Biology subjects

Minegishi, R.

Publications and source records attributed to Minegishi, R..

4 recordsLinked to original sources

bioRxiv2024

A central steering circuit in Drosophila

The transformation of navigational variables into coordinated motor actions is a fundamental requirement for autonomous locomotion. The circuit and control mechanisms that underlie this transformation are not well understood. Here, we combine connectomics, neuronal activity perturbations, functional imaging and electrophysiology to identify a central steering circuit in Drosophila. This steering circuit operates in both goal-directed navigation and exploratory search and controls turning during both walking and flight, by implementing a hierarchical, stepwise transformation from navigation-related signals to motor output. At the top of the hierarchy are the reciprocally connected DNa03 and LAL013 neurons. DNa03 integrates lateralized sensory and internal information to generate an effector-agnostic steering signal during goal-directed navigation. LAL013 promotes exploratory turning in response to bilateral input from ExR7 neurons of the central complex, which encode the uncertainty of the flys internal heading estimate. Both DNa03 and LAL013 provide input to a set of hierarchically organized descending neurons, at the top of which is DNa11. DNa11 targets leg motor circuits directly as well as indirectly through subordinate descending neurons, and its activation coordinately changes the stepping directions of all six legs to generate rapid saccadic turns. In contrast to DNa03, DNa11 shows unilateral, delayed and low pass filtered activity during a turn. The signal transformation between DNa03 and DNa11 thus marks the transition from motor planning to the execution of a walking turn. Together, our results reveal a hierarchical circuit architecture that transforms navigational variables into abstract steering representations and ultimately into motor commands, providing a general framework for flexible control of behaviour across contexts and motor systems.

neuroscience↗

bioRxiv2023

Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster

To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their functions. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse transgenic driver lines targeting 196 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. In addition, we identified correspondences between the cells in this collection and a recent connectomic data set of the ventral nerve cord. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neuronal circuits and connectivity of premotor circuits while linking them to behavioral outputs.

neuroscience↗

bioRxiv2022

Ascending neurons convey behavioral state to integrative sensory and action selection centers in the brain

Knowledge of ones own behavioral state--whether one is walking, grooming, or resting--is critical for contextualizing sensory cues including interpreting visual motion and tracking odor sources. Additionally, awareness of ones own posture is important to avoid initiating destabilizing or physically impossible actions. Ascending neurons (ANs), interneurons in the vertebrate spinal cord or insect ventral nerve cord (VNC) that project to the brain, may provide such high-fidelity behavioral state signals. However, little is known about what ANs encode and where they convey signals in any brain. To address this gap, we performed a large-scale functional screen of AN movement encoding, brain targeting, and motor system patterning in the adult fly, Drosophila melanogaster. Using a new library of AN sparse driver lines, we measured the functional properties of 247 genetically-identifiable ANs by performing two-photon microscopy recordings of neural activity in tethered, behaving flies. Quantitative, deep network-based neural and behavioral analyses revealed that ANs nearly exclusively encode high-level behaviors--primarily walking as well as resting and grooming--rather than low-level joint or limb movements. ANs that convey self-motion--resting, walking, and responses to gust-like puff stimuli--project to the brains anterior ventrolateral protocerebrum (AVLP), a multimodal, integrative sensory hub, while those that encode discrete actions--eye grooming, turning, and proboscis extension--project to the brains gnathal ganglion (GNG), a locus for action selection. The structure and polarity of AN projections within the VNC are predictive of their functional encoding and imply that ANs participate in motor computations while also relaying state signals to the brain. Illustrative of this are ANs that temporally integrate proboscis extensions over tens-of-seconds, likely through recurrent interconnectivity. Thus, in line with long-held theoretical predictions, ascending populations convey high-level behavioral state signals almost exclusively to brain regions implicated in sensory feature contextualization and action selection.

neuroscience↗

bioRxiv2020

An image resource of subdivided Drosophila GAL4-driver expression patterns for neuron-level searches

Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.

neuroscience↗