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Larsen, B.

Publications and source records attributed to Larsen, B..

At least 19 recordsLinked to original sources

Task-evoked flexibility of intrinsic neural timescales is hierarchically organized, behaviorally relevant, and refined across two developmental stages

Cortical regions integrate temporal information over different timescales at rest, ranging from fast in sensorimotor regions to slow in the association cortex. Here, we study how far regions adapt these timescales to meet task demands, as well as how this \emph{timescale flexibility} is organized across the cortical hierarchy, and how it develops in humans. We quantified rest-to-task changes in intrinsic neural timescales, referred to as \emph{timescale deflections}, using fMRI data from four independent datasets totaling 1,712 participants aged 8--64 years. We found that timescales reduced under cognitive load in all four datasets, most strongly in association cortex, which partially flattened the resting-state timescale hierarchy. Individual differences in timescale deflections were organized along the sensorimotor-association (S-A) axis and tracked cognitive performance, both in adults and in youth. Next, in youth, deflections followed a two-stage developmental course: a generalized reduction throughout childhood, followed by a selective expansion in association cortex from mid-adolescence. Furthermore, the timing of these stages aligned with cortical gradients of inhibitory gene expression and intracortical myelin content, both features implicated in the opening and closing of critical periods of neural plasticity. Overall, our results demonstrate that task-evoked timescale flexibility is hierarchically organized, behaviorally and neurobiologically relevant, and refined across adolescence.

neuroscience↗

An Open Test--Retest Dataset of Rapid Myelin Mapping Acquisitions

Myelin supports rapid and efficient neural communication and is implicated in brain development, learning, aging, and neurological disease. Although numerous magnetic resonance imaging (MRI) approaches have been proposed to characterize myelin in vivo, they have rarely been evaluated together within the same participants and across repeated acquisitions. To address these gaps, we introduce the Myelin Imaging Reliability and ReprOducibility Resource (MIRROR), an openly available multimodal test--retest MRI dataset of diffusion MRI (dMRI), inhomogeneous magnetization transfer imaging (ihMT), quantitative susceptibility mapping (QSM), MP2RAGE, T1w/T2w ratio mapping, and transverse relaxometry in 22 healthy adults. We evaluated gray--white matter differentiation, intermetric correspondence, test--retest reliability, and participant specificity across 27 myelin-sensitive metrics. Gray--white matter differentiation was strong for dMRI derivatives, MP2RAGE-derived R1, T1w/T2w, and ihMT, while being substantially weaker for QSM measures. Intermetric spatial correlations were generally strongest within acquisition or modeling families. Test--retest reliability was generally high, particularly for dMRI-derived metrics, but was more variable among QSM-, ihMT-, and R2*-derived measures. Regional spatial profiles were also highly participant-specific, with discriminability approaching its upper bound for most metrics. All imaging data, derived maps, and processing code are openly released. MIRROR provides a benchmark for characterizing the measurement properties and practical tradeoffs of scalable myelin-sensitive MRI methods, supporting principled acquisition selection and accelerating methodological development and validation.

neuroscience↗

Computational design of potent, broadly neutralizing anti-Nipah virus and Hendra virus miniproteins

The prototype members of the genus Henipavirus, Nipah virus (NiV) and Hendra virus (HeV), cause recurrent zoonotic spillovers with case fatality rates ranging from 40-90% in humans. Currently, there are no approved vaccines or therapeutics for use in humans. Neutralizing antibodies targeting the NiV/HeV F- or G-glycoproteins protect animals from lethal challenge and are a main correlate of protection. However, antibody-based formulations are expensive, typically requiring hospital admission for administration and cold-chain for storage and transportation. To address the lack of shelf-stable clinical countermeasures, we computationally designed thermostable miniproteins that cross-react with subnanomolar affinities with both NiV and HeV F and G glycoproteins and inhibit viral entry in vitro with potencies comparable to lead antibodies. Oligomerized forms of these miniproteins have enhanced potency relative to their monomeric building blocks and increase the barrier for emergence of escape mutants, establishing them as promising preclinical candidates against these deadly viruses.

bioengineering↗

A Scalable fMRI Estimate of Basal Ganglia Brain Tissue Iron for Use in Developmental and Translational Neuroscience

Dopaminergic (DA) function and basal ganglia neurobiology are central to reward learning, motivation, and cognitive control, and dysregulation of these systems contributes to neuropsychiatric conditions that emerge during development. Adolescence is marked by profound reorganization of DAergic basal ganglia circuitry, yet direct in vivo assessment of the DA system remains limited in youth. Brain tissue iron is a developmentally sensitive marker of DA-related neurobiology that can be measured non-invasively via magnetic resonance imaging (MRI). Iron is an essential co-factor for DA synthesis and a foundational metabolic resource that supports cellular metabolism, myelination, and energetic demands of the basal ganglia. T2*-weighted echo-planar imaging (EPI), collected during functional MRI (fMRI), is sensitive to magnetic susceptibility of non-heme brain iron. Leveraging this property, we demonstrate the validity and broad applicability of an iron-sensitive metric that can be derived from conventional single-echo fMRI: {Delta}R2*. In a longitudinal developmental dataset (N = 151; age range 12-31), {Delta}R2* showed high reliability, strong longitudinal stability, and validity via robust convergence with established quantitative relaxometry-based iron measures (R2* and R2). Critically, {Delta}R2* can be retrospectively estimated from extant fMRI data and derived in large-scale consortium data repositories, demonstrated here in the Adolescent Brain and Cognitive Development (ABCD) baseline cohort (N = 8,366; ages 9-11). We show that {Delta}R2* captures known age-related increases in basal ganglia iron, highlighting neurodevelopmental sensitivity at population-scale. Together, these findings establish {Delta}R2* as a reliable, widely accessible marker of basal ganglia iron, enabling scalable investigation of lifespan trajectories and neuropsychiatric risk in existing and future datasets.

neuroscience↗

Menarche onset is an inflection point for mental health and brain development

Menarche is a normative milestone of female puberty, yet its role in adolescent mental health and brain development remains poorly understood. Using longitudinal data from 5,016 females (7 annual visits, ages 10-16 years) in the Adolescent Brain Cognitive Development Study, we found that menarche onset functions as an inflection point for the development of internalizing symptoms and gross brain morphometry. The onset of menarche, largely independent of timing and socio-environmental factors, preceded a significant spike in internalizing symptoms, while altering the rate of ongoing structural brain development. Following menarche onset, individuals with faster declines in gray matter volume and surface area also had heightened internalizing symptoms. These findings suggest that menarche is not only a reproductive milestone but a neuroendocrine driver of adolescent brain and mental health trajectories. This normative and easily identifiable marker could define a critical window for mental health screenings with greater precision than current age-based guidelines.

neuroscience↗

Hierarchical Community Structure of the Adult Drosophila Connectome Reveals Conserved Circuit Archetypes

The community structure of connectomes supports functional specialization, adaptability, and cost-efficient wiring. However, little is known about communities in connectomes mapped at the level of individual neurons and synapses. Here, we analyze a whole-brain Drosophila adult connectome using a nested stochastic blockmodel to uncover its hierarchical community structure. Most of the roughly 1500 fine-scale communities-the smallest, and best resolved level of the hierarchy- are spatially compact, mostly assortative, and aligned with biological features. Nonetheless, we find evidence of nonassortative communities, spatially co-localized within the optic lobe and vision-processing pathways. Seeking "functional primitives"-small circuits with functionally narrow feature profiles-we use data-driven clustering to group communities into 45 archetypical meta-clusters based on their spatial, functional, and molecular properties, revealing modular building blocks from which larger, functionally diverse communities are composed. This work advances our understanding of how structure and function are organized in the fruit fly brain and highlights the value of statistical network models in interpreting nanoscale connectomes.

neuroscience↗

Dynamic Stiffening to Improve Vasculogenesis of hiPSC-Derived Endothelial Progenitors

Multiple groups have reported on the impact of hydrogel stiffness on vascular network formation in vitro, with overall findings indicating that less stiff hydrogels better support vasculogenesis. However, the majority of this research utilized hydrogels with static stiffness, even though vasculogenesis occurs in tandem with changes in extracellular matrix material properties. To that end, we hypothesize that dynamic modulation of hydrogel stiffness during the process of vasculogenesis, recapitulating changes observed during embryonic development, would improve vascular network formation. Using our Collagen I/Norbornene-modified hyaluronic acid hydrogel system, we swelled in additional crosslinker and photoinitiator and exposed the hydrogel to UV light, enabling hydrogel stiffening at user-defined time points with no significant effect on cell viability. We observed that in situ stiffening at early time points, prior to the onset of significant cell migration, resulted in more robust vascular network formation relative to unstiffened controls, while stiffening at later time points disrupted existing vascular networks. These trends continued in in vivo experiments in nude mice, with cell-laden hydrogels stiffened at early time points resulting in improved blood flow, while those stiffened at later time points had the opposite effect. We hypothesized that this was due to differential impacts of focal adhesion kinase (FAK) activation following in situ stiffening, as supplementation with a Rho kinase inhibitor, downstream of FAK, partially reversed the effects of in situ stiffening. Taken together, this research demonstrates the benefits of incorporating dynamic cues into hydrogel design to create more physiologically relevant vasculature.

bioengineering↗

Expanding the Global Map of Protein Post Translational Modifications with Immunoaffinity Enrichment and nDIA Analysis on the Orbitrap Astral Mass Spectrometer

Post-translational modifications (PTMs) contribute greatly to the diversity of the human proteome by affecting protein structure, function, interactions, stability, localization, and more. The study of PTMs is essential to understand various cellular functions, disease mechanisms, and aid in the development of biomarkers and design of therapeutic targets. Owing to their diversity, dynamic nature, and low stoichiometry compared to unmodified proteome counterparts, the analysis of PTMs remains challenging. In this study, immunoaffinity enrichment of PTM peptides was combined with analysis using Data Dependent Acquisition (DDA) and narrow window Data Independent Acquisition (nDIA) on the Orbitrap Astral mass spectrometer (MS) as well as comparative analysis using the Orbitrap Fusion Lumos MS for Ubiquitination, Phosphorylation, Acetylation, Succinylation, and Methylation. Human cell line and mouse tissue samples at various input peptide amounts were immuno-enriched and mass spectrometry data was acquired on both instruments to assess depth of coverage and number of novel sites identified. The study identified a total of 88,731 unique ubiquitin sites, 64,397 phosphorylation sites (43,721 phosphoserine, 8,414 phosphothreonine and 12,262 phosphotyrosine), 11,629 acetylation, 5,272 succinylation and 1,461 mono-methylation sites. In half the acquisition time, nDIA analysis of immuno-enriched samples on Orbitrap Astral MS provided much greater depth of coverage for all PTMs compared to DDA analysis on Orbitrap Fusion Lumos MS, with up to 33-fold more PTM peptides identified and quantified. Overall, the data presented in this study demonstrates the need for enrichment for PTM detection and the utility of combining antibody-based peptide capture and nDIA on the Orbitrap Astral MS as powerful tools for discovery and profiling of protein post-translational modifications in cells and tissues.

biochemistry↗

Donor Age Impairs Vasculogenic Potential of hiPSC-Derived Endothelial Progenitors

BackgroundHuman induced pluripotent stem cells (hiPSCs) hold promise for vascular regeneration, but preliminary research often relies on neonatal donors, whereas clinical applications will use cells derived from older adults. Although the impact of donor age on reprogramming efficiency has been studied, its effect on the functionality of hiPSC-derived endothelial progenitors (hiPSC-EPs) remains unclear. This question is the focus of the current study. Methods and ResultsWe derived EPs from iPSCs sourced from three neonatal donors (ND) and three mature donors (MD) matched 1:1 for sex and somatic cell origin. We assessed their functional, epigenetic, and transcriptomic characteristics. Despite higher CD34 yields from MD-iPSCs, MD-hiPSC-EPs formed poorly interconnected and non-lumenized vascular structures in 3D hydrogels, compared to neonatal donor (ND) lines. In 2D culture, MD-hiPSC-EPs exhibited reduced cell density and aberrant VE-Cadherin localization. DNA methylation analysis revealed that somatic cell origin was the dominant driver of variance, but consistent differences in methylation of mesoderm commitment, angiogenesis, ECM remodeling, and cytoskeleton-related genes were observed between age groups. Epigenetic age prediction showed MD-hiPSC-EPs had more developmentally advanced signatures, potentially explaining their shift away from vasculogenic competence. Our RNA-sequencing findings confirm trends seen in the DNA methylation data and show differential expression of pathways linked to mitochondrial regulation and nitric oxide signaling. ConclusionsDonor age significantly alters the vasculogenic function of hiPSC-EPs. These findings underscore the necessity of donor-specific considerations in hiPSC-based vascular engineering and highlight potential barriers to translating hiPSC-derived therapeutics into older patient populations.

bioengineering↗

Inferring macroscopic intrinsic neural timescales using optimal control theory

The temporal evolution of brain activity relies on complex interactions within and between brain regions that are mediated by neurobiology and connectivity. To understand these interactions, many large-scale efforts have measured structural connectivity, neural activity, gene expression, and cognition across multiple modalities and species. However, data-driven discovery of large-scale activity models remains difficult owing to the lack of flexible quantitative frameworks for estimating the interplay between brain structure and function while preserving biophysical realism. Here, we provide such a framework by integrating network control theory (NCT) with automatic differentiation to estimate model parameters with greater biophysical realism from data. Specifically, we estimate the structural form of regional self-inhibition--a quantity that is experimentally difficult to measure--from MRI data. Next, we demonstrate that the resulting model-based self-inhibition parameters correlate significantly with regions intrinsic neural timescales (INTs), neurobiological measures of gene expression and cell-type densities, as well as behavioral measures of cognition. We demonstrate consistent results across multiple datasets and species. Finally, we demonstrate that our self-inhibition parameters enable the efficient control of brain dynamics from fewer brain regions. Taken together, our results provide a simple and flexible quantitative framework that more accurately captures the interplay between brain structure, function, and dynamics with greater biophysical realism.

neuroscience↗

Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks

Biophysical modeling provides mechanistic insights into brain function, spanning single-neuron dynamics to large-scale circuit models. These models are governed by biologically meaningful parameters, many of which can be experimentally measured. Some parameters are unknown, and optimizing them improves fit to experimental data, enhancing biological plausibility. However, existing methods require repeated, computationally expensive numerical integration of differential equations, limiting scalability to population-level datasets. Here, we introduce DELSSOME (DEep Learning for Surrogate Statistics Optimization in MEan field modeling), a framework that bypasses numerical integration by directly predicting whether parameter sets produce realistic brain dynamics. Across three large-scale circuit models, DELSSOME achieves a 1500-8000x speedup over numerical integration in predicting model realism. When embedded within an evolutionary optimization strategy, DELSSOME enables 50-100x faster parameter estimation without sacrificing agreement with numerical integration. Because of computational constraints, most studies simulate large-scale circuit models only at the group level. DELSSOME enables efficient individual-level optimization of the feedback inhibition control model. By collating 12,005 individuals across 14 datasets, we derive - for the first time - normative trajectories of cortical E/I ratio across the lifespan, revealing new insights into sex differences and network-specific patterns. This acceleration enables population-scale mechanistic modeling and unlocks new opportunities for understanding brain function.

neuroscience↗

Two Axes of White Matter Development

Despite decades of neuroimaging research, how white matter develops along the length of major tracts in humans remains unknown. Here, we identify fundamental patterns of white matter maturation by examining developmental variation along major, long-range cortico-cortical tracts in youth ages 5-23 years using diffusion MRI from three large-scale, cross-sectional datasets (total N = 2,716). Across datasets, we delineate two replicable axes of human white matter development. First, we find a deep-to-superficial axis, in which superficial tract regions near the cortical surface exhibit greater age-related change than deep tract regions. Second, we demonstrate that the development of superficial tract regions aligns with the cortical hierarchy defined by the sensorimotor-association axis, with tract ends adjacent to sensorimotor cortices maturing earlier than those adjacent to association cortices. These results reveal developmental variation along tracts that conventional tract-average analyses have previously obscured, challenging the implicit assumption that white matter tracts mature uniformly along their length. Such developmental variation along tracts may have functional implications, including mitigating ephaptic coupling in densely packed deep tract regions and tuning neural synchrony through hierarchical development in superficial tract regions - ultimately refining neural transmission in youth.

neuroscience↗

Differentiation Protocol-Dependent Variability in hiPSC-Derived Endothelial Progenitor Functionality

PurposeWith multiple groups generating methods for differentiating induced pluripotent stem cells (hiPSCs) into endothelial cells/endothelial progenitors (ECs/EPs), there is a need to better understand the specific endothelial subtypes that different differentiation protocols produce. This is especially important for accurate tissue modeling as researchers continue to incorporate the endothelium into engineered tissues. MethodsWe illustrated the heterogeneity of cells produced from different differentiation protocols by focusing on two selected protocols, one driving differentiation exclusively using small molecules (SM Protocol) and one driving differentiation primarily using growth factors (GF Protocol). We characterized the cells through a combination of vasculogenic computational analysis following encapsulation in 3D hydrogels, RNA sequencing, and measurement of soluble factor release. ResultsVasculogenic computational analysis indicates that cells from the GF protocol formed more dense and interconnected vasculature compared to cells from the SM protocol. Likewise, RNA-seq analysis showed GF-derived cell enrichment in pathways involved in cell migration and angiogenesis. In addition, GF-derived cells favor differentiation to arterial endothelial cells as well as predisposition to undergoing a partial endothelial-to-mesenchymal transition, whereas SM-derived cells resemble immature progenitors based on higher proliferation rates as well as ECM remodeling. These trends also persisted following extended 3D culture. ConclusionsThe results demonstrate that despite using the same starting hiPSC population and isolating EPs using the same surface marker, the two differentiation protocols yield highly distinct cell populations. This work highlights the importance of understanding the specific endothelial subtypes produced by different differentiation protocols for the creation of more accurate tissue models. Lay SummaryAlthough multiple groups have created protocols for differentiating human induced pluripotent stem cells (hiPSCs) to endothelial progenitors (EPs), it is not clear if different differentiation protocols generate different endothelial subtypes, matching the variance seen in vivo To that end, we performed an in-depth characterization of two selected hiPSC-EP differentiation protocols, primarily focusing on cells cultured in 3D hydrogels, to better understand the specific endothelial subtypes produced. We found significant differences in both cell maturity and cell phenotype that persisted even after extended culture. Future WorkFuture work will involve extending the existing study to include additional hiPSC-EP differentiation protocols as well as conducting single-cell RNAseq to better understand the makeup of different cell populations both before and after isolating CD34+ cells. Because smooth muscle cells play an important role in vessel stabilization, we will also incorporate hiPSC-derived smooth muscle cells into the system.

bioengineering↗

Reproducible Sex Differences in Personalized Functional Network Topography in Youth

BackgroundA key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex. AimsWe aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks. MethodWe leveraged person-specific atlases of functional brain networks defined using non-negative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout ("topography") of personalized functional networks (PFNs). Next, we trained support vector machines to classify participants sex from multivariate patterns of PFN topography. Finally, we leveraged transcriptomic data from the Allen Human Brain Atlas to evaluate spatial correlations between sex differences in PFN topography and gene expression. ResultsSex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants PFNs were able to classify participant sex with high accuracy. Brain regions with the greatest sex differences in PFN topography were enriched in expression of X-linked genes as well as genes expressed in astrocytes and excitatory neurons. ConclusionsSex differences in PFN topography are robust, replicate across large-scale samples of youth, and are associated with expression patterns of X-linked genes. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence.

neuroscience↗

A sensorimotor-association axis of thalamocortical connection development

Human cortical development follows a sensorimotor-to-association sequence during childhood and adolescence1-6. The brains capacity to enact this sequence over decades indicates that it relies on intrinsic mechanisms to regulate inter-regional differences in the timing of cortical maturation, yet regulators of human developmental chronology are not well understood. Given evidence from animal models that thalamic axons modulate windows of cortical plasticity7-12, here we evaluate the overarching hypothesis that structural connections between the thalamus and cortex help to coordinate cortical maturational heterochronicity during youth. We first introduce, cortically annotate, and anatomically validate a new atlas of human thalamocortical connections using diffusion tractography. By applying this atlas to three independent youth datasets (ages 8-23 years; total N = 2,676), we reproducibly demonstrate that thalamocortical connections develop along a maturational gradient that aligns with the cortexs sensorimotor-association axis. Associative cortical regions with thalamic connections that take longest to mature exhibit protracted expression of neurochemical, structural, and functional markers indicative of higher circuit plasticity as well as heightened environmental sensitivity. This work highlights a central role for the thalamus in the orchestration of hierarchically organized and environmentally sensitive windows of cortical developmental malleability.

neuroscience↗

Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study

Heritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (>50%).

genomics↗

Multi-echo Acquisition and Thermal Denoising Advances Infant Precision Functional Imaging

The characterization of individual functional brain organization with Precision Functional Mapping has provided important insights in recent years in adults. However, little is known about the ontogeny of inter-individual differences in brain functional organization during human development. Precise characterization of systems organization during periods of high plasticity is likely to be essential for discoveries promoting lifelong health. Obtaining precision fMRI data during development has unique challenges that highlight the importance of establishing new methods to improve data acquisition, processing, and analysis. Here, we investigate two methods that can facilitate attaining this goal: multi-echo (ME) data acquisition and thermal noise removal with Noise Reduction with Distribution Corrected (NORDIC) principal component analysis. We applied these methods to precision fMRI data from adults, children, and newborn infants. In adults, both ME acquisitions and NORDIC increased temporal signal to noise ratio (tSNR) as well as the split-half reliability of functional connectivity matrices, with the combination helping more than either technique alone. The benefits of NORDIC denoising replicated in both our developmental samples. ME acquisitions revealed longer and more variable T2* relaxation times across the brain in infants relative to older children and adults, leading to major differences in the echo weighting for optimally combining ME data. This result suggests ME acquisitions may be a promising tool for optimizing developmental fMRI, albeit application in infants needs further investigation. The present work showcases methodological advances that improve Precision Functional Mapping in adults and developmental populations and, at the same time, highlights the need for further improvements in infant specific fMRI.

neuroscience↗

Functional Connectivity Development along the Sensorimotor-Association Axis Enhances the Cortical Hierarchy

Human cortical maturation has been posited to be organized along the sensorimotor-association (S-A) axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the S-A axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3,355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1,207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1,126). In each dataset, the development of functional connectivity systematically varied along the S-A axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These robust and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

neuroscience↗