Biology subjects

Yuval, O.

Publications and source records attributed to Yuval, O..

7 recordsLinked to original sources

bioRxiv2026

A hierarchy of locomotion costs shapes optimal foraging strategy

Animals must make decisions about how to move through their environment to find food, shelter and mates, yet the general principles underpinning effective search strategies remain poorly understood. Exploration patterns, such as alternating intensive local search with long-range relocation, are observed across many species, but whether these reflect universal organising principles, or are simply imposed by structured environments, is an open question. Here, we reconstruct hours of Caenorhabditis elegans foraging in homogeneous three-dimensional volumes and show that this animal achieves optimal volumetric coverage using a hierarchical search strategy of quasi-planar locomotion patches punctuated by costlier volumetric reorientations. We propose that underlying this cost hierarchy is the worms highly-constrained shape-space and show that despite being spanned by only five body-posture modes, it gives rise to effective locomotion, combining non-planar gaits, planar turns and three-dimensional reorientation manoeuvres. Our finding that action frequencies decay with inferred cost in a Boltzmann-like distribution is consistent with the Principle of Maximum Entropy: optimal search emerging from the tendency to maximise information gained subject to embodied constraints. This general principle offers a unifying framework to assess the optimality of animal decision-making, with implications for understanding nervous system function, foraging ecology, and the physics of living active matter.

animal behavior and cognition↗

bioRxiv2026

The Sniffbot: A biohybrid robot for active sensing-based odor localization and discrimination

The detection, identification and localization of volatile compounds are of critical importance for various applications, ranging from gas leak detection to drug and explosive sensing. Current technologies--such as gas chromatography-mass spectrometry and e-noses--are limited by slow analysis, low mobility, and reduced sensitivity and adaptability, making them unsuitable for real-time odor localization in real-world settings. Here, we present Sniffbot: an autonomous, mobile biohybrid robotic sensory system that overcomes these challenges by harnessing the extraordinary olfactory capabilities of the desert locust antenna, an advanced olfactory sensor, that generates odorant-specific electrophysiological responses to numerous odorants. Our Sniffbot platform consists of a compact robotic vehicle onto which we have assembled: (i) a sensing module, comprising a locust antenna and a miniaturized electrophysiology system; (ii) a "sniffing" module, which actively samples air in the environment, creating a timed airflow over the antenna, preventing the antenna from becoming habituated to odorant stimuli; and (iii) a decision-making module that analyzes the sensory input in real time to navigate or identify odors. Sniffbots movements are controlled by an odorant-search algorithm coupled with the sniffing module. This enables Sniffbot to detect and localize odors independently of wind-induced odorant gradients, and thus to be used in challenging windless environments. The Trident, a novel search algorithm, outperforms several commonly used algorithms in localizing the odorant source. We further demonstrate Sniffbots ability to discriminate a target odor among others. Our results demonstrate the potential of augmenting biological sensors with autonomous robotic components for next-generation chemical sensing and environmental monitoring.

bioengineering↗

bioRxiv2025

Biologically-constrained insect models enable realistic simulations and improve biomechanical predictions of locomotion

Animal locomotion emerges from the complex interplay of morphology, neural control, and biomechanics, involving both active and passive elements. Insect have attracted much interest, and a rich ecosystem of computational models exists for insect locomotion. However, while active control mechanisms have been extensively studied, obtaining accurate and useful models remains challenging due to limited understanding of how detailed anatomical constraints and passive biomechanical properties shape movement. To address this, we developed anatomically accurate 3D models of the adult desert locust and mole cricket, two orthopteran insects that share a basic body plan but exhibit strikingly different morphologies linked to their habitats and specialized locomotor behaviors -- jumping in locusts versus subterranean digging in mole crickets. We fine-tuned these models using precise morphometric measurements for each major body segment. Furthermore, we quantified passive joint dynamics through high-speed videography of anesthetized locust, revealing a two-phase return motion and history-dependent resting angles. By integrating these biologically grounded constraints into physical simulations, we significantly narrowed the parameter space, resulting in more realistic simulations. Our approach provides new tools for predicting biologically relevant, yet experimentally challenging variables, such as joint torques and contact forces, which contribute directly to the understanding of the underlying biological phenomena. Moreover, these improved simulations offer valuable insight for designing energy-efficient soft robotic systems.

animal behavior and cognition↗

bioRxiv2025

Multiple locomotion gaits in the mole cricket

Insects are exceptionally robust walkers. Although different species exhibit distinct anatomical and functional specializations, they are also highly adaptive within these constraints. How such adaptations enable insects to efficiently navigate diverse environments and perform mechanical tasks remains far from fully explored. The mole cricket, which dwells underground, is one of the least studied insects, largely due to its cryptic lifestyle. It excels at digging tunnels and exhibits extreme morphological adaptations, particularly its exceptional fossorial forelegs. Its versatile locomotion, above and below ground, makes the mole cricket an attractive model system for studying the biomechanics of insect movement. Here we provide the first quantitative characterization of mole cricket locomotion. Using a tunnel-like arena, we recorded freely-moving insects and analyzed their various locomotion gaits. We identified and described three main modes of locomotion, including a backward-bound gait that has not previously been reported in any insect. To test specific hypotheses regarding form-function relationships and the generation of thrust, we integrated biomechanical modeling and deep reinforcement learning to simulate the observed gaits. Our work opens several future directions, from exploring context-dependent gait transitions to bio-inspired technological innovations.

animal behavior and cognition↗

bioRxiv2024

Six-legged-bound: a newly-described insect gait

Locomotor behavior is a hallmark of animal biology and ecology. Mole crickets constitute a unique group of subterranean insects that present an exceptional model for locomotion-related research. In response to an aversive stimulus from the front, the mole cricket will consistently adopt a unique backwards gait that we have termed backward-bound. This never before reported six-legged gait comprises a cyclic alternation between the middle and hind-leg pairs with left-right in-phase synchronization, while the front legs display noisy and less consistent phase dynamics. This exceptional gait is transient and is usually expressed for up to a dozen cycles. It is employed to distance the animal quickly away from danger. A gait that can be characterized as "forward-bound" is also displayed by the mole cricket, albeit for a much shorter duration (up to two cycles).

animal behavior and cognition↗

bioRxiv2021

Neuron tracing and quantitative analyses of dendritic architecture reveal symmetrical three-way-junctions and phenotypes of git-1 in C. elegans

Complex dendritic trees are a distinctive feature of neurons. Alterations to dendritic morphology are associated with developmental, behavioral and neurodegenerative changes. The highly-arborized PVD neuron of C. elegans serves as a model to study dendritic patterning; however, quantitative, objective and automated analyses of PVD morphology are missing. Here, we present a method for neuronal feature extraction, based on deep-learning and fitting algorithms. The extracted neuronal architecture is represented by a database of structural elements for abstracted analysis. We obtain excellent automatic tracing of PVD trees and uncover that dendritic junctions are unevenly distributed. Surprisingly, these junctions are three-way-symmetrical on average, while dendritic processes are arranged orthogonally. We quantify the effect of mutation in git-1, a regulator of dendritic spine formation, on PVD morphology and discover a localized reduction in junctions. Our findings shed new light on PVD architecture, demonstrating the effectiveness of our objective analyses of dendritic morphology and suggest molecular control mechanisms. Author SummaryNerve cells (neurons) collect input signals via branched cellular projections called dendrites. A major aspect of the study of neurons, dating back over a century, involves the characterization of neuronal shapes and of their dendritic processes. Here, we present an algorithmic approach for detection and classification of the tree-like dendrites of the PVD neuron in C. elegans worms. A key feature of our approach is to represent dendritic trees by a set of fundamental shapes, such as junctions and linear elements. By analyzing this dataset, we discovered several novel structural features. We have found that the junctions connecting branched dendrites have a three-way-symmetry, although the dendrites are arranged in a crosshatch pattern; and that the distribution of junctions varies across distinct sub-classes of the PVDs dendritic tree. We further quantified subtle morphological effects due to mutation in the git-1 gene, a known regulator of dendritic spines. Our findings suggest molecular mechanisms for dendritic shape regulation and may help direct new avenues of research.

systems biology↗

bioRxiv2020

Inhibition underlies fast undulatory locomotion in C. elegans

Inhibition plays important roles in modulating the neural activities of sensory and motor systems at different levels from synapses to brain regions. To achieve coordinated movement, motor systems produce alternating contraction of antagonist muscles, whether along the body axis or within and among limbs. In the nematode C. elegans, a small network involving excitatory cholinergic and inhibitory GABAergic motoneurons generates the dorsoventral alternation of body-wall muscles that supports undulatory locomotion. Inhibition has been suggested to be necessary for backward undulation because mutants that are defective in GABA transmission exhibit a shrinking phenotype in response to a harsh touch to the head, whereas wild-type animals produce a backward escape response. Here, we demonstrate that the shrinking phenotype is exhibited by wild-type as well as mutant animals in response to harsh touch to the head or tail, but only GABA transmission mutants show slow locomotion after stimulation. Impairment of GABA transmission, either genetically or optogenetically, induces lower undulation frequency and lower translocation speed during crawling and swimming in both directions. The activity patterns of GABAergic motoneurons are different during low and high undulation frequencies. During low undulation frequency, GABAergic VD and DD motoneurons show similar activity patterns, while during high undulation frequency, their activity alternates. The experimental results suggest at least three non-mutually exclusive roles for inhibition that could underlie fast undulatory locomotion in C. elegans, which we tested with computational models: cross-inhibition or disinhibition of body-wall muscles, or inhibitory reset. Significance StatementInhibition serves multiple roles in the generation, maintenance, and modulation of the locomotive program and supports the alternating activation of antagonistic muscles. When the locomotor frequency increases, more inhibition is required. To better understand the role of inhibition in locomotion, we used C. elegans as an animal model, and challenged a prevalent hypothesis that cross-inhibition supports the dorsoventral alternation. We find that inhibition is related to the speed rather than the direction of locomotion and demonstrate that inhibition is unnecessary for muscle alternation during slow undulation in either direction but crucial to sustain rapid dorsoventral alternation. We combined calcium imaging of motoneurons and muscle with computational models to test hypotheses for the role of inhibition in locomotion.

neuroscience↗