Biology subjects

Vergassola, M.

Publications and source records attributed to Vergassola, M..

18 recordsLinked to original sources

bioRxiv2025

Mice navigate scent trails using predictive policies

Many terrestrial animals accurately follow odor trails, but their navigation strategies remain unclear. We presented mice with dynamic, non-repeating odor trails using a paper treadmill, and found that they rapidly learned to track trails effectively. Odor detections by one or both nostrils during inhalation evoked rapid, stereotyped motor responses. Blocking one nostril led to biased tracking, while disconnecting interhemispheric neural communication disrupted tracking almost entirely. We found that trail tracking is more than a reflex, with mice adapting their movements according to a memory of recently encountered trail geometry. A Bayesian model captures these behaviors, suggesting mice combine bilateral olfactory input with short-term memory to guide navigation actively. Functional perturbations and neural recordings from behaving animals implicate an early olfactory cortical region in trail tracking. These results lay the groundwork to uncover the computational architecture of sensorimotor integration in naturalistic tasks.

neuroscience↗

bioRxiv2025

Rapid transcriptional response to a dynamic morphogen by time integration

During development, cells must interpret extracellular signals with speed and accuracy. While morphogen gradients pattern tissues, how cells respond to dynamic morphogens remains unclear. Here, we investigate how dorsal patterning in the Drosophila embryo is specified by a rapidly evolving BMP gradient. Using a live reporter of BMP pathway activity and nascent transcription reporters, we find that gene expression is best predicted by time integration of BMP signaling, rather than instantaneous levels. However, in sog mutant embryos with broad BMP activity, integration alone fails to predict gene expression outside the normal domain. We show that the transcription factor Zen lowers the signaling threshold required for activation, enabling integration to drive rapid transcriptional responses even at low BMP levels. Together, these results suggest that cells interpret dynamic morphogen signals through the combined action of temporal integration and spatial competence, providing a framework for robust pattern formation on fast developmental timescales.

developmental biology↗

bioRxiv2025

Manifold learning for olfactory habituation to strongly fluctuating backgrounds

Animals rely on their sense of smell to survive, but important olfactory cues are mixed with confounding background odors that fluctuate due to atmospheric turbulence. It is unclear how the olfactory system habituates to such stochastic backgrounds to detect behaviorally important odors. Here, we explicitly consider the high-dimensional nature of odor coding, the natural statistics of odor fluctuations and the architecture of the early olfactory pathway. We show that their combination favors a manifold learning mechanism for olfactory habituation over alternatives based on predictive filtering. Manifold learning is implemented in our model by a biologically plausible network of inhibitory interneurons in the early olfactory pathway. We demonstrate that plasticity rules based on IBCM or online PCA are effective at implementing this mechanism in turbulent conditions and outperform previous models relying on mean background subtraction. Interneurons with an IBCM plasticity rule acquire selectivity to independently varying odors. This manifold learning mechanism offers a path towards distinguishing plasticity rules in experiments and could be leveraged by other biological circuits facing fluctuating environments.

neuroscience↗

bioRxiv2025

Decaying and expanding Erk gradients process memory of skeletal size during zebrafish fin regeneration

Regeneration of an amputated salamander limb or fish fin restores pre-injury size and structure, illustrating the phenomenon of positional memory. Although appreciated for centuries, the identity of position-dependent cues and how they control tissue growth are not resolved. Here, we quantify Erk signaling events in whole populations of osteoblasts during zebrafish fin regeneration. We find that osteoblast Erk activity is dependent on Fgf receptor signaling and organized into millimeter-long gradients that extend from the distal tip to the amputation site. Erk activity scales with the amount of tissue amputated, predicts the likelihood of osteoblast cycling, and predicts the size of regenerated skeletal structures. Mathematical modeling suggests gradients are established by the transient deposition of long-lived ligands that are transported by tissue growth. This concept is supported by the observed scaling of expression of the essential epidermal ligand fgf20a with extents of amputation. Our work provides evidence that localized, scaled expression of pro-regenerative ligands instructs long-range signaling and cycling to control skeletal size in regenerating appendages.

developmental biology↗

bioRxiv2024

Uncovering multiscale structure in the variability of larval zebrafish navigation

Animals chain movements into long-lived motor strategies, resulting in variability that ultimately reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build models that bridges across time scales that enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish exposed to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising and wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive (dark) stimuli or in search for prey. Our method enables us to encode the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies. By doing so, we uncover a hierarchical structure to the phenotypic variability that corresponds to exploration-exploitation trade-offs. Within a wide range of sensory cues, a major source of variation among fish is driven by prior and immediate exposure to prey that induces exploitation phenotypes. However, a large degree of variability is unexplained by environmental cues, pointing to hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, our approach extracts the timescales of motor strategies deployed during navigation, exposing undiscovered structure among individuals and pointing to internal states tuned by prior experience.

animal behavior and cognition↗

bioRxiv2023

Scale-independent topological interactions drive the first fate decision in the Drosophila embryo

During embryogenesis, the earliest cell fate decision is often linked to nuclear positioning, whose control arises from the integration of the cell cycle oscillator and associated cytoskeletal dynamics. Yet, the mechanisms that ensure that the correct number of nuclei move to the appropriate place remain poorly understood. Here, using light sheet microscopy, we show that in Drosophila embryos spindle orientation controls which nuclei migrate towards the cortex and which remains inside the embryo, thereby determining nuclear fate and the number of cells undergoing development. Combining computational methods inspired by integral geometry and manipulations of cell cycle genes, we show that spindle orientation is controlled by topological spindle-spindle interactions and not by internuclear distance. Using arguments describing the behavior of space-filling systems, we develop a theory for topological dependency in microtubule structures. Our work shows how topological interplay of microtubule mechanics can ensure robust control of density and cell fate determination.

developmental biology↗

bioRxiv2023

Two-fluid dynamics and micron-thin boundary layers shape cytoplasmic flows in early Drosophila embryos

Cytoplasmic flows are widely emerging as key functional players in development. In early Drosophila embryos, flows drive the spreading of nuclei across the embryo. Here, we combine hydrodynamic modeling with quantitative imaging to develop a two-fluid model that features an active actomyosin gel and a passive viscous cytosol. Gel contractility is controlled by the cell cycle oscillator, the two fluids being coupled by friction. In addition to recapitulating experimental flow patterns, our model explains observations that remained elusive, and makes a series of new predictions. First, the model captures the vorticity of cytosolic flows, which highlights deviations from Stokes flow that were observed experimentally but remained unexplained. Second, the model reveals strong differences in the gel and cytosol motion. In particular, a micron-sized boundary layer is predicted close to the cortex, where the gel slides tangentially whilst the cytosolic flow cannot slip. Third, the model unveils a mechanism that stabilizes the spreading of nuclei with respect to perturbations of their initial positions. This self-correcting mechanism is argued to be functionally important for proper nuclear spreading. Fourth, we use our model to analyze the effects of flows on the transport of the morphogen Bicoid, and the establishment of its gradients. Finally, the model predicts that the flow strength should be reduced if the shape of the domain is more round, which is experimentally confirmed in Drosophila mutants. Thus, our two-fluid model explains flows and nuclear positioning in early Drosophila, while making predictions that suggest novel future experiments.

biophysics↗

bioRxiv2023

Emergent complexity in slowly driven stochastic processes

Animal behavior is shaped by a myriad of mechanisms acting on a wide range of scales. This immense variability hampers quantitative reasoning and renders the identification of universal principles elusive. Through data analysis and theory, we here show that slow non-ergodic drives generally give rise to heavy-tailed statistics in behaving animals. We leverage high-resolution recordings of C. elegans locomotion to extract a self-consistent reduced order model for an inferred reaction coordinate, bridging from sub-second chaotic dynamics to long-lived stochastic transitions among metastable states. The slow mode dynamics exhibits heavy-tailed first passage time distributions and correlation functions, and we show that such heavy tails can be explained by dynamics on a time-dependent potential landscape. Inspired by these results, we introduce a generic model in which we separate faster mixing modes that evolve on a quasi-stationary potential, from slower non-ergodic modes that drive the potential landscape, and reflect slowly varying internal states. We show that, even for simple potential landscapes, heavy tails emerge when barrier heights fluctuate slowly and strongly enough. In particular, the distribution of first passage times and the correlation function can asymptote to a power law, with related exponents that depend on the strength and nature of the fluctuations. We support our theoretical findings through direct numerical simulations.

biophysics↗

bioRxiv2021

Alternation emerges as a multi-modal strategy for turbulent odor navigation

Foraging mammals exhibit a familiar yet poorly characterized phenomenon, "alternation", a momentary pause to sniff in the air often preceded by the animal rearing on its hind legs or raising its head. Intriguingly, rodents executing an olfactory search task spontaneously exhibit alternation in the presence of airflow, suggesting that alternation may serve an important role during turbulent plume-tracking. To test this hypothesis, we combine fully-resolved numerical simulations of turbulent odor transport and Bellman optimization methods for decision-making under partial observability. We show that an agent trained to minimize search time in a realistic odor plume exhibits extensive alternation together with the characteristic cast-and-surge behavior commonly observed in flying insects. Alternation is tightly linked with casting and occurs more frequently when the agent is far downwind of the source, where the likelihood of detecting airborne cues is higher relative to cues close to the ground. Casting and alternation emerge as complementary tools for effective exploration when cues are sparse. We develop a model based on marginal value theory to capture the interplay between casting, surging and alternation. More generally, we show how multiple sensorimotor modalities can be fruitfully integrated during complex goal-directed behavior.

animal behavior and cognition↗

bioRxiv2021

Affinity maturation for an optimal balance between long-term immune coverage and short-term resource constraints

In order to target threatening pathogens, the adaptive immune system performs a continuous reorganization of its lymphocyte repertoire. Following an immune challenge, the B cell repertoire can evolve cells of increased specificity for the encountered strain. This process of affinity maturation generates a memory pool whose diversity and size remain difficult to predict. We assume that the immune system follows a strategy that maximizes the long-term immune coverage and minimizes the short-term metabolic costs associated with affinity maturation. This strategy is defined as an optimal decision process on a finite dimensional phenotypic space, where a pre-existing population of naive cells is sequentially challenged with a neutrally evolving strain. We unveil a trade-off between immune protection against future strains and the necessary reorganization of the repertoire. This plasticity of the repertoire drives the emergence of distinct regimes for the size and diversity of the memory pool, depending on the density of naive cells and on the mutation rate of the strain. The model predicts power-law distributions of clonotype sizes observed in data, and rationalizes antigenic imprinting as a strategy to minimize metabolic costs while keeping good immune protection against future strains.

immunology↗

bioRxiv2021

Sector search strategies for odor trail tracking

Terrestrial animals such as ants, mice and dogs often use surface-bound scent trails to establish navigation routes or to find food and mates, yet their tracking strategies are poorly understood. Tracking behavior features zig-zagging paths with animals often staying in close contact with the trail. Upon sustained loss of contact, animals execute a characteristic sequence of sweeping "casts" - wide oscillations with increasing amplitude. Here, we provide a unified description of trail-tracking behavior by introducing an optimization framework where animals search in the angular sector defined by their estimate of the trails heading and its uncertainty. In silico experiments using reinforcement learning based on this hypothesis recapitulate experimentally observed tracking patterns. We show that search geometry imposes limits on the tracking speed, and quantify its dependence on trail statistics and memory of past contacts. By formulating trail-tracking as a Bellman-type sequential optimization problem, we quantify the basic geometric elements of optimal sector search strategy, effectively explaining why and when casting is necessary. We propose a set of experiments to infer how tracking animals acquire, integrate and respond to past information on the tracked trail. More generally, we define navigational strategies relevant for animals and bio-mimetic robots, and formulate trail-tracking as a novel behavioral paradigm for learning, memory and planning.

animal behavior and cognition↗

bioRxiv2019

Antagonistic odor interactions in olfactory sensory neurons are widespread in freely breathing mice

Odor landscapes contain complex blends of discrete molecules that each activate unique, overlapping populations of olfactory sensory neurons (OSNs). Despite the presence of hundreds of OSN subtypes in many animals, the overlapping nature of odor inputs may lead to saturation of neural responses at the early stages of stimulus encoding. Information loss due to saturation could be mitigated by normalizing mechanisms such as antagonism at the level of receptor-ligand interactions, whose existence and prevalence remains uncertain. By imaging OSN axon terminals in olfactory bulb glomeruli as well as OSN cell bodies within the olfactory epithelium in freely breathing mice, we found widespread antagonistic interactions in binary odor mixtures. In complex mixtures of up to 12 odorants, antagonistic interactions became stronger and more prevalent with increasing mixture complexity. Therefore, antagonism is a remarkably common feature of odor mixture encoding in olfactory sensory neurons and helps in normalizing activity to reduce saturation.

neuroscience↗

bioRxiv2019

ODORANT RECEPTOR INHIBITION IS FUNDAMENTAL TO ODOR ENCODING

Most natural odors are complex mixtures of many volatile components, competing to bind odorant receptors (ORs) expressed in olfactory sensory neurons (OSNs) of the nose. To date surprisingly little is known about how OR antagonism shapes neuronal representations in the periphery of the olfactory system. Here, we investigated its prevalence, the degree to which it disrupts OR ensemble activity, and its conservation across related ORs. Calcium imaging microscopy of dissociated OSNs revealed significant inhibition, often complete attenuation, of responses to indole, a commonly occurring volatile associated with both floral and fecal odors, by a set of 36 tested odorants. To confirm an OR mechanism for the observed inhibition, we performed single-cell transcriptomics on OSNs that exhibited specific response profiles to a diagnostic panel of odorants and identified the receptor Olfr743 which, when tested in vitro, recapitulated ex vivo responses. We screened ten ORs from the Olfr743 clade with 800 perfumery-related odorants spanning a range of chemical scaffolds and functional groups, over half of which (430) antagonized at least one of the ten ORs. Furthermore, OR activity outcomes were divergent rather than redundant, even for the most closely related paralogs. OR activity fitted a mathematical model of competitive receptor binding and suggests that normalization of OSN ensemble responses to odorant mixtures is the rule rather than the exception. In summary, we observed OR antagonism, inverse agonism and partial agonism occurring frequently and in a combinatorial manner. Thus, extensive receptor-mediated computation of mixture information appears to occur in the olfactory epithelium prior to transmission of odor information to the olfactory bulb.

neuroscience↗

bioRxiv2019

hunchback promoters can readout morphogenetic positional information in less than a minute

The first cell fate decisions in the developing fly embryo are made very rapidly: hunchback genes decide in a few minutes whether a given nucleus follows the anterior or the posterior developmental blueprint by reading out the positional information encoded in the Bicoid morphogen. This developmental system constitutes a prototypical instance of the broad spectrum of regulatory decision processes that combine speed and accuracy. Traditional arguments based on fixed-time sampling of Bicoid concentration indicate that an accurate readout is not possible within the short times observed experimentally. This raises the general issue of how speed-accuracy tradeoffs are achieved. Here, we compare fixed-time sampling strategies to decisions made on-the-fly, which are based on updating and comparing the likelihoods of being at an anterior or a posterior location. We found that these more efficient schemes can complete reliable cell fate decisions even within the very short embryological timescales. We discuss the influence of promoter architectures on the mean decision time and decision error rate and present concrete promoter architectures that allow for the fast readout of the morphogen. Lastly, we formulate explicit predictions for new experiments involving Bicoid mutants.

biophysics↗

bioRxiv2019

Progressive recruitment of distal MEC-4 channels determines touch response strength in C. elegans

Touch deforms, or strains, the skin beyond the immediate point of contact. The spatiotemporal nature of the touch-induced strain fields depend on the mechanical properties of the skin and the tissues below. Somatosensory neurons that sense touch branch out within the skin and rely on a set of mechano-electrical transduction channels distributed within their dendrites to detect mechanical stimuli. Here, we sought to understand how tissue mechanics shape touch-induced mechanical strain across the skin over time and how individual channels located in different regions of the strain field contribute to the overall touch response. We leveraged C. elegans touch receptor neurons (TRNs) as a simple model amenable to in vivo whole-cell patch clamp recording and an integrated experimental-computational approach to dissect the mechanisms underlying the spatial and temporal dynamics that we observed. Consistent with the idea that strain is produced at a distance, we show that delivering strong stimuli outside the anatomical extent of the neuron is sufficient to evoke MRCs. The amplitude and kinetics of the MRCs depended on both stimulus displacement and speed. Finally, we found that the main factor responsible for touch sensitivity is the recruitment of progressively more distant channels by stronger stimuli, rather than modulation of channel open probability. This principle may generalize to somatosensory neurons with more complex morphologies.\n\nSummaryThrough experiment and simulation, Katta et al. reveal that pushing faster and deeper recruits more and more distant mechano-electrical transduction channels during touch. The net result is a dynamic receptive field whose size and shape depends on tissue mechanics, stimulus parameters, and channel distribution within sensory neurons.

neuroscience↗

bioRxiv2018

Tissue mechanics and somatosensory neural responses govern touch sensation in C. elegans

The sense of touch hinges on tissues transducing stimuli applied to the skin and somatosensory neurons converting mechanical inputs into currents. Like mammalian Pacinian corpuscles, the light-touch response of the prime model organism C. elegans adapts rapidly, and is symmetrically activated by the onset and offset of a step indentation. Here, we propose a quantitative model that combines transduction of stimuli across the skin and subsequent gating of mechanoelectrical channels. For mechanics, we use an elastic model based on geometrically-nonlinear deformations of a pressurized cylindrical shell. For gating, we build upon consequences of the dermal layers thinness and tangential stimuli. Our model demonstrates how the onset-offset symmetry arises from the coupling of mechanics and adaptation, and accounts for experimental neural responses to a broad variety of stimuli. Predicted effects of modifications in the mechanics or the internal pressure of the body are tested against mechanical and neurophysiological experiments.

neuroscience↗

bioRxiv2017

Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures

Natural environments feature mixtures of odorants of diverse quantities, qualities and complexities. Olfactory receptor neurons (ORNs) are the first layer in the sensory pathway and transmit the olfactory signal to higher regions of the brain. Yet, the response of ORNs to mixtures is strongly non-additive, and exhibits antagonistic interactions among odorants. Here, we model the processing of mixtures by mammalian ORNs, focusing on the role of inhibitory mechanisms. Theoretically predicted response curves capture experimentally determined glomerular responses imaged by a calcium indicator expressed in ORNs of live, breathing mice. Antagonism leads to an effective \"normalization\" of the ensemble glomerular response, which arises from a novel mechanism involving the distinct statistical properties of receptor binding and activation, without any recurrent neuronal circuitry. Normalization allows our encoding model to outperform noninteracting models in odor discrimination tasks, and to explain several psychophysical experiments in humans.

neuroscience↗

bioRxiv2016

Complete coverage of space favors modularity of the grid system in the brain

Grid cells in the entorhinal cortex fire when animals that are exploring a certain region of space occupy the vertices of a triangular grid that spans the environment. Different neurons feature triangular grids that differ in their properties of periodicity, orientation and ellipticity. Taken together, these grids allow the animal to maintain an internal, mental representation of physical space. Experiments show that grid cells are modular, i.e. there are groups of neurons which have grids with similar periodicity, orientation and ellipticity. We use statistical physics methods to derive a relation between variability of the properties of the grids within a module and the range of space that can be covered completely (i.e. without gaps) by the grid system with high probability. Larger variability shrinks the range of representation, providing a functional rationale for the experimentally observed co-modularity of grid cell periodicity, orientation and ellipticity. We obtain a scaling relation between the number of neurons and the period of a module, given the variability and coverage range. Specifically, we predict how many more neurons are required at smaller grid scales than at larger ones.

neuroscience↗