Biology subjects

Gabbiani, F.

Publications and source records attributed to Gabbiani, F..

13 recordsLinked to original sources

bioRxiv2026

Multiple roads to swarming: divergent molecular machineries drive the repeated evolution of locusts

Locust swarming, one of nature's most spectacular examples of a repeated emergent polyphenism, has long been suspected to rely on conserved "swarming genes" or shared genomic features. By applying a model-clade approach comparing six species that vary in their degrees of plasticity and collective behavior, we show that the evolution of swarming locusts is not driven by shared genomic features or a universal set of swarming genes. In contrast, we find that this phenomenon evolved through flexible regulatory architectures, in which the degree of behavioral plasticity directly correlates with the total scale of density-responsive gene expression. While different locust species recruit largely non-overlapping gene sets to achieve the same syndrome, these divergent molecular machineries converge on similar higher-level biological functions. Thus, multiple molecular pathways achieve locust swarming, challenging the preconceived notion about the genetic prerequisites to transition from solitary to collective states. Further, we establish that a complex syndrome such as locust swarming emerges through modular regulatory systems that can be amplified, modified, or attenuated across the tree of life.

evolutionary biology↗

bioRxiv2026

The functional organization of retinal input to the mouse superior colliculus

The superior colliculus integrates retinal input to drive rapid, adaptive visual behavior, yet how the functional diversity of retinal ganglion cell types is represented in superior colliculus remains poorly understood. Using chronic two-photon calcium imaging of retinal ganglion cell axonal boutons in awake mice, we recorded over 200,000 boutons across superficial superior colliculus layers -- a scale that enabled systematic comparison with large-scale ex vivo retinal datasets. This revealed that the superior colliculus receives a near-complete sampling of retinal ganglion cell functional diversity. Functionally distinct response types were organized in systematic laminar gradients: not only response properties such as direction selectivity and contrast suppression, but retinal response types themselves varied systematically with depth. To probe how this organized input encodes natural scenes, we trained a "digital twin" deep network model on natural movie responses and validated its generalization to parametric stimuli, including cell type identification. Leveraging this model to generate predicted responses to looming stimuli, we identify a discrete subset of retinal response types tuned for collision detection at low angular thresholds -- a specialization embedded within a broader, non-specialized retinal population. The digital twin is made publicly available as a community resource. Together, these findings provide a comprehensive functional map of retinal drive to the superior colliculus and an in silico platform for linking retinal cell types to behaviorally relevant superior colliculus computations.

neuroscience↗

bioRxiv2025

To jump or not to jump: Comparing effects of phenotypic plasticity on the visual responses and escape behavior of locusts and grasshoppers

Locusts exhibit remarkable phenotypic plasticity changing their appearance and behavior from solitary grasshoppers to gregarious locusts when population density increases. These changes include morphological differences in the size and shape of brain regions, but little is known about plasticity within individual neurons and alterations in behavior not directly related to aggregation or swarming. We examined looming escape behavior and the properties of a well-studied collision-detection neuron in gregarious and solitarious animals of three closely related species, the desert locust (Schistocerca gregaria), the Central American locust (S. piceifrons) and the American bird grasshopper (S. americana). For this neuron, the lobula giant movement detector (LGMD), we examined dendritic morphology, membrane properties, gene expression, and looming responses. Gregarious animals reliably jumped in response to looming stimuli, but surprisingly solitarious desert locusts did not produce escape jumps. These solitarious animals also had smaller LGMD dendrites. This is the first study done on three different species of grasshoppers to observe the effects of phenotypic plasticity on the jump escape behavior, physiology and transcriptomics of these animals. Surprisingly, there were little differences in these properties between the two phases except for behavior. For all the three species, gregarious animals jumped more than solitarious animals, but no significant differences were found between the two phases of animals in the electrophysiological and transcriptomics studies. Our results suggest that phase change impacts mainly the motor system and that the physiological properties of motor neurons need to be characterized to understand fully the variation in jump escape behavior across phases. New & Noteworthy (74 words): Swarming is observed in some grasshopper species, called locusts. We compared jump escape behavior between gregarious and solitarious grasshoppers and locusts, as well as LGMD responses to looming stimuli, and analyzed the morphological differences in this neuron. This study provides insights into the effects of phase change on the visual system of locusts and grasshoppers as it relates to looming-evoked jump escape behavior. In this context, our results suggest that phenotypic plasticity mainly impacts the motor system.

neuroscience↗

bioRxiv2022

Approaching object acceleration differentially affects the predictions of neuronal collision-avoidance models

The processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the{eta} model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector (LGMD) as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually-guided collision avoidance in other animals. In goldfish, the{kappa} model has been proposed to describe the Mauthner cell, an identified neuron involved in startle escape responses. In the vinegar fly, a third model was developed for the giant fiber neuron, which trigger last resort escapes immediately before an impending collision. One key property of these models is their prediction that peak neuronal responses occur a fixed delay after the simulated approaching object reaches a threshold angular size on the retina. This prediction is valid for simulated objects approaching at a constant speed. We tested whether it remains valid when approaching objects accelerate. After characterizing and comparing the models responses to accelerating and constant speed stimuli, we find that the prediction holds true for the{kappa} and the giant fiber model, but not for the{eta} model. These results suggest that acceleration in the approach trajectory of an object may help distinguish and further constrain the neuronal computations required for collision avoidance in grasshoppers, fish, and vinegar flies.

neuroscience↗

bioRxiv2022

Convergent escape behavior from distinct visual processing of impending collision in fish and grasshoppers

In animal species ranging from invertebrate to mammals, visually guided escape behaviors have been studied using looming stimuli, the two-dimensional expanding projection on a screen of an object approaching on a collision course at constant speed. The peak firing rate or membrane potential of neurons responding to looming stimuli often tracks a fixed threshold angular size of the approaching stimulus that contributes to the triggering of escape behaviors. To study whether this result holds more generally, we designed stimuli that simulate acceleration or deceleration over the course of object approach on a collision course. Under these conditions, we found that collision detecting neurons in grasshoppers were sensitive to acceleration whereas the triggering of escape behaviors was less so. In contrast, neurons in goldfish identified indirectly through the characteristic features of the escape behaviors they trigger, showed little sensitivity to acceleration. This closely mirrored a broader lack of sensitivity to acceleration of the goldfish escape behavior. Thus, although the sensory coding of simulated colliding stimuli with non-zero acceleration likely differs in grasshoppers and goldfish, the triggering of escape behaviors converges towards similar characteristics. Approaching stimuli with non-zero acceleration may help refine our understanding of neural computations underlying escape behaviors in a broad range of animal species. Key pointsO_LIA companion manuscript showed that two mathematical models of collision-detecting neurons in grasshoppers and goldfish make distinct predictions for their responses to simulated objects approaching on a collision course with non-zero acceleration. C_LIO_LITesting these experimental predictions showed that grasshopper neurons are sensitive to acceleration while goldfish neurons are not, in agreement with the distinct models proposed previously in these species using constant velocity approaches. C_LIO_LIBoth the escape behaviors of grasshopper and goldfish were insensitive to acceleration suggesting a further transformation downstream in grasshopper motor circuits that matches the computation observed in the goldfish Mauthner cell. C_LIO_LIThus, in spite of different sensory processing in the two species, escape behaviors converge towards similar solutions. C_LIO_LIThe use of object acceleration during approach on a collision course may help better understand the neural computations implemented for collision avoidance in a broad range of species. C_LI

neuroscience↗

bioRxiv2022

Contrast-polarity specific mapping optimizes neuronal computation for collision detection

Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cells dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. This random synaptic arrangement results in the neurons inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animals escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.

neuroscience↗

bioRxiv2019

Neuronal ON/OFF Motion Detection Circuits Underlying Looming-Evoked Escape Behavior in Drosophila

In Drosophila, early visual processing of motion information segregates in separate ON and OFF pathways. These pathways have been studied in the context of local directional motion detection leading to the encoding of optic flow that provides visual information for flight stabilization. Less is known about their role in detecting impending collision and generating escape behaviors. Looming, the simulated approach of an object at constant speed towards an animal, provides a powerful stimulus eliciting jump escape behaviors in stationary flies. We presented looming stimuli mimicking the approach of either a dark object on a bright background or a light object on a dark background, while inactivating neurons belonging either to the ON- or the OFF-motion detection pathways by expressing the dominant Drosophila temperature-sensitive mutant shibirets in different cells of the ON/OFF pathway. Inactivation of ON, respectively OFF, neurons led to selective decreases in escape behavior to light, resp. dark, looming stimuli. Quantitative analysis showed a nearly perfect splitting of these effects according to the ON/OFF type of the targeted neural populations. Our results suggest that Drosophila ON/OFF motion detection pathways play an important role in controlling jump escape responses according to looming stimulus polarity. They further imply that the biophysical circuits triggering Drosophila jump escape behaviors likely differ substantially from those characterized in other arthropods. SummaryInactivating fly neurons of the ON or OFF directional motion detection pathways during escape behavior selectively reduced jump responses to light and dark looming stimuli, respectively.

neuroscience↗

bioRxiv2018

Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve membrane synchrony

Our brain processes information through the coordinated efforts of billions of individual neurons, each of which transforms a small part of the overall information stream. Central to this is how neurons integrate and transform complex patterns of synaptic inputs. The neuronal membrane impedance determines the change in membrane potential in response to input currents, and therefore sets the gain and timing for synaptic integration. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the role of two active conductances gH and gM, meditated respectively by hyperpolarization-activated cyclic nucleotide gated (HCN) channels and by muscarine sensitive M-channels, in shaping the membrane impedance of a collision detection neuron in female Schistocerca americana grasshoppers. The neuron is known by its acronym LGMD, which stands for lobula giant movement detector. In contrast to other neurons where these conductances have been studied, we found that gH and gM promote broadband, synchronous integration over the LGMDs functional range of membrane potentials and input frequencies. Additionally, we found that the branching morphology of the LGMD helped increase both the gain and synchrony associated with the neurons membrane impedance. The same result held for a wide range of dendritic morphologies, including those of mammalian neocortical pyramidal neurons and cerebellar Purkinje cells. Thus, these findings further our understanding of the integration properties of individual neurons by showing the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.\n\nSignificance StatementInformation in the brain is processed by neurons that receive thousands of synaptic inputs. Understanding how neurons integrate these inputs is critical to neuroscience. Neuronal integration depends on complex interactions of synaptic input patterns and the electrochemical properties of dendrites. Although examining the input patterns and dendritic processing in vivo is not yet possible in the mammalian brain, it is within simpler nervous systems. Here, we used an identified collision detection neuron in grasshoppers to examine how its morphology and membrane properties determine the gain and synchrony of synaptic integration in relation to the computations it performs. The neuronal properties examined are ubiquitous and therefore will further a general understanding of neuronal computations, including those in our own brain.

neuroscience↗

bioRxiv2018

M-current regulates firing mode and spike reliability in a collision detecting neuron

All animals must detect impending collisions to escape them, and they must reliably discriminate them from non-threatening stimuli to prevent false alarms. Therefore, it is no surprise that animals have evolved highly selective and sensitive neurons dedicated to such tasks. We examined a well-studied collision detection neuron in the grasshopper Schistocerca americana using in vivo electrophysiology, pharmacology, and computational modeling. This lobula giant movement detector (LGMD) neuron is excitable by inputs originating from each ommatidia of the compound eye, and it has many intrinsic properties that increase its selectivity to objects approaching on a collision course, including switching between burst and non-burst firing. Here, we demonstrate that the LGMD neuron exhibits a large M current, generated by non-inactivating K+ channels, that narrows the window of dendritic integration, regulates a firing mode switch between burst and isolated spiking, increases the precision of spike timing, and increases the reliability of spike propagation to downstream motor centers. By revealing how the M current increases the LGMDs ability to detect impending collisions our results suggest that it may play an analogous role in other collision detection circuits.\n\nNew & NoteworthyThe ability to reliably detect impending collisions is a critical survival skill. The nervous systems of many animals have developed dedicated neurons for accomplishing this task. We used a mix of in vivo electrophysiology and computational modeling to investigate the role of M potassium channels within one such collision detecting neuron and showed that through regulation of burst firing and increasing spiking reliability the M current increases the ability to detect impending collisions.

neuroscience↗

bioRxiv2018

Optogenetic manipulation of medullary neurons in the locust optic lobe

Locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts (Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered firing of a postsynaptic, looming-sensitive neuron, the Lobula Giant Movement Detector (LGMD). These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects.\n\nNew and NoteworthyUsing Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and of an identified postsynaptic target neuron, the LGMD neuron. This technique allows to manipulate the neuronal activity in locust neural circuits using optogenetics.

neuroscience↗

bioRxiv2017

Neural code subserving feed-forward inhibition in a collision detection circuit

Feed-forward inhibition is ubiquitous as a motif in the organization of neuronal circuits. During sensory information processing, it is traditionally thought to sharpen the responses and temporal tuning of feed-forward excitation onto principal neurons. As it often exhibits complex time-varying activation properties, feed-forward inhibition could also convey information used by single neurons to implement dendritic computations on sensory stimulus variables. We investigated this possibility in a collision detecting neuron of the locust optic lobe that receives both feed-forward excitation and inhibition. We identified a small population of neurons mediating feed-forward inhibition, with wide visual receptive fields and whose responses depend both on the size and speed of moving stimuli. By studying responses to simulated objects approaching on a collision course, we determined that they jointly encode the angular size of expansion of the stimulus. Feed-forward excitation on the other hand encodes a function of the angular velocity of expansion and the targeted collision detecting neuron combines these two variables non-linearly in its firing output. Thus, feed-forward inhibition actively contributes to the detailed firing rate time course of this collision detecting neuron, a feature critical to the appropriate execution of escape behaviors. These results suggest that feed-forward inhibition could similarly convey time-varying stimulus information in other neuronal circuits.

neuroscience↗

bioRxiv2017

Muscarinic Lateral Excitation Contributes to Visual Object Segmentation during Collision Avoidance

Visual neurons specialized in tracking objects on a collision course are often finely tuned to their target stimuli as this is critical for survival. The presynaptic neural networks converging on these neurons and their role in tuning them remains poorly understood. We took advantage of well-known characteristics of one such neuron to investigate the properties of its presynaptic input network. We find a structure more complex than hitherto realized. In addition to dynamic lateral inhibition used to filter out background motion, presynaptic circuits include normalizing inhibition and short-range lateral excitatory interactions mediated by muscarinic acetylcholine receptors. These interactions preferentially boost responses to coherently expanding visual stimuli generated by colliding objects, as opposed to spatially incoherent controls, helping implement object segmentation. Hence, in addition to active dendritic conductances within collision detecting neurons, multiple layers of both inhibitory and excitatory presynaptic connections are needed to finely tune neural circuits for collision detection.

neuroscience↗

bioRxiv2017

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. The most studied such collision-detecting neuron within the optic lobe of grasshoppers has long served as a model for understanding collision avoidance behaviors and their underlying neural computations. Here, we demonstrate that this neuron detects the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation as its pharmacological block abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Our results elucidate how active dendritic channels produce neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

neuroscience↗