DOI: 10.5061/dryad.kkwh70sgw
title: Visual circuitry for distance estimation in Drosophila

description: This dataset contains all the processed neural imaging and behavioral time
 series data associated with the manuscript as submitted to Current
 Biology. All data corresponds to measurements from Drosophila, and is
 sub-divided into two distinct data structures corresponding to the
 different types of data (neural imaging and behavioral time series).
 Neural imaging data is contained in one Matlab struct, and the behavioral
 time series data is contained in a different Matlab struct, both of which
 have their fields and units described in the corresponding README. All the
 data is to be made publicly available as open-source, and all associated
 code for recreating analysis done within the manuscript is also provided
 here and in the corresponding GitHub repository. The behavior structure
 includes all locomotor data from a genetic silencing screen in which
 neural substrates were identified in the Drosophila visual system for
 their involvement (or lack thereof) in distance estimation behaviors.
 Meanwhile, the neural imaging structure includes all the calcium
 fluorescence data from two-photon microscopy of LC15 neurons which were
 identified as motion parallax detectors in the manuscript. The visual
 stimuli shown during these recordings consisted of particular combinations
 of foreground and background motion that elicited various degrees of
 parallax cues.
description: # Visual circuitry for distance estimation in Drosophila Dataset DOI:
 [10.5061/dryad.kkwh70sgw](10.5061/dryad.kkwh70sgw) ## Description of the
 data and file structure The data were collected to identify and
 characterize neural circuits within the Drosophila visual system that are
 involved in distance estimation behaviors. ### Files and variables ####
 File: Processed_Behav_Data_WS.mat **Description:** Contains all of the
 summary-level behavioral gap crossing data taken as part of the neuronal
 silencing screen, along with wild-type experiments and any associated
 controls. This can be loaded into MATLAB and contains all of the data
 necessary to generate the gap crossing figures in the manuscript. #####
 Variables * `AllCrossStats`: 42x15 cell array that contains all of the gap
 crossing summary statistics from the screen. Rows (of which there are 42)
 correspond to different genotype groups, and columns (of which there are
 15) refer to different experiment groups. Column 1 consists of all
 experiments that used wild-type flies, column 2 consists of all
 experiments that used shibire to silence specific neuronal drivers, column
 3 consists of all genetic control experiments, and columns 4+ correspond
 to miscellaneous experiments associated with genotypes. Each cell within
 the cell array is a struct in which all of the gap crossing summary
 statistics are stored that were utilized in the paper. *
 `AllCrossStatsGenotypes`: Corresponding 42x15 cell array that contains the
 full genotype for the summary statistics stored in `AllCrossStats`. *
 `AllCrossStatsNames`: Corresponding 42x15 cell array that contains the
 names of the neurons and experiment types associated with the summary
 statistics stored in `AllCrossStats`. #### File: Behavior_Data.zip
 **Description:** Contains all of the behavioral gap crossing data taken as
 part of the neuronal silencing screen, along with wild-type experiments
 and any associated controls. This file is a compressed version of all the
 directories and experiments, so it should be downloaded as is and then
 extracted into the cloned "Data" directory. Each folder within
 this zipped directory structure follows the naming convention of
 `[genotype]_[experimental condition]`, and within each of these
 directories are directories containing the data from the associated
 experiment number (all labeled as `Experiment_[#]`). Also within these
 directories are the processed `.mat` and `.fig` files associated with
 those specific behavioral experiments. The highest level processed data
 from these files is contained within **`Processed_Behav_Data_WS.mat`**,
 but these `.mat` files in this directory structure contain slightly more
 of the raw data storage, including the behavioral time series data. To see
 how all of these analyses were done, including the sequential data
 processing that is stored within the `Experiment_[#]` directory, please
 refer to the analysis pipeline code. #### File:
 LC15_Imaging_and_Behavior_Data.zip **Description:** Contains all of the
 directories and data needed to produce the figures in the manuscript that
 correspond to simultaneous neural imaging and behavioral measurements.
 This file is a compressed version of all the directories and experiments,
 so it should be downloaded as is and then extracted into the cloned
 "Data" directory. In order to process the data within these
 subdirectories, please see below (**Figure_Generation_Scripts.zip**). ####
 File: LC15_Imaging_Data.zip **Description:** Contains all of the
 directories and data needed to produce the figures in the manuscript that
 correspond to neural imaging without simultaneous behavioral measurements.
 This file is a compressed version of all the directories and experiments,
 so it should be downloaded as is and then extracted into the cloned
 "Data" directory. In order to process the data within these
 subdirectories, please see below (**Figure_Generation_Scripts.zip**). ####
 File: Figure_Generation_Scripts.zip **Description:** Contains all of the
 directories and scripts needed to process the data provided in the
 above-mentioned files to produce the final figure panels within the
 manuscript. In order to utilize these functions, please download and
 extract this file in the same directory in which the "Data"
 directory is cloned. In the extracted directory, there are six
 subdirectories. All but one follow the naming scheme `[Experiment
 Type]_Fig_[Corresponding Fig # in Paper]`, and the other subdirectory is
 named `Final Figs`. * Within each `[Experiment Type]_Fig_[Corresponding
 Fig # in Paper]` directory, there exist up to three sub-directories as
 follows: * `fig_files`: Matlab figure files (`.fig`) that are produced by
 running the scripts in `Generation_Code`, which processes data from one of
 the above described data files. * `Generation_Code`: Matlab analysis
 scripts that process the data in the above described data files and
 generates the Matlab figure files (`.fig`) saved in the
 `fig_files` subdirectory described above. Each script is named after the
 figure panel in the paper or the information it generates. *
 `image_files`: Exported versions of the Matlab figure files, typically
 saved as `.png`, `.ai`, or `.svg`. * Within the `Final Figs` directory,
 there exist two subdirectories (`AI Files` and `PNG Files`) in which the
 final versions of the figures in the manuscript are saved. These consist
 of all the sub-figures generated in the above scripts as panels. ##
 Code/software All files utilize MATLAB for importing, visualization, and
 processing/analysis. Matlab2023a was the distribution used, but any
 distribution after Matlab2020b is compatible with the data. All code and
 scripts included in the submission have their instructions documented in
 the preceding data section, as well as the [GitHub
 repository](https://github.com/ClarkLabCode/Gap_Crossing) associated with
 this manuscript. Additionally, each individual function within the
 analysis pipeline contains all relevant information within its header as a
 comment in case the relationship between scripts is unclear due to an
 accidental displacement of the script location. For the smoothest
 experience, please follow the download and extraction instructions
 provided above (which can also be found in the GitHub `README`) in order
 to ensure that all directory structures are correctly preserved when
 downloading the data and scripts.