A Computational Model of a Descending Mechanosensory Pathway Involved in Active Tactile Sensing

Flow sensing on dragonfly wings

One feature of animal wings is their embedded mechanosensory system that can support flight control. Insect wings are particularly interesting as they are highly deformable yet the actuation is limited to the wing base. It is established that strain sensors on insect wings can directly mediate reflexive control; however, little is known about airflow sensing by insect wings. What information can flow sensors capture and how can flow sensing benefit flight control? Here, we use the dragonfly (Sympetrum striolatum) as a model to explore the function of wing sensory bristles in the context of flight control. Combining our detailed anatomical reconstructions of both the sensor microstructures and wing architecture, we used computational fluid dynamics simulations to ask the following questions. (1) Are there strategic locations on wings that sample flow for estimating aerodynamically relevant parameters such as the local effective angle of attack? (2) Is the sensory bristle distribution on dragonfly wings optimal for flow sensing? (3) What is the aerodynamic effect of microstructures found near the sensory bristles on dragonfly wings? We discuss the benefits of flow sensing for flexible wings and how the evolved sensor placement affects information encoding.

Descending interneurons of the stick insect connecting brain neuropiles with the prothoracic ganglion

Stick insects respond to visual or tactile stimuli with whole-body turning or directed reach-to-grasp movements. Such sensory-induced turning and reaching behaviour requires interneurons to convey information from sensory neuropils of the head ganglia to motor neuropils of the thoracic ganglia. To date, descending interneurons are largely unknown in stick insects. In particular, it is unclear whether the special role of the front legs in sensory-induced turning and reaching has a neuroanatomical correlate in terms of descending interneuron numbers. Here, we describe the population of descending interneurons with somata in the brain or gnathal ganglion in the stick insect Carausius morosus, providing a first map of soma cluster counts and locations. By comparison of interneuron populations with projections to the pro- and mesothoracic ganglia, we then estimate the fraction of descending interneurons that terminate in the prothoracic ganglion. With regard to short-latency, touch-mediated reach-to-grasp movements, we also locate likely sites of synaptic interactions between antennal proprioceptive afferents to the deutocerebrum and gnathal ganglion with descending or ascending interneuron fibres. To this end, we combine fluorescent dye stainings of thoracic connectives with stainings of antennal hair field sensilla. Backfills of neck connectives revealed up to 410 descending interneuron somata (brain: 205 in 19 clusters; gnathal ganglion: 205). In comparison, backfills of the prothorax-mesothorax connectives stained only up to 173 somata (brain: 83 in 16 clusters; gnathal ganglion: 90), suggesting that up to 60% of all descending interneurons may terminate in the prothoracic ganglion (estimated upper bound). Double stainings of connectives and antennal hair field sensilla revealed that ascending or descending fibres arborise in close proximity of afferent terminals in the deutocerebrum and in the middle part of the gnathal ganglia. We conclude that two cephalothoracic pathways may convey cues about antennal movement and pointing direction to thoracic motor centres via two synapses only.

A computational model of insect campaniform sensilla predicts encoding of forces during walking

Control of forces is essential in both animals and walking machines. Insects measure forces as strains in their exoskeletons via campaniform sensilla (CS). Deformations of cuticular caps embedded in the exoskeleton excite afferents that project to the central nervous system. CS afferent firing frequency (i.e. 'discharge') is highly dynamic, correlating with the rate of change of the force. Discharges adapt over time to tonic forces and exhibit hysteresis during cyclic loading.In this study we characterized a phenomenological model that predicts CS discharge, in which discharge is proportional to the instantaneous stimulus force relative to an adaptive variable. In contrast to previous studies of sensory adaptation, our model (1) is nonlinear and (2) reproduces the characteristic power-law adaptation with first order dynamics only (i.e. no 'fractional derivatives' are required to explain dynamics). We solve the response of the system analytically in multiple cases and use these solutions to derive the dynamics of the adaptive variable. We show that the model can reproduce responses of insect CS to many different force stimuli after being tuned to reproduce only one response, suggesting that the model captures the underlying dynamics of the system. We show that adaptation to tonic forces, rate-sensitivity, and hysteresis are different manifestations of the same underlying mechanism: the adaptive variable. We tune the model to replicate the dynamics of three different CS groups from two insects (cockroach and stick insect), demonstrating that it is generalizable. We also invert the model to estimate the stimulus force given the discharge recording from the animal. We discuss the adaptive neural and mechanical processes that the model may mimic and the model's use for understanding the role of load feedback in insect motor control. A preliminary model and results were previously published in the proceedings of the Conference on Biohybrid and Biomimetic Systems.

A leg to stand on: computational models of proprioception

Dexterous motor control requires feedback from proprioceptors, internal mechanosensory neurons that sense the body's position and movement. An outstanding question in neuroscience is how diverse proprioceptive feedback signals contribute to flexible motor control. Genetic tools now enable targeted recording and perturbation of proprioceptive neurons in behaving animals; however, these experiments can be challenging to interpret, due to the tight coupling of proprioception and motor control. Here, we argue that understanding the role of proprioceptive feedback in controlling behavior will be aided by the development of multiscale models of sensorimotor loops. We review current phenomenological and structural models for proprioceptor encoding and discuss how they may be integrated with existing models of posture, movement, and body state estimation.

Input of hair field afferents to a descending interneuron

In insects the tactile sense is important for near-range orientation and is involved in various behaviors. Nocturnal insects, such as the stick insect Carausius morosus, continuously explore their surroundings by actively moving their antennae when walking. Upon antennal contact with objects, stick insects show a targeted front-leg movement. As this reaction occurs within 40 ms, descending transfer of information from the brain to the thorax needs to be fast. So far, a number of descending interneurons have been described that may be involved in this reach-to-grasp behavior. One of these is the contralateral ON-type velocity-sensitive neuron (cONv). cONv was found to encode antennal joint-angle velocity during passive movement. Here, we characterize the transient response properties of cONv, including its dependence on joint angle range and direction. As antennal hair field afferent terminals were shown to arborize close to cONv dendrites, we test whether antennal hair fields contribute to the joint-angle velocity encoding of cONv. To do so, we conducted bilateral extracellular recordings of both cONv interneurons per animal before and after hair field ablations. Our results show that cONv responses are highly transient, with velocity-dependent differences in delay and response magnitude. As yet, the steady state activity level was maintained until the stop of antennal movement, irrespective of movement velocity. Hair field ablation caused a moderate but significant reduction of movement-induced cONv firing rate by up to 40%. We conclude that antennal proprioceptive hair fields contribute to the velocity-tuning of cONv, though further antennal mechanoreceptors must be involved, too.NEW & NOTEWORTHY Active tactile exploration and tactually induced behaviors are important for many animals. They require descending information transfer about tactile sensor movement to thoracic networks. Here, we investigate response properties and afferent input to the identified descending interneuron cONv in stick insects. cONv may be involved in tactually induced reach-to-grasp movements. We show that cONv response delay, transient and steady state are velocity-dependent and that antennal proprioceptive hair fields contribute to the velocity encoding of cONv.

Stable phase-shift despite quasi-rhythmic movements: a CPG-driven dynamic model of active tactile exploration in an insect

An essential component of autonomous and flexible behavior in animals is active exploration of the environment, allowing for perception-guided planning and control of actions. An important sensory system involved is active touch. Here, we introduce a general modeling framework of Central Pattern Generators (CPGs) for movement generation in active tactile exploration behavior. The CPG consists of two network levels: (i) phase-coupled Hopf oscillators for rhythm generation, and (ii) pattern formation networks for capturing the frequency and phase characteristics of individual joint oscillations. The model captured the natural, quasi-rhythmic joint kinematics as observed in coordinated antennal movements of walking stick insects. Moreover, it successfully produced tactile exploration behavior on a three-dimensional skeletal model of the insect antennal system with physically realistic parameters. The effect of proprioceptor ablations could be simulated by changing the amplitude and offset parameters of the joint oscillators, only. As in the animal, the movement of both antennal joints was coupled with a stable phase difference, despite the quasi-rhythmicity of the joint angle time courses. We found that the phase-lead of the distal scape-pedicel (SP) joint relative to the proximal head-scape (HS) joint was essential for producing the natural tactile exploration behavior and, thus, for tactile efficiency. For realistic movement patterns, the phase-lead could vary within a limited range of 10–30° only. Tests with artificial movement patterns strongly suggest that this phase sensitivity is not a matter of the frequency composition of the natural movement pattern. Based on our modeling results, we propose that a constant phase difference is coded into the CPG of the antennal motor system and that proprioceptors are acting locally to regulate the joint movement amplitude.