over diffusion times and are sensitive to cortical cytoarchitecture and its possible changes in neurodegenerative disease. When considering layer-specific cortical dMRI, effective resolution due to residence times is an important concern.

biophysics↗

bioRxiv2019

The mesoSPIM initiative: open-source light-sheet mesoscopes for imaging in cleared tissue

Over the course of the past decade, tissue clearing methods have reached a high level of sophistication with a wide variety of approaches now available1. To image large cleared samples, light-sheet microscopes have proven to be ideal due to their excellent optical sectioning capability in transparent tissue2. Such instruments have recently seen extensive technological and commercial development. However, despite this progress, the community is lacking instruments capable of exploring large samples with near-isotropic resolution within minutes. Here, we introduce the mesoscale selective plane-illumination microscopy (mesoSPIM) initiative, an open-hardware project that provides researchers with instructions and software to easily build and operate light-sheet microscopes for centimeter-sized cleared samples (http://www.mesospim.org).\n\nA wide range of commercial light-sheet microscopes have ...

neuroscience↗

bioRxiv2018

Robust and fast Monte Carlo Markov Chain sampling of diffusion MRI microstructure models

In diffusion MRI analysis, advances in biophysical multi-compartment modeling have gained popularity over the conventional Diffusion Tensor Imaging (DTI), because they possess greater specificity in relating the dMRI signal to underlying cellular microstructure. Biophysical multi-compartment models require parameter estimation, typically performed using either Maximum Likelihood Estimation (MLE) or using Monte Carlo Markov Chain (MCMC) sampling. Whereas MLE provides only a point estimate of the fitted model parameters, MCMC recovers the entire posterior distribution of the model parameters given the data, providing additional information such as parameter uncertainty and correlations. MCMC sampling is currently not routinely applied in dMRI microstructure modeling because it requires adjustments and tuning specific to each model, particularly in the choice of proposal distributions, burn-in length, thinning and the number of samples to store. In addition, sampling often takes at least an order of magnitude more time than non-linear optimization. Here we investigate the performance of MCMC algorithm variations over multiple popular diffusion microstructure models to see whether a single well performing variation could be applied efficiently and robustly to many models. Using an efficient GPU-based implementation, we show that run times can be removed as a prohibitive constraint for sampling of diffusion multi-compartment models. Using this implementation, we investigated the effectiveness of different adaptive MCMC algorithms, burn-in, initialization and thinning. Finally we apply the theory of Effective Sample Size to diffusion multi-compartment models as a way of determining a relatively general target for the number of samples needed to characterize parameter distributions for different models and datasets. We conclude that robust and fast sampling is achieved in most diffusion microstructure models with the Adaptive Metropolis-Within-Gibbs (AMWG) algorithm initialized with an MLE point estimate, in which case 100 to 200 samples are sufficient as a burn-in and thinning is mostly unnecessary. As a relatively general target for the number of samples, we recommend a multivariate Effective Sample Size of 2200.

neuroscience↗

bioRxiv2018

Scalable cytoarchitectonic characterization of large intact human neocortex samples

We describe MASH (Multiscale Architectonic Staining of Human cortex): a simple, fast and low-cost cytoarchitectonic labeling and optical clearing approach for human cortex samples, which can be applied to large formalin fixed adult brain samples. A suite of small-molecule fluorescent nuclear and cytoplasmic dyes in combination with new refractive index matching solutions allows deep volume imaging. This enables highly scalable human neocortical cytoarchitecture characterization with a large 3D scope.

neuroscience↗