Biology subjects

Uhl, Q.

Publications and source records attributed to Uhl, Q..

5 recordsLinked to original sources

bioRxiv2026

Validating the Standard Model of diffusion MRI in white matter with Numerical Substrates

The non-invasive estimation of intra- and extracellular microstructural parameters using biophysical models has been a major focus in brain microstructure imaging with MRI. The Standard Model (SM) of diffusion in white matter (WM) provides a unifying framework for various modelling approaches, representing axons as impermeable narrow cylinders embedded within a locally anisotropic extra-axonal space. However, the SM relies on simplifying assumptions that may not hold in realistic WM tissue, as they do not take into account axonal undulations, beading, the presence of glial cells, or membrane permeability. In this work, we investigate how SM-derived estimates behave when the model is applied to realistic numerical WM substrates generated by the CATERPillar tool. Specifically, we vary (i) axonal morphological features such as beading and undulations, (ii) axonal packing density, (iii) orientation dispersion, (iv) membrane permeability of axons and astrocytes separately, (v) myelin volume fraction, and (vi) diffusion time. In each part of the analysis, different noise levels are introduced. Overall, according to our results, the relative changes in SM estimates show that the intra-axonal volume fraction f increased with stronger beading, higher packing density, and greater myelin volume, and was strongly influenced by axonal and astrocytic permeability. The orientation dispersion index p2 was affected by undulation, but was substantially biased at low packing densities, with stronger beading and when astrocytes were impermeable. The effective intra-axonal diffusivity Da decreased with stronger beading and undulation and tended to be overestimated in most scenarios. The parallel extra-axonal diffusivity De|| was strongly influenced by axonal permeability, as well as packing density, dispersion, and undulation, and was the most noise-sensitive parameter, showing systematic overestimation at low SNR. Finally, the effective perpendicular extra-axonal diffusivity De{perp} was the most stable parameter relative to the effective ground truth across the tested conditions, while remaining sensitive to packing density, axonal permeability, myelin volume fraction, and undulation. These findings enable users to identify potential biases introduced by varying conditions and to adjust their interpretations accordingly.

neuroscience↗

bioRxiv2025

Microstructural correlates of white and gray matter in the healthy human brain: comparative analysis of diffusion biophysical models, inhomogeneous magnetization transfer, and macromolecular proton fraction

Abstract summaryDiffusion MRI (dMRI) and magnetization transfer (MT) rely on distinct biophysical principles and provide complementary insights into tissue microstructure. In this study, we investigated associations between microstructural metrics derived from the Standard Model (SMI) in white matter (WM) and the Standard Model with EXchange (SMEX/NEXI) in gray matter (GM) with two MT measures differing in specificity and sensitivity to myelination: the macromolecular proton fraction (MPF) and the inhomogeneous magnetization transfer ratio (ihMTR). Measurements were performed in WM and GM in ten healthy subjects scanned at 3T. In WM, the strongest significant association was observed between ihMTR and the axonal water fraction, consistent with higher myelination in regions of elevated axonal density and limited extra-axonal space. This correlation exceeded that of MPF, supporting the greater specificity of ihMTR to myelin. Interestingly, ihMTR displayed a gradient along the longitudinal axis of the corpus callosum, in agreement with previous histology measurements. Correlation between ihMTR and the extra-axonal perpendicular diffusivity (De{perp}), a putative myelination biomarker, was not significant, whereas MPF and De{perp} exhibited a moderate significant positive correlation. Since a negative correlation is expected if reflecting myelination, these results suggest that in healthy tissue De{perp} is mainly influenced by microstructural factors like fiber coherence and packing, the latter most likely affecting MPF but not ihMTR. In GM, ihMTR correlated significantly only with the exchange time (t), confirming tex as a proxy for cell membrane permeability modulated by myelin. MPF correlated exclusively with the cell-process fraction (f), suggesting the latter is modulated by total (neuronal and glial) cell membrane density. Overall, findings underscore the complementary and concurring microstructural information captured by these metrics, highlighting their potential to disentangle distinct tissue mechanisms in both healthy and pathological conditions. Future studies incorporating ground-truth histology should validate the precise sensitivity of each metric to various microstructural tissue features.

neuroscience↗

bioRxiv2025

Comparative Systematic Analysis of Gray Matter BiophysicalModels on a Public Dataset

Biophysical models of diffusion tailored to characterize gray matter (GM) microstructure are gaining traction in the neuroimaging community. NEXI, SMEX, SANDI, and SANDIX represent recent efforts to incorporate different microstructural features,such as soma contributions and inter-compartment exchange, into the diffusion MRI (dMRI) signal. In this work, we present a comparative evaluation of these four gray matter models on a single, publicly available in vivo human dataset, the Connectome Diffusion Microstructure Dataset (CDMD), acquired with two diffusion times. Using the open-source Gray Matter Swiss Knife toolbox, we estimate cortical microstructure metrics in 26 healthy subjects and evaluate goodness of fit, anatomical patterns and consistency with previous studies. CDMD data yielded GM parameter estimates consistent with values reported in previous studies. This retrospective cross-model analysis establishes the feasibility of estimating exchange models from only two diffusion times and highlights trade-offs in biological specificity, model complexity, and fitting robustness, critical considerations when choosing a model for future clinical and research applications.

neuroscience↗

bioRxiv2024

Human gray matter microstructure mapped using Neurite Exchange Imaging (NEXI) on a clinical scanner

Biophysical models of diffusion in gray matter (GM) can provide unique information about microstructure of the human brain, in health and disease. Therefore, their compatibility with clinical settings is key. Neurite Exchange Imaging (NEXI) is a two-compartment model of GM microstructure that accounts for inter-compartment exchange, whose parameter estimation requires multi-shell multi-diffusion time data. In this work, we report the first estimates of NEXI in human cortex obtained on a clinical MRI scanner. To do that, we establish an acquisition protocol and fitting routine compatible with clinical scanners. The model signal equation can be expressed either in the narrow-pulse approximation, NEXINPA, or accounting for the actual width of the diffusion gradient pulses, NEXIWP. While NEXINPA enables a faster analytical fit and is a valid approximation for data acquired on high-performance gradient systems (preclinical and Connectom scanners), on which NEXI was first implemented, NEXIWP has significant relevance for data acquired on clinical scanners with longer gradient pulses. We establish that, in the context of broad pulses, NEXIWP estimates were more comparable to previous literature values. Furthermore, we evaluate the repeatability of NEXI estimates in the human cortex on a clinical MRI scanner and show intra-subject variability to be lower than inter-subject variability, which is promising for characterizing healthy and patient cohorts. Finally, we analyze the relationship of NEXI parameters on the cortical surface to the Myelin Water Fraction (MWF), estimated using an established multicomponent T2 relaxation technique. Indeed, although it is present in small quantities in the cortex, myelin can be expected to decrease permeability. We confirm a strong correlation between the exchange time (tex) estimates and the MWF, although the spatial correspondence between the two is brain-region specific and other drivers of tex than myelin density are likely at play.

neuroscience↗

bioRxiv2022

Fast & Scrupulous: Gesture-Based Alarms Improve Performances Under Several Mental Workloads. An ERSP Study.

In high-risk environments, fast and accurate responses to warning systems are essential to efficiently handle emergency situations. The aim of the present study was twofold: 1) investigating whether hand action videos (i.e., gesture alarms) trigger faster and more accurate responses than text alarm messages (i.e., written alarms), especially when mental workload (MWL) is high; and 2) investigating the brain activity in response to both types of alarms as a function of MWL. Regardless of MWL, participants (N = 28) were found to be both faster and more accurate when responding to gesture alarms than to written alarms. Brain electrophysiological results suggest that this greater efficiency might be due to a facilitation of the action execution, reflected by the decrease in mu and beta power observed around the response time window. These results suggest that gesture alarms may improve operators performances in emergency situations.

neuroscience↗