Biology subjects

Pavan, T.

Publications and source records attributed to Pavan, T..

6 recordsLinked to original sources

bioRxiv2026

A Comprehensive Analysis Comparing Isotropic ADC to BOLD-fMRI: Sensitivity to Resting State Networks and Grey to White Matter Functional Connectivity

While Blood Oxygenation Level-Dependent (BOLD) fMRI remains the gold standard for mapping functional brain networks with MRI, its vascular origins inherently conflate haemodynamic effects with neural activity, limiting its sensitivity in white matter (WM) or its interpretation in neurovascular diseases. Apparent Diffusion Coefficient (ADC) fMRI offers an alternative, diffusion-based contrast that is theoretically more sensitive to neuromorphological coupling and therefore more specific to neuronal activation, though investigated primarily during task-based conditions. This study aimed to comprehensively evaluate the efficacy of isotropic ADC-fMRI in detecting established resting-state networks (RSNs) and to extend this methodology to the investigation of grey-to-white matter (GM-WM) functional connectivity. Our analyses revealed a gradient of ADC detectability shaped by the degree of static functional cohesion and structural tethering of each network. The visual and somatomotor networks, being both highly segregated and strongly anchored to underlying structural pathways, yielded the most robust detection. The default mode network (DMN) and dorsal attention network (DAN) reached group-level significance but with lower effect sizes, and their detection proved fragile across analytical approaches. The frontoparietal network (FPN) and salience network (SAN), whose functional identity is defined by dynamic cross-network reconfiguration, did not reach significance. This gradient partially mirrors the established hierarchy of network segregation observed in BOLD, while further suggesting that ADC sensitivity depends on the structural grounding of each network. Furthermore, ADC demonstrated superior sensitivity to GM-WM functional coupling compared to BOLD. GM-WM functional connectivity profiles derived from ADC were significantly more aligned with underlying structural WM architecture across subjects. Taken together, these findings position isotropic ADC-fMRI as a viable complementary modality to BOLD, offering a more direct window into the neural and structural foundations of brain connectivity.

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

Non-invasive prediction of conduction velocities in the human brain from MRI-derived microstructure features at 7 Tesla

The conduction velocity of neuronal signals along axons is a key neurophysiological property that can be altered in various disease processes. While cortico-cortical evoked potentials (CCEPs) can be measured in presurgical assessment to provide information about conduction delay between a subset of brain regions, it is currently not possible to efficiently and systematically estimate conduction velocity in vivo across the whole brain. Given the established link between conduction velocity and axon morphology (most notably axon diameter but also myelination), mapping a reliable and quantitative metric linked to axon properties could fill the gap of inferring conduction velocity across the entire human brain. By integrating multiple MRI-derived microstructural measures - including axon radius, axonal water fraction, extra-axonal perpendicular diffusivity, and longitudinal relaxation time - and conduction velocity estimates obtained from a large database of CCEPs, we developed a whole-brain prediction model of conduction velocity. Our multivariate MRI-based model explained 29% of variance in neurophysiological conduction velocity, making it possible to partially predict whole-brain conduction velocity and delay matrices along connections for which no direct measurement is commonly available from epilepsy surgery investigations. This integrative MRI-based approach could provide a non-invasive framework for comprehensively characterising conduction delays in vivo across the human brain white matter.

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↗

bioRxiv2024

Unveiling microstructural dynamics: Somatosensory-evoked response induces extensive diffusivity and kurtosis changes associated with neural activity in rodents

Neural tissue microstructure is dynamic during brain activity, presenting changes in cellular morphology and membrane permeability. The sensitivity of diffusion MRI (dMRI) to restrictions and hindrances in the form of cell membranes or subcellular structures enables the exploration of brain activity under a new paradigm, offering a more direct functional contrast than its BOLD counterpart. The current work aims at probing Mean Diffusivity (MD) and Mean Kurtosis (MK) changes and their time-dependence signature across various regions in the rat brain during somatosensory processing and integration, upon unilateral forepaw stimulation. We report a decrease in MD in the contralateral primary somatosensory cortex, forelimb region (S1FL), previously ascribed to cellular swelling and increased tortuosity in the extracellular space, paralleled by a positive BOLD response. For the first time, we also report a paired decrease in MK during stimulation in S1FL, suggesting increased membrane permeability. This observation was further supported by the reduction in exchange time estimated from the kurtosis time-dependence analyses. Conversely, the secondary somatosensory cortex and subcortical areas, formerly reported as responsive to sensory stimulation in rodents (thalamus, striatum, hippocampal subfields), displayed a marked MD and MK increase, paralleled by a weak-to-absent BOLD response. Overall, MD and MK uncovered functional-induced changes with higher sensitivity than BOLD. Although the exact origin of the MD and MK increase is yet to be unraveled, the potential of dMRI to provide complementary functional insights, even below the BOLD detection threshold, has been showcased.

neuroscience↗