Biology subjects

Young, A. J.

Publications and source records attributed to Young, A. J..

9 recordsLinked to original sources

bioRxiv2026

AMP: An Automated Marker Based Motion Capture Processing Pipeline for Kinematic Trajectory Label Scrubbing and Gaps Filling

Marker-based optical motion capture remains the gold standard for kinematic analysis across biomechanical research. However, when tracking dynamic movements, severe occlusions often create missing data and noisy signals that require time-consuming manual cleaning. Existing automated methods usually rely on predefined skeleton models or need massive training datasets for machine learning solutions. This study presents the AMP: an automated marker based motion capture processing pipeline. The AMP is a fully analytical approach that uses hierarchical algorithms including 1) rigid-body constraint, 2) Kalman Filter state estimation and 3) kinematic pattern match to label markers and fill data gaps without manual human intervention. First, the algorithm identifies and removes mislabeling markers before any data scrubbing. During the data cleaning process, our hierarchical algorithm uses a translation-based step to track segments even when there are insufficient donor markers to form a full rigid body. To reconstruct missing marker trajectories, the pipeline initially uses Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) interpolation for short marker gaps. However, the PCHIP creates massive spatial errors during long occlusions, the system automatically switches to rigid-body tracking for gaps over 40 ms. Results showed the pipeline drastically reduced processing time compared to manual human expert methods by 73.5%. In addition, the AMP kept spatial errors within 10 mm of the manual ground truth. By using this combined hierarchical approach to match marker processing accuracy, the pipeline provides a fast, general-purpose tool that fully automates data cleaning and saves hours of manual effort.

bioengineering↗

bioRxiv2026

Experiment-free learning of exoskeleton assistance remains an unsolved problem

In "Experiment-free exoskeleton assistance via learning in simulation", Luo et al. [1] present an ambitious framework for developing exoskeleton controllers through reinforcement learning exclusively in computer simulation. The authors report that a control policy trained on a small dataset from one subject was directly transferred to physical hardware, reducing human metabolic cost during walking, running, and stair climbing by more than any prior device. If confirmed, this would represent a major breakthrough for the field of wearable robotics and their clinical applications. However, a close examination of the published materials casts doubt on these claims. The reported experimental results violate physiological limits on the relationship between mechanical power and muscle energy use during gait2,3,4. The algorithmic claims are surprising and cannot be verified; in contrast with established replicability standards in machine learning5,6, executable code has not been made available. We conclude that the goals of this study have not yet been verifiably achieved and make recommendations for avoiding publication errors of this type in the future.

physiology↗

bioRxiv2025

Improved Stability and Interpretability of Motor Modules Computed with an Autoencoder

Motor module analysis is an important tool in the study of movement, particularly in people with impaired neural control. The most common method for computing motor modules is non-negative matrix factorization (NMF), which identifies a matrix of motor modules and their corresponding time-series activity from electromyography data. NMF has several limitations, including dependence of the muscle weightings on the number of modules selected. Approaches for selecting the number of modules vary between studies, making it difficult to compare and reproduce results. Some metrics of motor control complexity use the variance accounted for when extracting a single motor module (VAF1), yet that modules structure offers little biomechanical interpretability. In this work, we present a method for computing motor modules using an autoencoder, a neural network architecture that can find latent representations of data. Using a single layer autoencoder, we extracted motor modules from data in able-bodied and individuals post-stroke. The structure of autoencoder-computed modules were significantly less sensitive to selected module number. With the autoencoder-computed modules, increasing the number of modules added new information, instead of splitting previous modules. Autoencoder-computed modules, especially at low module counts, had more distinct and interpretable biomechanical functions. Lastly, the autoencoder-computed modules are consistent with previous NMF studies in persons with stroke, which found fewer modules needed to explain the muscle activity of paretic limbs. Our autoencoder-based method offers a new approach for computing motor modules, with advantages of better stability in module structure across module counts, and a more biomechanically relevant interpretation of VAF1. NEW & NOTEWORTHYThis work presents an approach for computing motor modules using an autoencoder and comprehensively compares the in stability of motor module structure, functional significance at low module counts, and interpretation of VAF1 to the current state of the art. The AE-computed module structures were more stable at different module counts. The AE has the potential to improve confidence in module structure and make analysis less dependent on the specific number of modules selected.

physiology↗

bioRxiv2025

Optimized Mappings from Biological Hip Moment Estimates to Exoskeleton Torque can Personalize Assistance Across Users and Generalize Across Tasks

Recent advancements in data-driven methods have enabled real-time estimation of biomechanical states for exoskeleton control. While biological joint moments can be directly used to scale exoskeleton assistance, this approach is often suboptimal. An optimized mapping between biological joint moments and exoskeleton assistance could enhance end-to-end controllers based on the users physiological state. We introduce a flexible parametrization of biological moment-based control using delay, scaling, and shaping terms to transform joint moment estimates into commanded torque. We performed human-in-the-loop optimization, using metabolic cost to evaluate each iterations controller parameters, for 9 subjects across three ambulation modes: level walking at 1.1 m/s, 1.5 m/s, and 5{degrees} inclined walking. We evaluated three methods of exoskeleton control: 1. Personalized/Task Dependent, 2. Task Dependent/Non-personalized, and 3. Task Agnostic/Non-personalized. On average, our personalized approach provided the greatest benefit of 18.3% reduction in metabolic cost compared to walking without the exoskeleton, with the task dependent and task agnostic controllers producing similar reductions of 8.6% and 8.4%, respectively. Our results show that while generalizable, task agnostic control parameters can improve user energetics across cyclic tasks, fully personalized exoskeleton control parameters yield larger metabolic reductions, highlighting the value of personalizing exoskeleton assistance to users across many diverse tasks.

bioengineering↗

bioRxiv2023

Sex differences in dispersal predict sex differences in helping across cooperative birds and mammals

Sex differences in cooperation are widespread, but their evolution remains poorly understood. Here we use phylogenetic comparative methods to test the Dispersal hypothesis for the evolution of sex differences in contributions to cooperative care across the cooperatively breeding birds and mammals. The Dispersal hypothesis predicts that, where non-breeding individuals of both sexes help to rear offspring within their natal group, the more dispersive sex will contribute less (either because leaving the natal group earlier reduces the downstream direct benefit from cooperation or because dispersal activities trade-off against cooperation). Our analyses reveal (i) support for the Dispersal hypothesis (sex biases in dispersal predict sex biases in natal cooperation across taxa), and (ii) that this pattern cannot be readily attributed to alternative hypothesized drivers of sex differences in cooperation (kin selection, heterogamety, paternity uncertainty, patterns of parental care or differences between birds and mammals). Our findings help to clarify the evolutionary drivers of sex differences in cooperation and highlight the need for single-species studies to now tease apart whether sex differences in dispersal predict sex differences in natal cooperation because dispersal impacts the direct benefits of natal cooperation (as is often proposed) or because activities that promote dispersal trade-off against natal cooperation.

evolutionary biology↗

bioRxiv2021

Mothers front-load their investment to the egg stage when helped in a wild cooperative bird

In many cooperative societies, including our own, helpers assist with the post-natal care of breeders young, and may thereby benefit the post-natal development of offspring. Here we present evidence of a novel mechanism by which such post-natal helping could also have hitherto unexplored beneficial effects on pre-natal development: by lightening post-natal maternal workloads, helpers may allow mothers to increase their pre-natal investment per offspring. We present the findings of a decade-long study of cooperatively breeding white-browed sparrow weaver, Plocepasser mahali, societies. Within each social group, reproduction is monopolized by a dominant breeding pair, and non-breeding helpers assist with nestling feeding. Using a within-mother reaction norm approach to formally identify maternal plasticity, we demonstrate that when mothers have more female helpers they decrease their own post-natal investment per offspring (feed their nestlings at lower rates) but increase their pre-natal investment per offspring (lay larger eggs, which yield heavier hatchlings). That these plastic maternal responses are predicted by female helper number, and not male helper number, implicates the availability of post-natal helping per se as the likely driver (rather than correlated effects of group size), because female helpers feed nestlings at substantially higher rates than males. We term this novel maternal strategy "maternal front-loading" and hypothesize that the expected availability of post-natal help allows helped mothers to focus maternal investment on the pre-natal phase, to which helpers cannot contribute directly. Such cryptic maternally mediated helper effects on pre-natal development may markedly complicate attempts to identify and quantify the fitness consequences of helping.

evolutionary biology↗

bioRxiv2020

Older mothers produce offspring with longer telomeres: a longitudinal within-parent analysis

As telomere length often predicts survival and lifespan, there is considerable interest in understanding the origins of inter-individual variation in telomere length. Transgenerational effects of parental age on offspring telomere length are thought to be a key source of variation, but the rarity of longitudinal studies that examine the telomeres of successive offspring born throughout the lives of parents leaves such parental age effects poorly understood. Here, we exploit telomere length measures of successive offspring produced throughout the long breeding tenures of parents in wild white-browed sparrow-weaver (Plocepasser mahali) societies, to isolate the effects of within-parent changes in age on offspring telomere lengths. Our analyses reveal the first evidence to date of a positive within-parent effect of advancing age on offspring telomere length: as individual mothers age they produce offspring with longer telomeres. We consider the potential for pre- and post-natal mechanisms to explain our findings. As telomere erosion predicts offspring mortality in this species, this positive parental age effect could significantly impact parent and offspring fitness. Our findings support the view that transgenerational effects of parental age can be an appreciable source of inter-individual variation in telomere length.

evolutionary biology↗

bioRxiv2019

Genetic integration of the stress response

The vertebrate stress response comprises a suite of behavioural and physiological traits that must be functionally integrated to ensure organisms cope adaptively with acute stressors. Natural selection should favour functional integration, leading to a prediction of genetic integration of these traits. Despite the implications of such genetic integration for our understanding of human and animal health, as well as evolutionary responses to natural and anthropogenic stressors, formal quantitative genetic tests of this prediction are lacking. Here we demonstrate that acute stress response components in Trinidadian guppies are both heritable and integrated on the major axis of genetic covariation. This integration could either facilitate or constrain evolutionary responses to selection, depending upon the alignment of selection with this axis. Such integration also suggests artificial selection on the genetically correlated behavioural responses to stress could offer a viable non-invasive route to the improvement of health and welfare in captive animal populations.

evolutionary biology↗

bioRxiv2018

Habituation and individual variation in the endocrine stress response in the Trinidadian guppy (Poecilia reticulata)

The vertebrate stress response enables individuals to react to and cope with environmental challenges. A crucial aspect of the stress response is the elevation of circulating glucocorticoids. However, continued activation of the stress response under repeated (or chronic) stress can be damaging to fitness. Under certain circumstances it may therefore be adaptive to habituate to repeated exposures to a particular stressor by reducing the magnitude of any associated release of glucocorticoids. Here, we investigate whether Trinidadian guppies (Poecilia reticulata) habituate to repeated exposure to a mild stressor, using a waterborne hormone sampling approach that has previously been shown to elicit a stress response in small fish. We also test for individual variation in the extent of habituation to this stressor. Concentrating on freely circulating cortisol, we found that the first exposure to the assay induced high cortisol release rates but that guppies tended to habituate quickly to subsequent exposures. There were consistent differences among individuals in their average cortisol release rate (after accounting for effects of variables such as body size) over repeated exposures. Our analyses did not find evidence of individual differences in habituation rate, although limitations in statistical power could account for this finding. We also present data on free 11-ketotestosterone, in addition to conjugated forms of both hormones. We discuss consistent individual differences around the general pattern of habituation in the flexible stress response, and highlight the potential for individual variation in habituation to facilitate selection against the deleterious effects of chronic stress.\n\nSummary statementTrinidadian guppies habituate quickly to repeated stress exposure, and exhibit consistent differences in their endocrine stress response. We provide a framework for analysing individual variation in habituation rate.

physiology↗