Synchronous firing by specific pairs of cercal giant interneurons in crickets encodes wind direction

A population of descending neurons that regulates the flight motor of Drosophila

Like many insect species, Drosophila melanogaster are capable of maintaining a stable flight trajectory for periods lasting up to several hours^1,2. Because aerodynamic torque is roughly proportional to the fifth power of wing length³, even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to both the damaged and intact wings⁴. Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this paper, we describe an unusual type of descending neuron (DNg02) that projects directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike many descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using 2-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of DNs that provide the sensitivity and dynamic range required for flight control.

Using an activation screen in flying flies, Namiki et al. identify a population of descending neurons that regulates wing amplitude over a large dynamic range. Via functional imaging and activation of different numbers of cells, they show that this population is a core component of the flight circuit, allowing the fly to steer and fly straight.

Responses of Drosophila giant descending neurons to visual and mechanical stimuli

In Drosophila, the paired giant descending neurons (GDNs), also known as giant fibers, and the paired giant antennal mechanosensory descending neurons (GAMDNs), are supplied by visual and mechanosensory inputs. Both neurons have the largest cell bodies in the brain and both supply slender axons to the neck connective. The GDN axon thereafter widens to become the largest axon in the thoracic ganglia, supplying information to leg extensor and wing depressor muscles. The GAMDN axon remains slender, interacting with other descending neuron axons medially. GDN and GAMDN dendrites are partitioned to receive inputs from antennal mechanosensory afferents and inputs from the optic lobes. Although GDN anatomy has been well studied in Musca domestica, less is known about the Drosophila homolog, including electrophysiological responses to sensory stimuli. Here we provide detailed anatomical comparisons of the GDN and the GAMDN, characterizing their sensory inputs. The GDN showed responses to light-on and light-off stimuli, expanding stimuli that result in luminance decrease, mechanical stimulation of the antennae, and combined mechanical and visual stimulation. We show that ensembles of lobula columnar neurons (type Col A) and mechanosensory antennal afferents are likely responsible for these responses. The reluctance of the GDN to spike in response to stimulation confirms observations of the Musca GDN. That this reluctance may be a unique property of the GDN is suggested by comparisons with the GAMDN, in which action potentials are readily elicited by mechanical and visual stimuli. The results are discussed in the context of descending pathways involved in multimodal integration and escape responses.

Eight pairs of descending visual neurons in the dragonfly give wing motor centers accurate population vector of prey direction

Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, who intercept their prey in midair with a 95% success rate. In this study, we show that a group of 16 neurons, called target-selective descending neurons (TSDNs), code a population vector that reflects the direction of the target with high accuracy and reliability across 360°. The TSDN spatial (receptive field) and temporal (latency) properties matched the area of the retina where the prey is focused and the reaction time, respectively, during predatory flights. The directional tuning curves and morphological traits (3D tracings) for each TSDN type were consistent among animals, but spike rates were not. Our results emphasize that a successful neural circuit for target tracking and interception can be achieved with few neurons and that in dragonflies this information is relayed from the brain to the wing motor centers in population vector form.

Responses of cricket cercal interneurons to realistic naturalistic stimuli in the field

The ability of the insect cercal system to detect approaching predators has been studied extensively in the laboratory and in the field. Some previous studies have assessed the extent to which sensory noise affects the operational characteristics of the cercal system, but these studies have only been carried out in laboratory settings using white noise stimuli of unrealistic nature. Using a piston mimicking the natural airflow of an approaching predator, we recorded the neural activity through the abdominal connectives from the terminal abdominal ganglion of freely moving wood crickets (Nemobius sylvestris) in a semi-field situation. A cluster analysis of spike amplitudes revealed six clusters, or 'units', corresponding to six different subsets of cercal interneurons. No spontaneous activity was recorded for the units of larger amplitude, reinforcing the idea they correspond to the largest giant interneurons. Many of the cercal units are already activated by background noise, sometimes only weakly, and the approach of a predator is signaled by an increase in their activity, in particular for the larger-amplitude units. A scaling law predicts that the cumulative number of spikes is a function of the velocity of the flow perceived at the rear of the cricket, including a multiplicative factor that increases linearly with piston velocity. We discuss the implications of this finding in terms of how the cricket might infer the imminence and nature of a predatory attack.

Escape behaviors in insects

Escape behaviors are, by necessity, fast and robust, making them excellent systems with which to study the neural basis of behavior. This is especially true in insects, which have comparatively tractable nervous systems and members who are amenable to manipulation with genetic tools. Recent technical developments in high-speed video reveal that, despite their short duration, insect escape behaviors are more complex than previously appreciated. For example, before initiating an escape jump, a fly performs sophisticated posture and stimulus-dependent preparatory leg movements that enable it to jump away from a looming threat. This newfound flexibility raises the question of how the nervous system generates a behavior that is both rapid and flexible. Recordings from the cricket nervous system suggest that synchrony between the activity of specific interneuron pairs may provide a rapid cue for the cricket to detect the direction of an approaching predator and thus which direction it should run. Technical advances make possible wireless recording from neurons while locusts escape from a looming threat, enabling, for the first time, a direct correlation between the activity of multiple neurons and the time-course of an insect escape behavior.

Danger detection and escape behaviour in wood crickets

The wind-sensitive cercal system of Orthopteroid insects that mediates the detection of the approach of a predator is a very sensitive sensory system. It has been intensively analysed from a behavioural and neurobiological point of view, and constitutes a classical model system in neuroethology. The escape behaviour is triggered in orthopteroids by the detection of air-currents produced by approaching objects, allowing these insects to keep away from potential dangers. Nevertheless, escape behaviour has not been studied in terms of success. Moreover, an attacking predator is more than "air movement", it is also a visible moving entity. The sensory basis of predator detection is thus probably more complex than the perception of air movement by the cerci. We have used a piston mimicking an attacking running predator for a quantitative evaluation of the escape behaviour of wood crickets Nemobius sylvestris. The movement of the piston not only generates air movement, but it can be seen by the insect and can touch it as a natural predator. This procedure allowed us to study the escape behaviour in terms of detection and also in terms of success. Our results showed that 5-52% of crickets that detected the piston thrust were indeed touched. Crickets escaped to stimulation from behind better than to a stimulation from the front, even though they detected the approaching object similarly in both cases. After cerci ablation, 48% crickets were still able to detect a piston approaching from behind (compared with 79% of detection in intact insects) and 24% crickets escaped successfully (compared with 62% in the case of intact insects). So, cerci play a major role in the detection of an approaching object but other mechanoreceptors or sensory modalities are implicated in this detection. It is not possible to assure that other sensory modalities participate (in the case of intact animals) in the behaviour; rather, than in the absence of cerci other sensory modalities can partially mediate the behaviour. Nevertheless, neither antennae nor eyes seem to be used for detecting approaching objects, as their inactivation did not reduce their detection and escape abilities in the presence of cerci.