Ascending neurons convey behavioral state to integrative sensory and action selection brain regions

Knowing one’s own behavioral state has long been theorized as critical for contextualizing dynamic sensory cues and identifying appropriate future behaviors. Ascending neurons (ANs) in the motor system that project to the brain are well positioned to provide such behavioral state signals. However, what ANs encode and where they convey these signals remains largely unknown. Here, through large-scale functional imaging in behaving animals and morphological quantification, we report the behavioral encoding and brain targeting of hundreds of genetically identifiable ANs in the adult fly, Drosophila melanogaster. We reveal that ANs encode behavioral states, specifically conveying self-motion to the anterior ventrolateral protocerebrum, an integrative sensory hub, as well as discrete actions to the gnathal ganglia, a locus for action selection. Additionally, AN projection patterns within the motor system are predictive of their encoding. Thus, ascending populations are well poised to inform distinct brain hubs of self-motion and ongoing behaviors and may provide an important substrate for computations that are required for adaptive behavior.

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Software and code
Policy information about availability of computer code Data collection Two-photon microscope images were acquired using ThorImage 3.1 software. Data synchronization was performed using ThorSync 3.1 software. Behavior images were acquired using custom Python scripts. Confocal images were acquired using Zen 2011 14.0 software.

Data analysis
Data analyses were performed using custom code written in Python 3. The code is available in the following repository: https://github.com/NeLy-EPFL/Ascending_neuron_screen_analysis_pipeline Fiji v.2.9.0 software was used to generate standard deviation z-projections of image stacks, combine monochromatic images to generate RGB images, mask MCFO confocal images, and trace neurons. AxoID software was developed and used to track ROIs in two-photon imaging data. The code is available in the following repository: https://github.com/NeLy-EPFL/AxoID Code for brain and VNC confocal image registration can be found at: https://github.com/NeLy-EPFL/MakeAverageBrain/tree/workstation MCFO brain and VNC confocal image registration was performed using the Computational Morphometry Toolkit: https://www.nitrc.org/ projects/cmtk For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Portfolio guidelines for submitting code & software for further information.

March 2021
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy Data are available at: https://dataverse.harvard.edu/dataverse/AN . Due to data storage limits, this does not include raw behavior camera images or raw twophoton imaging files. This repository includes: synchronized neural fluorescence, behavior, and ball rotation velocities; raw and traced MCFO confocal image data; neural data used for regression analyses, responses of PE-ANs, and neural responses on and off of the spherical treadmill; behavioral data as well as the deeplearning model for measuring proboscis extensions and annotations for training the behavior classifier; linear regression results; a machine-readable version of Table S1. Note that full information on the approval of the study protocol must also be provided in the manuscript.

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Life sciences study design
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Sample size
The study was designed as a functional and anatomical screen of many Drosophila driver lines. Each line was functionally examined in 2-5 animals each. Anatomical studies were very reliable across samples. AN encodings were qualitatively reliable for the same driver line across animals aside from differences in signal-to-noise ratio as well as minor variability in the number of ROIs for a subset of driver lines. No statistical methods were used to pre-determine sample sizes. Our sample sizes are justified by AN functional response reliability and the constraint of the time required to functionally screen 70 driver lines in behaving animals. The data presented in this manuscript were acquired from 245 flies: 108 flies for confocal imaging of smFP expression. 70 flies for two-photon AN imaging during behavior. 42 flies for tracing single AN morphologies using MCFO. 7 flies for imaging MCFO single neuron morphologies at high magnification. 7 flies for confocal imaging of syt:GFP. 3 flies for comparing puff-AN responses to air versus carbon dioxide. 8 flies for examining the ramping increase in PE-AN activity during PE trains.
Data exclusions Data from two-photon recordings of behaving flies were excluded for animals and trials in which we observed abnormal limb movements, or low vitality. Two-photon imaging data were also excluded if they suffered from optical occlusions due to tissue debris, or extreme motion artifacts resulting from animal behavior.

Replication
For the two-photon functional imaging screen, 2-5 replicates (animals) were recorded for each genotype. All attempts at replication were successful. Recordings from one representative fly of each genotype were used in linear modeling. This decision was made due to the difficulty, for some genotypes, of confidently identifying the same neurons across animals. For the SS31232 (PE-ANs) line, we analyzed 25 PE-trains from 8 replicates (animals). For the SS36112 (puff-ANs) line, we analyzed responses to air versus carbon dioxide for 3 replicates (animals). To measure syt:GFP expression in each genotype, 3-6 replicates (animals) were analyzed. One representative animal is shown for each of 7 March 2021 lines studied in-depth. To measure single neuron labeling with MCFO, 2-7 replicates (animals) were analyzed per genotype. One representative animal is shown for each of 42 lines. The same number of replicates were used for high-magnification studies of single neuron morphologies.
To examine the expression of smFP, 2-3 replicates (animals) were examined for each genotype. One representative example is shown for each of the 108 lines.
Randomization Because we performed a functional screen without prior hypotheses, the experiments were not randomized.

Blinding
Because we performed a functional screen without prior hypotheses, the data collection and analyses were not performed blind to the conditions of the experiments.
Reporting for specific materials, systems and methods We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response. Validation Primary antibodies were validated by the suppliers as follows: Rabbit anti-GFP (Thermofisher, RRID: AB_2536526) was validated through relative expression, rabbit anti-HA-tag (Cell Signaling Technology, RRID: AB_1549585) was validated through immunohistochemical expression analysis, and rabbit polyclonal anti-DsRed (Takara Biomedical Technology, RRID: AB_10013483) was validated by western blot. No manufacturer notes are available for the validation of other primary antibodies. No additional validation was performed.