Biology subjects

Marques, J. P.

Publications and source records attributed to Marques, J. P..

13 recordsLinked to original sources

bioRxiv2026

Extensive nuclear introgression accompanied ancient mitochondrial capture in the common ancestor of two sister hare species

Pleistocene climatic oscillations promoted contact and hybridization among hare species, leaving lasting genomic signatures. Two sister species, L. castroviejoi (broom hare, endemic to Iberia) and L. corsicanus (Italian hare, endemic to Italy), carry fixed mitogenomes from L. timidus (mountain hare), an Arctic species widespread in southern Europe before deglaciation. Whether such turnover was accompanied by nuclear introgression, and how it affects their genomes today, remains unclear. Here, we date the ancient mitochondrial replacement in the broom-Italian hare ancestor using whole mitogenomes incorporating Iron Age samples. Coalescent modelling of complete genomes infers a substantial mountain hare contribution (24%) to this ancestor ~900 Kya (~5N generations). Accordingly, phylogenetic segmentation identified genomic segments consistent with mountain-to-broom/Italian hare introgression, covering ~17.8% of the autosomes, close to ~18% expected under drift, given admixture's timing and magnitude. Genome polarisation corroborates this estimate, with 25-28% of the mountain hare genome polarising with broom and Italian hares rather than its sister Iberian hare, decreasing to 15-18% at diagnostic sites. The introgression segments concentrate fixed-introgression sites and show sharp transitions of ancestry at their borders. Highly introgressed regions are gene-dense, and regions of reduced introgression are repeat-rich, suggesting that recombination shapes the introgression landscape. They also harbour genes with mitochondrial function that mirror candidates linked to mito-nuclear coadaptation in the Iberian hare, hinting that mitonuclear interactions may influence which variants persist. Our study illustrates how combining demographic, phylogenomic and polarisation-based methods can quantify and localize extensive nuclear introgression, even in the absence of non-introgressed reference populations.

evolutionary biology↗

bioRxiv2025

Rapid modulation of choice behavior by ultrasound on the human frontal eye fields

A fundamental challenge in neuroscience is establishing causal brain-function relationships with spatial and temporal precision. Transcranial ultrasonic stimulation (TUS) offers a unique opportunity to modulate deep brain structures non-invasively with high spatial resolution, but temporally precise effects and their neurophysiological foundations have yet to be demonstrated in humans. Here, we develop a temporally precise TUS protocol targeting the frontal eye fields (FEFs) -- a well-characterized circuit critical for saccadic eye movements. We demonstrate that TUS induces robust excitatory behavioral effects. Importantly, individual differences in baseline GABAergic inhibitory tone predict response magnitude. These findings establish TUS as a reliable tool for chronometric circuit interrogation and highlight the importance of neurophysiological state in neuromodulation. This work bridges human and animal research, advancing targeted TUS applications in neuroscience and clinical settings. HighlightsO_LIFocused ultrasound modulates saccades with high spatial and temporal precision C_LIO_LIInhibitory circuits in the frontal eye fields shape choice computations C_LIO_LIGABA levels predict individual variability in ultrasound-induced behavioral changes C_LIO_LIUltrasound can be used to probe fast neural dynamics and individual differences C_LI

neuroscience↗

bioRxiv2024

In vivo human neurite exchange imaging (NEXI) at 500 mT/m diffusion gradients

Evaluating tissue microstructure and membrane integrity in the living human brain through diffusion-water exchange imaging is challenging due to requirements for a high signal-to-noise ratio and short diffusion times dictated by relatively fast exchange processes. The goal of this work was to demonstrate the feasibility of in vivo imaging of tissue micro-geometries and water exchange within the brain gray matter using the state-of-the-art Connectome 2.0 scanner equipped with an ultra-high-performance gradient system (maximum gradient strength=500 mT/m, maximum slew rate=600 T/m/s). We performed diffusion MRI measurements in 15 healthy volunteers at multiple diffusion times (13-30 ms) and b-values up to 17.5 ms/m2. The anisotropic Karger model was applied to estimate the exchange time between intra-neurite and extracellular water in gray matter. The estimated exchange time across the cortical ribbon was around (median{+/-}interquartile range) 13{+/-}8 ms on Connectome 2.0, substantially faster than that measured using an imaging protocol compatible with Connectome 1.0-alike systems on the same cohort. Our investigation suggested that the NEXI exchange time estimation using a Connectome 1.0 compatible protocol was more prone to residual noise floor biases due to the small time-dependent signal contrasts across diffusion times when the exchange is fast ([≤]20 ms). Furthermore, spatial variation of exchange time was observed across the cortex, where the motor cortex, somatosensory cortex and visual cortex exhibit longer exchange times compared to other cortical regions. Non-linear fitting for the anisotropic Karger model was accelerated 100 times using a GPU-based pipeline compared to the conventional CPU-based approach. This study highlighted the importance of the chosen diffusion times and measures to address Rician noise in dMRI data, which can have a substantial impact on the estimated NEXI exchange time and require extra attention when comparing NEXI results between various hardware setups. Highlights- The Connectome 2.0 scanner equipped with 500 mT/m gradients enables high-sensitivity diffusion MRI for imaging exchange times in vivo - The global exchange time across the living human cortex was estimated to be about 13 ms on Connectome 2.0, faster than measured using a protocol compatible to Connectome 1.0 - Spatially varying exchange times were observed across the cortex - A GPU-accelerated tool was developed to speed up parameter estimation by 100 times - The narrow pulse approximation used in neurite exchange imaging does not affect estimation performance in high gradient performance MRI systems

neuroscience↗

bioRxiv2024

Genome admixture among four hare species in Iberia: focus on the broom hare (Lepus castroviejoi)

Pleistocene climatic fluctuations have often driven range shifts and hybridization among related species, leaving present-day genomic footprints. In the Iberian Peninsula, Lepus timidus, after its post-deglaciation retreat, has left extensive mitochondrial DNA traces in three other hare species, but the genomic correlates and underlying biogeographic scenarios are still incompletely understood. This study focuses on Lepus castroviejoi, endemic to the Cantabrian region, using its non-Iberian sister species, L. corsicanus, for comparison. By analyzing coalescent patterns from 10 genomes, we estimate that these species remained isolated since their divergence, around 50,000 years ago, consistent with their current allopatry. Further analyses with 25 additional genomes indicate that small fractions of the L. castroviejoi genome originate from L. granatensis, L. timidus, and L. europaeus (0.72%, 0.08%, and 0.04%, respectively). Introgression dating based on tract lengths suggests L. granatensis was already admixed with L. timidus when it hybridized with L. castroviejoi, which could explain the granatensis-timidus ancestry tract junctions detected in L. castroviejoi. Genomic segments with such junctions contain genes enriched for cell signaling and olfactory receptor activity, possibly facilitating genetic exchange. This research demonstrates how genomic ancestry inferences can reveal complex multiway admixture histories and illuminate past biogeographic events.

evolutionary biology↗

bioRxiv2024

Normative trajectories of R1, R2* and magnetic susceptibility in basal ganglia on healthy ageing

Quantitative MRI techniques, including R1, R2*, and magnetic susceptibility mapping, have emerged as promising tools for generating surrogate imaging markers of brain tissue microstructure, enabling non-invasive in vivo measurements associated with myelination and iron deposition. Gaining insights into how these quantitative measurements evolve throughout a normal lifespan can enhance our understanding of brain maturation processes and facilitate the study of disease-related microstructural changes by distinguishing pathological alterations from normal brain development. In this study, we established the normative trajectories of R1, R2*, and magnetic susceptibility in the basal ganglia at 3T. We used a healthy ageing cohort comprising 260 subjects with an evenly distributed age range and sex ratio throughout adulthood. Utilizing the non-parametric Gaussian Process Regression model to derive the normative trajectories, we found that R1 in these structures predominantly exhibit a quadratic shape over age, while R2* and magnetic susceptibility are primarily linear. We validated the normative trajectories of R2* and magnetic susceptibility using an independent cohort. Additionally, we demonstrated that the spatial distributions of the quantitative MRI parameters also change with age in the putamen and caudate nucleus. This study not only reinforces existing findings on the association between age and qMRI but also provides valuable resources for studying cognitive ageing, in conjunction with the behavioural data available in the same data collection.

neuroscience↗

bioRxiv2023

The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study protocol and rationale

To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18-80 years, stratified by age decade and sex (median age 52, IQR 36-66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n = 120), we recorded sleep-wake rhythms with an actigraphy device for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience.

neuroscience↗

bioRxiv2022

On the performance of multi-compartment relaxometry for myelin water imaging - Intra-subject and inter-protocol reproducibility

We evaluate the test-retest repeatability and study the tissue properties of multicompartment relaxometry-based myelin water imaging (MCR-MWI) derived from different gradient echo (GRE) acquisition settings. Additionally, the variable flip angle acquisition scheme is optimised based on numerical simulations to reduce the acquisition time of MCR-MWI in a clinically practical range without using advanced image acquisition methods. For the test-retest analysis, in vivo imaging was performed to collect data from three healthy volunteers in two identical sessions. Three GRE sequence settings with different echo times and repetition times imitating various scanner setups were evaluated. The in vivo data was also used to validate the optimal variable flip angle combination derived from simulations. Bundle-specific profiles of MCR-MWI derived microstructural parameters were investigated, as well as the cross-correlations of those parameters. Good cross-session repeatability is observed for MCR-MWI. While good correlations can also be found in myelin water fraction (MWF) across protocols, systematic differences, particularly for protocols with different repetition times, are observed. Numerical simulations indicate that MCR-MWI can be performed with a minimum of three flip angles covering a wide range of T1 weighting without adding significant measurement bias and the result is supported by the in vivo experiment allowing whole brain 1.5mm isotropic MWF maps to be acquired in 9 minutes. Bundles-specific MWF analysis reveals that certain white matter bundles are similar in all three participants. We also found that microstructure relaxation parameters have low correlations with MWF. MCR-MWI is a reproducible measure of myelin. However, attention should be paid to considering the protocol related MWF differences for comparison studies, especially when different repetition times are used as this can introduce biases up to 0.5% of MWF in our tested protocols. The optimised flip angle acquisition scheme can reduce the total scan time to 40% of the original implementation without significant quality degradation. Highlights- Multi-compartment relaxometry based myelin water imaging (MCR-MWI) can be performed with data comprising as few as 3 flip angles without introducing substantial bias or instability in the fitting procedure; - MCR-MWI is a reproducible measure of myelin water fraction (MWF) and incorporating DWI can further improve the measurement reproducibility; - MCR-MWI allows the acquisition of whole brain 1.5mm isotropic MWF maps in 9 minutes, even without the use of advanced model-based reconstructions; - Small MWF bias can present in cross-protocol comparison if the MT effect is not constant across GRE protocols (e.g., different TRs or flip angle combinations); - Compartmental relaxation parameters derived from MCR-MWI possess complimentary information beyond myelin water concentration.

neuroscience↗

bioRxiv2021

Studying magnetic susceptibility, microstructural compartmentalisation and chemical exchange in a formalin-fixed ex vivo human brain specimen

PurposeEx vivo imaging is a preferable method to study the biophysical mechanism of white matter orientation-dependent signal phase evolution. Yet, how formalin fixation, commonly used for tissue preservation, affects the phase measurement is not fully known. We, therefore, study the impacts of formalin fixation on magnetic susceptibility, microstructural compartmentalisation and chemical exchange measurement on human brain tissue. MethodsA formalin-fixed, post-mortem human brain specimen was scanned with multiple orientations with respect to the main magnetic field direction for robust bulk magnetic susceptibility measurement with conventional quantitative susceptibility imaging models. Homogeneous white matter tissues were subsequently excised from the whole-brain specimen and scanned in multiple rotations on an MRI scanner to measure the anisotropic magnetic susceptibility and microstructure-related contributions in the signal phase. Electron microscopy was used to validate the MRI findings. ResultsThe bulk isotropic magnetic susceptibility of ex vivo whole-brain imaging is comparable to in vivo imaging, with noticeable enhanced non-susceptibility contributions. The excised specimen experiment reveals that anisotropic magnetic susceptibility and compartmentalisation phase effect were considerably reduced in formalin-fixed white matter tissue. ConclusionsDespite formalin-fixed white matter tissue has comparable bulk isotropic magnetic susceptibility to those measured via in vivo imaging, its orientation-dependent components in the signal phase related to the tissue microstructure is substantially weaker, making it less favourable in white matter microstructure studies using phase imaging.

biophysics↗

bioRxiv2020

QSM Reconstruction Challenge 2.0: Design and Report of Results

PurposeThe aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data. MethodsA two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground-truths available to mimic the clinical setting. At the second stage, ground-truths were provided for parameter optimization.Submissions were evaluated using eight numerical metrics and visual ratings. ResultsA total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep-learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. Algorithms based on iterative approaches and Total Variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art. ConclusionThe synthetic data provides a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithmsproduced the best results along all metrics. Future QSM challenges should asses if this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.

neuroscience↗

bioRxiv2020

QSM Reconstruction Challenge 2.0 Part 1: A Realistic in silico Head Phantom for MRI data simulation and evaluation of susceptibility mapping procedures

PurposeTo create a realistic in-silico head phantom for the second Quantitative Susceptibility Mapping (QSM) Reconstruction Challenge and for future evaluations of processing algorithms for QSM. MethodsWe created a digital whole-head tissue property phantom by segmenting and post-processing high-resolution (0.64mm isotropic), multi-parametric MRI data acquired at 7T from a healthy volunteer. We simulated the steady-state magnetization at 7T using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based processing. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the phantom in the future, such as the inclusion of pathologies, as well as the simulation of a wide range of acquisition protocols. Specifically, the following parameters and effects were implemented: repetition time and echo time, voxel size, background fields, and RF phase biases. Diffusion weighted imaging phantom data is provided allowing future investigations of tissue microstructure effects in phase and QSM algorithms. ResultsThe brain-part of the phantom featured realistic morphology with spatial variations in relaxation and susceptibility values similar to the in vivo setting. We demonstrated some of the phantoms properties, including the possibility of generating phase data with non-linear evolution over echo time due to partial volume effects or complex distributions of frequency shifts within the voxel. ConclusionThe presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative susceptibility reconstruction algorithms.

neuroscience↗

bioRxiv2020

Estimation of Laminar BOLD Activation Profiles using Deconvolution with a Physiological Point Spread Function

BackgroundThe specificity of gradient echo (GE)-BOLD laminar fMRI activation profiles is degraded by intracortical veins that drain blood from lower to upper cortical layers, propagating activation signal in the same direction. This work describes an approach to obtain layer specific profiles by deconvolving the measured profiles with a physiological Point Spread Function (PSF). New MethodIt is shown that the PSF can be characterised by a TE-dependent peak to tail (p2t) value that is independent of cortical depth and can be estimated by simulation. An experimental estimation of individual p2t values and the sensitivity of the deconvolved profiles to variations in p2t is obtained using laminar data measured with a multi-echo 3D-FLASH sequence. These profiles are echo time dependent, but the underlying neuronal response is the same, allowing a data-based estimation of the PSF. ResultsThe deconvolved profiles are highly similar to the gold-standard obtained from extremely high resolution 3D-EPI data, for a range of p2t values of 5-9, which covers both the empirically determined value (7.1) and the value obtained by simulation (6.3). Comparison with Existing Method(s)Corrected profiles show a flatter shape across the cortex and a high level of similarity with the gold-standard, defined as a subset of profiles that are unaffected by intracortical veins. ConclusionsWe conclude that deconvolution is a robust approach for removing the effect of signal propagation through intracortical veins. This makes it possible to obtain profiles with high laminar specificity while benefitting from the higher sensitivity and efficiency of GE-BOLD sequences.

neuroscience↗

bioRxiv2020

SEPIA - SuscEptibility mapping PIpeline tool for phAse images

Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that has a high sensitivity in quantifying iron deposition based on MRI phase images. Furthermore, it has a unique ability to distinguish paramagnetic and diamagnetic contributions such as haemorrhage and calcification based on image contrast. These properties have contributed to a growing interest to use QSM not only in research but also in clinical applications. However, it is challenging to obtain high quality susceptibility map because of its ill-posed nature, especially for researchers who have less experience with QSM and the optimisation of its pipeline. In this paper, we present an open-source processing pipeline tool called SuscEptibility mapping PIpeline tool for phAse images (SEPIA) dedicated to the post-processing of MRI phase images and QSM. SEPIA connects various QSM toolboxes freely available in the field to offer greater flexibility in QSM processing. It also provides an interactive graphical user interface to construct and execute a QSM processing pipeline, simplifying the workflow in QSM research. The extendable design of SEPIA also allows developers to deploy their methods in the framework, providing a platform for developers and researchers to share and utilise the state-of-the-art methods in QSM.

neuroscience↗

bioRxiv2020

White Matter microstructural property decoding from gradient echo data using realistic white matter models

Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed. In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics. [Highlights] - A pipeline to generate realistic white models of arbitrary fiber volume fraction and g-ratio is presented; - We present a methodology to simulated the gradient echo signal from segmented 2D and 3D models of white matter, which takes into account the interaction of the static magnetic field with the anisotropic susceptibility of the myelin phospholipids; - Deep Learning Networks can be used to decode microstructural white matter parameters from the signal of multi-echo multi-orientation data;

neuroscience↗