Biology subjects

Jayaram, K.

Publications and source records attributed to Jayaram, K..

6 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↗

bioRxiv2026

Multi-step femtosecond laser-fabricated membranes for regulated migration of biomolecules and cells

Organ-on-chip (OoC) systems enable the recapitulation of key structural and functional characteristics of human tissues within controlled micro-engineered environments. In mechanically active tissues such as musculoskeletal, cardiac, and vascular systems, the incorporation of dynamic physical forces is essential for replicating the biomechanical cues governing cellular morphology and functional responses in-vivo. Without such stimuli, OoC models may fail to capture physiologically relevant tissue behaviors. Porous and semi-permeable membranes are critical components of OoCs, facilitating selective transport of nutrients, gases, and signaling molecules between cellular compartments to support biologically accurate barrier replication. Hence, fabrication strategies that permit precise modulation of membrane permeability are desirable to accommodate for the varying needs in pore size and porosity across organ systems. This study presents a two-stage fabrication process for stretchable, microporous polydimethylsiloxane (PDMS) membranes using femtosecond (fs-) pulse laser drilling. The laser-ablated pores exhibit a characteristic conical morphology, with diameters tapering from the laser entry to exit point. By modulating laser power and number of pulses, 6-15 m exit-end pore diameters were achieved in 50 m thick PDMS films. The membranes demonstrated strong mechanical resilience, with a 5-12% reduction in Youngs modulus after 500 cycles of strain loading. Furthermore, membranes fabricated at lower laser powers exhibited superior retention of elasticity, highlighting the influence of processing parameters on mechanical behavior. Cytocompatibility and permeability assessments confirmed that the membranes supported sustained cell viability and proliferation over at least three days. In size-restricted membrane pore geometries, cellular migration was constrained without any inhibition of biomolecular transport. This selective permeability is critical in multilayer OoC architectures, where a balance between biomolecular diffusion and cellular compartmentalization is necessary to preserve distinct tissue interfaces and functional organization. This work presents fs-laser micro-drilling as a robust and tunable fabrication strategy for producing mechanically resilient, selectively permeable PDMS membranes for physiologically relevant OoC applications.

bioengineering↗

bioRxiv2026

Excitation-inhibition interactions mediate firefly flash synchronization

Large populations of fireflies can synchronize their bioluminescent flashes with remarkable precision, producing collective rhythms that emerge from interactions among intrinsically variable individuals. In the North American firefly Photuris frontalis, this behavior usually manifests as a stable, population-level single-period beat whose mechanistic origins remain unresolved. To identify the local interaction rules giving rise to this emergent synchrony, we performed controlled perturbation experiments on isolated P. frontalis males using fixed-period light stimuli. By measuring changes in flash period as a function of stimulus timing, we reconstructed the phase-response curve (PRC) governing individual flash dynamics. The resulting PRC exhibits a biphasic structure, revealing phase-advancing (excitatory) and phase-delaying (inhibitory) responses. Using this PRC, we formalized an integrate-and-fire model that quantitatively reproduced the observed adaptable entrainment across tested stimuli. These results establish a direct mechanistic link between phase sensitivity and emergent collective synchronization, demonstrating how excitation-inhibition interactions influence large-scale rhythmic coherence in firefly populations.

animal behavior and cognition↗

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↗

bioRxiv2022

Strength-mass scaling law governs mass distribution inside honey bee swarms

To survive during colony reproduction, bees create dense clusters of thousands of suspended individuals. How can this swarm, which is orders of magnitude larger than the size of an individual, maintain mechanical stability? We hypothesize that the internal structure in the bulk of the swarm, about which there is little prior information, plays a key role in mechanical stability and thermoregulation. Here, we provide the first-ever 3D reconstructions of the positions of the bees in the bulk of the swarm using x-ray computed tomography. We find that the mass of bees in a layer decreases with distance from the attachment surface. By quantifying the distribution of bees within swarms varying in size (made up of 4000-10000 bees), we find that the same power law governs the smallest and largest swarms, with the weight supported by each layer scaling with the mass of each layer to the {approx} 1.5 power. This arrangement ensures that each layer exerts the same fraction of its total strength, and on average a bee supports a lower weight than its maximum grip strength. This illustrates the extension of the scaling law relating weight to strength of single organisms to the weight distribution within a superorganism made up of thousands of individuals.

animal behavior and cognition↗