TwoLumps Ascending Neurons Mediate Touch-Evoked Reversal of Walking Direction in Drosophila

Neuronal mechanisms regulating locomotion in adult Drosophila

The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.

Organization of an ascending circuit that conveys flight motor state in Drosophila

Natural behaviors are a coordinated symphony of motor acts that drive reafferent (self-induced) sensory activation. Individual sensors cannot disambiguate exafferent (externally induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to carry out adaptive behaviors through corollary discharge circuits (CDCs), which provide predictive motor signals from motor pathways to sensory processing and other motor pathways. Yet, how CDCs comprehensively integrate into the nervous system remains unexplored. Here, we use connectomics, neuroanatomical, physiological, and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs) in Drosophila, which function as a predictive CDC in other insects. Both AHN pairs receive input primarily from a partially overlapping population of descending neurons, especially from DNg02, which controls wing motor output. Using Ca2+ imaging and behavioral recordings, we show that AHN activation is correlated to flight behavior and precedes wing motion. Optogenetic activation of DNg02 is sufficient to activate AHNs, indicating that AHNs are activated by descending commands in advance of behavior and not as a consequence of sensory input. Downstream, each AHN pair targets predominantly non-overlapping networks, including those that process visual, auditory, and mechanosensory information, as well as networks controlling wing, haltere, and leg sensorimotor control. These results support the conclusion that the AHNs provide a predictive motor signal about wing motor state to mostly non-overlapping sensory and motor networks. Future work will determine how AHN signaling is driven by other descending neurons and interpreted by AHN downstream targets to maintain adaptive sensorimotor performance.

Descending control of motor sequences in Drosophila

The descending neurons connecting the fly's brain to its ventral nerve cord respond to sensory stimuli and evoke motor programs of varying complexity. Anatomical characterization of the descending neurons and their synaptic connections suggests how these circuits organize movements, while optogenetic manipulation of their activity reveals what behaviors they can induce. Monitoring their responses to sensory stimuli or during behavior performance indicates what information they may encode. Recent advances in all three approaches make the descending neurons an excellent place to better understand the sensorimotor integration and transformation required for nervous systems to govern the motor sequences that constitute animal behavior.

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward

While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.

Organization of an Ascending Circuit that Conveys Flight Motor State

Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.

Olfactory stimuli and moonwalker SEZ neurons can drive backward locomotion in Drosophila

How different sensory stimuli are collected, processed, and further transformed into a coordinated motor response is a fundamental question in neuroscience. In particular, the internal and external conditions that drive animals to switch to backward walking and the mechanisms by which the nervous system supports such behavior are still unknown. In fruit flies, moonwalker descending neurons (MDNs) are considered command-type neurons for backward locomotion as they receive visual and mechanosensory inputs and transmit motor-related signals to downstream neurons to elicit backward locomotion. Whether other modalities converge onto MDNs, which central brain neurons activate MDNs, and whether other retreat-driving pathways exist is currently unknown. Here, we show that olfactory stimulation can elicit MDN-mediated backward locomotion. Moreover, we identify the moonwalker subesophageal zone neurons (MooSEZs), a pair of bilateral neurons, which can trigger straight and rotational backward locomotion. MooSEZs act via postsynaptic MDNs and via other descending neurons. Although they respond to olfactory input, they are not required for odor-induced backward walking. Thus, this work reveals an important modality input to MDNs, a novel set of neurons presynaptic to MDNs driving backward locomotion and an MDN-independent backward locomotion pathway.

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MooSEZs elicit backward locomotion via MDN-dependent and MDN-independent pathways

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MooSEZs are connected to MDNs and other descending neurons

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MooSEZs and MDNs both respond to olfactory input

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MooSEZs can trigger rotational backward locomotion

Mechanosensory input during circuit formation shapes Drosophila motor behavior through patterned spontaneous network activity

Neural activity sculpts circuit wiring in many animals. In vertebrates, patterned spontaneous network activity (PaSNA) generates sensory maps and establishes local circuits.1-3 However, it remains unclear how PaSNA might shape neuronal circuits and behavior in invertebrates. Previous work in the developing Drosophila embryo discovered intrinsic muscle activity that did not require synaptic transmission, and hence was myogenic, preceding PaSNA.4-6 These studies, however, monitored muscle movement, not neural activity, and were therefore unable to observe how myogenic activity might relate to subsequent neural network engagement. Here we use calcium imaging to directly record neural activity and characterize the emergence of PaSNA. We demonstrate that the spatiotemporal properties of PaSNA are highly stereotyped across embryos, arguing for genetic programming. Neural activity begins well before it becomes patterned, emerging during the myogenic stage. Remarkably, inhibition of mechanosensory input, as well as inhibition of muscle contractions, results in premature and excessive PaSNA, demonstrating that muscle movement serves as a brake on this process. Finally, transient mechanosensory inhibition during PaSNA, followed by quantitative modeling of larval behavior, shows that mechanosensory modulation during development is required for proper larval foraging. This work provides a foundation for using the Drosophila embryo to study the role of PaSNA in circuit formation, provides mechanistic insight into how PaSNA is entrained by motor activity, and demonstrates that spontaneous network activity is essential for locomotor behavior. These studies argue that sensory feedback during the earliest stages of circuit formation can sculpt locomotor behaviors through innate motor learning.

Optogenetic approaches for understanding homeostatic and degenerative processes in Drosophila

Many organs and tissues have an intrinsic ability to regenerate from a dedicated, tissue-specific stem cell pool. As organisms age, the process of self-regulation or homeostasis begins to slow down with fewer stem cells available for tissue repair. Tissues become more fragile and organs less efficient. This slowdown of homeostatic processes leads to the development of cellular and neurodegenerative diseases. In this review, we highlight the recent use and future potential of optogenetic approaches to study homeostasis. Optogenetics uses photosensitive molecules and genetic engineering to modulate cellular activity in vivo, allowing precise experiments with spatiotemporal control. We look at applications of this technology for understanding the mechanisms governing homeostasis and degeneration as applied to widely used model organisms, such as Drosophila melanogaster, where other common tools are less effective or unavailable.

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.

The Drosophila Split Gal4 System for Neural Circuit Mapping

The diversity and dense interconnectivity of cells in the nervous system present a huge challenge to understanding how brains work. Recent progress toward such understanding, however, has been fuelled by the development of techniques for selectively monitoring and manipulating the function of distinct cell types-and even individual neurons-in the brains of living animals. These sophisticated techniques are fundamentally genetic and have found their greatest application in genetic model organisms, such as the fruit fly Drosophila melanogaster. Drosophila combines genetic tractability with a compact, but cell-type rich, nervous system and has been the incubator for a variety of methods of neuronal targeting. One such method, called Split Gal4, is playing an increasingly important role in mapping neural circuits in the fly. In conjunction with functional perturbations and behavioral screens, Split Gal4 has been used to characterize circuits governing such activities as grooming, aggression, and mating. It has also been leveraged to comprehensively map and functionally characterize cells composing important brain regions, such as the central complex, lateral horn, and the mushroom body-the latter being the insect seat of learning and memory. With connectomics data emerging for both the larval and adult brains of Drosophila, Split Gal4 is also poised to play an important role in characterizing neurons of interest based on their connectivity. We summarize the history and current state of the Split Gal4 method and indicate promising areas for further development or future application.

A pair of ascending neurons in the subesophageal zone mediates aversive sensory inputs-evoked backward locomotion in Drosophila larvae

Animals typically avoid unwanted situations with stereotyped escape behavior. For instance, Drosophila larvae often escape from aversive stimuli to the head, such as mechanical stimuli and blue light irradiation, by backward locomotion. Responses to these aversive stimuli are mediated by a variety of sensory neurons including mechanosensory class III da (C3da) sensory neurons and blue-light responsive class IV da (C4da) sensory neurons and Bolwig's organ (BO). How these distinct sensory pathways evoke backward locomotion at the circuit level is still incompletely understood. Here we show that a pair of cholinergic neurons in the subesophageal zone, designated AMBs, evoke robust backward locomotion upon optogenetic activation. Anatomical and functional analysis shows that AMBs act upstream of MDNs, the command-like neurons for backward locomotion. Further functional analysis indicates that AMBs preferentially convey aversive blue light information from C4da neurons to MDNs to elicit backward locomotion, whereas aversive information from BO converges on MDNs through AMB-independent pathways. We also found that, unlike in adult flies, MDNs are dispensable for the dead end-evoked backward locomotion in larvae. Our findings thus reveal the neural circuits by which two distinct blue light-sensing pathways converge on the command-like neurons to evoke robust backward locomotion, and suggest that distinct but partially redundant neural circuits including the command-like neurons might be utilized to drive backward locomotion in response to different sensory stimuli as well as in adults and larvae.

Cre-assisted fine-mapping of neural circuits using orthogonal split inteins

Existing genetic methods of neuronal targeting do not routinely achieve the resolution required for mapping brain circuits. New approaches are thus necessary. Here, we introduce a method for refined neuronal targeting that can be applied iteratively. Restriction achieved at the first step can be further refined in a second step, if necessary. The method relies on first isolating neurons within a targeted group (i.e. Gal4 pattern) according to their developmental lineages, and then intersectionally limiting the number of lineages by selecting only those in which two distinct neuroblast enhancers are active. The neuroblast enhancers drive expression of split Cre recombinase fragments. These are fused to non-interacting pairs of split inteins, which ensure reconstitution of active Cre when all fragments are expressed in the same neuroblast. Active Cre renders all neuroblast-derived cells in a lineage permissive for Gal4 activity. We demonstrate how this system can facilitate neural circuit-mapping in Drosophila.