Biology subjects

Truman, J. W.

Publications and source records attributed to Truman, J. W..

13 recordsLinked to original sources

bioRxiv2024

Steering From the Rear: Coordination of Central Pattern Generators Underlying Navigation by Ascending Interneurons

Understanding how animals coordinate movements to achieve goals is a fundamental pursuit in neuroscience. Here we explore how neurons that reside in posterior lower-order regions of a locomotor system project to anterior higher-order regions to influence steering and navigation. We characterized the anatomy and functional role of a population of ascending interneurons in the ventral nerve cord of Drosophila larvae. Through electron microscopy reconstructions and light microscopy, we determined that the cholinergic 19f cells receive input primarily from premotor interneurons and synapse upon a diverse array of postsynaptic targets within the anterior segments including other 19f cells. Calcium imaging of 19f activity in isolated central nervous system (CNS) preparations in relation to motor neurons revealed that 19f neurons are recruited into most larval motor programmes. 19f activity lags behind motor neuron activity and as a population, the cells encode spatio-temporal patterns of locomotor activity in the larval CNS. Optogenetic manipulations of 19f cell activity in isolated CNS preparations revealed that they coordinate the activity of central pattern generators underlying exploratory headsweeps and forward locomotion in a context and location specific manner. In behaving animals, activating 19f cells suppressed exploratory headsweeps and slowed forward locomotion, while inhibition of 19f activity potentiated headsweeps, slowing forward movement. Inhibiting activity in 19f cells ultimately affected the ability of larvae to remain in the vicinity of an odor source during an olfactory navigation task. Overall, our findings provide insights into how ascending interneurons monitor motor activity and shape interactions amongst rhythm generators underlying complex navigational tasks.

neuroscience↗

bioRxiv2023

The embryonic role of juvenile hormone in the firebrat, Thermobia domestica, reveals its function before its involvement in metamorphosis

To gain insights into how juvenile hormone (JH) came to regulate insect metamorphosis, we studied its function in the ametabolous firebrat, Thermobia domestica. Highest levels of JH occur during late embryogenesis, with only low levels thereafter. Loss-of-function and gain-of-function experiments show that JH acts on embryonic tissues to suppress morphogenesis and cell determination and to promote their terminal differentiation. Similar embryonic actions of JH on hemimetabolous insects with short germ band embryos indicate that JHs embryonic role preceded its derived function as the postembryonic regulator of metamorphosis. The postembryonic expansion of JH function likely followed the evolution of flight. Archaic flying insects were considered to lack metamorphosis because tiny, movable wings were evident on the thoraces of young juveniles and their positive allometric growth eventually allowed them to support flight in late juveniles. Like in Thermobia, we assume that these juveniles lacked JH. However, a postembryonic reappearance of JH during wing morphogenesis in the young juvenile likely redirected wing development to make a wing pad rather than a wing. Maintenance of JH then allowed wing pad growth and its disappearance in the mature juvenile then allowed wing differentiation. Subsequent modification of JH action for hemi- and holometabolous lifestyles are discussed. SignificanceThe likely action of this sesquiterpene hormone as a morphogenesis-to-differentiation switch in archaic embryos preadapted it for later assuming its function as the status quo regulator of insect metamorphosis.

developmental biology↗

bioRxiv2022

Metamorphosis of memory circuits in Drosophila reveal a strategy for evolving a larval brain.

Insects like Drosophila produce a second brain adapted to the form and behavior of a larva. Neurons for both larval and adult brains are produced by the same stem cells (neuroblasts) but the larva possesses only the earliest born neurons produced from each. To understand how a functional larval brain is made from this reduced set of neurons, we examined the origins and metamorphic fates of the neurons of the larval and adult mushroom body circuits. The adult mushroom body core is built sequentially of {gamma} Kenyon cells, that form a medial lobe, followed by {beta}, and {beta} Kenyon cells that form additional medial lobes and two vertical lobes. Extrinsic input (MBINs) and output (MBONs) neurons divide this core into computational compartments. The larval mushroom body contains only {gamma} neurons. Its medial lobe compartments are roughly homologous to those of the adult and same MBONs are used for both. The larval vertical lobe, however, is an analogous "facsimile" that uses a larval-specific branch on the {gamma} neurons to make up for the missing {beta}, and {beta} neurons. The extrinsic cells for the facsimile are early-born neurons that trans-differentiate to serve a mushroom body function in the larva and then shift to other brain circuits in the adult. These findings are discussed in the context of the evolution of a larval brain in insects with complete metamorphosis.

developmental biology↗

bioRxiv2020

Unveiling the sensory and interneuronal pathways of the neuroendocrine system in Drosophila

Neuroendocrine systems in animals maintain organismal homeostasis and regulate stress response. Although a great deal of work has been done on the neuropeptides and hormones that are released and act on target organs in the periphery, the synaptic inputs onto these neuroendocrine outputs in the brain are less well understood. Here, we use the transmission electron microscopy reconstruction of a whole central nervous system in the Drosophila larva to elucidate the sensory pathways and the interneurons that provide synaptic input to the neurosecretory cells projecting to the endocrine organs. Predicted by network modeling, we also identify a new carbon dioxide responsive network that acts on a specific set of neurosecretory cells and which include those expressing Corazonin (Crz) and Diuretic hormone 44 (DH44) neuropeptides. Our analysis reveals a neuronal network architecture for combinatorial action based on sensory and interneuronal pathways that converge onto distinct combinations of neuroendocrine outputs.

neuroscience↗

bioRxiv2020

Central processing of leg proprioception in Drosophila

Proprioception, the sense of self-movement and position, is mediated by mechanosensory neurons that detect diverse features of body kinematics. Although proprioceptive feedback is crucial for accurate motor control, little is known about how downstream circuits transform limb sensory information to guide motor output. Here, we investigate neural circuits in Drosophila that process proprioceptive information from the fly leg. We identify three cell-types from distinct developmental lineages that are positioned to receive input from proprioceptor subtypes encoding tibia position, movement, and vibration. 13B neurons encode femur-tibia joint angle and mediate postural changes in tibia position. 9A neurons also drive changes in leg posture, but encode a combination of directional movement, high frequency vibration, and joint angle. Activating 10B neurons, which encode tibia vibration at specific joint angles, elicits pausing in walking flies. Altogether, our results reveal that central circuits integrate information across proprioceptor subtypes to construct complex sensorimotor representations that mediate diverse behaviors, including reflexive control of limb posture and detection of leg vibration.

neuroscience↗

bioRxiv2020

Circuits for integrating learnt and innate valences in the fly brain

Animal behavior is shaped both by evolution and by individual experience. In many species parallel brain pathways are thought to encode innate and learnt behavior drives and as a result may link the same sensory cue to different actions if innate and learnt drives are in opposition. How these opposing drives are integrated into a single coherent action is not well understood. In insects, the Mushroom Body Output Neurons (MBONs) and the Lateral Horn Neurons (LHNs) are thought to provide the learnt and innate drives, respectively. However their patterns of convergence and the mechanisms by which their outputs are used to select actions are not well understood. We used electron microscopy reconstruction to comprehensively map the downstream targets of all MBONs in Drosophila larva and characterise their patterns of convergence with LHNs. We discovered convergence neurons that receive direct input from MBONs and LHNs and compare opposite behaviour drives. Functional imaging and optogenetic manipulation suggest these convergence neurons compute the overall predicted value of approaching or avoiding an odor and mediate action selection. Our study describes the circuit mechanisms allowing integration of opposing drives from parallel olfactory pathways.

neuroscience↗

bioRxiv2019

Unc-4 acts to promote neuronal identity and development of the take-off circuit in the Drosophila CNS

The Drosophila ventral nerve cord (VNC), the fly equivalent of the spinal cord, is composed of thousands of neurons that are born from a set of individually identifiable stem cells. The VNC harbors neuronal circuits required for the execution of vital behaviors, such as flying and walking. Taking advantage of the lineage-based functional organization of the VNC and genetic tools we developed, we investigated the molecular and developmental basis of behavior by focusing on lineage-specific functions of the homeodomain transcription factor, Unc-4. We found that Unc-4 functions in lineage 11A to promote cholinergic neurotransmitter identity and suppress the GABA fate. In 7B lineage, Unc-4 promotes proper neuronal projections to the leg neuropil, the hub for leg-related neuronal circuits and a specific flight-related take-off behavior. We also uncovered that Unc-4 acts peripherally to promote the development of proprioceptive sense organs and the abilities of flies to execute specific leg-related behaviors such as walking, climbing, and grooming. Our findings, thus, initiates the work on revealing molecular and developmental events that shape the VNC related behaviors.

developmental biology↗

bioRxiv2019

Comparative single-cell transcriptomics of complete insect nervous systems

Molecular profiles of neurons influence information processing, but bridging the gap between genes, circuits, and behavior has been very difficult. Furthermore, the behavioral state of an animal continuously changes across development and as a result of sensory experience. How behavioral state influences molecular cell state is poorly understood. Here we present a complete atlas of the Drosophila larval central nervous system composed of over 200,000 single cells across four developmental stages. We develop polyseq, a python package, to perform cell-type analyses. We use single-molecule RNA-FISH to validate our scRNAseq findings. To investigate how internal state affects cell state, we optogentically altered internal state with high-throughput behavior protocols designed to mimic wasp sting and over activation of the memory system. We found nervous system-wide and neuron-specific gene expression changes. This resource is valuable for developmental biology and neuroscience, and it advances our understanding of how genes, neurons, and circuits generate behavior.

neuroscience↗

bioRxiv2019

Multilevel feedback architecture for adaptive regulation of learning in the insect brain

Modulatory (e.g. dopaminergic) neurons provide \"teaching signals\" that drive associative learning across the animal kingdom, but the circuits that regulate their activity and compute teaching signals are still poorly understood. We provide the first synaptic-resolution connectome of the circuitry upstream of all modulatory neurons in a brain center for associative learning, the mushroom body (MB) of the Drosophila larva. We discovered afferent pathways from sensory neurons, as well as an unexpected large population of 61 feedback neuron pairs that provide one- and two-step feedback from MB output neurons. The majority of these feedback pathways link distinct memory systems (e.g. aversive and appetitive). We functionally confirmed some of the structural pathways and found that some modulatory neurons compare inhibitory input from their own compartment and excitatory input from compartments of opposite valence, enabling them to compute integrated common-currency predicted values across aversive and appetitive memory systems. This architecture suggests that the MB functions as an interconnected ensemble during learning and that distinct types of previously formed memories can regulate future learning about a stimulus. We developed a model of the circuit constrained by the connectome and by the functional data which revealed that the newly discovered architectural motifs, namely the multilevel feedback architecture and the extensive cross-compartment connections, increase the computational performance and flexibility on learning tasks. Together our study provides the most detailed view to date of a recurrent brain circuit that computes teaching signals and provides insights into the architectural motifs that support reinforcement learning in a biological system.

neuroscience↗

bioRxiv2019

The role of lineage, hemilineage and temporal identity in establishing neuronal targeting and connectivity in the Drosophila embryo

The mechanisms specifying neuronal diversity are well-characterized, yet it remains unclear how or if these mechanisms regulate neural circuit assembly. To address this, we mapped the developmental origin of 160 interneurons from seven bilateral neural progenitors (neuroblasts), and identify them in a synapse-scale TEM reconstruction of the Drosophila larval CNS. We find that lineages concurrently build the sensory and motor neuropils by generating sensory and motor hemilineages in a Notch-dependent manner. Neurons in a hemilineage share common synaptic targeting within the neuropil, which is further refined based on neuronal temporal identity. Connectome analysis shows that hemilineage-temporal cohorts share common connectivity. Finally, we show that proximity alone cannot explain the observed connectivity structure, suggesting hemilineage/temporal identity confers an added layer of specificity. Thus, we demonstrate that the mechanisms specifying neuronal diversity also govern circuit formation and function, and that these principles are broadly applicable throughout the nervous system.

neuroscience↗

bioRxiv2018

Neural substrates of navigational decision-making in Drosophila larva anemotaxis

Small animals use sensory information to navigate their environment in order to reach more favorable conditions. in gradients of light, temperature, odors and CO2, Drosophila larvae alternate periods of runs and turns, regulating the frequency size and direction of turns, to move in a favorable direction. Whether larvae use the same strategies when navigating in response to somatosensory input is unknown. Further, while many of the sensory neurons that mediate navigation behaviors have been described, where and how these navigational strategies are implemented in the central nervous system and controlled by neuronal circuit elements is not well known. Here we characterize for the first time the navigational strategies of Drosophila larvae in gradients of air-current speeds using high-throughput behavioral assays and quantitative behavioral analysis. We find that larvae extend runs towards favorable directions and shorten runs in unfavorable directions, and that larvae regulate both the direction and amplitudes of turns. These results suggest similar central decision-making mechanisms underlie navigation behaviors in somatosensory and other sensory modalities. By silencing the activity of individual neurons and very sparse expression patterns (2 or 3 neuron types), we further identify the sensory neurons and circuit elements in the ventral nerve cord and brain of the larva required for navigational decisions during anemotaxis. The phenotypes of these central neurons are consistent with a mechanism where the increase of the turning rate in unfavorable conditions and decrease in turning rate in favorable conditions are independently controlled. In addition, we find phenotypes that suggest that the decisions of whether and which way to turn are controlled independently. Our study reveals that different neuronal modules in the nerve cord and brain mediate different aspects of navigational decision making. The neurons identified in our screen provide a basis for future detailed mechanistic understanding of the circuit principles of navigational decisionmaking.

neuroscience↗

bioRxiv2017

Mapping neurons and brain regions underlying sensorimotor decisions and sequences

A fundamental property of the nervous systems across the animal kingdom is the ability to select appropriate actions and sequences of actions in response to sensory cues. Many behaviors are physically mutually exclusive so commitment to one requires complete suppression of others. Further, because many behaviors are serially organized into sequences of actions, mechanisms must also exist that control transitions from one action to the next. The circuit mechanisms by which nervous systems achieve behavioral choice, stability and transitions are still incompletely understood. A key step in understanding these functions is to identify neurons and brain areas involved in controlling behavioral choice, stability and transitions. To do this, we developed an approach where we combined a large-scale neuronal inactivation screen with an automated action detection of sensorimotor decisions and sequences in response to a sensory cue. We characterized the response of wild-type larvae to a mechanosensory stimulus and found they can respond to the stimulus with a probabilistic sequence of 4 possible actions (head-cast, head-retraction, back-up and stop). We analyzed behaviors from around three hundred thousand larvae (N=2.9x105) where we selectively silenced small numbers of neuron types and individual neuron types systematically across the nervous system using a library of Drosophila GAL4 lines and determined the effect of these manipulations on larval mechanosensory responses. We identified neurons and brain-regions that when inactivated affected Drosophila larval sensorimotor decisions and sequence transitions between the different actions. Specifically, we identified 51 candidate lines for sensory processing and 24 candidate lines for competitive interactions. We also detected phenotype categories for sequence transitions consistent with a model of sequence generation where transitions and reversals are independently controlled. These findings provide the basis for understanding how sensorimotor decisions and sequence transition are controlled by the nervous system.

neuroscience↗

bioRxiv2017

The Complete Connectome Of A Learning And Memory Center In An Insect Brain

Associating stimuli with positive or negative reinforcement is essential for survival, but a complete wiring diagram of a higherorder circuit supporting associative memory has not been previously available. We reconstructed one such circuit at synaptic resolution, the Drosophila larval mushroom body, and found that most Kenyon cells integrate random combinations of inputs but a subset receives stereotyped inputs from single projection neurons. This organization maximizes performance of a model output neuron on a stimulus discrimination task. We also report a novel canonical circuit in each mushroom body compartment with previously unidentified connections: reciprocal Kenyon cell to modulatory neuron connections, modulatory neuron to output neuron connections, and a surprisingly high number of recurrent connections between Kenyon cells. Stereotyped connections between output neurons could enhance the selection of learned responses. The complete circuit map of the mushroom body should guide future functional studies of this learning and memory center.

neuroscience↗