Biology subjects

Warrington, S.

Publications and source records attributed to Warrington, S..

15 recordsLinked to original sources

bioRxiv2026

Diagnose Harmonisation (DHARM): An open-source tool for the harmonisation and analysis of batch effects in MRI-derived measures.

Technical differences between scanners, acquisition protocols, machine hardware and processing pipelines can introduce systematic variation into MRI-derived measures. Numerous harmonisation methods have been developed to reduce these effects. However, validation of these methods is often performed using different criteria depending on the method itself, the datasets used and the study design. Consequently, determining whether harmonisation is required, selecting an appropriate method and establishing whether or not technical variation has been sufficiently removed without compromising biological signal remain challenging. In this manuscript, we introduce Diagnose Harmonisation (DHARM), an open-source Python toolbox for diagnosing batch effects, applying harmonisation and evaluating harmonisation performance in cross-sectional and repeated-measures settings. DHARM is user-friendly, comes with GUI-based and command-line interfaces, and has graphical reporting. It provides standardised reporting workflows combining complementary measures of batch-associated differences in feature location, scale, empirical distributions, covariance and multivariate structure, together with measures assessing preservation of biological covariate effects and repeated-measures consistency. The framework includes several established harmonisation approaches, but its evaluation workflow is method-agnostic: users can also supply data harmonised using external or newly developed methods and benchmark their outputs using the same common set of diagnostics. We demonstrate DHARM using multisite cross-sectional MRI measures from UK Biobank, Cam-CAN and OxBAC as well as travelling-heads data from the ON-Harmony dataset. Across the cross-sectional datasets, harmonisation substantially reduced additive batch effects, while residual differences in variance and empirical distributions varied between methods. Multivariate diagnostics further demonstrated that reduction of batch-associated structure can coexist with preservation or increased detectability of biologically relevant variation. In the repeated-measures example, harmonisation reduced batch-associated and within-subject variability, while broadly preserving subject-level and biological relationships. DHARM provides a reproducible framework for diagnosing batch effects, applying different harmonisation methods and evaluating harmonisation as a multi-criteria problem rather than relying on a single measure of success. By jointly characterising technical variation and preservation of biologically meaningful information, DHARM can support dataset- and objective-specific selection, benchmarking and validation of harmonisation strategies.

neuroscience↗

bioRxiv2025

10.5 Tesla High-Resolution Macaque Brain MRI for Connectivity Studies

Mapping brain connectivity in primates remains a major challenge due to difficulties in resolving microscopic white matter architecture, while maintaining whole-brain coverage. Increasing imaging spatial resolution is key for disambiguating fibre configurations within smaller anatomical volumes. Here, we present novel developments that allow high-resolution diffusion MRI of the macaque brain using one of the world's highest-field human MRI scanners operating at 10.5 Tesla, allowing both in vivo and ex vivo macaque brain imaging. Our approach achieves very high spatial resolution across both tissue states, (up to 580 m)3 in vivo and (300 m)3 ex vivo, with diffusion weighting up to b = 6000 s/mm2. We detail methodological advances in data acquisition, image reconstruction, processing and whole-brain tractography that overcome critical challenges associated with ultra-high-field imaging. This work establishes a new framework for high-resolution in vivo and ex vivo neuroimaging of the NHP brain at 10.5 T using a human bore scanner, paving the way for subsequent analyses of brain connectivity across species and tissue states at unprecedented detail. The dataset, along with all processing pipelines, containerised workflows, and reusable web services, is openly shared to support reproducibility and future integration with microscopy for studying white matter microstructure and connections at the mesoscale.

neuroscience↗

bioRxiv2025

Diffusion-weighted steady-state free precession imaging in the ex vivo macaque brain on a 10.5T human MRI scanner

Diffusion MRI provides a non-invasive probe of local fibre bundles and long-range anatomical connections to characterise the structural connectome. One way to achieve very high spatial resolution diffusion MRI data for connectivity investigations is to scan ex-vivo brains over many hours or days, ideally at ultra-high field strength to boost signal levels. However, conventional diffusion MRI acquisition techniques do not generally deliver good data quality for the challenging conditions of ex-vivo tissue, characterised by reduced diffusivities and relaxation times when compared to in vivo. In this work, we investigate the potential of the diffusion-weighted steady-state free precession (DW-SSFP) sequence for ex vivo diffusion imaging of the macaque brain using a 10.5 T human MRI scanner with a conventional (Gmax = 70 mT/m) gradient set. SNR-efficiency optimisations incorporating experimental relaxation times demonstrate that the DW-SSFP sequence is predicted to achieve improved or similar SNR efficiency compared to a diffusion-weighted spin- and stimulated-echo sequence. Importantly, DW-SSFP can achieve this with the additional benefit of negligible geometric distortions, unlike conventional diffusion MRI using an echo-planar imaging readout. Using optimised DW-SSFP sequence parameters, we propose a protocol at 0.4 mm isotropic resolution using a two-shell multi-orientation protocol (effective b-values of 3200 s/mm2 and 5600 s/mm2). We fit the data using Tensor, Ball and 3-Sticks and Constrained Spherical Deconvolution signal representations. The results demonstrate high-quality diffusivity estimates across the entire brain with the ability to resolve multiple fibre populations in challenging crossing-fibre regions. The data will be made fully open source and multimodal as part of the Center for Mesoscale Connectomics, providing a resource for future connectivity investigations.

neuroscience↗

bioRxiv2025

An RF coil array system for in vivo & ex vivo non-human primate brain studies at 10.5 Tesla

PurposeWe aimed to develop an innovative RF coil toolset for high resolution in vivo and ex vivo non-human primate neuroimaging applications at 10.5T MRI. The main goal was to improve our multimodal neural connectivity pipeline through the improved SNR, CNR, and spatial resolution that result from utilizing high-density RF coil arrays in combination with ultra-high field MRI. MethodsTwo RF coil arrays, both comprising 8 transmit and 40 receive channels, were designed and built for in vivo and ex vivo NHP imaging at 10.5 T. Experimental data was collected on multiple in vivo and ex vivo specimens, showing the utility UHF MRI for NHP neuroscience. ResultsExperimental results demonstrate uniform whole-brain coverage within both in vivo--which included the cerebellar, and spinal cord regions--and ex vivo specimens. High spatial resolutions (in vivo: 0.1x0.1x0.5 mm, ex vivo: 120 micron isotropic) were achieved, revealing detailed anatomical structures throughout. High temporal stability allowed for EPI and dMRI applications. ConclusionAn RF coil toolset comprising two 8ch transmit/40ch receive arrays was successfully designed for both in vivo and ex vivo NHP brain applications at 10.5 T. Both high-density RF coil arrays coupled with the SNR and CNR benefits available at UHF supported unmatched anatomical, functional, and diffusion applications at some of the highest spatial resolutions to date. Additionally, the combined capability of both in vivo and ex vivo MRI with the same brain specimen allows for tighter control for experimental-paradigm multistage studies examining translation between in vivo and ex vivo methodologies.

neuroscience↗

bioRxiv2025

Offline Reconstruction of Diffusion MRI Acquisitions for Comparison Between Complex PCA-based and AI-based Denoising

PurposeOptimal diffusion MRI (dMRI) data for image denoising is often unavailable from scanner reconstruction. In this work, we make available an offline reconstruction pipeline for GE dMRI acquisitions, giving access to complex dMRI data. Furthermore, we compare the efficacy of GE HealthCares AIR-Recon DL (ARDL), a proprietary convolutional neural network-based reconstruction and denoising approach, to open-source PCA-based MPPCASVS and NORDIC denoising methods on high-resolution dMRI data. MethodsWe developed an end-to-end offline dMRI reconstruction pipeline for GE HealthCare acquisitions, augmenting the Orchestra software development kit, and validated its output against scanner reconstruction. We used it to compare MPPCASVS, NORDIC and ARDL denoising approaches, considering underlying metrics reflecting noise variance and bias, such as the ADC profiles in highly anisotropic areas, and downstream measurements, such as fiber orientation estimation and white matter tractography. ResultsOur validated offline reconstruction supports various in-plane/out-of-plane accelerations and partial Fourier reconstruction methods. Unlike scanner reconstruction, it provides access to complex dMRI data, enabling denoising in the complex domain, which demonstrated superior noise floor suppression compared to magnitude-constrained denoising. PCA-based denoising methods had improved spatial resolution, contrast-to-noise and more robust fiber orientation estimation compared to ARDL. ConclusionWe found significant gains in dMRI data quality when using the proposed offline reconstruction pipeline, allowing complex-domain denoising to obtain high-quality data at high spatial resolution and b-value, using a wide-bore scanner and a standard PGSE EPI sequence. MPPCASVS and NORDIC (4D PCA-based) outperformed ARDL (2D) in terms of spatial resolution, reduction of noise-floor bias and variance.

neuroscience↗

bioRxiv2025

An anthropoid/strepsirrhine divergence in ventral visual stream connectivity

The ventral visual stream has undergone extensive reorganisation within the primate lineage. While some work has examined restructuring of the ventral prefrontal cortical grey matter across primates, comparative studies of white matter connectivity are lacking primarily due to difficulties in data acquisition and processing. Here, we present a data-driven approach to the study of white matter connectivity using post-mortem diffusion MRI data. With this approach, we reconstruct anterior temporal-frontal and occipitotemporal-frontal connections across two anthropoids and one strepsirrhine: the rhesus macaque, the black-capped squirrel monkey, and the ring-tailed lemur. We find that the anthropoids exhibit more dorsal prefrontal innervation of these ventral visual connections. This study supports the hypothesis that anthropoid primates underwent extensive reorganisation of both grey and white matter during their emergence as visual foragers in a complex ecological niche. The data-driven techniques presented here enable further research on white matter connectivity in previously understudied species.

neuroscience↗

bioRxiv2025

Cross-species Standardised Cortico-Subcortical Tractography

Despite their importance for brain function, cortico-subcortical white matter tracts are underrepresented in diffusion MRI tractography studies. Their non-invasive mapping is more challenging and less explored compared to other major cortico-cortical bundles. We introduce a set of standardised tractography protocols for delineating tracts between the cortex and various deep subcortical structures, including the caudate, putamen, amygdala, thalamus and hippocampus. To enable comparative studies, our protocols are designed for both human and macaque brains. We demonstrate how tractography reconstructions follow topographical principles obtained from tracers in the macaque and how these translate to humans. We show that the proposed protocols are robust against data quality and preserve aspects of individual variability stemming from family structure in humans. Lastly, we demonstrate the value of these species-matched protocols in mapping homologous grey matter regions in humans and macaques, both in cortex and subcortex.

neuroscience↗

bioRxiv2024

Connectivity in the human and the monkey brain probes causal involvement of the fornix in Mild Cognitive Impairment and Alzheimer's Disease

Alzheimers disease (AD) is characterised by memory loss and severe deficits in cognitive function associated with neural degeneration in a network of brain regions. However, little is known about those regions connectivity patterns and how that differs from mild cognitive impairment (MCI) or healthy aging. To address that, we used diffusion-weighted MRI to determine connectivity across 11 key memory-related regions and their unique set of connections (connectivity fingerprints) to 14 white matter (WM) tracts. One WM tract particularly important for memory, and attractive target for therapeutic interventions in AD, is the fornix. However, determining fornix-specific contributions to memory deficits or therapeutic benefits is difficult, partly because the fornix carries numerous subcortical and cortical projections. To explore that, we additionally examined MRI-derived connectivity across homologous structures in non-human primates before and after fornix transections. We report several important findings. First, that connectivity between the hippocampus and the anterior thalamus (ATh) is strongly compromised in cognitive decline, as is fornix integrity. We also found strong reductions in the hippocampus-fornix and ATh-fornix connectivity in AD, demonstrating that fingerprint divergence across groups in hippocampal CA1 and ATh can identify differences between people with AD and MCI. In AD, we observed also elevated connectivity between WM tracts and the hippocampus or the ATh, suggesting a compensatory mechanism, which, importantly, depends on a viable fornix. We finally demonstrate that certain thalamic nuclei and hippocampal subfields link through the retrosplenial cortex in both species, highlighting its potential role as an alternative target for interventions in memory disorders.

neuroscience↗

bioRxiv2024

Connectivity profile and function of uniquely human cortical areas

Quantitative comparison of the white matter organization of the human neocortex with that of the chimpanzee and macaque shows a wide distribution of areas with a uniquely human connectivity profile, including the frontal-parietal fiber systems and the temporal visual pathway. Functional decoding of these areas shows their involvement in language, abstract reasoning, and social information processing. Overall, these results counter models that assign primacy to prefrontal cortex for human uniqueness.

neuroscience↗

bioRxiv2023

Using a function-first "scout fragment"-based approach to develop allosteric covalent inhibitors of conformationally dynamic helicase mechanoenzymes

Helicases, classified into six superfamilies, are mechanoenzymes that utilize energy derived from ATP hydrolysis to remodel DNA and RNA substrates. These enzymes have key roles in diverse cellular processes, such as genome replication and maintenance, ribosome assembly and translation. Helicases with essential functions only in certain cancer cells have been identified and helicases expressed by certain viruses are required for their pathogenicity. As a result, helicases are important targets for chemical probes and therapeutics. However, it has been very challenging to develop selective chemical inhibitors for helicases, enzymes with highly dynamic conformations. We envisioned that electrophilic scout fragments, which have been used for chemical proteomic based profiling, could be leveraged to develop covalent inhibitors of helicases. We adopted a function-first approach, combining enzymatic assays with enantiomeric probe pairs and mass spectrometry, to develop a covalent inhibitor that selectively targets an allosteric site in SARS-CoV-2 nsp13, a superfamily-1 helicase. Further, we demonstrate that scout fragments inhibit the activity of two human superfamily-2 helicases, BLM and WRN, involved in genome maintenance. Together, our findings suggest a covalent inhibitor discovery approach to target helicases and potentially other conformationally dynamic mechanoenzymes.

biochemistry↗

bioRxiv2023

Spatial patterns of within-thalamus anatomical connectivity vary across the cortical hierarchy in humans and macaques

Each cortical area has a distinct pattern of anatomical connections within the thalamus, a central subcortical structure composed of functionally and structurally distinct nuclei. Previous studies have suggested that certain cortical areas may have more extensive anatomical connections that target multiple thalamic nuclei, which potentially allows them to modulate distributed information flow. However, there is a lack of quantitative investigations into anatomical connectivity patterns within the thalamus. Consequently, it remains unknown if cortical areas exhibit systematic differences in the extent of their anatomical connections within the thalamus. To address this knowledge gap, we used diffusion magnetic resonance imaging (dMRI) to perform brain-wide probabilistic tractography for 828 healthy adults from the Human Connectome Project. We then developed a framework to quantify the spatial extent of each cortical areas anatomical connections within the thalamus. Additionally, we leveraged resting-state functional MRI, cortical myelin, and human neural gene expression data to test if the extent of anatomical connections within the thalamus varied along the cortical hierarchy, from sensory and motor to multimodal associative cortical areas. Our results revealed two distinct corticothalamic tractography motifs: 1) a sensorimotor cortical motif characterized by focal thalamic connections targeting posterolateral thalamus, associated with fast, feed-forward information flow; and 2) an associative cortical motif characterized by diffuse thalamic connections targeting anteromedial thalamus, associated with slow, feed-back information flow. These findings were consistent across human subjects and were also observed in macaques, indicating cross-species generalizability. Overall, our study demonstrates that sensorimotor and association cortical areas exhibit differences in the spatial extent of their anatomical connections within the thalamus, which may support functionally-distinct cortico-thalamic information flow.

neuroscience↗

bioRxiv2023

A resource for development and comparison of multi-modal brain 3T MRI harmonisation approaches

Despite the huge potential of magnetic resonance imaging (MRI) in mapping and exploring the brain, MRI measures can often be limited in their consistency, reproducibility and accuracy which subsequently restricts their quantifiability. Nuisance nonbiological factors, such as hardware, software, calibration differences between scanners, and post-processing options can contribute to, or drive trends in, neuroimaging features to an extent that interferes with biological variability. Such lack of consistency, known as lack of harmonisation, across neuroimaging datasets poses a great challenge for our capabilities in quantitative MRI. Here, we build a new resource for comprehensively mapping the extent of the problem and objectively evaluating neuroimaging harmonisation approaches. We use a travelling-heads paradigm consisting of multimodal MRI data of 10 travelling subjects, each scanned at 5 different sites on 6 different 3T scanners from all the 3 major vendors and using 5 neuroimaging modalities, providing more comprehensive coverage than before. We also acquire multiple within-scanner repeats for a subset of subjects, setting baselines for multi-modal scan-rescan variability. Having extracted hundreds of image-derived features, we compare three forms of variability: (i) between-scanner, (ii) within-scanner (within-subject), and (iii) biological (between-subject). We characterise the reliability of features across scanners and use our resource as a testbed to enable new investigations that until now have been relatively unexplored. Specifically, we identify optimal pipeline processing steps that minimise between-scanner variability in extracted features (implicit harmonisation). We also test the performance of post-processing harmonisation tools (explicit harmonisation) and specifically check their efficiency in reducing between-scanner variability against baseline standards provided by our data. Our explorations allow us to come up with good practice suggestions on processing steps and sets of features where results are more consistent, while our publicly-released datasets establish references for future studies in this field.

neuroscience↗

bioRxiv2022

QuNex -- An Integrative Platform forReproducible Neuroimaging Analytics

Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration (1-3), particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a "turnkey" command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features. The platform enables inter-operable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia (4), including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform. Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease.

neuroscience↗

bioRxiv2022

Concurrent mapping of brain ontogeny and phylogeny within a common connectivity space

Developmental and evolutionary effects on brain organisation are complex, yet linked, as evidenced by the striking correspondence in cortical expansion changes. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric changes. Here, we propose a novel framework that allows the integration of connectivity maps from humans (adults and neonates) and non-human primates (macaques) onto a common space. We use white matter bundles to anchor the definition of the common space and employ the uniqueness of the areal connection patterns to these bundles to probe areal specialisation. This enables us to quantitatively study divergences and similarities in cortical connectivity over both evolutionary and developmental scales. It further allows us to map brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains.

neuroscience↗

bioRxiv2019

XTRACT - Standardised protocols for automated tractography and connectivity blueprints in the human and macaque brain

We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science.

neuroscience↗