Biology subjects

Pine, K. J.

Publications and source records attributed to Pine, K. J..

4 recordsLinked to original sources

bioRxiv2024

Connectivity at fine scale: mapping structural connective fields by tractography of short association fibres in vivo

The extraordinary number of short association fibres (SAF) connecting neighbouring cortical areas is a prominent feature of the large gyrified human brain. The contribution of SAF to the human connectome is largely unknown because of methodological challenges in mapping them. We present a method to characterise cortico-cortical connectivity mediated by SAF in topologically organised cortical areas. We introduce the structural connective fields (sCF) metric which specifically quantifies neuronal signal propagation and integration mediated by SAF. This new metric complements functional connective field metrics integrating across contributions from short- and long-range white matter and intracortical fibres. Applying the method in the human early visual processing stream, we show that SAF preserve cortical functional topology. Retinotopic maps of V2 and V3 could be predicted from retinotopy in V1 and SAF connectivity. The sCF sizes increased along the cortical hierarchy and were smaller than their functional counterparts, in line with the latter being additionally broadened by long-range and intracortical connections. In vivo sCF mapping provides insights into short-range cortico- cortical connectivity in humans comparable to tract tracing studies in animal research and is an essential step towards creating a complete human connectome. HighlightsO_LINon-invasive mapping of Short Association Fibre (SAF) connectivity via diffusion-weighted MRI-based probabilistic tractography accurately predicted cortical functional neuroanatomy. C_LIO_LIThe novel structural Connective Fields (sCF) concept provides a quantitative measure of cortico-cortical integration facilitated by SAF, complementing the existing functional Connective Field (CF) concept. C_LIO_LISub-millimeter resolution diffusion-weighted MRI enables tractography and connective field modeling of SAF, unlocking applications previously restricted to invasive tract tracing in animal studies. C_LI

neuroscience↗

bioRxiv2022

B1+-correction of MT saturation maps optimized for 7T postmortem MRI of the brain

PurposeMagnetization transfer saturation (MTsat) is a useful marker to probe tissue macromolecular content and myelination in the brain. The increased [Formula] -inhomogeneity at [≥] 7T and significantly larger saturation pulse flip angles which are often used for postmortem studies exceed the limits where previous MTsat [Formula] correction methods are applicable. Here, we develop a calibration-based correction model and procedure, and validate and evaluate it in postmortem 7T data of whole chimpanzee brains. TheoryThe [Formula] dependence of MTsat was investigated by varying the off-resonance saturation pulse flip angle. For the range of saturation pulse flip angles applied in typical experiments on postmortem tissue, the dependence was close to linear. A linear model with a single calibration constant C is proposed to correct bias in MTsat by mapping it to the reference value of the saturation pulse flip angle. MethodsC was estimated voxel-wise in five postmortem chimpanzee brains. "Individual-based global parameters" were obtained by calculating the mean C within individual specimen brains and "group-based global parameters" by calculating the means of the individual-based global parameters across the five brains. ResultsThe linear calibration model described the data well, though C was not entirely independent of the underlying tissue and [Formula]. Individual-based and group-based global correction parameters (C = 1.2) led to visible, quantifiable reductions of [Formula]-biases in high resolution MTsat maps. ConclusionThe presented model and calibration approach effectively corrects for [Formula] in-homogeneities in postmortem 7T data.

neuroscience↗

bioRxiv2022

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative MRI (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (R1), effective transverse relaxation rate (R2*), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (R2* at 3T, R1 at 7T), endothelial cells (R1 and MTsat at 3T), microglia (R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes (R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.

neuroscience↗

bioRxiv2022

Deciphering the fibre-orientation independent component of R2* (R2,iso*) in the human brain with a single multi-echo gradient-recalled-echo measurement under varying microstructural conditions

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain, e.g. the g-ratio characterising the relative myelination of axons. However, R2* depends on the orientation of the fibres relative to the main magnetic field degrading its reproducibility and that of any microstructural derivative measure. To decipher its orientation-independent part (R2,iso*), a second-order polynomial in time (M2) can be applied to single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientation. The linear-time dependent parameter, {beta}1, of M2 can be biophysically related to R2,iso* when neglecting the signal from the myelin water (MW) in the hollow cylinder fibre model (HCFM). Here, we examined the effectiveness of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We showed that the fitted {beta}1 effectively estimates R2,iso*when using meGRE with long maximum echo time (TEmax {approx} 54 ms) but its microscopic dependence on the g-ratio was not accurately captured. This error was reduced to less than 12% when accounting for the MW contribution in a newly introduced biophysical expression for {beta}1. We further used this new expression to estimate the MW fraction (0.14) and g-ratio (0.79) in a human optic chiasm. However, the proposed method failed to estimate R2,iso* for a typical in-vivo meGRE protocol (TEmax {approx} 18 ms). At this TEmax and around the magic angle, the HCFM-based simulations failed to explain the R2*-orientation-dependence. In conclusion, estimation of R2,iso* with M2 in vivo requires meGRE protocols with very long TEmax {approx} 54 ms.

neuroscience↗