Biology subjects

Alkemade, A.

Publications and source records attributed to Alkemade, A..

9 recordsLinked to original sources

bioRxiv2026

Giving you five: A neuroimaging atlas of the nigrosomes in the substantia nigra based on 3D histology

Nigrosomes are formed by clusters of pigmented dopaminergic cells in the substantia nigra that critically contribute to dopaminergic function. The ever-increasing resolution of ultra-high-field MRI brings clinical imaging of these clusters into reach, promising unprecedented insight into the functional role of the nigrosomes and their early degeneration in Parkinsons disease. However, due to the nigrosomes small extents and intricate shapes, they are not included in current MRI brain atlases, preventing nigrosome-specific MRI data analysis. We provide a comprehensive 3D histological atlas of the five nigrosomes co-aligned to the widely-used MNI152 2009b space. This atlas is based on 3D-reconstructed, ultra-high-resolution block-face images and gold-standard nigrosome delineations in calbindin-D28K immunohistochemistry. We validated the atlass accuracy using the multimodal ultra-high-resolution post mortem BigBrain dataset and demonstrated its consistency with qualitative nigrosome atlases based on classical 2D histology. We provide detailed usage instructions for applying our atlas to ultra-high-resolution and -field MRI data. The openly available atlas enables neuroimaging studies of the nigrosomes, opening a new avenue toward understanding the differential involvement of the nigrosomes in the healthy and diseased brain and the development of neuroimaging biomarkers of dopaminergic neurodegeneration.

neuroscience↗

bioRxiv2026

Pooling quantitative MRI data: A multi-protocol study of healthy subcortical ageing

Quantitative MRI (qMRI) measures relaxation rates, exchange rates and proton densities that reflect biophysical properties of tissue and are ideally free from protocol- and scanner-dependence. In practice, qMRI has not yet achieved this level of independence from sequence and hardware choice, and quantitative estimates often differ across sites and acquisition schemes. At the same time pooling data across different sources can be beneficial to statistical power of longitudinal, cross-sectional or case-control studies. Here we investigate how protocol and hardware differences can affect pooling data from different sources in large ultra high field (UHF) qMRI studies in the context of healthy aging. We combine the openly available ageing UHF qMRI MP2RAGEME-based dataset with two different MPM-based sets of qMRI data. We evaluate how pooling affects age dependence of qMRI parameters and investigate protocol-related biases, with a particular focus on subcortical structures. We focus the analysis, first, on replication and expansion of the reference qMRI dataset on normative aging, second, the examination of the protocol influence on the estimated qMRI values, and third, on detecting the protocol effect on the age dependence inferred from the data. We find that the age-related changes for R1 measure around 4-17% of the lifespan mean in different structures. Similarly, age-related R2* variation in different structures constitutes around 6-30%. Subcortical structure volume change is on the order of 5-27%. We further observe larger relative difference between protocols for R1 and volume, while R2* remains more consistent for most regions. We show how pooling the UHF qMRI data from different sites and collected with different quantitative protocols can be both detrimental and beneficial for the analysis outcomes.

neuroscience↗

bioRxiv2025

Mesoscale imaging of the human cerebellum reveals converging regional specialization of its morphology, vasculature and cytoarchitecture.

The human cerebellar cortex contains the highest density and number of neurons in the human brain, yet this thin and tightly-folded structure has remained largely inaccessible to in-vivo imaging. We introduce an imaging framework to enable high-resolution, comprehensive imaging of the human cerebellar cortex. We validated the in-vivo estimates of cortical morphology against post-mortem measures. Crucially, our findings challenge the commonly held view of the cerebellar cortex as being uniform. Our findings reveal interlobular heterogeneity in both cortical morphology and vascular organization. We demonstrate that this spatial heterogeneity correlates with granular layer cell density. This convergence of morphology, cytoarchitecture and vascularization offers new mechanistic insights and reframes how cerebellar structure and function should be interpreted in health and disease.

neuroscience↗

bioRxiv2024

Joint models reveal human subcortical underpinnings of choice and learning behaviour

Decision making and learning processes together enable adaptive goal-oriented behaviour. Animal studies demonstrated the importance of subcortical regions in these cognitive processes, but the human subcortical contributions remain poorly characterised. Here, we study choice and learning processes in the human subcor-tex, using a tailored ultra-high field 7 T fMRI imaging protocol combined with joint models. Joint models provide unbiased estimates of brain-behaviour rela-tions by simultaneously including behavioural and neural data at the participant and group level. Results demonstrate relations between subcortical regions and the adjustment of decision urgency. Value-related BOLD differences were found with opposite BOLD polarity in different parts of the striatum. Multiple sub-cortical regions showed BOLD signatures of reward prediction error processing, but contrary to expectations, these did not include the dopaminergic midbrain. Combined, this study characterises the human subcortical contributions to choice and learning, and demonstrates the feasibility and value of joint modelling in facilitating our understanding of brain-behaviour relationships.

neuroscience↗

bioRxiv2021

Charting human subcortical maturation with in vivo 7 T MRI

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, 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.

neuroscience↗

bioRxiv2020

Measuring the iron content of dopaminergic neurons in substantia nigra with MRI relaxometry

In Parkinsons disease, the depletion of iron-rich dopaminergic neurons in substantia nigras 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 [Formula] in nigrosome 1 originates from iron accumulated in the neuromelanin of dopaminergic neurons. We linked [Formula] 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 Parkinsons disease.

neuroscience↗

bioRxiv2020

3 versus 7 Tesla Magnetic Resonance Imaging for parcellations of subcortical brain structures

7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa, created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. While the clinical 3T MRI scan did not allow delineation of an anatomical plausible structure due to its limited spatial resolution, optimized 3T and 7T parcellations could be directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results did not confirm increased Dice scores for 7T, although they revealed a higher consistency for structure volumes for 7T compared to optimized 3T, potentially indicative of more agreement with increased field strength. Together these results indicate the importance of the use of isotropic voxels with both 3T and 7T, and the potential for clinical applications.

neuroscience↗

bioRxiv2020

Multi-contrast Anatomical Subcortical Structures Parcellation

The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here we present a new open source parcellation algorithm to automatically map the subcortex. The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita.

neuroscience↗

bioRxiv2019

Denoising High-field Multi-dimensional MRI with Local Complex PCA

Modern high field and ultra high field magnetic resonance imaging (MRI) experiments routinely collect multi-dimensional data with high spatial resolution, whether multi-parametric structural, diffusion or functional MRI. While diffusion and functional imaging have benefited from recent advances in multi-dimensional signal analysis and denoising, structural MRI has remained untouched. In this work, we propose a denoising technique for multi-parametric quantitative MRI, combining a highly popular denoising method from diffusion imaging, over-complete local PCA, with a reconstruction of the complex-valued MR signal in order to define stable estimates of the noise in the decomposition. With this approach, we show signal to noise ratio (SNR) improvements in high resolution MRI without compromising the spatial accuracy or generating spurious perceptual boundaries.

bioinformatics↗