Phase-dependent presynaptic modulation of mechanosensory signals in the locust flight system

Central pattern generating networks in insect locomotion

Central pattern generators (CPGs) are neural circuits that based on their connectivity can generate rhythmic and patterned output in the absence of rhythmic external inputs. This property makes CPGs crucial elements in the generation of many kinds of rhythmic motor behaviors in insects, such as flying, walking, swimming, or crawling. Arguably representing the most diverse group of animals, insects utilize at least one of these types of locomotion during one stage of their ontogenesis. Insects have been extensively used to study the neural basis of rhythmic motor behaviors, and particularly the structure and operation of CPGs involved in locomotion. Here, we review insect locomotion with regard to flying, walking, and crawling, and we discuss the contribution of central pattern generation to these three forms of locomotion. In each case, we compare and contrast the topology and structure of the CPGs, and we point out how these factors are involved in the generation of the respective motor pattern. We focus on the importance of sensory information for establishing a functional motor output and we indicate behavior-specific adaptations. Furthermore, we report on the mechanisms underlying coordination between different body parts. Last but not least, by reviewing the state-of-the-art knowledge concerning the role of CPGs in insect locomotion, we endeavor to create a common ground, upon which future research in the field of motor control in insects can build.

A New Perspective on Predictive Motor Signaling

Adaptive behavior relies on complex neural processing in multiple interacting networks of both motor and sensory systems. One such interaction employs intrinsic neuronal signals, so-called 'corollary discharge' or 'efference copy', that may be used to predict the sensory consequences of a specific behavioral action, thereby enabling self-generated (reafferent) sensory information and extrinsic (exafferent) sensory inflow to be dissociated. Here, by using well-established examples, we seek to identify the distinguishing features of corollary discharge and efference copy within the framework of predictive motor-to-sensory system coordination. We then extend the more general concept of predictive signaling by showing how neural replicas of a particular motor command not only inform sensory pathways in order to gate reafferent stimulation, but can also be used to directly coordinate distinct and otherwise independent behaviors to the original motor task. Moreover, this motor-to-motor pairing may additionally extend to a gating of sensory input to either or both of the coupled systems. The employment of predictive internal signaling in such motor systems coupling and remote sensory input control thus adds to our understanding of how an organism's central nervous system is able to coordinate the activity of multiple and generally disparate motor and sensory circuits in the production of effective behavior.

State-dependent sensorimotor gating in a rhythmic motor system

Sensory feedback influences motor circuits and/or their projection neuron inputs to adjust ongoing motor activity, but its efficacy varies. Currently, less is known about regulation of sensory feedback onto projection neurons that control downstream motor circuits than about sensory regulation of the motor circuit neurons themselves. In this study, we tested whether sensory feedback onto projection neurons is sensitive only to activation of a motor system, or also to the modulatory state underlying that activation, using the crab Cancer borealis stomatogastric nervous system. We examined how proprioceptor neurons (gastropyloric receptors, GPRs) influence the gastric mill (chewing) circuit neurons and the projection neurons (MCN1, CPN2) that drive the gastric mill rhythm. During gastric mill rhythms triggered by the mechanosensory ventral cardiac neurons (VCNs), GPR was shown previously to influence gastric mill circuit neurons, but its excitation of MCN1/CPN2 was absent. In this study, we tested whether GPR effects on MCN1/CPN2 are also absent during gastric mill rhythms triggered by the peptidergic postoesophageal commissure (POC) neurons. The VCN and POC pathways both trigger lasting MCN1/CPN2 activation, but their distinct influence on circuit feedback to these neurons produces different gastric mill motor patterns. We show that GPR excites MCN1 and CPN2 during the POC-gastric mill rhythm, altering their firing rates and activity patterns. This action changes both phases of the POC-gastric mill rhythm, whereas GPR only alters one phase of the VCN-gastric mill rhythm. Thus sensory feedback to projection neurons can be gated as a function of the modulatory state of an active motor system, not simply switched on/off with the onset of motor activity.NEW & NOTEWORTHY Sensory feedback influences motor systems (i.e., motor circuits and their projection neuron inputs). However, whether regulation of sensory feedback to these projection neurons is consistent across different versions of the same motor pattern driven by the same motor system was not known. We found that gating of sensory feedback to projection neurons is determined by the modulatory state of the motor system, and not simply by whether the system is active or inactive.

Body side-specific control of motor activity during turning in a walking animal

Animals and humans need to move deftly and flexibly to adapt to environmental demands. Despite a large body of work on the neural control of walking in invertebrates and vertebrates alike, the mechanisms underlying the motor flexibility that is needed to adjust the motor behavior remain largely unknown. Here, we investigated optomotor-induced turning and the neuronal mechanisms underlying the differences between the leg movements of the two body sides in the stick insect Carausius morosus. We present data to show that the generation of turning kinematics in an insect are the combined result of descending unilateral commands that change the leg motor output via task-specific modifications in the processing of local sensory feedback as well as modification of the activity of local central pattern generating networks in a body-side-specific way. To our knowledge, this is the first study to demonstrate the specificity of such modifications in a defined motor task.

DOI:http://dx.doi.org/10.7554/eLife.13799.001

Walking along a curve or turning is a complex manoeuvre for the nervous system, as it must coordinate different leg movements on each side of the body. Rhythmic processes such as walking are controlled by networks of neurons called central pattern generators. The resulting movements can be adjusted by feedback from sense organs in response to environmental conditions. For example, sensory feedback that provides information about the load placed on each leg, allows the animal to control the duration of a stance. How the nerve cells, or neurons, involved in these processes work together to produce complex, flexible movements such as turning is largely unknown.

Previous work on how the brain negotiates turning movements has been carried out mostly in animals that swim or fly. To understand what happens during walking, Gruhn et al. monitored stick insects that walked in a curve on a slippery surface, and recorded the electrical activity within the animals' nervous system as they turned.

By comparing the activity of the nervous system on each side of the body while the insects walked a curve, Gruhn et al. found that the nervous system uses at least three different mechanisms to produce the different movements on the inside and outside. Firstly, the sensory feedback signals that communicate the load on the leg are processed in the legs on the outside of the curve to support forward steps, while they are processed on the inside legs to support forward, sideward, and backward steps. Secondly, the motor activity produced by the central pattern generator is modulated to be stronger for the muscle that moves the leg backward on the outside of the curve. At the same time, this activity is stronger for the muscle that moves the leg forward on the inside of the curve. Thirdly, signals from a front leg influence the movement of the other legs on the same side of the body. This influence is strong on the inside and weak on the outside of the curve.

Together or separately, these three mechanisms could provide the animal with the means to perform turns in all their different curvatures. Future work will need to work out exactly which local neurons process the signals sent from the brain to control movement.

DOI:http://dx.doi.org/10.7554/eLife.13799.002

Frequency control of motor patterning by negative sensory feedback

The sensory system plays a key role in the generation of behavior by providing the nervous system with information about the environment and feedback about body movements such that motor output can continuously be adapted to changing circumstances. Although the effects of sensory organs on nervous system function have been demonstrated in many systems, the impact of sensory activity has rarely been studied in conditions in which motor output and sensory activity can interact as they do in behaving animals. In such situations, emergent properties may surface and govern the characteristics of the motor system. We studied the dynamics of sensorimotor interaction with a combination of electrophysiological experiments and computational modeling in the locust flight pattern generator, including its sensory components. The locust flight motor output is produced by a central pattern generator that interacts with phasic sensory feedback from the tegula, a proprioceptor that signals downstroke movement of the wing. We modeled the flight control system, and we tested the model predictions by replacing tegula feedback in the animal with artificial feedback through computer-controlled electric stimulation of the appropriate sensory nerves. With reference to the cycle frequency in the locust flight rhythm, our results show that motor patterns can be regulated via the variation of sensory feedback loops. In closed-loop conditions, tegula feedback strength determines cycle frequency in the model and the biological preparation such that stronger feedback results in lower frequencies. This regulatory mechanism appears to be a general emergent property of negative feedback systems.

Neural mechanisms for prediction: do insects have forward models?

'Forward models' are increasingly recognized as a crucial explanatory concept in vertebrate motor control. The essential idea is that an important function implemented by nervous systems is prediction of the sensory consequences of action. This is often associated with higher cognitive capabilities; however, many of the purposes forward models are thought to have analogues in insect behaviour, and the concept is closely connected to those of 'efference copy' and 'corollary discharge'. This article considers recent evidence from invertebrates that demonstrates the predictive modulation of sensory processes by motor output, and discusses to what extent this supports the conclusion that insect nervous systems also implement forward models. Several promising directions for further research are outlined.

Presynaptic modulation of sensory neurons in the segmental ganglia of arthropods

The afferent terminals of arthropod sensory neurones receive abundant input synapses, usually closely intermingled with the sites of synaptic output. The majority of the input synapses use the neurotransmitter GABA, but in some afferents there is a significant glutamatergic or histaminergic component. GABA and histamine shunt afferent action potentials by increasing chloride conductance. Though glutamate can also have this effect in the arthropod central nervous system, its action on afferent terminals appears to be mediated by increases in potassium conductance or by the action of metabotropic receptors. The action of the presynaptic synapses on the afferents are many and varied. Even on the same afferent, they may have several distinct roles that can involve both tonic and phasic patterns of primary afferent depolarisation. Despite the ubiquity and importance of their effects however, the populations of neurones from which the presynaptic synapses are made, remain largely unidentified.

Intrinsic noise at synapses between a wing hinge stretch receptor and flight motor neurons in the locust

Variability in postsynaptic potential (PSP) amplitude due to intrinsic noise limits the reliability of communication between neurons. I measured PSP variability at synapses between a forewing stretch receptor and wing depressor motor neurons in locusts, a pathway that is important in the control of flying. The intrinsic noise in the stretch receptor output synapse was measured by subtracting the background noise, originating in other synaptic pathways onto the motor neuron, from the variability in the amplitudes of PSPs evoked by the stretch receptor. Intrinsic synaptic noise caused successive PSPs to vary by 4–10 % in basalar and subalar flight motor neurons. Recordings from pairs of these wing depressor motor neurons showed that the amount of transmitter released varied independently between different output sites from the stretch receptor. Histograms of excitatory postsynaptic potential amplitude were normal distributions that lacked separate peaks. I estimate that quantal amplitude is significantly less than 0.1 mV and that several hundred quanta are released for each presynaptic spike. This accords well with a previous estimate of the number of discrete anatomical synapses and would facilitate modulation of output from the stretch receptor.