Biology subjects

Carpenter, J.

Publications and source records attributed to Carpenter, J..

18 recordsLinked to original sources

bioRxiv2026

Parrots imitate song and dance with mixed vocal-gestural neural signals

Humans shrug when saying "I don't know" and nod when saying "yes," yet it remains unclear how the brain coordinates vocal and gestural motor systems for learned, multimodal communication. Here we find that budgerigar parrots precisely imitate the fine temporal alignment between song and affiliative headbob gestures. Distinct colonies developed unique vocal-gestural motifs, which reorganized into new shared forms following social re-pairing. Neural recordings from the central nucleus of the anterior arcopallium (AAC), the cortical output of the parrot song system, revealed intermixed representations of vocalizations and head kinematics, including mixed selectivity at the level of single neurons. These findings show that socially learned multimodal communication is implemented by the joint representation of vocal and gestural motor signals within single neurons, revealing neural mechanisms that may extend to frontal cortical regions controlling speech and gesture in humans.

neuroscience↗

bioRxiv2026

Degeneration-Inspired Architectural States Defined by Voronoi Point Spacing and Surface-Mediated Rescue of Osteogenic Dysfunction in 3D-Printed Scaffolds

Osteoporotic bone degeneration involves progressive deterioration of trabecular microarchitecture, yet most scaffold-based bone tissue engineering studies evaluate osteogenesis in structurally favorable architectures that poorly represent compromised bone environments. Here, we establish a degeneration-inspired Voronoi scaffold platform in which point spacing serves as a single tunable architectural parameter to model transitions from dense mechanically integrated to severely deteriorated trabecular-like microenvironments. Increasing point spacing from 1.25 to 2.5 mm progressively reduced scaffold connectivity and stiffness while shifting deformation behavior from distributed load transfer to localized stress concentration, as confirmed by finite element analysis and mechanical testing. Benchmarking against clinically reported HR-pQCT datasets from postmenopausal women demonstrated that the intermediate 1.75 mm point spacing scaffold represents a clinically relevant compromised trabecular-like state, whereas the 2.5 mm scaffold represents a more severely deteriorated architectural condition. These architecture-dependent mechanical and structural transitions directly regulated hMSC behavior, where high point spacing scaffolds reduced cytoskeletal organization, stress fiber density, and osteogenic mineralization, establishing an architecture-associated osteogenic dysfunction regime. Polydopamine (PDA) coating progressively enhanced cytoskeletal organization and mineralization within architecturally compromised scaffolds without altering scaffold geometry. To quantitatively assess biointerface-mediated functional recovery, a Mineralization Rescue Percentage (MRP) framework was introduced, demonstrating up to 43% restoration of architecture-associated mineralization loss following PDA coating. Collectively, this work establishes a clinically contextualized degeneration-to-rescue biomaterials framework that shifts current scaffold design paradigms beyond structurally favorable architectures toward systematic investigation and functional rescue of architecture-associated osteogenic dysfunction within compromised bone-like microenvironments. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/725650v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@15b1204org.highwire.dtl.DTLVardef@1fbdce6org.highwire.dtl.DTLVardef@638215org.highwire.dtl.DTLVardef@f1370d_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of SignificanceMost scaffold-based bone tissue engineering studies evaluate osteogenesis in structurally favorable architectures that poorly represent compromised bone microenvironments associated with osteoporosis. Here, a clinically contextualized Voronoi scaffold platform is established in which point spacing serves as a single tunable architectural parameter to model transitions from mechanically integrated to structurally deteriorated trabecular-like states. By decoupling architectural and surface biointerface effects, the study demonstrates that architectural deterioration alone can drive cytoskeletal disruption and osteogenic failure. Importantly, polydopamine-mediated surface engineering partially restored cytoskeletal organization and mineralization within architecturally compromised scaffolds without altering bulk geometry. A Mineralization Rescue Percentage (MRP) framework was further introduced to quantitatively assess biointerface-mediated functional recovery within degeneration-inspired scaffold microenvironments.

bioengineering↗

bioRxiv2026

Plasma-Enabled Multiscale Coupling of Architecture and Biointerfaces Drives Osteogenesis in 3D-Printed Gyroid Scaffolds

Engineering functional bone scaffolds can be enhanced by integrating biologically instructive nanoscale surface features (e.g., nanotopography and nanoroughness), micro-scale geometric cues (e.g., curvature and porosity), and macro-scale mechanical properties (e.g., bulk stiffness); however, these length scales are often optimized independently. Here, we present a multiscale design framework combining additive manufacturing of triply periodic minimal surface (TPMS) gyroid scaffolds with plasma-assisted nanoscale surface engineering to regulate osteogenesis. Controlled variation in strut thickness generates distinct architectural regimes with coupled changes in curvature, porosity, and compressive modulus, recapitulating key aspects of trabecular bone mechanics. Micro-computed tomography confirms trabecular bone-like features, while finite element modeling and compression testing reveal that thinner architectures (0.6 mm) exhibit curvature-preserving geometry and distributed stress profiles favorable for cellular interaction. A low-temperature plasma electroless reduction (PER) strategy enables controlled silver nanoparticle deposition, while polydopamine-mediated adhesion ensures uniform and cytocompatible coatings. Notably, PDA-AgNP-functionalized 0.6 mm scaffolds significantly outperform unmodified and AgNP-only groups, exhibiting enhanced cytoskeletal organization, stress fiber formation, matrix mineralization, and osteogenic gene expression. These findings demonstrate that coupling nanoscale biointerface features with micro- and macro-scale architecture produces a synergistic enhancement in osteogenesis, providing a design framework for functional bone scaffolds. Table of Content GraphicsA plasma-enabled strategy integrates 3D-printed scaffold architecture with nanoscale surface engineering to enhance bone formation. By combining tunable structural design with uniform nanoparticle coating, the study shows that optimal biological responses occur only when mechanical and surface cues act together, highlighting a synergistic multiscale approach for designing advanced biomaterials for bone regeneration. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/718992v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1d29685org.highwire.dtl.DTLVardef@983752org.highwire.dtl.DTLVardef@15816f5org.highwire.dtl.DTLVardef@4b4f50_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

Toroidal topology of grid-cell activity precedes spatial navigation during development

The medial entorhinal cortex (MEC) is a central component of the mammalian navigation system1-5, in which spatially and directionally tuned neurons, including grid cells and head-direction cells, encode an animals position and orientation6-8. These cells form internal maps with periodic topologies: head-direction cells traverse ring-like manifolds9,10, while grid cells are organized on toroidal manifolds11. The persistence of these topologies across behavioral states and environments11,12 raises the possibility that they arise intrinsically from network architecture rather than through sensory experience4,5,13-17. Consistent with this view, observations in juvenile rats have shown that rudimentary spatial tuning appears in place cells, head direction cells and grid cells almost as soon as pups begin to explore their surroundings at 2-3 weeks of age18-20. However, it remains unclear whether spatial experience is required for the initial emergence of positional tuning and for the organization of tuned cells into periodic maps. Here we show, using large-scale ensemble recordings in rat pups, that toroidal manifolds emerge in MEC subnetworks as early as postnatal day 10 (P10), preceding eye and ear opening, upright posture, quadrupedal gait, and active exploration21,22. These toroidal networks were modular from the beginning, with increasing differentiation of their dynamics appearing on P11-12. The onset of toroidal topology coincided with a transition in MEC network activity characterized by desynchronization and increased inhibitory connectivity, a developmental shift observed broadly across cortical regions at this age23,24. In contrast, ring-like manifolds were already detectable by P9, with traces of directional tuning appearing in individual cells at P8 -- consistent with an earlier maturation of subcortical circuitry25. As pups subsequently began to explore the environment around P15-16, these internally generated maps progressively aligned with external landmarks, culminating in stable, periodic firing fields by three weeks of age. Taken together, these findings identify ring-like and toroidal manifolds as instinctive computational motifs of the developing brain. Their early emergence, preceding major sensory input and navigation, supports the view that spatial representations are preconfigured and later anchored to the external world through experience-dependent plasticity.

neuroscience↗

bioRxiv2026

Distinct Chiral Nanostructures of Graphene Quantum Dots Govern Divergent Passive and Active Enantioselective Transport across Biological Membranes

Chirality in two-dimensional nanomaterials provides a powerful lever to control biological interfaces, yet the structural origins of nanoscale chirality remain poorly understood. Here, we systematically investigate chiral ligand modulated graphene quantum dots (GQDs) and reveal how ligand stereochemistry and edge chemistry modulate the formation of diverse chiral or achiral nanostructures. Spectroscopy, microscopy, and density functional theory with ring-puckering analysis identified six structural motifs, twisted-, twisted-boat, saddle-shaped, hybrid, unbuckled, and random. Among these, twisted-, twisted-boat, and saddle-shaped GQDs exhibited genuine nanoscale structural chirality, while unbuckled, hybrid, and random conformations lacked organized distortion. Importantly, structural chirality governed passive permeation into biological membrane (e.g. lipid membrane of extracellular vesicles), whereas achiral variants relied mainly on hydrophobic interactions. In contrast, active transport across biological membrane (e.g. endocytosis) is insensitive to nanoscale structural chirality but strongly influenced by chiral ligand identity and transporter recognition. Collectively, these results establish chiral ligand conjugation as a modular route to program both chiral and achiral motifs in graphene nanostructures and highlight nanoscale structural chirality as a design principle for engineering bio-nano interactions.

bioengineering↗

bioRxiv2025

Functional independence of entorhinal grid cell modules enables remapping in hippocampal place cells

A systems-level understanding of cortical computation requires insight into how neural codes are transformed across distinct brain circuits. In the mammalian cortex, one of the few systems where such transformations are tractable is the spatial mapping circuit. This circuit comprises interconnected regions of medial entorhinal cortex (MEC) and hippocampus, which encode location using fundamentally different neural codes. A key distinction is that neural activity in MEC, including that of directionally tuned cells and grid cells, evolves along low-dimensional manifolds, preserving stable phase relationships across different environments and behaviors1-8. In contrast, hippocampal place cells frequently undergo global remapping: their collective firing patterns reorganize randomly across different environments9-12, revealing an apparently limitless repertoire of orthogonal spatial representations12-14. The mechanisms by which spatial maps are transformed between the two coding schemes remain unresolved. Here, we used large-scale multi-area Neuropixels recordings to show that when rats were transferred from one familiar environment to another, each module of grid cells underwent a unique change in phase on its low-dimensional manifold, at the same time as simultaneously recorded place cells exhibited global remapping. In contrast, training conditions that produced smaller differences in the phase shifts of simultaneously recorded grid modules resulted in incomplete place cell remapping, mirroring previous reports of partial remapping15-19. Hippocampal remapping was not associated with rotational differences between grid modules under any condition. Taken together, these findings suggest that differential phase shifts across grid cell modules form the basis for the orthogonalization of downstream hippocampal spatial codes during remapping. The transformation from low-dimensional spatial representations in the MEC to high-dimensional codes in the hippocampus may underlie the hippocampus ability to support high-capacity memory storage3,13,14,20-22.

neuroscience↗

bioRxiv2025

Automated High-Content, High-Throughput Spatial Analysis Pipeline for Drug Screening in 3D Tumor Spheroid Inverted Colloidal Crystal Arrays

High-content, high-throughput (HCHT) screening platforms are essential for drug discovery, yet conventional 2D assays lack physiological relevance, and current 3D spheroid systems often face challenges to scalability, uniformity, and the analytical efficiency required for statistically robust screening. Here, we present a fully integrated 3D HCHT platform that synergizes tumor spheroid arrays generated from a bioinert inverted colloidal crystal (iCC) hydrogel frame-work with an automated, high-speed image analysis pipeline for rapid and spatially resolved therapeutic profiling. The iCC framework enables spontaneous self-assembly of highly-ordered tumor spheroid array at high spheroid density ([~]79.8 spheroids{middle dot}mm-2) with tight size uniformity (<10% standard deviation), supporting reproducible and high-content imaging ([~]40 spheroids{middle dot}image-1). The automated image-processing algorithm achieves robust region-of-interest segmentation, fluorescence-weighted centroiding, and multi-parametric spatial analysis in <5 seconds per image--markedly faster than conventional well-plate (5 min per 96 throughput) or single-spheroid analysis workflows methods ([~]1 sec per spheroid). Using this platform, we capture dose-dependent diffusion of doxorubicin, tumor penetration profile of small extracellular vesicles, and cell-type-specific infiltration behaviors of monocytes versus macrophages. Comparative viability profiling across chemotherapeutics further reveals distinct spatial toxicity signatures, highlighting the importance of spatial context in drug response assessment. Collectively, this platform enables rapid, reproducible, and spatially informative screening in 3D, offering a powerful tool for drug discovery, tumor modeling, and immunotherapeutic development.

cancer biology↗

bioRxiv2025

A 3D Modeling Framework for Quantifying Variation in Soybean Root Structure Architecture

Root system architecture (RSA) underpins plant access to water and nutrients, making its characterization critical for improving crop performance in environments with limited soil fertility. However, current methods for quantifying root features face several challenges. They may rely on 2D images that suffer from occlusion, use expensive sensing technologies like X-ray computed tomography, or depend on 3D modeling approaches with assumptions about branching that make them difficult to generalize. To address these challenges, we introduce an open-source Python framework for quantifying RSA samples from 3D point clouds generated from low-cost photogrammetry. Critically, this method incorporates no assumptions about taxon-specific branching orientation, making it both well-suited for modeling naturally grown annual dicots such as soybean and generalizable across species. Using field-grown soybean as a test case, we demonstrate the utility of this framework to extract biologically meaningful 3D features of divergent root systems sampled across developmental stages and soil environments, and enable new analyses not possible with 2D approaches, such as modeling metabolic scaling relationships. Results indicate that, in our soybean samples, while certain individual features like taproot tortuosity are potentially influenced by the soil environment, and while roots in sandy loam exhibited greater feature plasticity, fundamental scaling properties remain consistent. By combining low-cost photogrammetry with 3D reconstruction of root systems from point clouds, this approach provides the plant science community with new opportunities for more comprehensive root studies.

plant biology↗

bioRxiv2025

Divergence of root system traits in soybean between breeding and diversity lines

Roots are critical for supporting basic plant functions such as anchoring in various substrates, uptake of water and nutrients, and hosting symbiotic relationships. In crops, indirect changes to root system architecture (RSA) have occurred largely as a result of selection for yield or other related aboveground traits. In cultivated soybean (Glycine max), evidence of changes to RSA resulting from breeding for crop performance has been inconsistent, with some studies supporting an overall decrease in performance-related trait values, such as root length and density, and other work showing the opposite. The current study sets out to ask whether there is any systematic differentiation in RSA between a set of elite breeding lines (n=8) of soybean developed for the Midwest United States and a group of biogeographically diverse landraces from the USDA Soybean Germplasm Collection (n=16. Groups are compared across three distinct developmental stages (V2-V6, V7-R2, R3-R7) and two contrasting soil environments. In total, 432 root systems were phenotyped for 12 structural traits derived from 2D images along with root and shoot biomass. A new 3D root modeling approach leveraging photogrammetry-derived pointclouds is additionally tested on a subset of 30 contrasting root systems. Results indicate that the diversity lines had smaller root systems overall but greater phenotypic plasticity in response to soil environment as compared to breeding lines. Additionally, the study finds evidence for trade-offs between above-ground and below-ground trait plasticity. Core ideasO_LIPrevious work suggests crop root system architecture (RSA) has changed as a result of indirect selection C_LIO_LIThis study compares RSA in elite breeding lines with that of diverse landraces in cultivated soybean C_LIO_LIA total of 432 root systems are analyzed across 24 genotypes, two soil environments and three developmental stages C_LIO_LIFindings show diversity lines have smaller root systems but greater plasticity in response to soil environment C_LI

plant biology↗

bioRxiv2024

Evolution of vocal production learning in parrots

Vocal production learning (VPL), the capacity to imitate sounds, is a crucial, but not exclusive component of human language. VPL is rare in animals but common in birds, where it evolved independently in songbirds, hummingbirds, and parrots. Parrots (Psittaciformes) learn new vocalizations throughout their lives and exhibit astonishing vocal flexibility and imitation capacity. They can copy allospecific sounds, e.g., human words and learn their associated meanings. Parrots, therefore, present an intriguing model to shed light on how VPL evolved and how it may relate to other language-relevant traits. How widely VPL is distributed across Psittaciformes and to what extent (qualitative) species differences exist, remains unknown. Here, we provide the first comprehensive overview of the phylogenetic distribution of (allospecific) VPL in this clade by conducting surveys of publicly available video footage. Out of the 398 currently recognized extant species, we found videos for 163, of which 136 showed evidence of VPL. Phylogenetic analyses suggest secondary losses and reacquisitions of VPL covarying with socioecological parameters (gregariousness), life-history (longevity), and morphological (body size) traits. This study provides the first insights into interspecific variation in vocal learning across all parrot species and reveals potential socio-ecological drivers of its evolution. SignificanceLittle is known about the selective forces that favor the evolution of vocal production learning (VPL), a rare trait in animals and a prerequisite for the evolution of human language. We provide the first insights into interspecific variation in VPL in the evolutionary history of parrots and uncover candidate evolutionary drivers. The current data suggest that the evolution of VPL within parrots has been highly dynamic, with multiple secondary losses and reacquisitions. Our model showed that VPL most likely was the ancestral state. Sociality, longevity and body size explain variation in VPL together with a highly uncertain effect of brain size. The findings may motivate comparative work in other taxa and contribute to research into the evolutionary origins of human language.

evolutionary biology↗

bioRxiv2024

A Bioinert Hydrogel Framework for Precision 3D Cell Cultures: Advancing Automated High-Content and High-Throughput Drug Screening

Enhanced drug testing efficiency has driven the prominence of high-content (HC) and high-throughput (HT) screening (HCHTS) in drug discovery and development. However, traditional HCHTS in well-plates often lack complexity of in vivo conditions. 3D cell cultures, like cellular spheroids/organoids, offer a promising alternative by replicating in vivo conditions and improving the reliability of drug responses. Integrating spheroids/organoids into HCHTS requires strategies to ensure uniform formation, systemic function, and compatibility with analysis techniques. This study introduces an easy-to-fabricate, low-cost, safe, and scalable approach to create a bioinert hydrogel-based inverted colloidal crystal (BhiCC) framework for uniform and high-yield spheroid cultivation. Highly uniform alginate microgels were fabricated and assembled into a colloidal crystal template with controllable contact area, creating engineered void spaces and interconnecting channels within agarose-based BhiCC through the template degradation by alginate lyase and buffer. This results in a multi-layered iCC domain, enabling the generation of in-vitro 3D culture models with over 1,000 spheroids per well in a 96-well plate. The unique hexagonal-close-packed (HCP) geometry of iCC structure enables HCHTS through conventional plate reader analysis and fluorescent microscopy assisted by house-developed automated data processing algorithm. This advancement offers promising applications in tissue engineering, disease modeling, and drug development in biomedical research.

bioengineering↗

bioRxiv2023

Mucus polymer concentration and in vivo adaptation converge to define the antibiotic response of Pseudomonas aeruginosa during chronic lung infection

The airway milieu of individuals with muco-obstructive airway diseases (MADs) is defined by the accumulation of dehydrated mucus due to hyperabsorption of airway surface liquid and defective mucociliary clearance. Pathological mucus becomes progressively more viscous with age and disease severity due to the concentration and overproduction of mucin and accumulation of host-derived extracellular DNA (eDNA). Respiratory mucus of MADs provides a niche for recurrent and persistent colonization by respiratory pathogens, including Pseudomonas aeruginosa, which is responsible for the majority of morbidity and mortality in MADs. Despite high concentration inhaled antibiotic therapies and the absence of antibiotic resistance, antipseudomonal treatment failure in MADs remains a significant clinical challenge. Understanding the drivers of antibiotic recalcitrance is essential for developing more effective treatments that eradicate persistent infections. The complex and dynamic environment of diseased airways makes it difficult to model antibiotic efficacy in vitro. We aimed to understand how mucin and eDNA concentrations, the two dominant polymers in respiratory mucus, alter the antibiotic tolerance of P. aeruginosa. Our results demonstrate that polymer concentration and molecular weight affect P. aeruginosa survival post antibiotic challenge. Polymer-driven antibiotic tolerance was not explicitly associated with reduced antibiotic diffusion. Lastly, we established a robust and standardized in vitro model for recapitulating the ex vivo antibiotic tolerance of P. aeruginosa observed in expectorated sputum across age, underlying MAD etiology, and disease severity, which revealed the inherent variability in intrinsic antibiotic tolerance of host-evolved P. aeruginosa populations. ImportanceAntibiotic treatment failure in Pseudomonas aeruginosa chronic lung infections is associated with increased morbidity and mortality, illustrating the clinical challenge of bacterial infection control. Understanding the underlying infection environment, as well as the host and bacterial factors driving antibiotic tolerance and the ability to accurately recapitulate these factors in vitro, is crucial for improving antibiotic treatment outcomes. Here, we demonstrate that increasing concentration and molecular weight of mucin and host eDNA drive increased antibiotic tolerance to tobramycin. Through systematic testing and modeling, we identified a biologically relevant in vitro condition that recapitulates antibiotic tolerance observed in ex vivo treated sputum. Ultimately, this study revealed a dominant effect of in vivo evolved bacterial populations in defining inter-subject ex vivo antibiotic tolerance and establishes a robust and translatable in vitro model for therapeutic development.

microbiology↗

bioRxiv2023

High throughput screening of mesenchymal stromal cell morphological response to inflammatory signals for bioreactor-based manufacturing of extracellular vesicles that modulate microglia

Due to their immunomodulatory function, mesenchymal stromal cells (MSCs) are a promising therapeutic with the potential to treat neuroinflammation associated with neurodegenerative diseases. This function can be mediated by secreted extracellular vesicles (MSC-EVs). Despite established safety, MSC clinical translation has been unsuccessful due to inconsistent clinical outcomes resulting from functional heterogeneity. Current approaches to mitigate functional heterogeneity include priming MSCs with inflammatory signals to enhance function. However, comprehensive evaluation of priming and its effects on MSC-EV function has not been performed. Clinical translation of MSC-EV therapies requires significant manufacturing scale-up, yet few studies have investigated the effects of priming in bioreactors. As MSC morphology has been shown to predict their immunomodulatory function, we screened MSC morphological response to an array of priming signals and evaluated MSC-EV identity and potency in response to priming in flasks and bioreactors. We identified unique priming conditions corresponding to distinct morphologies. These conditions demonstrated a range of MSC-EV preparation quality and lipidome, allowing us to discover a novel MSC-EV manufacturing condition, as well as gain insight into potential mechanisms of MSC-EV microglia modulation. Our novel screening approach and application of priming to MSC-EV bioreactor manufacturing informs refinement of larger-scale manufacturing and enhancement of MSC-EV function. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/567730v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1fca79forg.highwire.dtl.DTLVardef@60f543org.highwire.dtl.DTLVardef@186394borg.highwire.dtl.DTLVardef@11b94bd_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMSCs morphologically respond to inflammatory priming conditions. C_LIO_LIPriming hits identified from morphological screen increase MSC-EV production. C_LIO_LIPriming MSCs in bioreactors enhances MSC-EV modulation of microglia. C_LIO_LIChanges in MSC-EV production and potency reflected by lipid content. C_LIO_LIFirst demonstration of effects of priming on MSC production of EVs in a bioreactor. C_LI

bioengineering↗

bioRxiv2023

Investigating egocentric tuning in hippocampal CA1 neurons using simulated data

Navigation requires integrating sensory information with a stable schema to create a dynamic map of an animals position using egocentric and allocentric coordinate systems. In the hippocampus, place cells encode allocentric space, but their firing rates may also exhibit directional tuning within egocentric or allocentric reference frames. We compared experimental and simulated data to assess the prevalence of tuning to egocentric bearing (EB) among hippocampal cells in rats foraging in an open field. Using established procedures, we confirmed egocentric modulation of place cell activity in recorded data; however, simulated data revealed a high false positive rate. When we accounted for false positives by comparing with shuffled data that retain correlations between the animals direction and position, only a very low number of hippocampal neurons appeared modulated by EB. Our study highlights biases affecting false positive rates and provides insights into the challenges of identifying egocentric modulation in hippocampal neurons.

neuroscience↗

bioRxiv2023

An anterior forebrain pathway in parrots is necessary for individual signatures of learned vocalizations

Parrots have enormous vocal imitation capacities and produce individually unique vocal signatures. Like songbirds, parrots have a nucleated neural song system with distinct anterior (AFP) and posterior forebrain pathways (PFP). To test if song systems of parrots and songbirds, which diverged over 50 million years ago, have a similar functional organization, we first established a neuroscience-compatible call-and-response behavioral paradigm to elicit learned contact calls in budgerigars (Melopsittacus undulatus). Using variational autoencoder-based machine learning methods, we show that contact calls within affiliated groups converge but that individuals maintain unique acoustic features, or vocal signatures, even after call convergence. Next, we transiently inactivated the outputs of AFP to test if learned vocalizations can be produced by the PFP alone. As in songbirds, AFP inactivation had an immediate effect on vocalizations, consistent with a premotor role. But in contrast to songbirds, where the isolated PFP is sufficient to produce stereotyped and acoustically normal vocalizations, isolation of the budgerigar PFP caused a degradation of call acoustic structure, stereotypy, and individual uniqueness. Thus the contribution of AFP and the capacity of isolated PFP to produce learned vocalizations have diverged substantially between songbirds and parrots, likely driven by their distinct behavioral ecology and neural connectivity.

neuroscience↗

bioRxiv2020

Functional immune mapping with deep-learning enabled phenomics applied to immunomodulatory and COVID-19 drug discovery

Development of accurate disease models and discovery of immune-modulating drugs is challenged by the immune systems highly interconnected and context-dependent nature. Here we apply deep-learning-driven analysis of cellular morphology to develop a scalable "phenomics" platform and demonstrate its ability to identify dose-dependent, high-dimensional relationships among and between immunomodulators, toxins, pathogens, genetic perturbations, and small and large molecules at scale. High-throughput screening on this platform demonstrates rapid identification and triage of hits for TGF-{beta}- and TNF--driven phenotypes. We deploy the platform to develop phenotypic models of active SARS-CoV-2 infection and of COVID-19-associated cytokine storm, surfacing compounds with demonstrated clinical benefit and identifying several new candidates for drug repurposing. The presented library of images, deep learning features, and compound screening data from immune profiling and COVID-19 screens serves as a deep resource for immune biology and cellular-model drug discovery with immediate impact on the COVID-19 pandemic.

immunology↗

bioRxiv2019

Local adaptation drives the diversification of effectors in the fungal wheat pathogen Parastagonospora nodorum in the United States

Filamentous fungi rapidly evolve in response to environmental selection pressures, exemplified by their genomic plasticity. Parastagonospora nodorum, a fungal pathogen of wheat and causal agent of septoria nodorum blotch, responds to selection pressure exerted by its host, influencing the gain, loss, or functional diversification of putative effector genes. Whole genome resequencing of 197 P. nodorum isolates collected from spring, durum, and winter wheat production regions of the United States enabled the examination of effector diversity and genomic regions under selection specific to geographically discrete populations. A total of 1,026,859 quality SNPs/InDels were identified within the natural population. Implementation of GWAS identified novel loci, as well as SnToxA and SnTox3 as major factors in disease. Genes displaying presence/absence variation and predicted effector genes, as well as genes localized on an accessory chromosome, had significantly higher pN/pS ratios, indicating a greater level of diversifying selection. Population structure analyses indicated two major P. nodorum populations corresponding to the Upper Midwest (Population 1) and Southern/Eastern United States (Population 2). Prevalence of SnToxA varied greatly between the two populations which correlated with presence of the host sensitivity gene Tsn1. Additionally, 12 and 5 candidate effector genes were observed to be diversifying among isolates from Population 1 and Population 2, respectively, but under purifying or neutral selection in the opposite population. Selective sweep analysis revealed 10 and 19 regions of positive selection from Population 1 and Population 2, respectively, with 92 genes underlying population-specific selective sweeps. Also, genes exhibiting presence/absence variation were significantly closer to transposable elements. Taken together, these results indicate that P. nodorum is rapidly adapting to distinct selection pressures unique to spring and winter wheat production regions by various routes of genomic diversification, potentially facilitated through transposable element activity.\n\nAuthor SummaryParastagonospora nodorum is an economically important pathogen of wheat, employing proteinaceous effector molecules to cause disease. Recognition of effectors by host susceptibility genes often leads to the elicitation of programmed cell death. However, little is known on the correlation between effector diversity and the spatial distribution of host resistance/susceptibility or the genomic mechanisms of diversification. This research presents the genome resequencing of 197 P. nodorum isolates collected from spring, winter, and durum wheat production regions of the United States, enabling the investigation of genome dynamics and evolution. Results illustrate local adaptation to host resistance or susceptibility, as evidenced by population-specific evolution of predicted effector genes and positively selected selective sweeps. Predicted effector genes, genes exhibiting presence/absence variation, and genes residing on an accessory chromosome, were found to be diversifying more rapidly. Additionally, transposable elements were predicted to play a role in the maintenance or elimination of genes. A GWAS approach identified the previously reported SnToxA and SnTox3 as well as novel virulence candidates, as major elicitors of disease on winter wheat. These results highlight the flexibility of the P. nodorum genome in response to population-specific selection pressures and illustrates the utility of whole genome resequencing for the identification of putative virulence mechanisms.

evolutionary biology↗

bioRxiv2018

Domain-general enhancements of metacognitive ability through adaptive training

The metacognitive ability to introspect about self-performance varies substantially across individuals. Given that effective monitoring of performance is deemed important for effective behavioural control, intervening to improve metacognition may have widespread benefits, for example in educational and clinical settings. However, it is unknown whether and how metacognition can be systematically improved through training independently of task performance, or whether metacognitive improvements generalize across different task domains. Across 8 sessions, here we provided feedback to two groups of participants in a perceptual discrimination task: an experimental group (N = 29) received feedback on their metacognitive judgments, while an active control group (N = 32) received feedback on their decision performance only. Relative to the control group, adaptive training led to increases in metacognitive calibration (as assessed by Brier scores) which generalized both to untrained stimuli and an untrained task (recognition memory). Leveraging signal detection modeling we found that metacognitive improvements were driven both by changes in metacognitive efficiency (meta-d/d) and confidence level, and that later increases in metacognitive efficiency were positively mediated by earlier shifts in confidence. Our results reveal a striking malleability of introspection and indicate the potential for a domain-general enhancement of metacognitive abilities.

animal behavior and cognition↗