Biology subjects

Archer, D.

Publications and source records attributed to Archer, D..

4 recordsLinked to original sources

bioRxiv2026

Automated Segmentation of Brainstem and Subcortical White Matter: Mapping the Deep Tegmental Core with BundleParc

Diffusion MRI enables noninvasive mapping of human white matter pathways, but automated segmentation methods have largely focused on large association, projection, and commissural bundles. Brainstem and subcortical pathways supporting basal ganglia, cerebellar, limbic/reward, sensory, and homeostatic functions remain underrepresented in large-scale connectomic analyses. To address this gap, we adapted BundleParc, a recently introduced bundle-parcellation architecture, into an automated pipeline for direct segmentation and along-tract parcellation of 97 subcortical and brainstem white matter pathways. The model was trained on a curated reference dataset derived from Human Connectome Project diffusion MRI using anatomy-guided tractography, explicit inclusion and exclusion criteria, automated outlier filtering, and manual quality assurance. Operating directly on native-space fiber orientation distributions, the algorithm successfully recovers these intricate anatomical trajectories and ordered parcellations. We show the model generalizes to diverse external datasets spanning development, aging, and neurodegenerative disease cohorts, maintaining robust performance across variations in spatial resolution and angular sampling. The released container, trained model, population atlas, reference streamlines, and quality assurance outputs provide a resource for studying deep brainstem and subcortical pathways in development, aging, disease, and neuromodulation-relevant anatomy.

neuroscience↗

bioRxiv2026

Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts

Brain charts, or normative models of quantitative neuroimaging measures, can identify trajectories of brain development and abnormalities in groups and individuals by leveraging large populations. Recent work has extended these brain charts to model microstructural and macrostructural features of white matter. Assessments of variance for these brain charts are necessary to determine whether the models being used for these data are stable. We implement an analytic approach to characterize variability of the parameters in previously released brain charts created using the generalized additive models for location, scale, and shape (GAMLSS) framework. Additionally, we empirically validate the accuracy of each analytic model through a comparison to a bootstrapping approach from 0.2 to 90 years of age. We find that across all models, the analytic coefficient of variation (COV) remains below 5% for ages greater than 0.25 years, with the maximum empirical observed COV reaching 7% at 0.2 years of age. Further, the empirical assessment shows high agreement with the analytic assessment, with COV estimates averaged across the lifespan for all models having a Pearson correlation coefficient of 0.776 and a mean difference of 4 x 10-4. Both methods exhibit volume and surface area as the features with the largest average COV for the majority of tracts. However, the analytic assessment yields axial diffusivity as the feature most frequently having the smallest COV, whereas the corresponding feature for the empirical assessment is average length. These results suggest that the analytic approach overestimates model stability for WM brain charts when the COV is low and that the validation method is suitable for assessing whether GAMLSS models are unstable.

bioengineering↗

bioRxiv2025

White matter microstructure and macrostructure brain charts across the human lifespan

Normative reference charts are widely used in healthcare, especially for assessing the development of individuals by benchmarking anatomic and physiological features against population trajectories across the lifespan. Recent work has extended this concept to gray matter morphology in the brain, but no such reference framework currently exists for white matter (WM) even though WM constitutes the essential substrate for neuronal communication and large-scale network integration. Here, we present the first comprehensive WM brain charts, which describe how microstructural and macrostructural features of WM evolve across the lifespan, by leveraging over 35,120 diffusion MRI scans from 50 harmonized studies. Using generalized additive models for location, scale, and shape (GAMLSS), we estimate age- and sex-stratified trajectories for 72 individual white matter pathways, quantifying both tract-specific microstructural and morphometric features. We demonstrate that these WM brain charts enable four important applications: (1) defining normative trajectories of WM maturation and decline across distinct pathways, (2) identifying previously uncharacterized developmental milestones and spatial gradients of tract maturation, (3) detecting individualized deviations from normative patterns with clinical relevance across multiple neurological disorders, and (4) facilitating standardized, cross-study centile scoring of new datasets. By establishing a unified, interpretable reference framework for WM structure, these brain charts provide a foundational metric for research and clinical neuroscience. The accompanying open-access trajectories, centile scoring tools, and harmonization methods facilitate precise mapping of WM development, aging, and pathology across diverse populations. We release the brain charts and provide an out-of-sample alignment process as a Docker image: https://zenodo.org/records/17561821.

neuroscience↗

bioRxiv2016

Ancient individuals from the North American Northwest Coast reveal 10,000 years of regional genetic continuity

Recent genome-wide studies of both ancient and modern indigenous people of the Americas have shed light on the demographic processes involved during the first peopling. The Pacific northwest coast proves an intriguing focus for these studies due to its association with coastal migration models and genetic ancestral patterns that are difficult to reconcile with modern DNA alone. Here we report the genome-wide sequence of an ancient individual known as \"Shuka Kaa\" (\"Man Ahead of Us\") recovered from the On Your Knees Cave (OYKC) in southeastern Alaska (archaeological site 49-PET-408). The human remains date to approximately 10,300 cal years before present (BP). We also analyze low coverage genomes of three more recent individuals from the nearby coast of British Columbia dating from approximately 6075 to 1750 cal years BP. From the resulting time series of genetic data, we show that the Pacific Northwest Coast exhibits genetic continuity for at least the past 10,300 cal BP. We also infer that population structure existed in the late Pleistocene of North America with Shuka Kaa on a different ancestral line compared to other North American individuals (i.e., Anzick-1 and Kennewick Man) from the late Pleistocene or early Holocene. Despite regional shifts in mitochondrial DNA haplogroups we conclude from individuals sampled through time that people of the northern Northwest Coast belong to an early genetic lineage that may stem from a late Pleistocene coastal migration into the Americas.\n\nSignificance StatementThe peopling of the Americas has been examined on the continental level with the aid of single-nucleotide polymorphism arrays, next generation sequencing, and advancements in ancient DNA, all of which have helped elucidate major population movements. Regional paleogenomic studies, however, have received less attention and may reveal a more nuanced demographic history. Here we present genomewide sequences of individuals from the northern Northwest Coast covering a time span of ~10,000 years and show that continental patterns of demography do not necessarily apply on the regional level. In comparison with existing paleogenomic data, we demonstrate that geographically linked population samples from the Northwest Coast exhibit an early ancestral lineage and find that population structure existed among Native North American groups as early as the late Pleistocene.

genomics↗