A comparative approach to closed-loop computation

Control and recalibration of path integration in place cells using optic flow

Hippocampal place cells are influenced by both self-motion (idiothetic) signals and external sensory landmarks as an animal navigates its environment. To continuously update a position signal on an internal 'cognitive map', the hippocampal system integrates self-motion signals over time, a process that relies on a finely calibrated path integration gain that relates movement in physical space to movement on the cognitive map. It is unclear whether idiothetic cues alone, such as optic flow, exert sufficient influence on the cognitive map to enable recalibration of path integration, or if polarizing position information provided by landmarks is essential for this recalibration. Here, we demonstrate both recalibration of path integration gain and systematic control of place fields by pure optic flow information in freely moving rats. These findings demonstrate that the brain continuously rebalances the influence of conflicting idiothetic cues to fine-tune the neural dynamics of path integration, and that this recalibration process does not require a top-down, unambiguous position signal from landmarks.

Geometric phase predicts locomotion performance in undulating living systems across scales

Self-propelling organisms locomote via generation of patterns of self-deformation. Despite the diversity of body plans, internal actuation schemes and environments in limbless vertebrates and invertebrates, such organisms often use similar traveling waves of axial body bending for movement. Delineating how self-deformation parameters lead to locomotor performance (e.g. speed, energy, turning capabilities) remains challenging. We show that a geometric framework, replacing laborious calculation with a diagrammatic scheme, is well-suited to discovery and comparison of effective patterns of wave dynamics in diverse living systems. We focus on a regime of undulatory locomotion, that of highly damped environments, which is applicable not only to small organisms in viscous fluids, but also larger animals in frictional fluids (sand) and on frictional ground. We find that the traveling wave dynamics used by mm-scale nematode worms and cm-scale desert dwelling snakes and lizards can be described by time series of weights associated with two principal modes. The approximately circular closed path trajectories of mode weights in a self-deformation space enclose near-maximal surface integral (geometric phase) for organisms spanning two decades in body length. We hypothesize that such trajectories are targets of control (which we refer to as "serpenoid templates"). Further, the geometric approach reveals how seemingly complex behaviors such as turning in worms and sidewinding snakes can be described as modulations of templates. Thus, the use of differential geometry in the locomotion of living systems generates a common description of locomotion across taxa and provides hypotheses for neuromechanical control schemes at lower levels of organization.

Sensorimotor adaptation to destabilizing dynamics in weakly electric fish

Humans and other animals can readily learn to compensate for changes in the dynamics of movement. Such changes can result from an injury or changes in the weight of carried objects. These changes in dynamics can lead not only to reduced performance but also to dramatic instabilities. We evaluated the impacts of compensatory changes in control policies in relation to stability and robustness in Eigenmannia virescens, a species of weakly electric fish. We discovered that these fish retune their sensorimotor control system in response to experimentally generated destabilizing dynamics. Specifically, we used an augmented reality system to manipulate sensory feedback during an image stabilization task in which a fish maintained its position within a refuge. The augmented reality system measured the fish's movements in real time. These movements were passed through a high-pass filter and multiplied by a gain factor before being fed back to the refuge motion. We adjusted the gain factor to gradually destabilize the fish's sensorimotor loop. The fish retuned their sensorimotor control system to compensate for the experimentally induced destabilizing dynamics. This retuning was partially maintained when the augmented reality feedback was abruptly removed. The compensatory changes in sensorimotor control improved tracking performance as well as control-theoretic measures of robustness, including reduced sensitivity to disturbances and improved phase margins.

The spatiotemporal richness of hummingbird wing deformations

Animals exhibit an abundant diversity of forms, and this diversity is even more evident when considering animals that can change shape on demand. The evolution of flexibility contributes to aspects of performance from propulsive efficiency to environmental navigation. It is, however, challenging to quantify and compare body parts that, by their nature, dynamically vary in shape over many time scales. Commonly, body configurations are tracked by labelled markers and quantified parametrically through conventional measures of size and shape (descriptor approach) or non-parametrically through data-driven analyses that broadly capture spatiotemporal deformation patterns (shape variable approach). We developed a weightless marker tracking technique and combined these analytic approaches to study wing morphological flexibility in hoverfeeding Anna's hummingbirds (Calypte anna). Four shape variables explained >95% of typical stroke cycle wing shape variation and were broadly correlated with specific conventional descriptors such as wing twist and area. Moreover, shape variables decomposed wing deformations into pairs of in-plane and out-of-plane components at integer multiples of the stroke frequency. This property allowed us to identify spatiotemporal deformation profiles characteristic of hoverfeeding with experimentally imposed kinematic constraints, including through shape variables explaining <10% of typical shape variation. Hoverfeeding in front of a visual barrier restricted stroke amplitude and elicited increased stroke frequencies together with in-plane and out-of-plane deformations throughout the stroke cycle. Lifting submaximal loads increased stroke amplitudes at similar stroke frequencies together with prominent in-plane deformations during the upstroke and pronation. Our study highlights how spatially and temporally distinct changes in wing shape can contribute to agile fluidic locomotion.

Drosophila flying in augmented reality reveals the vision-based control autonomy of the optomotor response

For walking, swimming, and flying animals, the optomotor response is essential to stabilize gaze. How flexible is the optomotor response? Classic work in Drosophila has argued that flies adapt flight control under augmented visual feedback conditions during goal-directed bar fixation. However, whether the lower-level, reflexive optomotor response can similarly adapt to augmented visual feedback (partially autonomous) or not (autonomous) over long timescales is poorly understood. To address this question, we developed an augmented reality paradigm to study the vision-based control autonomy of the yaw optomotor response of flying fruit flies (Drosophila). Flies were placed in a flight simulator, which permitted free body rotation about the yaw axis. By feeding back body movements in real time to a visual display, we augmented and inverted visual feedback. Thus, this experimental paradigm caused a constant visual error between expected and actual visual feedback to study potential adaptive visuomotor control. By combining experiments with control theory, we demonstrate that the optomotor response is autonomous during augmented reality flight bouts of up to 30 min, which exceeds the reported learning epoch during bar fixation. Agreement between predictions from linear systems theory and experimental data supports the notion that the optomotor response is approximately linear and time invariant within our experimental assay. Even under positive visual feedback, which revealed the stability limit of flies in augmented reality, the optomotor response was autonomous. Our results support a hierarchical motor control architecture in flies with fast and autonomous reflexes at the bottom and more flexible behavior at higher levels.

An unsupervised real-time spike sorting system based on optimized OSort

Objective. The OSort algorithm, a pivotal unsupervised spike sorting method, has been implemented in dedicated hardware devices for real-time spike sorting. However, due to the inherent complexity of neural recording environments, OSort still grapples with numerous transient cluster occurrences during the practical sorting process. This leads to substantial memory usage, heavy computational load, and complex hardware architectures, especially in noisy recordings and multi-channel systems.Approach. This study introduces an optimized OSort algorithm (opt-OSort) which utilizes correlation coefficient (CC), instead of Euclidean distance as classification criterion. TheCCmethod not only bolsters the robustness of spike classification amidst the diverse and ever-changing conditions of physiological and recording noise environments, but also can finish the entire sorting procedure within a fixed number of cluster slots, thus preventing a large number of transient clusters. Moreover, the opt-OSort incorporates two configurable validation loops to efficiently reject cluster outliers and track recording variations caused by electrode drifting in real-time.Main results. The opt-OSort significantly reduces transient cluster occurrences by two orders of magnitude and decreases memory usage by 2.5-80 times in the number of pre-allocated transient clusters compared with other hardware implementations of OSort. The opt-OSort maintains an accuracy comparable to offline OSort and other commonly-used algorithms, with a sorting time of 0.68µs as measured by the hardware-implemented system in both simulated datasets and experimental data. The opt-OSort's ability to handle variations in neural activity caused by electrode drifting is also demonstrated.Significance. These results present a rapid, precise, and robust spike sorting solution suitable for integration into low-power, portable, closed-loop neural control systems and brain-computer interfaces.

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 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. Flies with added inertia were placed inside a virtual reality arena which permitted free rotation about the vertical (yaw) axis. Adding inertia increased the fly's response time yet had little influence on overall gaze stabilization performance. Flies maintained stability following the addition of inertia by adaptively modulating both visuomotor gain and damping. By contrast, mathematical modelling predicted a significant decrease in gaze stabilization performance. Adding inertia altered saccades, however, flies compensated for the added inertia by increasing saccade torque. Taken together, in response to added inertia flies increase reaction time but maintain flight performance through adaptive neural control. Overall, adding inertia decreases closed-loop flight robustness. Our work highlights the flexibility and capacity of motor control in flight.

Dynamic light filtering over dermal opsin as a sensory feedback system in fish color change

Dynamic color change has evolved multiple times, with a physiological basis that has been repeatedly linked to dermal photoreception via the study of excised skin preparations. Despite the widespread prevalence of dermal photoreception, both its physiology and its function in regulating color change remain poorly understood. By examining the morphology, physiology, and optics of dermal photoreception in hogfish (Lachnolaimus maximus), we describe a cellular mechanism in which chromatophore pigment activity (i.e., dispersion and aggregation) alters the transmitted light striking SWS1 receptors in the skin. When dispersed, chromatophore pigment selectively absorbs the short-wavelength light required to activate the skin's SWS1 opsin, which we localized to a morphologically specialized population of putative dermal photoreceptors. As SWS1 is nested beneath chromatophores and thus subject to light changes from pigment activity, one possible function of dermal photoreception in hogfish is to monitor chromatophores to detect information about color change performance. This framework of sensory feedback provides insight into the significance of dermal photoreception among color-changing animals.

Proprioception gates visual object fixation in flying flies

Visual object tracking in animals as diverse as felines, frogs, and fish supports behaviors including predation, predator avoidance, and landscape navigation. Decades of experimental results show that a rigidly body-fixed tethered fly in a "virtual reality" visual flight simulator steers to follow the motion of a vertical bar, thereby "fixating" it on visual midline. This behavior likely reflects a desire to seek natural features such as plant stalks and has inspired algorithms for visual object tracking predicated on robust responses to bar velocity, particularly near visual midline. Using a modified flight simulator equipped with a magnetic pivot to allow frictionless turns about the yaw axis, we discovered that bar fixation as well as smooth steering responses to bar velocity are attenuated or eliminated in yaw-free conditions. Body-fixed Drosophila melanogaster respond to bar oscillation on a stationary ground with frequency-matched wing kinematics and fixate the bar on midline. Yaw-free flies respond to the same stimulus by ignoring the bar and maintaining their original heading. These differences are driven by proprioceptive signals, rather than visual signals, as artificially "clamping" a bar in the periphery of a yaw-free fly has no effect. When presented with a bar and ground oscillating at different frequencies, a yaw-free fly follows the frequency of the ground only, whereas a body-fixed fly robustly steers at the frequencies of both the bar and ground. Our findings support a model in which proprioceptive feedback promote active damping of high-gain optomotor responses to object motion.

Spring and latch dynamics can act as control pathways in ultrafast systems

Ultrafast movements propelled by springs and released by latches are thought limited to energetic adjustments prior to movement, and seemingly cannot adjust once movement begins. Even so, across the tree of life, ultrafast organisms navigate dynamic environments and generate a range of movements, suggesting unrecognized capabilities for control. We develop a framework of control pathways leveraging the non-linear dynamics of spring-propelled, latch-released systems. We analytically model spring dynamics and develop reduced-parameter models of latch dynamics to quantify how they can be tuned internally or through changing external environments. Using Lagrangian mechanics, we test feedforward and feedback control implementation via spring and latch dynamics. We establish through empirically-informed modeling that ultrafast movement can be controllably varied during latch release and spring propulsion. A deeper understanding of the interconnection between multiple control pathways, and the tunability of each control pathway, in ultrafast biomechanical systems presented here has the potential to expand the capabilities of synthetic ultra-fast systems and provides a new framework to understand the behaviors of fast organisms subject to perturbations and environmental non-idealities.

Flies trade off stability and performance via adaptive compensation to wing damage

Physical injury often impairs mobility, which can have dire consequences for survival in animals. Revealing mechanisms of robust biological intelligence to prevent system failure can provide critical insights into how complex brains generate adaptive movement and inspiration to design fault-tolerant robots. For flying animals, physical injury to a wing can have severe consequences, as flight is inherently unstable. Using a virtual reality flight arena, we studied how flying fruit flies compensate for damage to one wing. By combining experimental and mathematical methods, we show that flies compensate for wing damage by corrective wing movement modulated by closed-loop sensing and robust mechanics. Injured flies actively increase damping and, in doing so, modestly decrease flight performance but fly as stably as uninjured flies. Quantifying responses to injury can uncover the flexibility and robustness of biological systems while informing the development of bio-inspired fault-tolerant strategies.

Bumblebees land rapidly by intermittently accelerating and decelerating toward the surface during visually guided landings

Many flying animals parse visual information to control their landing, whereby they can decelerate smoothly by flying at a constant radial optic expansion rate. Here, we studied how bumblebees (Bombus terrestris) use optic expansion information to control their landing, by analyzing 10,005 landing maneuvers on vertical platforms with various optic information, and at three dim light conditions. We showed that bumblebees both decelerate and accelerate during these landings. Bumblebees decelerate by flying at a constant optic expansion rate, but they mostly accelerate toward the surface each time they switched to a new, often higher, optic expansion rate set-point. These transient acceleration phases allow bumblebees to increase their approach speed, and thereby land rapidly and robustly, even in dim twilight conditions. This helps explain why bumblebees are such robust foragers in challenging environmental conditions. The here-proposed sensorimotor landing control system can serve as bio-inspiration for landing control in unmanned aerial vehicles.

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Bumblebees land by intermittently decelerating and accelerating toward a surface

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Acceleration and deceleration phases result from a single visual-motor controller

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The accelerations toward the surface allow bees to maximize their landing speed

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Bumblebees adjust their sensorimotor control response to fly slower in dim light

The Dome: A virtual reality apparatus for freely locomoting rodents

The cognitive map in the hippocampal formation of rodents and other mammals integrates multiple classes of sensory and motor information into a coherent representation of space. Here, we describe the Dome, a virtual reality apparatus for freely locomoting rats, designed to examine the relative contributions of various spatial inputs to an animal’s spatial representation. The Dome was designed to preserve the range of spatial inputs typically available to an animal in free, untethered locomotion while providing the ability to perturb specific sensory cues. We present the design rationale and corresponding specifications of the Dome, along with a variety of engineering and biological analyses to validate the efficacy of the Dome as an experimental tool to examine the interaction between visual information and path integration in place cells in rodents.

De novo learning versus adaptation of continuous control in a manual tracking task

How do people learn to perform tasks that require continuous adjustments of motor output, like riding a bicycle? People rely heavily on cognitive strategies when learning discrete movement tasks, but such time-consuming strategies are infeasible in continuous control tasks that demand rapid responses to ongoing sensory feedback. To understand how people can learn to perform such tasks without the benefit of cognitive strategies, we imposed a rotation/mirror reversal of visual feedback while participants performed a continuous tracking task. We analyzed behavior using a system identification approach, which revealed two qualitatively different components of learning: adaptation of a baseline controller and formation of a new, task-specific continuous controller. These components exhibited different signatures in the frequency domain and were differentially engaged under the rotation/mirror reversal. Our results demonstrate that people can rapidly build a new continuous controller de novo and can simultaneously deploy this process with adaptation of an existing controller.

Auditory Virtual Reality for Insect Phonotaxis

Insects have a sophisticated ability to navigate real environments. Virtual reality (VR) is a powerful tool for analyzing animal navigation in laboratory studies and is the most successful when used in the study of visually guided behaviors. However, the use of VR with non-visual sensory information, such as sound, on which nocturnal insects rely, for analyzing animal navigation has not been fully studied. We developed an auditory VR for the study of auditory navigation in crickets, Gryllus bimaculatus. The system consisted of a spherical treadmill on which a tethered female cricket walked. Sixteen speakers were placed around the cricket for auditory stimuli. The two optical mice attached to the treadmill measured the cricket’s locomotion, and the sound pressure and direction of the auditory stimuli were controlled at 100 Hz based on the position and heading of the cricket relative to a sound source in a virtual arena. We demonstrated that tethered female crickets selectively responded to the conspecific male calling song and localized the sound source in a virtual arena, which was similar to the behavior of freely walking crickets. Further combinations of our system with neurophysiological techniques will help understand the neural mechanisms for insect auditory navigation.

Wing damage affects flight kinematics but not flower tracking performance in hummingbird hawkmoths

Wing integrity is crucial to the many insect species that spend distinct portions of their life in flight. How insects cope with the consequences of wing damage is therefore a central question when studying how robust flight performance is possible with such fragile chitinous wings. It has been shown in a variety of insect species that the loss in lift-force production resulting from wing damage is generally compensated by an increase in wing beat frequency rather than amplitude. The consequences of wing damage for flight performance, however, are less well understood, and vary considerably between species and behavioural tasks. One hypothesis reconciling the varying results is that wing damage might affect fast flight manoeuvres with high acceleration, but not slower ones. To test this hypothesis, we investigated the effect of wing damage on the manoeuvrability of hummingbird hawkmoths (Macroglossum stellatarum) tracking a motorised flower. This assay allowed us to sample a range of movements at different temporal frequencies, and thus assess whether wing damage affected faster or slower flight manoeuvres. We show that hummingbird hawkmoths compensate for the loss in lift force mainly by increasing wing beat amplitude, yet with a significant contribution of wing beat frequency. We did not observe any effects of wing damage on flight manoeuvrability at either high or low temporal frequencies.

Insect-machine hybrid robot

Recently, insect-machine hybrid robots have been developed that incorporate insects into robots or incorporate machines into insects. Most previous studies were motivated to use the function of insects for robots, but this technology can also prove to be useful as an experimental tool for neuroethology. We reviewed hybrid robots in terms of the closed-loop between an insect, a robot, and the real environment. The incorporated biological components provided the robot sensory signals that were received by the insects and the adaptive functions of the brain. The incorporated artificial components permitted us to understand the biological system by controlling insect behavior. Hybrid robots thus extend the roles of mobile robot experiments in neuroethology for both model evaluation and brain function analysis.

Numerical differentiation of noisy data: A unifying multi-objective optimization framework

Computing derivatives of noisy measurement data is ubiquitous in the physical, engineering, and biological sciences, and it is often a critical step in developing dynamic models or designing control. Unfortunately, the mathematical formulation of numerical differentiation is typically ill-posed, and researchers often resort to an ad hoc process for choosing one of many computational methods and its parameters. In this work, we take a principled approach and propose a multi-objective optimization framework for choosing parameters that minimize a loss function to balance the faithfulness and smoothness of the derivative estimate. Our framework has three significant advantages. First, the task of selecting multiple parameters is reduced to choosing a single hyper-parameter. Second, where ground-truth data is unknown, we provide a heuristic for selecting this hyper-parameter based on the power spectrum and temporal resolution of the data. Third, the optimal value of the hyper-parameter is consistent across different differentiation methods, thus our approach unifies vastly different numerical differentiation methods and facilitates unbiased comparison of their results. Finally, we provide an extensive open-source Python library pynumdiff to facilitate easy application to diverse datasets (https://github.com/florisvb/PyNumDiff).

Cerebellar patients have intact feedback control that can be leveraged to improve reaching

It is thought that the brain does not simply react to sensory feedback, but rather uses an internal model of the body to predict the consequences of motor commands before sensory feedback arrives. Time-delayed sensory feedback can then be used to correct for the unexpected—perturbations, motor noise, or a moving target. The cerebellum has been implicated in this predictive control process. Here, we show that the feedback gain in patients with cerebellar ataxia matches that of healthy subjects, but that patients exhibit substantially more phase lag. This difference is captured by a computational model incorporating a Smith predictor in healthy subjects that is missing in patients, supporting the predictive role of the cerebellum in feedback control. Lastly, we improve cerebellar patients’ movement control by altering (phase advancing) the visual feedback they receive from their own self movement in a simplified virtual reality setup.

Active vision shapes and coordinates flight motor responses in flies

Animals use active sensing to respond to sensory inputs and guide future motor decisions. In flight, flies generate a pattern of head and body movements to stabilize gaze. How the brain relays visual information to control head and body movements and how active head movements influence downstream motor control remains elusive. Using a control theoretic framework, we studied the optomotor gaze stabilization reflex in tethered flight and quantified how head movements stabilize visual motion and shape wing steering efforts in fruit flies (Drosophila). By shaping visual inputs, head movements increased the gain of wing steering responses and coordination between stimulus and wings, pointing to a tight coupling between head and wing movements. Head movements followed the visual stimulus in as little as 10 ms-a delay similar to the human vestibulo-ocular reflex-whereas wing steering responses lagged by more than 40 ms. This timing difference suggests a temporal order in the flow of visual information such that the head filters visual information eliciting downstream wing steering responses. Head fixation significantly decreased the mechanical power generated by the flight motor by reducing wingbeat frequency and overall thrust. By simulating an elementary motion detector array, we show that head movements shift the effective visual input dynamic range onto the sensitivity optimum of the motion vision pathway. Taken together, our results reveal a transformative influence of active vision on flight motor responses in flies. Our work provides a framework for understanding how to coordinate moving sensors on a moving body.

Tuning of feedforward control enables stable muscle force-length dynamics after loss of autogenic proprioceptive feedback

Animals must integrate feedforward, feedback and intrinsic mechanical control mechanisms to maintain stable locomotion. Recent studies of guinea fowl (Numida meleagris) revealed that the distal leg muscles rapidly modulate force and work output to minimize perturbations in uneven terrain. Here we probe the role of reflexes in the rapid perturbation responses of muscle by studying the effects of proprioceptive loss. We induced bilateral loss of autogenic proprioception in the lateral gastrocnemius muscle (LG) using self-reinnervation. We compared in vivo muscle dynamics and ankle kinematics in birds with reinnervated and intact LG. Reinnervated and intact LG exhibit similar steady state mechanical function and similar work modulation in response to obstacle encounters. Reinnervated LG exhibits 23ms earlier steady-state activation, consistent with feedforward tuning of activation phase to compensate for lost proprioception. Modulation of activity duration is impaired in rLG, confirming the role of reflex feedback in regulating force duration in intact muscle.

Variability in locomotor dynamics reveals the critical role of feedback in task control

Animals vary considerably in size, shape, and physiological features across individuals, but yet achieve remarkably similar behavioral performances. We examined how animals compensate for morphophysiological variation by measuring the system dynamics of individual knifefish (Eigenmannia virescens) in a refuge tracking task. Kinematic measurements of Eigenmannia were used to generate individualized estimates of each fish’s locomotor plant and controller, revealing substantial variability between fish. To test the impact of this variability on behavioral performance, these models were used to perform simulated ‘brain transplants’—computationally swapping controllers and plants between individuals. We found that simulated closed-loop performance was robust to mismatch between plant and controller. This suggests that animals rely on feedback rather than precisely tuned neural controllers to compensate for morphophysiological variability.

People come in different shapes and sizes, but most will perform similarly well if asked to complete a task requiring fine manual dexterity – such as holding a pen or picking up a single grape. How can different individuals, with different sized hands and muscles, produce such similar movements? One explanation is that an individual’s brain and nervous system become precisely tuned to mechanics of the body’s muscles and skeleton. An alternative explanation is that brain and nervous system use a more “robust” control policy that can compensate for differences in the body by relying on feedback from the senses to guide the movements.

To distinguish between these two explanations, Uyanik et al. turned to weakly electric freshwater fish known as glass knifefish. These fish seek refuge within root systems, reed grass and among other objects in the water. They swim backwards and forwards to stay hidden despite constantly changing currents. Each fish shuttles back and forth by moving a long ribbon-like fin on the underside of its body. Uyanik et al. measured the movements of the ribbon fin under controlled conditions in the laboratory, and then used the data to create computer models of the brain and body of each fish. The models of each fish’s brain and body were quite different.

To study how the brain interacts with the body, Uyanik et al. then conducted experiments reminiscent of those described in the story of Frankenstein and transplanted the brain from each computer model into the body of different model fish. These “brain swaps” had almost no effect on the model’s simulated swimming behavior. Instead, these “Frankenfish” used sensory feedback to compensate for any mismatch between their brain and body.

This suggests that, for some behaviors, an animal’s brain does not need to be precisely tuned to the specific characteristics of its body. Instead, robust control of movement relies on many seemingly redundant systems that provide sensory feedback. This has implications for the field of robotics. It further suggests that when designing robots, engineers should prioritize enabling the robots to use sensory feedback to cope with unexpected events, a well-known idea in control engineering.

Real-time contextual feedback for close-loop control of navigation

OBJECTIVE

Close-loop control of brain and behavior will benefit from real-time detection of behavioral events to enable low-latency communication with peripheral devices. In animal experiments, this is typically achieved by using sparsely distributed (embedded) sensors that detect animal presence in select regions of interest. High-speed cameras provide high-density sampling across large arenas, capturing the richness of animal behavior, however, the image processing bottleneck prohibits real-time feedback in the context of rapidly evolving behaviors.

APPROACH

Here we developed an open-source software, named PolyTouch, to track animal behavior in large arenas and provide rapid close-loop feedback in ~5.7 ms, ie. average latency from the detection of an event to analog stimulus delivery, e.g. auditory tone, TTL pulse, when tracking a single body. This stand-alone software is written in JAVA. The included wrapper for MATLAB provides experimental flexibility for data acquisition, analysis and visualization.

MAIN RESULTS

As a proof-of-principle application we deployed the PolyTouch for place awareness training. A user-defined portion of the arena was used as a virtual target; visit (or approach) to the target triggered auditory feedback. We show that mice develop awareness to virtual spaces, tend to stay shorter and move faster when they reside in the virtual target zone if their visits are coupled to relatively high stimulus intensity (⩾49 dB). Thus, close-loop presentation of perceived aversive feedback is sufficient to condition mice to avoid virtual targets within the span of a single session (~20 min).

SIGNIFICANCE

Neuromodulation techniques now allow control of neural activity in a cell-type specific manner in spiking resolution. Using animal behavior to drive closed-loop control of neural activity would help to address the neural basis of behavioral state and environmental context-dependent information processing in the brain.

Body stiffness and damping depend sensitively on the timing of muscle activation in lampreys

Unlike most manmade machines, animals move through their world using flexible bodies and appendages, which bend due to internal muscle and body forces, and also due to forces from the environment. Fishes in particular must cope with fluid dynamic forces that not only resist their overall swimming movements but also may have unsteady flow patterns, vortices, and turbulence, many of which occur more rapidly than what the nervous system can process. Has natural selection led to mechanical properties of fish bodies and their component tissues that can respond very quickly to environmental perturbations? Here, we focus on the mechanical properties of isolated muscle tissue and of the entire intact body in the silver lamprey, Ichthyomyzon unicuspis. We developed two modified work loop protocols to determine the effect of small perturbations on the whole body and on isolated segments of muscle as a function of muscle activation and phase within the swimming cycle. First, we examined how the mechanical properties of the whole lamprey body change depending on the timing of muscle activity. Relative to passive muscle, muscle activation can modulate the effective stiffness by about two-fold and modulate the effective damping by >10-fold depending on the activation phase. Next, we performed a standard work loop test on small sections of axial musculature while adding low-amplitude sinusoidal perturbations at specific frequencies. We modeled the data using a new system identification technique based on time-periodic system analysis and harmonic transfer functions (HTFs) and used the resulting models to predict muscle function under novel conditions. We found that the effective stiffness and damping of muscle varies during the swimming cycle, and that the timing of activation can alter both the magnitude and timing of peak stiffness and damping. Moreover, the response of the isolated muscle was highly nonlinear and length dependent, but the body's response was much more linear. We applied the resulting HTFs from our experiments to explore the effect of pairs of antagonistic muscles. The results suggest that when muscles work against each other as antagonists, the combined system has weaker nonlinearities than either muscle segment alone. Together, these results begin to provide an integrative understanding of how activation timing can tune the mechanical response properties of muscles, enabling fish to swim effectively in their complex and unpredictable environment.

Complementary spatial and timing control in rhythmic arm movements

Volitional rhythmic motor behaviors such as limb cycling and locomotion exhibit spatial and timing regularity. Such rhythmic movements are executed in the presence of exogenous visual and nonvisual cues, and previous studies have shown the pivotal role that vision plays in guiding spatial and temporal regulation. However, the influence of nonvisual information conveyed through auditory or touch sensory pathways, and its effect on control, remains poorly understood. To characterize the function of nonvisual feedback in rhythmic arm control, we designed a paddle juggling task in which volunteers bounced a ball off a rigid elastic surface to a target height in virtual reality by moving a physical handle with the right hand. Feedback was delivered at two key phases of movement: visual feedback at ball peaks only and simultaneous audio and haptic feedback at ball-paddle collisions. In contrast to previous work, we limited visual feedback to the minimum required for jugglers to assess spatial accuracy, and we independently perturbed the spatial dimensions and the timing of feedback. By separately perturbing this information, we evoked dissociable effects on spatial accuracy and timing, confirming that juggling, and potentially other rhythmic tasks, involves two complementary processes with distinct dynamics: spatial error correction and feedback timing synchronization. Moreover, we show evidence that audio and haptic feedback provide sufficient information for the brain to control the timing synchronization process by acting as a metronome-like cue that triggers hand movement. NEW & NOTEWORTHY Vision contains rich information for control of rhythmic arm movements; less is known, however, about the role of nonvisual feedback (touch and sound). Using a virtual ball bouncing task allowing independent real-time manipulation of spatial location and timing of cues, we show their dissociable roles in regulating motor behavior. We confirm that visual feedback is used to correct spatial error and provide new evidence that nonvisual event cues act to reset the timing of arm movements.

RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience

Closed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.

The roles of vision and antennal mechanoreception in hawkmoth flight control

Flying animals need continual sensory feedback about their body position and orientation for flight control. The visual system provides essential but slow feedback. In contrast, mechanosensory channels can provide feedback at much shorter timescales. How the contributions from these two senses are integrated remains an open question in most insect groups. In Diptera, fast mechanosensory feedback is provided by organs called halteres and is crucial for the control of rapid flight manoeuvres, while vision controls manoeuvres in lower temporal frequency bands. Here, we have investigated the visual-mechanosensory integration in the hawkmoth Macroglossum stellatarum. They represent a large group of insects that use Johnston’s organs in their antennae to provide mechanosensory feedback on perturbations in body position. Our experiments show that antennal mechanosensory feedback specifically mediates fast flight manoeuvres, but not slow ones. Moreover, we did not observe compensatory interactions between antennal and visual feedback.

Insect and insect-inspired aerodynamics: unsteadiness, structural mechanics and flight control

Flying insects impress by their versatility and have been a recurrent source of inspiration for engineering devices. A large body of literature has focused on various aspects of insect flight, with an essential part dedicated to the dynamics of flapping wings and their intrinsically unsteady aerodynamic mechanisms. Insect wings flex during flight and a better understanding of structural mechanics and aeroelasticity is emerging. Most recently, insights from solid and fluid mechanics have been integrated with physiological measurements from visual and mechanosensors in the context of flight control in steady airs and through turbulent conditions. We review the key recent advances concerning flight in unsteady environments and how the multi-body mechanics of the insect structure-wings and body-are at the core of the flight control question. The issues herein should be considered when applying bio-informed design principles to robotic flapping wings.

Closed-Loop Control of Active Sensing Movements Regulates Sensory Slip

Active sensing involves the production of motor signals for the purpose of acquiring sensory information [1-3]. The most common form of active sensing, found across animal taxa and behaviors, involves the generation of movements-e.g., whisking [4-6], touching [7, 8], sniffing [9, 10], and eye movements [11]. Active sensing movements profoundly affect the information carried by sensory feedback pathways [12-15] and are modulated by both top-down goals (e.g., measuring weight versus texture [1, 16]) and bottom-up stimuli (e.g., lights on or off [12]), but it remains unclear whether and how these movements are controlled in relation to the ongoing feedback they generate. To investigate the control of movements for active sensing, we created an experimental apparatus for freely swimming weakly electric fish, Eigenmannia virescens, that modulates the gain of reafferent feedback by adjusting the position of a refuge based on real-time videographic measurements of fish position. We discovered that fish robustly regulate sensory slip via closed-loop control of active sensing movements. Specifically, as fish performed the task of maintaining position inside the refuge [17-22], they dramatically up- or downregulated fore-aft active sensing movements in relation to a 4-fold change of experimentally modulated reafferent gain. These changes in swimming movements served to maintain a constant magnitude of sensory slip. The magnitude of sensory slip depended on the presence or absence of visual cues. These results indicate that fish use two controllers: one that controls the acquisition of information by regulating feedback from active sensing movements and another that maintains position in the refuge, a control structure that may be ubiquitous in animals [23, 24].

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.

The role of curvature feedback in the energetics and dynamics of lamprey swimming: A closed-loop model

Like other animals, lampreys have a central pattern generator (CPG) circuit that activates muscles for locomotion and also adjusts the activity to respond to sensory inputs from the environment. Such a feedback system is crucial for responding appropriately to unexpected perturbations, but it is also active during normal unperturbed steady swimming and influences the baseline swimming pattern. In this study, we investigate different functional forms of body curvature-based sensory feedback and evaluate their effects on steady swimming energetics and kinematics, since little is known experimentally about the functional form of curvature feedback. The distributed CPG is modeled as chains of coupled oscillators. Pairs of phase oscillators represent the left and right sides of segments along the lamprey body. These activate muscles that flex the body and move the lamprey through a fluid environment, which is simulated using a full Navier-Stokes model. The emergent curvature of the body then serves as an input to the CPG oscillators, closing the loop. We consider two forms of feedback, each consistent with experimental results on lamprey proprioceptive sensory receptors. The first, referred to as directional feedback, excites or inhibits the oscillators on the same side, depending on the sign of a chosen gain parameter, and has the opposite effect on oscillators on the opposite side. We find that directional feedback does not affect beat frequency, but does change the duration of muscle activity. The second feedback model, referred to as magnitude feedback, provides a symmetric excitatory or inhibitory effect to oscillators on both sides. This model tends to increase beat frequency and reduces the energetic cost to the lamprey when the gain is high and positive. With both types of feedback, the body curvature has a similar magnitude. Thus, these results indicate that the same magnitude of curvature-based feedback on the CPG with different functional forms can cause distinct differences in swimming performance.

When animals move, they receive sensory inputs, which in turn are used to modulate the movement. Relatively little is known about how these inputs affect performance during steady locomotion. Using a computational model of a swimming lamprey, we investigated two different types of feedback, both consistent with experimental data. Both have strong, but different, effects on swimming speed and energy consumption, suggesting that sensory feedback is crucial not just for responding to perturbations, but also for high performance steady locomotion.

Measuring behavior across scales

The need for high-throughput, precise, and meaningful methods for measuring behavior has been amplified by our recent successes in measuring and manipulating neural circuitry. The largest challenges associated with moving in this direction, however, are not technical but are instead conceptual: what numbers should one put on the movements an animal is performing (or not performing)? In this review, I will describe how theoretical and data analytical ideas are interfacing with recently-developed computational and experimental methodologies to answer these questions across a variety of contexts, length scales, and time scales. I will attempt to highlight commonalities between approaches and areas where further advances are necessary to place behavior on the same quantitative footing as other scientific fields.

Comparative system identification of flower tracking performance in three hawkmoth species reveals adaptations for dim light vision

Flight control in insects is heavily dependent on vision. Thus, in dim light, the decreased reliability of visual signal detection also prompts consequences for insect flight. We have an emerging understanding of the neural mechanisms that different species employ to adapt the visual system to low light. However, much less explored are comparative analyses of how low light affects the flight behaviour of insect species, and the corresponding links between physiological adaptations and behaviour. We investigated whether the flower tracking behaviour of three hawkmoth species with different diel activity patterns revealed luminance-dependent adaptations, using a system identification approach. We found clear luminance-dependent differences in flower tracking in all three species, which were explained by a simple luminance-dependent delay model, which generalized across species. We discuss physiological and anatomical explanations for the variance in tracking responses, which could not be explained by such simple models. Differences between species could not be explained by the simple delay model. However, in several cases, they could be explained through the addition on a second model parameter, a simple scaling term, that captures the responsiveness of each species to flower movements. Thus, we demonstrate here that much of the variance in the luminance-dependent flower tracking responses of hawkmoths with different diel activity patterns can be captured by simple models of neural processing.This article is part of the themed issue 'Vision in dim light'.

Dynamic modulation of visual and electrosensory gains for locomotor control

Animal nervous systems resolve sensory conflict for the control of movement. For example, the glass knifefish, Eigenmannia virescens, relies on visual and electrosensory feedback as it swims to maintain position within a moving refuge. To study how signals from these two parallel sensory streams are used in refuge tracking, we constructed a novel augmented reality apparatus that enables the independent manipulation of visual and electrosensory cues to freely swimming fish (n = 5). We evaluated the linearity of multisensory integration, the change to the relative perceptual weights given to vision and electrosense in relation to sensory salience, and the effect of the magnitude of sensory conflict on sensorimotor gain. First, we found that tracking behaviour obeys superposition of the sensory inputs, suggesting linear sensorimotor integration. In addition, fish rely more on vision when electrosensory salience is reduced, suggesting that fish dynamically alter sensorimotor gains in a manner consistent with Bayesian integration. However, the magnitude of sensory conflict did not significantly affect sensorimotor gain. These studies lay the theoretical and experimental groundwork for future work investigating multisensory control of locomotion.

In situ vocal fold properties and pitch prediction by dynamic actuation of the songbird syrinx

The biomechanics of sound production forms an integral part of the neuromechanical control loop of avian vocal motor control. However, we critically lack quantification of basic biomechanical parameters describing the vocal organ, the syrinx, such as material properties of syringeal elements, forces and torques exerted on, and motion of the syringeal skeleton during song. Here, we present a novel marker-based 3D stereoscopic imaging technique to reconstruct 3D motion of servo-controlled actuation of syringeal muscle insertions sites in vitro and focus on two muscles controlling sound pitch. We furthermore combine kinematic analysis with force measurements to quantify elastic properties of sound producing medial labia (ML). The elastic modulus of the zebra finch ML is 18 kPa at 5% strain, which is comparable to elastic moduli of mammalian vocal folds. Additionally ML lengthening due to musculus syringealis ventralis (VS) shortening is intrinsically constraint at maximally 12% strain. Using these values we predict sound pitch to range from 350–800 Hz by VS modulation, corresponding well to previous observations. The presented methodology allows for quantification of syringeal skeleton motion and forces, acoustic effects of muscle recruitment, and calibration of computational birdsong models, enabling experimental access to the entire neuromechanical control loop of vocal motor control.

Using insects to drive mobile robots - hybrid robots bridge the gap between biological and artificial systems

The use of mobile robots is an effective method of validating sensory-motor models of animals in a real environment. The well-identified insect sensory-motor systems have been the major targets for modeling. Furthermore, mobile robots implemented with such insect models attract engineers who aim to avail advantages from organisms. However, directly comparing the robots with real insects is still difficult, even if we successfully model the biological systems, because of the physical differences between them. We developed a hybrid robot to bridge the gap. This hybrid robot is an insect-controlled robot, in which a tethered male silkmoth (Bombyx mori) drives the robot in order to localize an odor source. This robot has the following three advantages: 1) from a biomimetic perspective, the robot enables us to evaluate the potential performance of future insect-mimetic robots; 2) from a biological perspective, the robot enables us to manipulate the closed-loop of an onboard insect for further understanding of its sensory-motor system; and 3) the robot enables comparison with insect models as a reference biological system. In this paper, we review the recent works regarding insect-controlled robots and discuss the significance for both engineering and biology.

Eupnea, tachypnea, and autoresuscitation in a closed-loop respiratory control model

How sensory information influences the dynamics of rhythm generation varies across systems, and general principles for understanding this aspect of motor control are lacking. Determining the origin of respiratory rhythm generation is challenging because the mechanisms in a central circuit considered in isolation may be different from those in the intact organism. We analyze a closed-loop respiratory control model incorporating a central pattern generator (CPG), the Butera-Rinzel-Smith (BRS) model, together with lung mechanics, oxygen handling, and chemosensory components. We show that 1) embedding the BRS model neuron in a control loop creates a bistable system; 2) although closed-loop and open-loop (isolated) CPG systems both support eupnea-like bursting activity, they do so via distinct mechanisms; 3) chemosensory feedback in the closed loop improves robustness to variable metabolic demand; 4) the BRS model conductances provide an autoresuscitation mechanism for recovery from transient interruption of chemosensory feedback; and 5) the in vitro brain stem CPG slice responds to hypoxia with transient bursting that is qualitatively similar to in silico autoresuscitation. Bistability of bursting and tonic spiking in the closed-loop system corresponds to coexistence of eupnea-like breathing, with normal minute ventilation and blood oxygen level and a tachypnea-like state, with pathologically reduced minute ventilation and critically low blood oxygen. Disruption of the normal breathing rhythm, through either imposition of hypoxia or interruption of chemosensory feedback, can push the system from the eupneic state into the tachypneic state. We use geometric singular perturbation theory to analyze the system dynamics at the boundary separating eupnea-like and tachypnea-like outcomes.NEW & NOTEWORTHY A common challenge facing rhythmic biological processes is the adaptive regulation of central pattern generator (CPG) activity in response to sensory feedback. We apply dynamical systems tools to understand several properties of a closed-loop respiratory control model, including the coexistence of normal and pathological breathing, robustness to changes in metabolic demand, spontaneous autoresuscitation in response to hypoxia, and the distinct mechanisms that underlie rhythmogenesis in the intact control circuit vs. the isolated, open-loop CPG.

Limitations of rotational manoeuvrability in insects and hummingbirds: evaluating the effects of neuro-biomechanical delays and muscle mechanical power

Flying animals ranging in size from fruit flies to hummingbirds are nimble fliers with remarkable rotational manoeuvrability. The degrees of manoeuvrability among these animals, however, are noticeably diverse and do not simply follow scaling rules of flight dynamics or muscle power capacity. As all manoeuvres emerge from the complex interactions of neural, physiological and biomechanical processes of an animal's flight control system, these processes give rise to multiple limiting factors that dictate the maximal manoeuvrability attainable by an animal. Here using functional models of an animal's flight control system, we investigate the effects of three such limiting factors, including neural and biomechanical (from limited flapping frequency) delays and muscle mechanical power, for two insect species and two hummingbird species, undergoing roll, pitch and yaw rotations. The results show that for animals with similar degree of manoeuvrability, for example, fruit flies and hummingbirds, the underlying limiting factors are different, as the manoeuvrability of fruit flies is only limited by neural delays and that of hummingbirds could be limited by all three factors. In addition, the manoeuvrability also appears to be the highest about the roll axis as it requires the least muscle mechanical power and can tolerate the largest neural delays.

Using a System Identification Approach to Investigate Subtask Control during Human Locomotion

Here we apply a control theoretic view of movement to the behavior of human locomotion with the goal of using perturbations to learn about subtask control. Controlling one's speed and maintaining upright posture are two critical subtasks, or underlying functions, of human locomotion. How the nervous system simultaneously controls these two subtasks was investigated in this study. Continuous visual and mechanical perturbations were applied concurrently to subjects (n = 20) as probes to investigate these two subtasks during treadmill walking. Novel application of harmonic transfer function (HTF) analysis to human motor behavior was used, and these HTFs were converted to the time-domain based representation of phase-dependent impulse response functions (ϕIRFs). These ϕIRFs were used to identify the mapping from perturbation inputs to kinematic and electromyographic (EMG) outputs throughout the phases of the gait cycle. Mechanical perturbations caused an initial, passive change in trunk orientation and, at some phases of stimulus presentation, a corrective trunk EMG and orientation response. Visual perturbations elicited a trunk EMG response prior to a trunk orientation response, which was subsequently followed by an anterior-posterior displacement response. This finding supports the notion that there is a temporal hierarchy of functional subtasks during locomotion in which the control of upper-body posture precedes other subtasks. Moreover, the novel analysis we apply has the potential to probe a broad range of rhythmic behaviors to better understand their neural control.

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.

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Robotic odor source localization has been a challenging area and one to which biological knowledge has been expected to contribute, as finding odor sources is an essential task for organism survival. Insects are well-studied organisms with regard to odor tracking, and their behavioral strategies have been applied to mobile robots for evaluation. This "bottom-up" approach is a fundamental way to develop biomimetic robots; however, the biological analyses and the modeling of behavioral mechanisms are still ongoing. Therefore, it is still unknown how such a biological system actually works as the controller of a robotic platform. To answer this question, we have developed an insect-controlled robot in which a male adult silkmoth (Bombyx mori) drives a robot car in response to odor stimuli; this can be regarded as a prototype of a future insect-mimetic robot. In the cockpit of the robot, a tethered silkmoth walked on an air-supported ball and an optical sensor measured the ball rotations. These rotations were translated into the movement of the two-wheeled robot. The advantage of this "hybrid" approach is that experimenters can manipulate any parameter of the robot, which enables the evaluation of the odor-tracking capability of insects and provides useful suggestions for robotic odor-tracking. Furthermore, these manipulations are non-invasive ways to alter the sensory-motor relationship of a pilot insect and will be a useful technique for understanding adaptive behaviors.

Entrainment Ranges for Chains of Forced Neural and Phase Oscillators

Sensory input to the lamprey central pattern generator (CPG) for locomotion is known to have a significant role in modulating lamprey swimming. Lamprey CPGs are known to have the ability to entrain to a bending stimulus, that is, in the presence of a rhythmic signal, the CPG will change its frequency to match the stimulus frequency. Bending experiments in which the lamprey spinal cord has been removed and mechanically bent back and forth at a single point have been used to determine the range of frequencies that can entrain the CPG rhythm. First, we model the lamprey locomotor CPG as a chain of neural oscillators with three classes of neurons and sinusoidal forcing representing edge cell input. We derive a phase model using the connections described in the neural model. This results in a simpler model yet maintains some properties of the neural model. For both the neural model and the derived phase model, entrainment ranges are computed for forcing at different points along the chain while varying both intersegmental coupling strength and the coupling strength between the forcer and chain. Entrainment ranges for chains with nonuniform intersegmental coupling asymmetry are larger when forcing is applied to the middle of the chain than when it is applied to either end, a result that is qualitatively similar to the experimental results. In the limit of weak coupling in the chain, the entrainment results of the neural model approach the entrainment results for the derived phase model. Both biological experiments and the robustness of non-monotonic entrainment ranges as a function of the forcing position across different classes of CPG models with nonuniform asymmetric coupling suggest that a specific property of the intersegmental coupling of the CPG is key to entrainment.

A review on locomotion robophysics: the study of movement at the intersection of robotics, soft matter and dynamical systems

Discovery of fundamental principles which govern and limit effective locomotion (self-propulsion) is of intellectual interest and practical importance. Human technology has created robotic moving systems that excel in movement on and within environments of societal interest: paved roads, open air and water. However, such devices cannot yet robustly and efficiently navigate (as animals do) the enormous diversity of natural environments which might be of future interest for autonomous robots; examples include vertical surfaces like trees and cliffs, heterogeneous ground like desert rubble and brush, turbulent flows found near seashores, and deformable/flowable substrates like sand, mud and soil. In this review we argue for the creation of a physics of moving systems-a 'locomotion robophysics'-which we define as the pursuit of principles of self-generated motion. Robophysics can provide an important intellectual complement to the discipline of robotics, largely the domain of researchers from engineering and computer science. The essential idea is that we must complement the study of complex robots in complex situations with systematic study of simplified robotic devices in controlled laboratory settings and in simplified theoretical models. We must thus use the methods of physics to examine both locomotor successes and failures using parameter space exploration, systematic control, and techniques from dynamical systems. Using examples from our and others' research, we will discuss how such robophysical studies have begun to aid engineers in the creation of devices that have begun to achieve life-like locomotor abilities on and within complex environments, have inspired interesting physics questions in low dimensional dynamical systems, geometric mechanics and soft matter physics, and have been useful to develop models for biological locomotion in complex terrain. The rapidly decreasing cost of constructing robot models with easy access to significant computational power bodes well for scientists and engineers to engage in a discipline which can readily integrate experiment, theory and computation.

Integration of parallel mechanosensory and visual pathways resolved through sensory conflict

The acquisition of information from parallel sensory pathways is a hallmark of coordinated movement in animals. Insect flight, for example, relies on both mechanosensory and visual pathways. Our challenge is to disentangle the relative contribution of each modality to the control of behavior. Toward this end, we show an experimental and analytical framework leveraging sensory conflict, a means for independently exciting and modeling separate sensory pathways within a multisensory behavior. As a model, we examine the hovering flower-feeding behavior in the hawkmoth Manduca sexta In the laboratory, moths feed from a robotically actuated two-part artificial flower that allows independent presentation of visual and mechanosensory cues. Freely flying moths track lateral flower motion stimuli in an assay spanning both coupled motion, in which visual and mechanosensory cues follow the same motion trajectory, and sensory conflict, in which the two sensory modalities encode different motion stimuli. Applying a frequency-domain system identification analysis, we find that the tracking behavior is, in fact, multisensory and arises from a linear summation of visual and mechanosensory pathways. The response dynamics are highly preserved across individuals, providing a model for predicting the response to novel multimodal stimuli. Surprisingly, we find that each pathway in and of itself is sufficient for driving tracking behavior. When multiple sensory pathways elicit strong behavioral responses, this parallel architecture furnishes robustness via redundancy.

Temporal Code-Driven Stimulation: Definition and Application to Electric Fish Signaling

Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox.

Walking dynamics are symmetric (enough)

Many biological phenomena such as locomotion, circadian cycles and breathing are rhythmic in nature and can be modelled as rhythmic dynamical systems. Dynamical systems modelling often involves neglecting certain characteristics of a physical system as a modelling convenience. For example, human locomotion is frequently treated as symmetric about the sagittal plane. In this work, we test this assumption by examining human walking dynamics around the steady state (limit-cycle). Here, we adapt statistical cross-validation in order to examine whether there are statistically significant asymmetries and, even if so, test the consequences of assuming bilateral symmetry anyway. Indeed, we identify significant asymmetries in the dynamics of human walking, but nevertheless show that ignoring these asymmetries results in a more consistent and predictive model. In general, neglecting evident characteristics of a system can be more than a modelling convenience--it can produce a better model.