Biology subjects

Frost, R.

Publications and source records attributed to Frost, R..

6 recordsLinked to original sources

bioRxiv2023

Segmentation of supragranular and infragranular layers in ultra-high resolution 7T ex vivo MRI of the human cerebral cortex

Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Lever-aging recent advancements in ultra-high resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 {micro}m, we propose a multi-resolution U-Nets framework (MUS) that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation, while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases.

neuroscience↗

bioRxiv2021

A multimodal imaging and analysis pipeline for creating a cellular census of the human cerebral cortex

Cells are not uniformly distributed in the human cerebral cortex. Rather, they are arranged in a regional and laminar fashion that span a range of scales. Here we demonstrate an innovative imaging and analysis pipeline to construct a reliable cell census across the human cerebral cortex. Magnetic resonance imaging (MRI) is used to establish a macroscopic reference coordinate system of laminar and cytoarchitectural boundaries. Cell counting is obtained with both traditional immunohistochemistry, to provide a stereological gold-standard, and with a custom-made inverted confocal light-sheet fluorescence microscope (LSFM) for 3D imaging at cellular resolution. Finally, mesoscale optical coherence tomography (OCT) enables the registration of the distorted histological cell typing obtained with LSFM to the MRI-based atlas coordinate system.

neuroscience↗

bioRxiv2021

The Forget-Me-Not dHCP study: 7 Tesla high resolution diffusion imaging in the unfixed post-mortem neonatal brain

Diffusion MRI of the neonatal brain allows investigation of the organisational structure of maturing fibres during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. The Forget-Me-Not study, part of the Developing Human Connectome Project (dHCP), aims to acquire and publicly distribute high-resolution diffusion MRI data for unfixed post-mortem neonatal brain at 7T with a custom-built head coil. This paper describes how the study addressed logistical, technical and ethical challenges relating to recruitment pipeline, care pathway, tissue preservation, scan setup and protocol optimisation. Results from the first subject recruited to the study demonstrate high-quality diffusion MRI data. Preliminary voxel-wise and tractography-based analyses are presented for the cortical plate, subplate and white matter pathways, with comparison to age-matched in vivo dHCP data. These results demonstrate that high quality post-mortem data can be acquired and provide a sensitive means to explore the developing human brain, as well as altered diffusion properties consistent with post-mortem changes, at high resolution.

bioengineering↗

bioRxiv2020

The impact of second language immersion: Evidence from a bi-directional longitudinal cross-linguistic study

Brice et al. (2019) presented data from the first epoch of a longitudinal study of the neurobiological underpinnings of first-language (L1) and second-language (L2) processing. Results showed a similar network of activation for reading across L1 and L2, as well as significant convergence of print and speech processing across a network of left-hemisphere regions in both L1 and L2 with greater activation and convergence for L2 in anterior regions, and greater activation and convergence for L1 in posterior regions of the reading network. Here, we present the first look at longitudinal changes in these effects. L2 showed relatively few changes in activation, with some shifts in the weighting between ventral and dorsal processing. L1, however, showed more widespread differences in processing, suggesting that the neurobiological footprint of reading is dynamic, with both L1 and L2 impacting each other. Print/speech convergence showed very little longitudinal change, suggesting that it is a stable marker of the differences in L1 and L2 processing.

neuroscience↗

bioRxiv2020

Pre-stimulus beta-band activity is a signature of statistical learning

Statistical learning (SL) is taken to be the main mechanism by which cognitive systems discover the underlying regularities of the environment. We document, in the context of a classical visual SL task, divergent rhythmic EEG activity during the anticipation of stimuli within patterns versus pattern transitions. Our findings reveal differential pre-stimulus oscillatory activity in the beta band ([~]20 Hz) that indexes learning: it emerges with increased pattern repetitions, and importantly, it is highly correlated with behavioral learning outcomes. These findings hold the promise of converging on an online measure of learning regularities and provide important theoretical insights regarding the mechanisms of SL and prediction. Significance StatementSL has become a major theoretical construct in cognitive science, providing the primary means by which organisms learn about regularities in the environment. As such it is a critical building block for basic and higher-order cognitive functions. Here we identify for the first time a spectral neural index in the time window prior to stimulus presentation, which evolves with increased pattern exposure, and is predictive of learning performance. The manifestation of learning that is revealed not in stimulus processing but in anticipatory moments of the learning episode, makes a direct link between the fields of statistical learning and predictive processing, and suggests a possible mechanistic account of visual SL.

neuroscience↗

bioRxiv2017

On the Origins of the Cerebral IVIM Signal

PurposeIntravoxel incoherent motion (IVIM) has been proposed as a means of non-invasive MRI measurement of perfusion parameters such as blood flow and blood volume. Its main competitor in the brain is arterial spin labelling (ASL). In theory, IVIM should not suffer from some of the same limitations as ASL such as poor signal in white matter, and assumptions about arterial arrival times that may be violated in the presence of pathology.\n\nMethodsIn this study we aimed to test IVIM as a viable alternative to ASL for quantitative imaging of perfusion parameters in the brain. First, a direct comparison was performed between IVIM and multi-post label delay pseudo-continuous ASL; second, IVIM images were acquired with and without nulling cerebrospinal fluid; and finally, ultra-high resolution IVIM was performed to minimise partial voluming.\n\nResultsIn all three tests, IVIM failed to disprove the null hypothesis, strongly suggesting that, at least within the brain, the technique does not measure perfusion parameters as proposed.\n\nConclusionFurthermore, the results obtained suggest that the contrast visible in IVIM-derived images is primarily sensitive to cerebrospinal fluid, and not the microvascular blood compartment.

neuroscience↗