The impulse response of optic flow-sensitive descending neurons to roll m-sequences

ABSTRACT When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.

Facilitation of neural responses to targets moving against optic flow

For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. In contrast, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. We here recorded from target selective descending neurons (TSDNs), which likely subserve these impressive behaviors. To simulate the type of optic flow that would be generated by the pursuer’s own movements through the world, we used the motion of a perspective corrected sparse dot field. We show that hoverfly TSDN responses to target motion are suppressed when such optic flow moves syn-directional to the target. Indeed, neural responses are strongly suppressed when targets move over either translational sideslip or rotational yaw. More strikingly, we show that TSDNs are facilitated by optic flow moving counterdirectional to the target, if the target moves horizontally. Furthermore, we show that a small, frontal spatial window of optic flow is enough to fully facilitate or suppress TSDN responses to target motion. We argue that such TSDN response facilitation could be beneficial in modulating corrective turns during target pursuit.

A population of descending neurons that regulate 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 length(3), 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 the both damaged and intact wings(4). 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 neurons (DNg02) that project directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike most 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.

Two Parallel Pathways Mediate Olfactory-Driven Backward Locomotion

Although animals switch to backward walking upon sensing an obstacle or danger in their path, the initiation and execution of backward locomotion is poorly understood. The discovery of Moonwalker Descending Neurons (MDNs), made Drosophila useful to study neural circuits underlying backward locomotion. MDNs were demonstrated to receive visual and mechanosensory inputs. However, whether other modalities converge onto MDNs and what are the neural circuits activating MDNs are unknown. We show that aversive but not appetitive olfactory input triggers MDN-mediated backward locomotion. We identify in each hemisphere, a single Moonwalker Subesophageal Zone neuron (MooSEZ), which triggers backward locomotion. MooSEZs act both upstream and in parallel to MDNs. Surprisingly, MooSEZs also respond mostly to aversive odor. Contrary to MDNs, blocking MooSEZs activity has little effect on odor-evoked backward locomotion. Thus, this work reveals another important modality input to MDNs in addition to a novel olfactory pathway and MDN-independent backward locomotion pathway.

The connectome of the adult Drosophila mushroom body provides insights into function

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

Distributed control of motor circuits for backward walking in Drosophila

How do descending inputs from the brain control leg motor circuits to change how an animal walks? Conceptually, descending neurons are thought to function either as command-type neurons, in which a single type of descending neuron exerts a high-level control to elicit a coordinated change in motor output, or through a population coding mechanism, whereby a group of neurons, each with local effects, act in combination to elicit a global motor response. The Drosophila Moonwalker Descending Neurons (MDNs), which alter leg motor circuit dynamics so that the fly walks backwards, exemplify the command-type mechanism. Here, we identify several dozen MDN target neurons within the leg motor circuits, and show that two of them mediate distinct and highly-specific changes in leg muscle activity during backward walking: LBL40 neurons provide the hindleg power stroke during stance phase; LUL130 neurons lift the legs at the end of stance to initiate swing. Through these two effector neurons, MDN directly controls both the stance and swing phases of the backward stepping cycle. These findings suggest that command-type descending neurons can also operate through the distributed control of local motor circuits.

Two Parallel Pathways Mediate Olfactory-Driven Backward Locomotion

Although animals switch to backward walking upon sensing an obstacle or danger in their path, the initiation and execution of backward locomotion is poorly understood. The discovery of Moonwalker Descending Neurons (MDNs), made Drosophila useful to study neural circuits underlying backward locomotion. MDNs were demonstrated to receive visual and mechanosensory inputs. However, whether other modalities converge onto MDNs and what are the neural circuits activating MDNs are unknown. We show that aversive but not appetitive olfactory input triggers MDN-mediated backward locomotion. We identify in each hemisphere, a single Moonwalker Subesophageal Zone neuron (MooSEZ), which triggers backward locomotion. MooSEZs act both upstream and in parallel to MDNs. Surprisingly, MooSEZs also respond mostly to aversive odor. Contrary to MDNs, blocking MooSEZs activity has little effect on odor-evoked backward locomotion. Thus, this work reveals another important modality input to MDNs in addition to a novel olfactory pathway and MDN-independent backward locomotion pathway.

Cell types and neuronal circuitry underlying female aggression in Drosophila

Aggressive social interactions are used to compete for limited resources and are regulated by complex sensory cues and the organism’s internal state. While both sexes exhibit aggression, its neuronal underpinnings are understudied in females. Here, we identify a population of sexually dimorphic aIPg neurons in the adult Drosophila melanogaster central brain whose optogenetic activation increased, and genetic inactivation reduced, female aggression. Analysis of GAL4 lines identified in an unbiased screen for increased female chasing behavior revealed the involvement of another sexually dimorphic neuron, pC1d, and implicated aIPg and pC1d neurons as core nodes regulating female aggression. Connectomic analysis demonstrated that aIPg neurons and pC1d are interconnected and suggest that aIPg neurons may exert part of their effect by gating the flow of visual information to descending neurons. Our work reveals important regulatory components of the neuronal circuitry that underlies female aggressive social interactions and provides tools for their manipulation.

The connectome of the adult Drosophila mushroom body: implications for function

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

A neural model for insect steering applied to olfaction and path integration

Many animal behaviours require orientation and steering with respect to the environment. For insects, a key brain area involved in spatial orientation and navigation is the central complex. Activity in this neural circuit has been shown to track the insect’s current heading relative to its environment, and has also been proposed to be the substrate of path integration. However, it remains unclear how the output of the central complex is integrated into motor commands. Central complex output neurons project to the lateral accessory lobes (LAL), from which descending neurons project to thoracic motor centres. Here, we present a computational model of a simple neural network that has been described anatomically and physiologically in the LALs of male silkworm moths, in the context of odour-mediated steering. We present and analyze two versions of this network, both implemented in the Nengo framework, one rate-based and one based on spiking neurons. The modelled network consists of an inhibitory local interneuron and a bistable descending neuron (‘flip-flop’), which both receive input in the LAL. The flip-flop neuron projects onto neck motor neurons to induce steering. We show that this simple computational model not only replicates the basic parameters of male silkworm moth behaviour in a simulated odour plume, but can also take input from a computational model of path integration in the central complex and use it to steer back to a point of origin. Furthermore, we find that increasing the level of detail within the model improves the realism of the model’s behaviour. Our results suggest that descending neurons originating in the lateral accessory lobes, such as flip-flop neurons, are sufficient to mediate multiple steering behaviours. This study is therefore a first step to close the gap between orientation circuits in the central complex and downstream motor centres.Author summaryTargeted movements and steering within an environment are essential for many behaviours. In insects, the brain’s center for spatial orientation and navigation is the central complex, which processes information about the configuration of the local environment as well as global orientation cues such as the Sun position. Neural networks in the central complex also compute the insect’s heading direction, and are thought to be involved in generating steering commands. However, it is unclear how these steering commands are transmitted to downstream motor centers. Output neurons from the central complex project to the lateral accessory lobes, a neuropil which also gives rise to descending pre-motor neurons that are involved in steering in the silkworm moth Bombyx mori. In this study, we provide a computational model of a pre-motor neural network in the lateral accessory lobes. We show that this network can steer an agent towards the source of a simulated odor plume, but that it can also steer efficiently when getting input from an anatomically constrained network model of the central complex. This model is therefore a first step to close the gap between the central complex and thoracic motor circuits.