Biology subjects

Nelson, M. C.

Publications and source records attributed to Nelson, M. C..

6 recordsLinked to original sources

bioRxiv2026

Dose-dependent myelin g-ratio alterations in the white matter of 16p11.2 copy number variations

Copy number variations (CNVs) at the 16p11.2 locus are major genetic risk factors for neurodevelopmental conditions and drive reciprocal alterations in cerebral white matter structure and connectivity. However, whether these alterations reflect differences in the axonal or myelin compartments remains unresolved with conventional diffusion MRI. We combined diffusion MRI with magnetization transfer saturation mapping across two ComBat-harmonized cohorts comprising 80 controls, 26 16p11.2 deletion carriers, and 13 duplication carriers. We quantified axonal volume, myelin volume, and aggregate g-ratio of white matter tracts forming the structural connectome. Metrics were evaluated using normative modeling across tract length, resting-state functional networks, and cortical nodes. We additionally examined 29 individuals carrying other neurodevelopmental CNVs. 16p11.2 gene dosage was associated with regional reciprocal differences in tract axonal volume, with greater volume in deletion carriers and lower volume in duplication carriers. In contrast, myelin volume did not differ significantly from controls. This mismatch resulted in pervasive aggregate g-ratio alterations, with higher g-ratios (relatively thinner myelin sheaths) in deletion carriers and lower g-ratios (relatively thicker sheaths) in duplication carriers. Regional g-ratio alterations also extended to other neurodevelopmental CNVs. These findings resolve some of the biological ambiguity underlying white matter alterations in 16p11.2 CNV carriers, implicating the axonal compartment while revealing comparatively stable myelin volume. The disrupted axon-myelin scaling results in connectome-wide g-ratio alterations and may represent a shared microstructural hallmark of genetic neurodevelopmental risk.

neuroscience↗

bioRxiv2026

White Matter Myelin Shapes Macroscale Functional Connectivity Through Integrative Communication

White matter structural connectivity constrains large-scale brain communication, yet most network models do not account for biologically meaningful differences between connections. Although axonal diameter and myelination influence neural signaling at the microscale, how these features shape systems-level functional connectivity remains unclear. Here, we test whether structural connectomes weighted by white matter microstructure give rise to distinct communication regimes that differentially predict multimodal functional connectivity. Combining quantitative MRI and advanced diffusion modeling, we constructed whole-brain networks weighted by tract caliber and multiple myelin-sensitive measures. To these, we applied routing- and diffusion-based communication models and used the resulting communication metrics to predict haemodynamic and frequency-resolved electromagnetic connectivity. Myelin-weighted networks preferentially enhanced long-range communication efficiency and redistributed spectral energy toward globally integrative topological eigenmodes. In contrast, caliber-weighted networks emphasized mesoscale organization and short-range communication. Across nested regression models controlling for geometric embedding and network topology, myelin-sensitive communication explained unique variance in functional connectivity with effects varying systematically across cortical systems and frequency bands. The strongest coupling was observed for alpha-band connectivity in association and attentional networks, consistent with a role for myelin-dependent communication delays in supporting long-range alpha synchrony. These findings demonstrate how distinct white matter microstructural features give rise to heterogeneous large-scale communication regimes: tract caliber and myelin bias communication toward locally specialized and globally integrative architectures, respectively. By integrating biologically informed connectomics with communication modeling and multimodal functional data, this work advances a mechanistic account of how white matter microstructure shapes macroscale brain dynamics.

neuroscience↗

bioRxiv2025

The role of white matter myelin in structural-functional network coupling

The brain is a complex network of neuronal populations interconnected by white matter tracts. The composition of these white matter connections (SC) shapes inter-regional signaling dynamics giving rise to spatial patterns of synchronous functional connectivity (FC). Several modeling approaches have proven useful for studying the mechanisms underlying the relationship between SC and FC. However, the myelination of white matter tracts -- a major component of white matter connectivity -- is not accounted for by conventional SC networks, and thus, has largely been excluded from models of FC. Here, we expand structure-function brain modeling by integrating a multi-feature white matter SC network. We use multi-modal MRI to compute an SC network with connections (edges) weighted by the caliber, myelination, and length of white matter tracts. We investigate the relationship of this multi-feature SC network with both haemodynamic and electromagnetic FC. Edge myelin was strongly predictive of FC in a pattern that was heterogeneous across brain regions and timescales of neural function. Edge myelin showed strong, frequency-specific interactions with both edge caliber and length suggesting a modulatory role for white matter myelin in structure-function coupling. This was further supported by antagonistic gradients of white matter myelin and structure-function coupling along the sensory-association axis. We describe in detail the individual and joint relationships between these major white matter features and multi-frequency FC. These results illustrate the advantage of a more comprehensive characterization of white matter in structure-function models and establish how white matter myelin -- known for roles in conduction velocity, plasticity, and metabolic support at the microscale -- shapes brain function at the macroscale.

neuroscience↗

bioRxiv2024

Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI

The g-ratio of a myelinated axon is defined as the ratio of the inner-to-outer diameter of the myelin sheath and modulates conduction speed of action potentials along axons. This g-ratio can be mapped in vivo at the macroscopic scale across the entire human brain using multi-modal MRI and sampled along white matter streamlines reconstructed from diffusion-weighted images to derive the g-ratio of a white matter tract. This tractometry approach has shown spatiotemporal variations in myelin g-ratio across white matter tracts and networks. However, tractometry is biased by partial volume effects where voxels contain multiple fiber populations. To address this limitation, we used the Convex Optimization Modeling for Microstructure-Informed Tractography (COMMIT) framework to derive tract-specific axonal and myelin volumes, which are used to compute the tract-specific aggregate g-ratio. We compare our novel COMMIT-based tract-specific g-ratio mapping approach to conventional tractometry in a group of 10 healthy adults. Our findings demonstrate that the tract-specific g-ratio mapping approach preserves the overall spatial distribution observed in tractometry and enhances contrast between tracts. Additionally, our scan-rescan data shows high repeatability for medium to large caliber tracts. We show that short and large caliber tracts have a lower g-ratio, whereas tractometry results show the opposite trends. This technique advances tract-specific analysis by reducing biases introduced by the complex network of crossing white matter fibers.

neuroscience↗

bioRxiv2023

The Human Brain Connectome Weighted by the Myelin Content and Total Intra-Axonal Cross-Sectional Area of White Matter Tracts

A central goal in neuroscience is the development of a comprehensive mapping between structural and functional brain features. Computational models support in vivo investigation of the mechanisms mediating this relationship but currently lack the requisite biological detail. Here, we characterize human structural brain networks weighted by multiple white matter microstructural features to assess their potential joint utilization in computational models. We report edge-weight-dependent spatial distributions, variance, small-worldness, rich club, hubs, as well as relationships with function, edge length and myelin. Contrasting networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts, we find opposite relationships with functional connectivity, an edge-length-independent inverse relationship with each other, and the lack of a canonical rich club in myelin-weighted networks. When controlling for edge length, tractometry-derived networks weighted by either tensor-based metrics or neurite density show no relationship with whole-brain functional connectivity. We conclude that structure-function brain models are likely to be improved by the co-utilization of structural networks weighted by total intra-axonal cross-sectional area and myelin content. We anticipate that the proposed microstructure-weighted computational modeling approach will support mechanistic understanding of the structure-function relationship of the human brain. AUTHOR SUMMARYFor computational network models to provide mechanistic links between brain structure and function, they must be informed by networks in which edge weights quantify structural features relevant to brain function. Here, we characterized several weighted structural networks capturing multiscale features of white matter connectivity. We describe these networks in terms of edge weight distribution, variance and network topology, as well as their relationships with each other, edge length and function. Overall, these findings support the joint use of structural networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts in structure-function models. This thorough characterization serves as a benchmark for future investigations of weighted structural brain networks.

neuroscience↗

bioRxiv2019

Macrobdella decora: Old World Leech Gut Microbial Community Structure Conserved in a New World Leech

Leeches are found in terrestrial, aquatic, and marine habitats on all continents. Sanguivorous leeches have been used in medicine for millennia. Modern scientific uses include studies of neurons, anticoagulants, and gut microbial symbioses. Hirudo verbana, the European medicinal leech, maintains a gut community dominated by two bacterial symbionts, Aeromonas veronii and Mucinivorans hirudinis, which sometimes account for as much as 97% of the total crop microbiota. The highly simplified gut anatomy and microbiome of H. verbana make it an excellent model organism for studying gut microbial dynamics. The North American medicinal leech, Macrobdella decora, is a hirudinid leech native to Canada and the northern U.S.A. In this study we show that M. decora symbiont communities are very similar to those in H. verbana. This similarity allowed for an extensive study in which wild caught animals were sampled to determine effects of geographic separation, time of collection, and feeding on the microbiome. Through 16S V4 rRNA deep sequencing we show that: i) the M. decora gut and bladder microbial communities are distinct, ii) the M. decora gut community is affected by feeding and long periods of starvation, and iii) geographic separation does not appear to affect the overall gut microbial community structure. We propose that M. decora is a replacement for H. verbana for studies of wild-caught animals and offer evidence for the conservation of annelid symbionts. Successful culturing and comparison of dominant symbionts from M. decora and H. verbena will provide the ability to assess host-symbiont co-evolution in future work.\n\nIMPORTANCEBuilding evidence implicates the gut microbiome in regulating animal digestion, nutritional acquisition, immune regulation, development, and even mood regulation. Because of the difficulty of assigning causative relationships in complex gut microbiomes a simplified model for testing hypotheses is necessary. Previous research in Hirudo verbana has suggested this animal as a highly simplified and tractable animal model of gut symbioses. Our data show that Macrobdella decora may work just as well as H. verbana without the drawback of being an endangered organism and with the added convenience of easy access to field-caught specimens. The similarity of the microbial community structure of species from two different continents reveals the highly-conserved nature of the microbial symbionts in sanguivorous leeches and confirms the medicinal leech as a highly simplified, natural animal model in which to study gut symbioses.

microbiology↗