Biology subjects

Gautrais, J.

Publications and source records attributed to Gautrais, J..

8 recordsLinked to original sources

bioRxiv2025

Social attraction mediates collective foraging decisions in invasive hornets

Group-living animals commonly use social information to better locate and exploit resources. In many insects, birds, fish and mammals, this can lead to collective foraging decisions by which animals share a single food source among alternatives of equal qualities. Here, we report collective foraging decisions in a social wasp, the yellow-legged hornet Vespa velutina nigrithorax, a major predator of bees and other terrestrial invertebrates invasive across Asia, Europe and North America. When given a choice between two identical liquid food sources (feeders or traps containing sugar solutions), wild hornets distributed asymmetrically on the two options, and this phenomenon was more frequent as group size increased. Priming one of the food sources with dead hornets predictably biased the collective choices towards this particular option, irrespective of whether the dead insects were conspecifics or hornets from a closely related species. Inter-attraction in yellow-legged hornets is thus a passive and non-specific mechanism, possibly mediated by visual or chemical cues displayed by dead hornets. This collective behaviour may provide important foraging advantages to hornets invading new territories and bring new perspectives for population control.

animal behavior and cognition↗

bioRxiv2025

Discovering search behaviour in black garden ant trajectories

Exploration of space plays an important role in many animals, in particular for social insects who have to feed and protect a whole colony. In a laboratory study, Khuong et al (2013) studied how the workers of the black garden ant Lasius niger move around in an unknown environment. They assumed that, in a homogeneous arena with no visual cues, ants had no information about their position in space. Based on this hypothesis, they modelled their ants in a Boltzmann Walker framework which describes an ants random walk as a series of straight segments separated by reorientation events. They assumed that on plain horizontal surfaces the ants direction of movement would not influence their average speed, segment lengths and reorientation decisions, thus leading to diffusive trajectories. However, published experiments indicate that L. niger ants are not completely devoid of directional information even in standard laboratory setups with no obvious landmarks. Moreover, many ant species are known to develop specific search strategies when they want to find a particular place in space, a situation that may apply to the analysed data. We re-analyze Khuong et al s data on non-inclined surfaces, this time taking into account the ants orientation in relation to its starting point in the arena. We discovered that, with this information taken into account, the ants trajectory is biased towards its starting point (biased random walk), revealing an advecto-diffusive process. In fact, the distributions of segment lengths and reorientation angles turned out to be modulated by the ants orientation in relation to its starting point. By simulating these biased trajectories, we show that this modulation halves the time it takes for an ant to come back towards its starting point. We conclude that not taking into account the animals cognitive abilities in data analysis may lead to incomplete or biased conclusions. The discovered search behaviour in L. niger can play a significant role in the colonys exploration and foraging ecology.

animal behavior and cognition↗

bioRxiv2025

Sensitivity analysis enlightens effects of connectivity in a Neural Mass Model under Control-Target mode

Biophysical models of human brain represent the latter as a graph of inter-connected neural regions. Building from the model by Naskar et al. [1], our motivation was to understand how these brain regions can be connected at neural level to implement some inhibitory control, which calls for inhibitory connectivity rarely considered in such models. In this model, regions are made of inter-connected excitatory and inhibitory pools of neurons, but are long-range connected only via excitatory pools (mutual excitation). We thus extend this model by generalizing connectivity, and we analyse how connectivity affects the behaviour of this model. Focusing on the simplest paradigm made of a Control area and a Target area, we explore four typical kinds of connectivity: mutual excitation, Target inhibition by Control, Control inhibition by Target, and mutual inhibition. For this, we build an analytical sensitivity framework, nesting up sensitivities of isolated pools, of isolated regions, and of the full system. We show that inhibitory control can emerge only in Target inhibition by Control and mutual inhibition connectivities. We next offer an analysis of how the model sensitivities depends on connectivity structure, depending on a parameter controling the strength of the self-inhibition within Target region. Finally, we illustrate the effect of connectivity structure upon control effectivity in response to an external forcing in the Control area. Beyond the case explored here, our methodology to build analytical sensitivities by nesting up levels (pool, region, system) lays the groundwork for expressing nested sensitivities for more complex network configurations, either for this model or any other one.

neuroscience↗

bioRxiv2022

Modeling bee movement shows how a perceptual masking effect can influence flower discovery, foraging efficiency and pollination

Understanding how pollinators move across space is key to understanding plant mating patterns. Bees are typically assumed to search for flowers randomly or using simple movement rules, so that the probability of discovering a flower should primarily depend on its distance to the nest. However, experimental work shows this is not always the case. Here, we explored the influence of flower size and density on their probability of being discovered by bees by developing a movement model of central place foraging bees, based on experimental data collected on bumblebees. Our model produces realistic bee trajectories by taking into account the autocorrelation of the bees angular speed, the attraction to the nest, and a gaussian noise. Simulations revealed a << masking effect >> that reduces the detection of flowers close to another, which may have critical consequences for pollination and foraging success. At the plant level, flowers distant to the nest were more often visited in low density environments, suggesting lower probabilities of pollination at high densities. At the bee colony level, foragers found more flowers when they were small and at medium densities, suggesting that there is an optimal flower size and density at which collective foraging efficiency is optimized. Our results indicate that the processes of search and discovery of resources are potentially more complex than usually assumed, and question the importance of resource distribution and abundance on plant-pollinator interactions. Authors summaryUnderstanding how pollinators move in space is key to understanding plant reproduction, which in turn shapes entire ecosystems. Most current models assume simple movement rules that predict that flowers are more likely to be visited--and hence pollinated--the closer they are to the pollinators nest. Here we developed an explicit movement model that incorporates realistic features of bumblebees, including their flight characteristics and their tendency to return regularly to the nest, and calibrated it with experimental data collected in naturalistic conditions. This model revealed that the probability to visit a flower does not only depend on its position, but also on the position of other flowers that may mask it from the forager. This masking effect means that pollination efficiency depends on the density and spatial arrangement of flowers around the pollinators nest, often in counter-intuitive ways. Taking these effects into account will be key for improving precision pollination and pollinator conservation.

animal behavior and cognition↗

bioRxiv2020

A model of resource partitioning between foraging bees

Central place foraging pollinators tend to develop multi-destination routes (traplines) to visit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in details, how populations of foragers exploit resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, addition of negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structure, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging.

animal behavior and cognition↗

bioRxiv2020

G1 PHASE LENGTHENING DURING NEURAL TISSUE DEVELOPMENT INVOLVES CDC25B INDUCED G1 HETEROGENEITY.

While lengthening of the cell cycle and G1 phase is a generic feature of tissue maturation during development, the underlying mechanism remains still poorly understood. Here we develop a time lapse imaging strategy to measure the four phases of the cell cycle in single neural progenitor cells in their endogenous environment. Our results show that neural progenitors possess a great heterogeneity of the cell cycle length. This duration variability is distributed over all phases of the cell cycle, with the G1 phase being the one contributing primarily to cell cycle variability. Within one cell cycle, each phase duration appears stochastic and independent except for a surprising correlation between S and M phase. Lineage analysis indicates that the majority of daughter cells display longer G1 phase than their mothers suggesting that at each cell cycle a mechanism lengthens the G1 phase. We identify an actor of the core cell cycle machinery, the CDC25B phosphatase known to regulate G2/M transition, as an indirect regulator of the duration of the G1 phase. We propose that CDC25B acts via a cell to cell increase in G1 phase heterogeneity revealing a novel mechanism of G1 lengthening associated with tissue development.

developmental biology↗

bioRxiv2018

Mathematical modeling supports fate restriction in neurogenic progenitors of the embryonic ventral spinal cord

In the developing neural tube in chicken and mammals, neural stem cells proliferate and differentiate according to a stereotyped spatio-temporal pattern. Several actors have been identified in the control of this process, from tissue-scale morphogens patterning (Shh, BMP) to intrinsic determinants in neural progenitor cells. In a previous study (Bonnet et al. eLife 7, 2018), we have shown that the CDC25B phosphatase promotes the transition from proliferation to differentiation in a cell-cycle independent fashion. In this study, we set up a mathematical model linking progenitor modes of division to the dynamics of progenitors and differentiated populations. Here, we build on this previous model to propose a complete dynamical picture of this process. We start from the standard model in which progenitors are homogeneous and can perform any type of divisions (proliferative division yielding two progenitors, asymmetric neurogenic divisions yielding one progenitor and one neuron, and terminal symmetric divisions yielding two neurons). We constraint this model using published data about mode of divisions and population dynamics of progenitors/neurons at different developmental stages (Saade et al. Cell Reports 4, 2013), and check the effect of CDC25B gain of function in this context. Next, we explore the scenarios in which progenitors population is actually split into two different pools, one of which composed of cells that have lost the capacity to perform proliferative divisions (fate restriction). We show that one such scenario appears relevant and calls for further identification of the alternative role of CDC25B in such a fate restriction.

developmental biology↗

bioRxiv2017

Neurogenic decisions require a cell cycle independent function of the CD25B phosphatase

A fundamental issue in developmental biology and in organ homeostasis is understanding the molecular mechanisms governing the balance between stem cell maintenance and differentiation into a specific lineage. Accumulating data suggest that cell cycle dynamics plays a major role in the regulation of this balance. Here we show that the G2/M cell cycle regulator CDC25B phosphatase is required in mammals to finely tune neuronal production in the neural tube. We show that in chick neural progenitors, CDC25B activity is both required and sufficient to stimulate neurogenic divisions and to promote neuronal differentiation. We design a mathematical model showing that within a limited period of time, cell cycle length modifications cannot account for changes in the ratio of the mode of division. Using a CDC25B point mutation that cannot interact with CDK, we show that part of CDC25B activity on neurogenic divisions is independent of its action on the cell cycle.

developmental biology↗