Biology subjects

Mongeau, J.-M.

Publications and source records attributed to Mongeau, J.-M..

7 recordsLinked to original sources

bioRxiv2026

Insect-inspired, efficient event-based classification of tactile features

Tactile sensing enables humans and animals to detect and discriminate features during exploration and guide context appropriate actions. Compared to conventional touch sensors, sensing of tactile features in animals is fundamentally event-based through spikes. Yet how sensor mechanics shape spike activity for tactile perception is not well understood. Inspired by the American cockroach--an insect touch specialist--we developed a neuromechanical framework that linked antenna passive mechanics, mechanosensory encoding, and spike-based computation. A physics-based model of antenna bending simulated spatiotemporal strain patterns during contact, which were encoded into spike trains through a strain-to-firing mapping calibrated against electrophysiological recordings. The model captured antennal nerve activity observed in vivo by reproducing key features of population-level neural responses across multiple contact locations and speeds. Compared with conventional threshold-based encoding, the insect-inspired spike encoder preserved the spatiotemporal structure of tactile signals while achieving sparser activity. To establish a link between spiking activity and perception, we trained a spiking neural network to classify contact location and speed directly from the predicted spike trains. The network achieved >95% accuracy with reduced computational demands and enabled rapid discrimination within the first 170 ms of contact, indicating that sparse, event-based codes support fast and reliable tactile perception. Together, these results establish a mechanistic bridge between sensor mechanics and neural computation, revealing how physical interactions shape efficient sensory coding. This integrative framework advances our understanding of tactile perception and provides design principles for energy-efficient, neuromorphic tactile systems. Author SummaryAnimals use touch to explore their surroundings, identify objects, and make rapid decisions. Unlike most engineered touch sensors, which continuously transmit data, biological touch systems communicate through brief electrical signals called spikes. However, how the physical properties of a touch sensor influence these signals remains poorly understood. In this study, we used the antenna of the American cockroach as a model system to investigate how mechanics and neural activity work together during touch. We developed a computational framework that links the way an antenna bends during contact to the neural signals generated by touch-sensitive sensors. By comparing our model with neural recordings from living insects, we showed that it can reproduce key patterns of neural activity observed during tactile interactions. We found that the insect-inspired encoding strategy produces sparse signals that retain important information about where and how contact occurs. These signals enabled a neural network to rapidly and accurately identify contact location and speed while using fewer computational resources. Our results suggest that tactile perception emerges from a close interaction between sensor mechanics and neural processing. Beyond advancing our understanding of animal sensation, this work provides principles for designing energy-efficient touch sensors and neuromorphic robotic systems.

neuroscience↗

bioRxiv2025

Physically intelligent soft antennae enhance tactile perception by active touch

Soft robotic sensors today struggle to interpret complex tactile scenes without incurring significant computational costs. Inspired by insect antennae--compliant, distributed sensors that efficiently process tactile information through physical intelligence--we investigated whether mechanical design and active touch sensing strategies could enhance robotic tactile feature perception. We hypothesized that insect-inspired antenna dynamics, specifically flexural stiffness gradients and active touch speed, could simplify tactile classification. Using a sim-to-real framework that bridges bioinspired computational models with a multi-link soft robot antenna, we introduce the notion of tactile fields--spatiotemporal representations of tactile stimuli shaped by contact location, feature type, and active touch speed. Our analyses show that cockroach-inspired antenna mechanics jointly with active touch speeds improve feature classification accuracy compared to conventional sensors with uniform flexural stiffness gradient by increasing tactile data sparsity and dispersion. An exploration of stiffness and damping of antenna mechanics revealed design trade-offs that influence tactile discrimination and structural stability. Through sim-to-real transfer, stiffness gradients and structured active touch motions were demonstrated on a miniature distributed soft robotic antenna, validating their effectiveness in real-world robotic systems. Taken together, this work presents a biologically grounded framework for tactile sensor design that reduces computational load and enhances adaptability.

bioengineering↗

bioRxiv2025

Mechanical and morphological features of the cockroach antenna confer flexibility, reveal a kinematic chain system and predict strain information for proprioception

A broad class of animals rely on touch sensation for perception. Among insects, the American cockroach P. americana is a touch specialist that uses a pair of soft antennae with distributed sensors to touch its environment to guide decision making. During touch, forces on the antenna can activate thousands of mechanosensors. To understand the content of this sensory information, it is critical to understand how antenna mechanics shape the transmission of contact forces. Here, we investigate the mechanical behavior and morphology of the American cockroach antenna at the individual segment level through experiments, mathematical modeling, imaging with Micro-Computed Tomography (Micro-CT), 3D reconstruction of antenna morphology, and finite element modeling (FEM). Our experimental results and model predictions reveal that the antenna flagellum bends according to a kinematic chain model, with rigid segments connected by joints. Whereas the middle region of the antenna consistently fractured under cyclic bending, the tip region remained intact under large deformations, revealing mechanical specialization along the antenna. Micro-CT imaging revealed an invagination of the exocuticle at segment intersections of the tip. To test the hypothesis that this structure can enhance flexibility and robustness, we used FEM and confirmed that the invagination allows for larger bending without structural failure (buckling). Applying FEM to a morphologically accurate kinematic chain model of the flagellum revealed the relationship between the local strain at the location of marginal sensilla and intersegment angle, predicting the information available for antenna proprioception. Taken together, these findings reveal biomechanical adaptations of insect antennae and provide a critical step toward a mechanistic understanding of touch sensation in a touch specialist. SUMMARY STATEMENTBy combining experiments, imaging and modeling, we demonstrate distinct mechanical features in the cockroach antenna and provide a framework to model the neuromechanics of the antenna in an insect touch specialist.

biophysics↗

bioRxiv2023

Hummingbirds rapidly respond to the removal of vision and control a sequence of rate-commanded maneuvers in milliseconds

Hummingbird flight is the epitome of extreme aerial agility and controlled stability, as hummingbirds routinely exercise a variety of stunning aerobatic feats. Yet, the control of these amazing maneuvers is not well understood. Here we examined how hummingbirds control a sequence of maneuvers within milliseconds and tested whether and when their vision is active during this rapid process. We elicited escape flight in calliope hummingbirds and removed visible light at various instants during the maneuvers and quantified their flight kinematics and responses. We show that the escape maneuvers were composed of rapidly-controlled sequential modules, including evasion, reorientation, nose-down dive, forward flight, and nose-up to hover. The hummingbirds did not respond to the light removal during evasion and reorientation until a critical light-removal time; afterward they showed two categories of luminance-based responses that rapidly altered maneuvering modules to terminate the escape. We also show that hummingbird maneuvers are rate-commanded and require no active braking, i.e., their body angular velocities were proportional to the change of wing motion patterns, a trait that likely alleviates the computational demand on flight control. Together, this work uncovers the key traits of hummingbird agility, which can also inform and inspire designs for next-generation agile aerial systems.

animal behavior and cognition↗

bioRxiv2022

Flies adaptively control flight to compensate for added inertia

Animal locomotion is highly adaptive, displaying a large degree of flexibility, yet how this flexibility arises from the integration of mechanics, sensing and neural control remains elusive. For instance, animals require flexible strategies to maintain performance as changes in mass or inertia impact stability. Compensatory strategies to mechanical loading are especially critical for animals that rely on flight for survival. To shed light on the capacity and flexibility of flight neuromechanics to mechanical loading, we pushed the performance of fruit flies (Drosophila) near its limit and implemented a control theoretic framework to quantify how flies compensated for added inertia. Flies with added inertia were placed inside a virtual reality arena which enabled free rotation about the vertical (yaw) axis. Adding inertia increased the flys response time yet had little influence on overall gaze performance. Flies maintained stability following the addition of inertia by adaptively modulating both visuomotor gain and damping. In contrast, mathematical modeling predicted a significant decrease in flight stability and performance. Adding inertia altered saccades, however flies compensated for the added inertia by increasing yaw torque production, indicating that flies sense that they are mechanically loaded. Taken together, in response to added inertia flies trade off reaction time to maintain flight performance through adaptive neural modulation. Our work highlights the flexibility and capacity of motor control in flight.

biophysics↗

bioRxiv2021

Performance and stability of fly-inspired,saccade-based hybrid control

In a way analogous to human vision, the fruit fly D. melanogaster and many other flying insects generate smooth and saccadic movements to stabilize and shift their gaze in flight, respectively. It has been hypothesized that this combination of continuous and discrete movements benefits both flight stability and performance, particularly at high frequencies or visual motion speeds [1]. Here we develop a hybrid control system model to explore the effects of saccades on the yaw gaze stabilization reflex of D. melanogaster. Inspired from experimental studies, the model includes a first order plant, a Proportional-Integral (PI) continuous controller, and a saccadic reset system that fires based on the integrated error of the continuous controller. We explore the gain, delay and switching threshold parameter space to quantify the optimum regions for yaw stability and performance. We show that the addition of saccades to a continuous controller provides benefits to both stability and performance across a range of visual motion speeds. Our model suggests that Drosophila operates near its optimal switching threshold for its experimental gain set. We also show that based on experimental data, D. melanogaster operates in a region that trades off performance and stability. This trade-off increases flight robustness, which could facilitate compensation for internal perturbations such as wing damage.

biophysics↗

bioRxiv2020

Mechanisms of punctuated vision in fly flight

To guide locomotion, animals control their gaze via movements of their eyes, head, and/or body, but how the nervous system controls gaze during complex motor tasks remains elusive. Notably, eye movements are constrained by anatomical limits, which requires resetting eye position. By studying tethered, flying flies (Drosophila) in a virtual reality flight simulator, we show that ballistic head movements (saccades) reset eye position, are stereotyped and leverage elastic recoil of the neck joint, enabling mechanically assisted redirection of gaze. Head reset saccades were of proprioceptive origin and interrupted smooth movements for as little as 50 ms, enabling punctuated, near-continuous gaze stabilization. Wing saccades were modulated by head orientation, establishing a causal link between neck signals and execution of body saccades. Furthermore, we demonstrate that head movements are gated by behavioral state. We propose a control architecture for biological and bio-inspired active vision systems with limits in sensor range of motion.

neuroscience↗