Abdicating power for control: a precision timing strategy to modulate function of flight power muscles

Temporal resolution of spike coding in feedforward networks with signal convergence and divergence

Convergent and divergent structures in the networks that make up biological brains are found across many species and brain regions at various spatial scales. Neurons in these networks fire action potentials, or "spikes", whose precise timing is becoming increasingly appreciated as large sources of information about both sensory input and motor output. While previous theories on coding in convergent and divergent networks have largely neglected the role of precise spike timing, our model and analyses place this aspect at the forefront. For a suite of stimuli with different timescales, we demonstrate that structural bottlenecks- small groups of neurons post-synaptic to network convergence - have a stronger preference for spike timing codes than expansion layers created by structural divergence. Additionally, we found that a simple network model based on convergence and divergence ratios of a hawkmoth (Manduca sexta) nervous system can reproduce the relative contribution of spike timing information in its motor output, providing testable predictions on optimal temporal resolutions of spike coding across the moth sensory-motor pathway at both the single-neuron and population levels. Our simulations and analyses suggest a relationship between the level of convergent/divergent structure present in a feedforward network and the loss of stimulus information encoded by its population spike trains as their temporal resolution decreases, which could be tested experimentally across diverse neural systems in future studies. We further show that this relationship can be generalized across different spike-generating models and measures of coding capacity, implying a potentially fundamental link between network structure and coding strategy using spikes.

An information theoretic method to resolve millisecond-scale spike timing precision in a comprehensive motor program

Sensory inputs in nervous systems are often encoded at the millisecond scale in a precise spike timing code. There is now growing evidence in behaviors ranging from slow breathing to rapid flight for the prevalence of precise timing encoding in motor systems. Despite this, we largely do not know at what scale timing matters in these circuits due to the difficulty of recording a complete set of spike-resolved motor signals and assessing spike timing precision for encoding continuous motor signals. We also do not know if the precision scale varies depending on the functional role of different motor units. We introduce a method to estimate spike timing precision in motor circuits using continuous MI estimation at increasing levels of added uniform noise. This method can assess spike timing precision at fine scales for encoding rich motor output variation. We demonstrate the advantages of this approach compared to a previously established discrete information theoretic method of assessing spike timing precision. We use this method to analyze the precision in a nearly complete, spike resolved recording of the 10 primary wing muscles control flight in an agile hawk moth, Manduca sexta. Tethered moths visually tracked a robotic flower producing a range of turning (yaw) torques. We know that all 10 muscles in this motor program encode the majority of information about yaw torque in spike timings, but we do not know whether individual muscles encode motor information at different levels of precision. We demonstrate that the scale of temporal precision in all motor units in this insect flight circuit is at the sub-millisecond or millisecond-scale, with variation in precision scale present between muscle types. This method can be applied broadly to estimate spike timing precision in sensory and motor circuits in both invertebrates and vertebrates.

Modeling the musculoskeletal system of an insect thorax for flapping flight

Indirect actuation of the wings via thoracic deformation is a unique mechanism widely observed in flying insect species. The physical properties of the thorax have been intensively studied in terms of their ability to efficiently generate wingbeats. The basic mechanism of indirect wing actuation is generally explained as a lever model on a cross-sectional plane, where the dorsoventral movement of the mesonotum (dorsal exoskeleton of the mesothorax) generated by contractions of indirect muscles actuates the wing. However, the model considers the mesonotum as an ideal flat plane, whereas the mesonotum is hemispherical and becomes locally deformed during flight. Furthermore, the conventional model is two-dimensional; therefore, three-dimensional wing kinematics by indirect muscles have not been studied to date. In this study, we develop structural models of the mesonotum and mesothorax of the hawkmothAgrius convolvuli, reconstructed from serial cross-sectional images. External forces are applied to the models to mimic muscle contraction, and mesonotum deformation and wing trajectories are analyzed using finite element analysis. We find that applying longitudinal strain to the mesonotum to mimic strain by depressor muscle contraction reproduces local deformation comparable to that of the thorax during flight. Furthermore, the phase difference of the forces applied to the depressor and elevator muscles changes the wing trajectory from a figure eight to a circle, which is qualitatively consistent with the tethered flight experiment. These results indicate that the local deformation of the mesonotum due to its morphology and the thoracic deformation via indirect power muscles can modulate three-dimensional wing trajectories.

Temporal differences between load and movement signal integration in the sensorimotor network of an insect leg

Nervous systems face a torrent of sensory inputs, including proprioceptive feedback. Signal integration depends on spatially and temporally coinciding signals. It is unclear how relative time delays affect multimodal signal integration from spatially distant sense organs. We measured transmission times and latencies along all processing stages of sensorimotor pathways in the stick insect leg muscle control system, using intra- and extracellular recordings. Transmission times of signals from load-sensing tibial and trochanterofemoral campaniform sensilla (tiCS, tr/fCS) to the premotor network were longer than from the movement-sensing femoral chordotonal organ (fCO). We characterized connectivity patterns from tiCS, tr/fCS, and fCO afferents to identified premotor nonspiking interneurons (NSIs) and motor neurons (MNs) by distinguishing short- and long-latency responses to sensory stimuli. Functional NSI connectivity depended on sensory context. The timeline of multisensory integration in the NSI network showed an early phase of movement signal processing and a delayed phase of load signal integration. The temporal delay of load signals relative to movement feedback persisted into MN activity and muscle force development. We demonstrate differential delays in the processing of two distinct sensory modalities generated by the sensorimotor network and affecting motor output. The reported temporal differences in sensory processing and signal integration improve our understanding of sensory network computation and function in motor control.NEW & NOTEWORTHY Networks integrating multisensory input face the challenge of not only spatial but also temporal integration. In the local network controlling insect leg movements, proprioceptive signal delays differ between sensory modalities. Specifically, signal transmission times to and neuronal connectivity within the sensorimotor network lead to delayed information about leg loading relative to movement signals. Temporal delays persist up to the level of the motor output, demonstrating its relevance for motor control.

Wings and halteres act as coupled dual oscillators in flies

The mechanics of Dipteran thorax is dictated by a network of exoskeletal linkages that, when deformed by the flight muscles, generate coordinated wing movements. In Diptera, the forewings power flight, whereas the hindwings have evolved into specialized structures called halteres, which provide rapid mechanosensory feedback for flight stabilization. Although actuated by independent muscles, wing and haltere motion is precisely phase-coordinated at high frequencies. Because wingbeat frequency is a product of wing-thorax resonance, any wear-and-tear of wings or thorax should impair flight ability. How robust is the Dipteran flight system against such perturbations? Here, we show that wings and halteres are independently driven, coupled oscillators. We systematically reduced the wing length in flies and observed how wing-haltere synchronization was affected. The wing-wing system is a strongly coupled oscillator, whereas the wing-haltere system is weakly coupled through mechanical linkages that synchronize phase and frequency. Wing-haltere link acts in a unidirectional manner; altering wingbeat frequency affects haltere frequency, but not vice versa. Exoskeletal linkages are thus key morphological features of the Dipteran thorax that ensure wing-haltere synchrony, despite severe wing damage.

Rapid frequency modulation in a resonant system: aerial perturbation recovery in hawkmoths

Centimetre-scale fliers must contend with the high power requirements of flapping flight. Insects have elastic elements in their thoraxes which may reduce the inertial costs of their flapping wings. Matching wingbeat frequency to a mechanical resonance can be energetically favourable, but also poses control challenges. Many insects use frequency modulation on long timescales, but wingstroke-to-wingstroke modulation of wingbeat frequencies in a resonant spring-wing system is potentially costly because muscles must work against the elastic flight system. Nonetheless, rapid frequency and amplitude modulation may be a useful control modality. The hawkmoth Manduca sexta has an elastic thorax capable of storing and returning significant energy. However, its nervous system also has the potential to modulate the driving frequency of flapping because its flight muscles are synchronous. We tested whether hovering hawkmoths rapidly alter frequency during perturbations with vortex rings. We observed both frequency modulation (32% around mean) and amplitude modulation (37%) occurring over several wingstrokes. Instantaneous phase analysis of wing kinematics revealed that more than 85% of perturbation responses required active changes in neurogenic driving frequency. Unlike their robotic counterparts that abdicate frequency modulation for energy efficiency, synchronous insects use wingstroke-to-wingstroke frequency modulation despite the power demands required for deviating from resonance.

Measuring the frequency response of the honeybee thorax

Insects with asynchronous flight muscles are believed to flap at the effective fundamental frequency of their thorax-wing system. Flapping in this manner leverages the natural elasticity of the thorax to reduce the energetic requirements of flight. However, to the best of our knowledge, the fundamental frequency of the insect wing-muscle-thorax system has not been measured. Here, we measure the linear frequency response function (FRF) of honeybee Apis mellifera thoraxes about their equilibrium state in order to determine their fundamental frequencies. FRFs relate the input force to output acceleration at the insect tergum and are acquired via a mechanical vibration shaker assembly. When compressed 50 μm, the thorax fundamental frequency averaged across all subjects was about 50% higher than reported wingbeat frequencies. We suspect that the measured fundamental frequencies are higher in the experiment than during flight due to boundary conditions and posthumous muscle stiffening. Next, we compress the thorax between 100-300 μm in 50 μm intervals to assess the sensitivity of the fundamental frequency to geometric modifications. For all specimens considered, the thorax fundamental frequency increased nearly monotonically with respect to level of compression. This implies that the thorax behaves as a nonlinear hardening spring when subject to large displacements, which we confirmed via static force-displacement testing. While there is little evidence that insects utilize this non-linearity during flight, the hardening characteristic may be emulated by small resonant-type flapping wing micro air vehicles to increase flapping frequency bandwidth. Overall, methods established through this work provide a foundation for further dynamical studies on insect thoraxes moving forward.

Precise timing is ubiquitous, consistent, and coordinated across a comprehensive, spike-resolved flight motor program

Sequences of action potentials, or spikes, carry information in the number of spikes and their timing. Spike timing codes are critical in many sensory systems, but there is now growing evidence that millisecond-scale changes in timing also carry information in motor brain regions, descending decision-making circuits, and individual motor units. Across all of the many signals that control a behavior, how ubiquitous, consistent, and coordinated are spike timing codes? Assessing these open questions ideally involves recording across the whole motor program with spike-level resolution. To do this, we took advantage of the relatively few motor units controlling the wings of a hawk moth, Manduca sexta. We simultaneously recorded nearly every action potential from all major wing muscles and the resulting forces in tethered flight. We found that timing encodes more information about turning behavior than spike count in every motor unit, even though there is sufficient variation in count alone. Flight muscles vary broadly in function as well as in the number and timing of spikes. Nonetheless, each muscle with multiple spikes consistently blends spike timing and count information in a 3:1 ratio. Coding strategies are consistent. Finally, we assess the coordination of muscles using pairwise redundancy measured through interaction information. Surprisingly, not only are all muscle pairs coordinated, but all coordination is accomplished almost exclusively through spike timing, not spike count. Spike timing codes are ubiquitous, consistent, and essential for coordination.

Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy across Timescales

Classical and modern ethological studies suggest that animal behavior is organized hierarchically across timescales, such that longer-timescale behaviors are composed of specific shorter-timescale actions. Despite progress relating neuronal dynamics to single-timescale behavior, it remains unclear how different timescale dynamics interact to give rise to such higher-order behavioral organization. Here, we show, in the nematode Caenorhabditis elegans, that a behavioral hierarchy spanning three timescales is implemented by nested neuronal dynamics. At the uppermost hierarchical level, slow neuronal population dynamics spanning brain and motor periphery control two faster motor neuron oscillations, toggling them between different activity states and functional roles. At lower hierarchical levels, these faster oscillations are further nested in a manner that enables flexible behavioral control in an otherwise rigid hierarchical framework. Our findings establish nested neuronal activity patterns as a repeated dynamical motif of the C. elegans nervous system, which together implement a controllable hierarchical organization of behavior.

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Slow dynamics across brain and motor circuits drive upper-hierarchy motor states

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Fast dynamics in motor circuits drive lower-hierarchy movements within these states

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Slower dynamics tightly constrain the state and function of faster ones

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This rigid hierarchy nevertheless enables flexible behavioral control

Sensory processing by motoneurons: a numerical model for low-level flight control in flies

Rhythmic locomotor behaviour in animals requires exact timing of muscle activation within the locomotor cycle. In rapidly oscillating motor systems, conventional control strategies may be affected by neural delays, making these strategies inappropriate for precise timing control. In flies, wing control thus requires sensory processing within the peripheral nervous system, circumventing the central brain. The underlying mechanism, with which flies integrate graded depolarization of visual interneurons and spiking proprioceptive feedback for precise muscle activation, is under debate. Based on physiological parameters, we developed a numerical model of spike initiation in flight muscles of a blowfly. The simulated Hodgkin–Huxley neuron reproduces multiple experimental findings and explains on the cellular level how vision might control wing kinematics. Sensory processing by single motoneurons appears to be sufficient for control of muscle power during flight in flies and potentially other flying insects, reducing computational load on the central brain during body posture reflexes and manoeuvring flight.

Information-based centralization of locomotion in animals and robots

The centralization of locomotor control from weak and local coupling to strong and global is hard to assess outside of particular modeling frameworks. We developed an empirical, model-free measure of centralization that compares information between control signals and both global and local states. A second measure, co-information, quantifies the net redundancy in global and local control. We first validate that our measures predict centralization in simulations of phase-coupled oscillators. We then test how centralization changes with speed in freely running cockroaches. Surprisingly, across all speeds centralization is constant and muscle activity is more informative of the global kinematic state (the averages of all legs) than the local state of that muscle's leg. Finally we use a legged robot to show that mechanical coupling alone can change the centralization of legged locomotion. The results of these systems span a design space of centralization and co-information for biological and robotic systems.

Muscle Function from Organisms to Molecules

Gaps in our understanding of muscle contraction at the molecular level limit the ability to predict in vivo muscle forces in humans and animals during natural movements. Because muscles function as motors, springs, brakes, or struts, it is not surprising that uncertainties remain as to how sarcomeres produce these different behaviors. Current theories fail to explain why a single extra stimulus, added shortly after the onset of a train of stimuli, doubles the rate of force development. When stretch and doublet stimulation are combined in a work loop, muscle force doubles and work increases by 50% per cycle, yet no theory explains why this occurs. Current theories also fail to predict persistent increases in force after stretch and decreases in force after shortening. Early studies suggested that all of the instantaneous elasticity of muscle resides in the cross-bridges. Subsequent cross-bridge models explained the increase in force during active stretch, but required ad hoc assumptions that are now thought to be unreasonable. Recent estimates suggest that cross-bridges account for only ∼12% of the energy stored by muscles during active stretch. The inability of cross-bridges to account for the increase in force that persists after active stretching led to development of the sarcomere inhomogeneity theory. Nearly all predictions of this theory fail, yet the theory persists. In stretch-shortening cycles, muscles with similar activation and contractile properties function as motors or brakes. A change in the phase of activation relative to the phase of length changes can convert a muscle from a motor into a spring or brake. Based on these considerations, it is apparent that the current paradigm of muscle mechanics is incomplete. Recent advances in our understanding of giant muscle proteins, including twitchin and titin, allow us to expand our vision beyond cross-bridges to understand how muscles contribute to the biomechanics and control of movement.

Hawkmoth flight in the unsteady wakes of flowers

Flying animals maneuver and hover through environments where wind gusts and flower wakes produce unsteady flow. Although both flight maneuvers and aerodynamic mechanisms have been studied independently, little is known about how these interact in an environment where flow is already unsteady. Moths forage from flowers by hovering in the flower's wake. We investigated hawkmoths tracking a 3D-printed robotic flower in a wind tunnel. We visualized the flow in the wake and around the wings and compared tracking performance with previous experiments in a still-air flight chamber. As in still air, moths flying in the flower wake exhibit near-perfect tracking at the low frequencies at which natural flowers move. However, tracking in the flower wake results in a larger overshoot between 2 and 5 Hz. System identification of flower tracking reveals that moths also display reduced-order dynamics in wind compared with still air. Smoke visualization of the flower wake shows that the dominant vortex shedding corresponds to the same frequency band as the increased overshoot. Despite these large effects on tracking dynamics in wind, the leading edge vortex (LEV) remains bound to the wing throughout the wingstroke and does not burst. The LEV also maintains the same qualitative structure seen in steady air. Persistence of a stable LEV during decreased flower tracking demonstrates the interplay between hovering and maneuvering.

Millisecond Spike Timing Codes for Motor Control

Millisecond variations in spiking patterns can radically alter motor behavior, suggesting that traditional rate-based theories of motor control require revision. The importance of spike timing in sensorimotor control arises from dynamic interactions between the nervous system, muscles, and the body. New mechanisms, model systems, and theories are revealing how these interactions shape behavior.

Flexibility and control of thorax deformation during hawkmoth flight

The interaction between neuromuscular systems and body mechanics plays an important role in the production of coordinated movements in animals. Lepidopteran insects move their wings by distortion of the thorax structure via the indirect flight muscles (IFMs), which are activated by neural signals at every stroke. However, how the action of these muscles affects thorax deformation and wing kinematics is poorly understood. We measured the deformation of the dorsal thorax (mesonotum) of tethered flying hawkmoths, Agrius convolvuli, using a high-speed laser profilometer combined with simultaneous recordings of electromyograms and wing kinematics. We observed that locally amplified mesonotum deformation near the wing hinges ensures sufficient wing movement. Furthermore, phase asymmetry in IFM activity leads to phase asymmetry in mesonotum oscillations and wingbeats. Our results revealed the flexibility and controllability of the single structure of the mesonotum by neurogenic action of the IFMs.

Neural control and precision of flight muscle activation in Drosophila

Precision of motor commands is highly relevant in a large context of various locomotor behaviors, including stabilization of body posture, heading control and directed escape responses. While posture stability and heading control in walking and swimming animals benefit from high friction via ground reaction forces and elevated viscosity of water, respectively, flying animals have to cope with comparatively little aerodynamic friction on body and wings. Although low frictional damping in flight is the key to the extraordinary aerial performance and agility of flying birds, bats and insects, it challenges these animals with extraordinary demands on sensory integration and motor precision. Our review focuses on the dynamic precision with which Drosophila activates its flight muscular system during maneuvering flight, considering relevant studies on neural and muscular mechanisms of thoracic propulsion. In particular, we tackle the precision with which flies adjust power output of asynchronous power muscles and synchronous flight control muscles by monitoring muscle calcium and spike timing within the stroke cycle. A substantial proportion of the review is engaged in the significance of visual and proprioceptive feedback loops for wing motion control including sensory integration at the cellular level. We highlight that sensory feedback is the basis for precise heading control and body stability in flies.

Flight motor modulation with speed in the hawkmoth Manduca sexta

The theoretical underpinnings for flight, including animal flight with flapping wings, predict a curvilinear U-shaped or J-shaped relationship between flight speed and the power required to maintain that speed. Experimental data have confirmed this relationship for a variety of bird and bat species but not insects, possibly due to differences in aerodynamics and physiology or experimental difficulties. Here we quantify modulation of the main flight motor muscles (the dorsolongitudinal and dorsoventral) via electromyography in hawkmoths (Manduca sexta) flying freely over a range of speeds in a wind tunnel and show that these insects exhibit a U-shaped speed-power relationship, with a minimum power speed of 2ms^-1, indicating that at least large flying insects achieve sufficiently high flight speeds that drag and power become limiting factors.

A novel method for full locomotion compensation of an untethered walking insect

In this study, we developed a novel unfixed-type experimental system that we call a '3-DOF servosphere.' This system comprises one sphere and three omniwheels that support the sphere. The measurement method is very simple. An experimental animal is placed on top of the sphere. The position and heading angle of the animal are observed by using a high-speed camera installed above the sphere. Because the system can rotate the sphere with three degrees of freedom (DOFs) independently, the position and heading angle at the origin can be maintained without fixing the body. This system can be used to measure an animal's natural behavior while simultaneously providing it with precise stimuli. Moreover, electrodes can be inserted at specific sites to measure biosignals with locomotion. Therefore, this system can simultaneously measure the stimulus input-internal state-locomotion output of an animal. In this study, we focused on the chemical plume tracing (CPT) behavior of the Bombyx mori male silkworm moth in order to identify its CPT algorithm for mounting on a robot. In an experiment, we simultaneously measured the stimulus input, flight muscle electromyogram (EMG), and CPT behavior by using the 3-DOF servosphere to verify the system. We elucidated the relationship between the CPT behavior and flight muscle EMG.

Joint torques in a freely walking insect reveal distinct functions of leg joints in propulsion and posture control

Determining the mechanical output of limb joints is critical for understanding the control of complex motor behaviours such as walking. In the case of insect walking, the neural infrastructure for single-joint control is well described. However, a detailed description of the motor output in form of time-varying joint torques is lacking. Here, we determine joint torques in the stick insect to identify leg joint function in the control of body height and propulsion. Torques were determined by measuring whole-body kinematics and ground reaction forces in freely walking animals. We demonstrate that despite strong differences in morphology and posture, stick insects show a functional division of joints similar to other insect model systems. Propulsion was generated by strong depression torques about the coxa-trochanter joint, not by retraction or flexion/extension torques. Torques about the respective thorax-coxa and femur-tibia joints were often directed opposite to fore-aft forces and joint movements. This suggests a posture-dependent mechanism that counteracts collapse of the leg under body load and directs the resultant force vector such that strong depression torques can control both body height and propulsion. Our findings parallel propulsive mechanisms described in other walking, jumping and flying insects, and challenge current control models of insect walking.

Proprioceptive feedback determines visuomotor gain in Drosophila

Multisensory integration is a prerequisite for effective locomotor control in most animals. Especially, the impressive aerial performance of insects relies on rapid and precise integration of multiple sensory modalities that provide feedback on different time scales. In flies, continuous visual signalling from the compound eyes is fused with phasic proprioceptive feedback to ensure precise neural activation of wing steering muscles (WSM) within narrow temporal phase bands of the stroke cycle. This phase-locked activation relies on mechanoreceptors distributed over wings and gyroscopic halteres. Here we investigate visual steering performance of tethered flying fruit flies with reduced haltere and wing feedback signalling. Using a flight simulator, we evaluated visual object fixation behaviour, optomotor altitude control and saccadic escape reflexes. The behavioural assays show an antagonistic effect of wing and haltere signalling on visuomotor gain during flight. Compared with controls, suppression of haltere feedback attenuates while suppression of wing feedback enhances the animal's wing steering range. Our results suggest that the generation of motor commands owing to visual perception is dynamically controlled by proprioception. We outline a potential physiological mechanism based on the biomechanical properties of WSM and sensory integration processes at the level of motoneurons. Collectively, the findings contribute to our general understanding how moving animals integrate sensory information with dynamically changing temporal structure.

Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control

What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity) consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in high dimensional sensory or motor transformations.

Understanding movement control is challenging because the brains of nearly all animals send motor command signals to many muscles, and these signals produce complex movements. In studying animal movement, one cannot always record all the motor commands an animal uses or know all the ways in which movement varies in response. A combined approach is necessary to find the relevant patterns: the changes in movement that correspond to changes in the recorded motor commands. Techniques exist to identify simple patterns in either the motor commands or the movements, but in this paper we develop an approach that identifies patterns in both simultaneously. We use this technique to understand how agile flying insects control aerial turns. The two main downstroke muscles of moths are thought to produce turns by creating a power difference between the left and right wings. The moth’s brain may only need to specify the difference in activation between the two muscles. We discover that moth’s brain actually has independent control over each muscle, and this separate control increases the moth’s ability to adjust turning within a single wingstroke. Our computational approach reveals sophisticated patterns of movement processing even in the small nervous systems of insects.

Feedback control as a framework for understanding tradeoffs in biology

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with regulation via feedback, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here, we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism's response to perturbations. We use examples from aquatic (two behaviors performed by electric fish), terrestrial (following of walls by cockroaches), and aerial environments (flight control by moths) to highlight how one can use control theory to understand the way feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system.

Female pheromones modulate flight muscle activation patterns during preflight warm-up

At low ambient temperature Helicoverpa zea male moths engage in warm-up behavior prior to taking flight in response to an attractive female pheromone blend. Male H. zea warm up at a faster rate when sensing the attractive pheromone blend compared with unattractive blends or blank controls (Crespo et al. 2012), but the mechanisms involved in this olfactory modulation of the heating rate during preflight warm-up are unknown. Here, we test three possible mechanisms for increasing heat production: 1) increased rate of muscle contraction; 2) reduction in mechanical movement by increased overlap in activation of the antagonistic flight muscles; and 3) increased activation of motor units. To test which mechanisms play a role, we simultaneously recorded electrical activation patterns of the main flight muscles (dorsolongitudinal and dorsoventral muscles), wing movement, and thoracic temperature in moths exposed to both the attractive pheromone blend and a blank control. Results indicate that the main mechanism responsible for the observed increase in thoracic heating rate with pheromone stimulation is the differential activation of motor units during each muscle contraction cycle in both antagonistic flight muscles. This additional activation lengthens the contracted state within each cycle and thus accounts for the greater heat production. Interestingly, the rate of activation (frequency of contraction cycles) of motor units, which is temperature dependent, did not vary between treatments. This result suggests that the activation rate is determined by a temperature-dependent oscillator, which is not affected by the olfactory stimulus, but activation of motor units is modulated during each cycle.