This readme.txt file was generated on 2022-01-07 by Tworig, J. GENERAL INFORMATION 1. Title of Dataset: "Excitatory neurotransmission activates compartmentalized calcium transients in Müller glia without affecting lateral process motility" 2. Author Information A. Principal Investigator Contact Information Name: Marla Feller Institution: University of California, Berkeley Address: 142 Weill Hall, Berkeley, CA, 94720 Email: mfeller@berkeley.edu B. Associate or Co-investigator Contact Information Name: Joshua Tworig Institution: University of California, Berkeley Address: 142 Weill Hall, Berkeley, CA, 94720 Email: jtworig@berkeley.edu 3. Date of data collection (date range; YYYY-MM-DD): 2017-10-03 to 2021-10-18 4. Geographic location of data collection: Berkeley, CA 5. Information about funding sources that supported the collection of the data: -National Science Foundation, Award: DGE 1752814 -National Institutes of Health, Award: R01EY019498 -National Institutes of Health, Award: R01EY013528 -National Institutes of Health, Award: P30EY003176 SHARING/ACCESS INFORMATION 1. Links to publications that cite or use the data: https://doi.org/10.7554/eLife.73202 2. Links to other publicly accessible locations of the data: https://dx.doi.org/10.6078/d12d9f 3. Was data derived from another source? No 4. Recommended citation for this dataset: Tworig J, Coate C, Feller M (2021) Data from: Excitatory neurotransmission activates compartmentalized calcium transients in Müller glia without affecting lateral process motility. Dryad Digital Repository, doi:10.6078/d12d9f DATA & FILE OVERVIEW 1. File List: -'motilityDataWithZ.mat' is a MATLAB structure that contains data and experimental conditions for all imaging fields of view in which glial processes were counted and categorized into the following categories: extension, retraction, stable, new process ('np'), lost process ('lp'), extension followed by retraction ('e_r'), and retraction followed by extension ('r_e'). Each entry within these fields is a Z-location of an individual process. Z-locations indicating borders of IPL are denoted in this structure under the fields 'minZ' and 'maxZ'. These were used to normalize the Z locations for motility categories from 0 to 1. These normalized values are indicated within fields with the prefix 'norm' (eg. 'normExtension'). -'motilityData_colormap.mat' is the color map used for generating stacked histograms in Figures 1 and 5. -'caImagingData.mat' is a MATLAB workspace containing processed calcium imaging data in the form of separate stuctures for each experiment. Each experiment has two structures associated with it, one for stalks and one for lateral processes (LPs). After loading the dataset into MATLAB, run the .m script(s) associated with the figure of interest to extract and plot relevant summary data. -'fillData.mat', 'sholl_xy.mat', 'sholl_xz.mat', and 'sholl_yz.mat' are MATLAB structures that contain morphological measurements (fillData.mat) and Sholl analysis intersections (sholl_xy,xz,yz) from traced Muller glial cells that were filled with fluorescent dye. In 'fillData.mat' are morphological parameters and other metadata, with each row a different cell. 'sholl_xy.mat', 'sholl_xz.mat', and 'sholl_yz.mat' are Sholl intersection data, with columns corresponding to cells, and rows corresponding to Sholl radii. With these four structures loaded into MATLAB, run the script 'Fig6_plots+morphology stats.m' to extract and plot data for Figure 6. This script also runs unpaired t-tests for morphological data of interest, comparing wt to ko.
-'fig1DE_plots.m': MATLAB script used with 'motilityDataWithZ.mat' and 'motilityData_colormap.mat' to generate plots and source data used in Fig. 1D-F -'Figure 1-source data 1.csv': source data for Figure 1D-F statistical testing -'fig1G_plots.m': MATLAB script used with 'motilityDataWithZ.mat' and 'motilityData_colormap.mat' to generate plots and source data used in Fig. 1G -'fig1H_plots.m': MATLAB script used with 'motilityDataWithZ.mat' and 'motilityData_colormap.mat' to generate plots and source data used in Fig. 1H -'Figure 1-source data 2.csv': source data for Figure 1G-H -'fig1_statistics.r': R script which pulls data from Figure 1-source data 1.csv and Figure 1-source data 2.csv to perform statistical testing for Figure 1.
-'fig2C_compareStalkLP_participation_ACSF.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 2C -'fig2D_intercompartmentLatency_ACSF.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 2D -'Figure 2-source data 1.csv': source data for Figure 2C-D -'fig2_statistics.r': R script which pulls data from Figure 2-source data 1.csv to perform statistical testing for Figure 2.
-'fig3B_acsf_v_pirenzepine_proportionParticipating.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 3B -'fig3C_acsf_v_pirenzepine_latency.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 3C -'fig3D_acsf_v_pirenzepine_transientAmplitudes.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 3D -'fig3E_acsf_v_pirenzepine_waveProperties+stats.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 3E, along with statistical tests for Fig 3E. -'Figure 3-source data 1.csv': source data for Figure 3B-D. -'fig3BCD_statistics.r': R script which pulls data from Figure 3-source data 1.csv to perform statistical testing for Figure 3. -'fig3s1A_DNQX_proportionParticipating.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 3 - supplement 1A. -'fig3s1B_DNQX_proportionParticipating.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 3 - supplement 1B. -'Figure 3-source data 2.csv': source data for Fig. 3 - supplement 1. -'fig3_supplmement1_statistics.r': R script which pulls data from Figure 3-source data 2.csv to perform statistical testing for Fig. 3 - supplement 1.
-'fig4B_acsf_gbz_pir_proportionResponding.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 4B. -'fig4C_acsf_gbz_pir_transientAmplitudes.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 4C. -'fig4D_acsf_gbz_pir_latencies.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 4D. -'fig4E_acsf_gbz_pir_waveProperties.m': MATLAB script used with 'caImagingData.mat' to generate plots and source data used in Fig. 4E, along with statistical tests for Fig. 4E. -'Figure 4-source data 1.csv': source data for Fig. 4B-D. -'fig4_statistics.r': R script which pulls data from Figure 4-source data 1.csv to perform statistical testing for Fig. 4B-D.
-'Fig6_plots+morphology stats': MATLAB script used with 'motilityDataWithZ.mat' and 'motilityData_colormap.mat' to generate plots and source data used in Fig. 5F. -'Figure 5-source data 1.csv': source data for Fig. 5F. -'fig5F_statistics.r': R script which pulls data from Figure 5-source data 1.csv to perform statistical testing for Fig. 5F.
-'Fig6_plots+morphology stats': MATLAB script used with 'fillData.mat', 'sholl_xy.mat', 'sholl_xz.mat', and 'sholl_yz.mat' to generate plots and Sholl analysis source data used in Fig. 6D-E. -'Figure 6-source data 1.csv': source data for Fig. 6E. -'fig6_sholl_statistics.r': R script which pulls data from Figure 6-source data 1.csv to perform statistical testing on Sholl profiles for Fig. 6E. 2. Relationship between files: The datasets should be loaded into MATLAB, and then in order to extract relevant data, run the MATLAB script(s) associated with each figure from the accompanying study. Statistical analyses for Figures 1-6 may be run using the enclosed R scripts. There is a separate R script for each figure, and each references a .csv source data file for the relevant figure. METHODOLOGICAL INFORMATION 1. Description of methods used for collection and processing of data: This dataset includes Müller glial calcium imaging and morphological data underlying all figures for the referenced manuscript, in which details about data acquisition and processing can be found in the 'Materials and Methods' section. For Figures 1 and 5, morphological measurements were obtained from two-photon volumetric images of membrane-tagged Müller glial processes in live flat mount retina. All morphological images were band pass filtered in XY space to reduce noise, corrected for 3D drift and photobleaching, and time course movies were collapsed into a single temporally color-coded image stack for subsequent quantification. For each field of view (FOV), processes were counted and grouped into one of 7 categories depending on whether motility occurred. Process counts and their associated Z-planes were then imported into MATLAB, where Z-planes for all counts within each FOV were normalized from 0 to 1 to enable comparison across cells and experiments. This morphological dataset is found in "motilityDataWithZ.mat". For Figures 2-4, two-photon calcium imaging was performed on live flat mount retina in which Müller glia were labeled with a genetically encoded or organic calcium indicator. Following motion correction, regions of interest (ROIs) were semiautomatically placed over glial stalks and lateral processes using a segmentation algorithm. Average fluorescence intensity within these ROIs was normalized and smoothed using a median filter. Traces were Z scored, and a threshold Z score of 3 was used to define calcium transients, which were then further defined as wave-associated if they occurred within 3 seconds of the peak of a wave-associated EPSC. Using MATLAB scripts, measurements including proportion of ROIs participating in retinal waves, calcium transient amplitudes, and calcium transient latencies between stalks and lateral processes were obtained and can be found in "caImagingData.mat". This dataset also contains data from simultaneous electrophysiological recording of retinal waves, including EPSC amplitude and inter-wave interval. For Figure 6, Müller glial morphology was visualized by filling individual cells with fluorescent dye and obtaining volumetric two-photon images of dye-filled cells. Cells were traced using FIJI's Simple Neurite Tracer plugin, and measurements including number of tips, total process length, total branch points, and primary branches from stalk were derived from traced paths. Paths were converted into binarized skeletons and registered to correct for XY displacement of the stalk between the GCL and INL. Sholl analysis was performed using concentric rings spaced 1 µm apart, in the XY, XZ, and YZ planes. For the XZ and YZ planes, the center of each Sholl radius was placed on the end of the stalk closest to the INL in orthogonal projections of traced cells. Sholl radii were normalized to the total IPL thickness. Convex hull area was defined as the area of the smallest convex polygon enclosing the entire skeleton in an XY maximum projection image. These measurements and Sholl analysis data are in the MATLAB structures 'fillData.mat', 'sholl_xy.mat', 'sholl_xz.mat', and sholl_yz.mat'. MATLAB scripts were used to extract data points of interest from these datasets for subsequent computation of summary statistics. There is a separate script associated with each figure. For each figure, the underlying data to be included was compiled into a source data file (eg. "Figure 1-source data 1.csv"). R scripts referencing these source data files were used to apply statistical testing. 2. Instrument- or software-specific information needed to interpret the data: -MATLAB (MathWorks) is required to generate plots from .mat datasets using provided scripts. -R is required for statistical analyses of processed data contained in source data files using provided R scripts. DATA-SPECIFIC INFORMATION FOR: 'caImagingData.m' 1. Number of variables: 30 2. Number of cases/rows: 20 experiments, multiple fields of view for each experiment 3. Variable List: 1. experiment date (separate MATLAB structure for each experiment; date is contained in name of structure as 'summaryExptData_YYMMDD_stalks' or 'summaryExptData_YYMMDD_LPs') 2. imgNum: acquisition number of image during each experiment 3. EPSCtimes: timing of retinal wave-associated EPSCs (seconds) 4. EPSCmags: magnitudes of retinal wave-associated EPSCs (pA) 5. condition: experimental condition (acsf/control or drug) 6. age: age of mouse used in experiment 7. waveTimes: timing of waves in imaging (frames), with bursts counted as one wave 8. roiThresh: Z score threshold used for peak detection in individual ROI traces 9. frames: range of image frames used for analysis 10. multiWaveTimes: array containing frames of all wave peaks, including multiple peaks for wave bursts 11. totalROIs: number of stalk or lateral process ROIs in the field of view 12. traces: array of deltaF/F traces for all ROIs (ROI x frame) 13. allRoiTransients: cell array with all detected calcium transients, separated by ROI 14. roiWaveTransients: cell array with wave-associated calcium transients, separated by ROI 15. roiNonWaveTransients: cell array with non-wave-associated calcium transients, separated by ROI 16. roiWaveAmps: cell array with deltaF/F amplitudes for wave-associated calcium transients, separated by retinal wave (rows). column 1: dF/F amplitude; column 2: ROI index; column 3: peak response frame 17. nonWaveIEIs: cell array with inter-event intervals for non-wave-associated transients, separated by ROI 18. nonWaveFreqs: cell array with frequencies of non-wave-associated transients, separated by ROI 19. caAmpsAll: cell array with dF/F amplitudes of all calcium transients, separated by ROI 20. caAmpsWaves: cell array with dF/F amplitudes of wave-associated calcium transients, separated by ROI 21. caAmpsNonWaves: cell array with dF/F amplitudes of non-wave-associated calcium transients, separated by ROI 22. iwi: interwave-intervals (seconds) 23. numResponsesSum: number of responding ROIs for each wave (array length equals number of waves) 24. randResponsesSum: number ROIs responding at random non-wave times (array length equals number of waves) 25. zAmpsWaves: cell array with Z scored amplitudes of wave-associated calcium transients, separated by ROI 26. zAmpsNonWaves: cell array with Z scored amplitudes of non-wave-associated calcium transients, separated by ROI 27. randWaveTimes: frames of randomly selected non-wave times 29. responsesByWaveHT_5: cell array containing frames of peak wave-associated responses for stalks or lateral processes for latency calculations (# waves x # ROIs) 30. LPhalfResponseTimesHT_5: array containing frames at which half of all lateral processes have responded to each retinal wave (median response frame for all lateral processes per wave), for latency calculations. DATA-SPECIFIC INFORMATION FOR: 'motilityDataWithZ.mat' 1. Number of variables: 20 2. Number of cases/rows: 250 3. Variable List: 1. file: prefix of filename for each image stack; 'YYMMDD_NNN' 2. extension: Z-locations of extending processes in inner plexiform layer 3. retraction: Z-locations of retracting processes in inner plexiform layer 4. stable: Z-locations of stable processes in inner plexiform layer 5. np: Z-locations of newly sprouted processes in inner plexiform layer 6. lp: Z-locations of lost processes in inner plexiform layer 7. e_r: Z-locations of processes extending and then retracting in inner plexiform layer 8. r_e: Z-locations of processes retracting and then extending in inner plexiform layer 9. minZ: Z-slice of lateral process closest to GCL (GCL/IPL border) 10. maxZ: Z-slice of process closest to INL (IPL/INL border) 11. normExtension: Z-locations of extending processes, normalized to IPL borders 12. normRetraction: Z-locations of retracting processes, normalized to IPL borders 13. normStable: Z-locations of stable processes, normalized to IPL borders 14. normNp: Z-locations of newly sprouted processes, normalized to IPL borders 15. normLp: Z-locations of lost processes, normalized to IPL borders 16. normE_r: Z-locations of processes extending and then retracting, normalized to IPL borders 17. normR_e: Z-locations of processes retracting and then extending, normalized to IPL borders 18. condition: experimental condition (acsf/control or drug application) 19. age: age of mouse 20. FOV: number of FOV during acquisition, for matching of control and drug conditions 4. supporting filename: 'motilityData_colormap.mat' (colormap for plotting) DATA-SPECIFIC INFORMATION FOR: 'fillData.mat' 1. Number of variables: 19 2. Number of cases/rows: 90 3. Variable List: 1. experiment: experiment/animal number 2. cell: cell/acquisition number within each experiment 3. cable length: total length of traced processes plus stalk (um) 4. # branch points: number of points at which one path splits into two or more paths 5. # branches: number of path segments in traced skeleton 6. stalk length: length of traced stalk (um) 7. process length: total length of traced lateral processes (um) 8. # process tips: number of tips/terminal branches 9. convex hull area: area of convex polygon around glial process arbor in max intensity projection of traced skeleton (um^2) 10. branches from stalk: number of branches extending from the stalk 11. date: date of experiment as YYMMDD 12. geno: mouse genotype 13. age: age of mouse (days) DATA-SPECIFIC INFORMATION FOR: 'sholl_xy.mat', 'sholl_xz.mat', 'sholl_yz.mat' 1. Number of variables: 3 2. Number of cases/rows: 90 3. Variable List: 1. experiment: experiment/animal number 2. cell: cell/acquisition number within each experiment 3. sholl: Sholl profile containing # intersections at each radius; center (0um) is row 3 in sholl_xy/xz/yz array DATA-SPECIFIC INFORMATION FOR: 'Figure 1-source data 1.csv' 1. Number of variables: 8 2. Number of cases/rows: 104 3. Variable List: 1. proportion processes: proportion of total processes in each sublayer per field of view (columns 1-20; each row is a separate FOV) 2. age: age of mouse for comparisons of proportion processes per sublayer 3. sublayer: IPL sublayer (S1-S5) 4. number processes: counts of processes in each sublayer; used to calculate proportion processes (columns 21-40; rows/cells correspond with those in columns 1-20) 5. motility category: description of morphological dynamics for each process (extension, new process, retraction, lost process, extension followed by retraction, retraction followed by extension, stable; column 41) 6. motility counts: number of processes in each motility category (columns 42-61) 7. stable proportions: proportion of total processes stable for each cell (column 62) 8. age group: groups for comparisons of proportion stable across all ages (column 63) DATA-SPECIFIC INFORMATION FOR: 'Figure 1-source data 2.csv' 1. Number of variables: 12 2. Number of cases/rows: 12 3. Variable List: 1. motility category: description of morphological dynamics for each process in cytoskeletal block conditions (column 1; corresponds to columns 2-5, 19-22) 2. motility counts (cytoskeletal blockers): number of processes in each motility category with cytoskeletal manipulation (columns 2-5) 3. condition (cytoskeletal blockers): acsf, cytochalasin-D, nocodazole, or cytochalasin-D + nocodazole (for columns 2-5, 7-10, 11-14, 15-18) 3. cell (cytoskeletal blockers): cell/FOV number in cytoskeletal blockers (corresponds to columns 7-18) 4. stable counts (cytoskeletal blockers): number of stable processes for each FOV in cytoskeletal blockers (columns 7-10) 5. total counts (cytoskeletal blockers): total number of processes for each FOV in cytoskeletal blockers (columns 11-14) 6. stable proportions (cytoskeletal blockers): proportion of total stable processes for each FOV in cytoskeletal blockers (columns 15-18) 7. motility counts (EGF): number of processes in each motility category with EGF application (columns 19-22) 8. condition (EGF): acsf or EGF (for columns 19-22, 24-27, 28-31, 32-35) 8. age (EGF): age of mouse in EGF experiments (P8 or P17) 9. cell (EGF): cell/FOV number in EGF condition (corresponds to columns 24-35) 10. stable counts (EGF): number of stable processes for each FOV with EGF application (24-27) 11. total counts (EGF): total number of processes for each FOV with EGF application (columns 28-31) 12. stable proportions (EGF): proportion of total stable processes for each FOV with EGF application (columns 32-35) DATA-SPECIFIC INFORMATION FOR: 'Figure 2-source data 1.csv' 1. Number of variables: 14 2. Number of cases/rows: 1582 3. Variable List: 1. proportion responding per wave: proportion of total stalk or lateral process ROIs responding to each retinal wave (each row is a retinal wave) 2. group 1: grouping variable for proportion responding (not used in analysis; corresponds to column 1) 3. age 1: age groups for proportion responding (1: P9/10, 2: P11/12; corresponds to column 1) 4. compartment 1: compartment groups for proportion responding (1: stalks; 2: lateral processes; corresponds to column 1) 5. id 1: identifier for stalk and lateral process ROIs paired by wave (corresponds to column 1) 6. average prop. responding per FOV: average proportion of total stalk or lateral process ROIs responding per retinal wave, by FOV (each row is a FOV) 7. group 2: grouping variable for average prop. responding per FOV (not used in analysis; corresponds to column 6) 8. age 2: age groups for average prop. responding per FOV (1: P9/10, 2: P11/12; corresponds to column 6) 9. compartment 2: compartment groups for average prop. responding per FOV (1: stalks; 2: lateral processes; corresponds to column 6) 10. id 2: identifier for stalk and lateral process ROIs paired by FOV (corresponds to column 6) 11. stalk response latency: time (seconds) between individual stalk ROI wave-associated responses and the median wave-associated transient timepoint for all responding lateral processes within the FOV 12. age 3: age group for individual stalk-lateral process latencies (young: P8/9, old: P11/12) 13. average latency per FOV: average stalk-lateral process response latency per wave for each FOV. 14. age 4: age group for average latency per FOV (young: P8/9, old: P11/12) DATA-SPECIFIC INFORMATION FOR: 'Figure 3-source data 1.csv' 1. Number of variables: 28 2. Number of cases/rows: 31377 3. Variable List: 1. proportion responding per wave: proportion of total stalk or lateral process ROIs responding to each retinal wave (each row is a retinal wave) 2. drug 1: drug condition (ACSF or pirenzepine; corresponds to column 1) 3. compartment 1: compartment groups for proportion responding (stalks or lateral processes; corresponds to column 1) 4. id 1: identifier for stalk and lateral process ROIs paired by wave (corresponds to column 1) 5. proportion responding; ages separated: proportion of total stalk or lateral process ROIs responding to each retinal wave, with corresponding ages denoted in a subsequent column (each row is a retinal wave) 6. drug 2: drug condition (ACSF or pirenzepine; corresponds to column 5) 7. compartment 2: compartment groups for proportion responding (stalks or lateral processes; corresponds to column 5) 8. age 2: age groups for proportion ROIs responding per wave (P9/10 or P11/12; corresponds to column 5) 9. id 2: identifier for stalk and lateral process ROIs paired by wave (corresponds to column 5) 10. fold_change_particip: fold change in average proportion ROIs responding to retinal waves (each row is a FOV) 11. compartment 3: compartment groups for fold change in proportion responding (stalks or lateral processes; corresponds to column 10) 12. age 3: age groups for fold change in proportion responding (P9/10 or P11/12; corresponds to column 10) 13. fov 3: identifier for stalks and lateral processes paired by FOV (corresponds to column 10) 14. stalk response latency: time (seconds) between individual stalk ROI wave-associated responses and the median wave-associated transient timepoint for all responding lateral processes within the FOV (each row is one wave-associated stalk response) 15. drug 4: drug condition for latency measurements (corresponds to column 14) 16. age 4: age groups for latency measurements (corresponds to column 14) 17. fov 4: identifier for responses in same FOV (corresponds to column 14) 18. transient amplitude: Z scored wave-associated calcium transient df/f amplitude (each row is one wave-associated response) 19. drug 5: drug condition for transient amplitude measurements (corresponds to column 18) 20. compartment 5: compartment group for transient amplitude measurements (corresponds to column 18) 21. transient; separate ages: wave-associated calcium transient amplitudes with associated ages denoted in a subsequent row 22. drug 6: drug condition for transient amplitude measurements (corresponds to column 21) 23. compartment 6: compartment group for transient amplitude measurements (corresponds to column 21) 24. age 6: age groups for transient amplitude measurements (corresponds to column 21) 25. fold_change_amplitude: fold change in average wave-associated transient amplitude (each row is a FOV) 26. compartment 7: compartment groups for fold change in average wave-associated transient amplitude (stalks or lateral processes; corresponds to column 25) 27. age 7: age groups for fold change in average wave-associated transient amplitude (P9/10 or P11/12; corresponds to column 25) 28. fov 7: identifier for stalks and lateral processes paired by FOV (corresponds to column 25) DATA-SPECIFIC INFORMATION FOR: 'Figure 3-source data 2.csv' 1. Number of variables: 7 2. Number of cases/rows: 1657 3. Variable List: 1. proportion responding per wave: proportion of total stalk or lateral process ROIs responding to each retinal wave (each row is a retinal wave) 2. drug 1: drug condition (ACSF or DNQX; corresponds to column 1) 3. compartment 1: compartment groups for proportion responding (stalks or lateral processes; corresponds to column 1) 4. id : identifier for stalk and lateral process ROIs paired by wave (corresponds to column 1) 5. amplitude: Z scored wave-associated calcium transient df/f amplitude (each row is one wave-associated response) 6. drug 2: drug condition for transient amplitude measurements (corresponds to column 5) 7. compartment 2: compartment group for transient amplitude measurements (corresponds to column 5) DATA-SPECIFIC INFORMATION FOR: 'Figure 4-source data 1.csv' 1. Number of variables: 43 2. Number of cases/rows: 43052 3. Variable List: 1. proportion; pooled ages: proportion of total stalk or lateral process ROIs responding to each retinal wave (each row is a retinal wave) 2. drug 1: drug condition (ACSF or pirenzepine; corresponds to column 1) 3. compartment 1: compartment groups for proportion responding (stalks or lateral processes; corresponds to column 1) 4. id 1: identifier for stalk and lateral process ROIs paired by wave (corresponds to column 1) 5. proportion; separate ages: proportion of total stalk or lateral process ROIs responding to each retinal wave, with corresponding ages denoted in a subsequent column (each row is a retinal wave) 6. drug 2: drug condition (ACSF or pirenzepine; corresponds to column 5) 7. compartment 2: compartment groups for proportion responding (stalks or lateral processes; corresponds to column 5) 8. age 2: age groups for proportion ROIs responding per wave (P9/10 or P11/12; corresponds to column 5) 9. id 2: identifier for stalk and lateral process ROIs paired by wave (corresponds to column 5) 10. fold change acsf-gbz: fold change in average proportion ROIs responding to retinal waves from acsf to gabazine (each row is a FOV) 11. compartment 3: compartment groups for fold change in proportion responding (stalks or lateral processes; corresponds to column 10) 12. age 3: age groups for fold change in proportion responding (P9/10 or P11/12; corresponds to column 10) 13. fov 3: identifier for stalks and lateral processes paired by FOV (corresponds to column 10) 14. fold change gbz-gbz+pir: fold change in average proportion ROIs responding to retinal waves from gabazine to gabazine+pirenzepine (each row is a FOV) 15. compartment 4: compartment groups for fold change in proportion responding (stalks or lateral processes; corresponds to column 14) 16. age 4: age groups for fold change in proportion responding (P9/10 or P11/12; corresponds to column 14) 17. fov 4: identifier for stalks and lateral processes paired by FOV (corresponds to column 14) 18. transient amplitude; pooled ages: Z scored df/f wave-associated calcium transient amplitude (each row is one wave-associated response) 19. drug 5: drug condition for transient amplitude measurements (corresponds to column 18) 20. compartment 5: compartment group for transient amplitude measurements (corresponds to column 18) 21. transient amplitude; separate ages: Z scored df/f wave-associated calcium transient amplitudes with associated ages denoted in a subsequent row 22. drug 6: drug condition for transient amplitude measurements (corresponds to column 21) 23. compartment 6: compartment group for transient amplitude measurements (corresponds to column 21) 24. age 6: age groups for transient amplitude measurements (corresponds to column 21) 25. fc amplitude; acsf-gbz: fold change in average wave-associated transient amplitude, acsf to gabazine (each row is a FOV) 26. compartment 7: compartment groups for fold change in average wave-associated transient amplitude (stalks or lateral processes; corresponds to column 25) 27. age 7: age groups for fold change in average wave-associated transient amplitude (P9/10 or P11/12; corresponds to column 25) 28. fov 7: identifier for stalks and lateral processes paired by FOV (corresponds to column 25) 29. fc amplitude; gbz to gbz+pir: fold change in average wave-associated transient amplitude, gabazine to gabazine+pirenzepine (each row is a FOV) 30. compartment 8: compartment groups for fold change in average wave-associated transient amplitude (stalks or lateral processes; corresponds to column 29) 31. age 8: age groups for fold change in average wave-associated transient amplitude (P9/10 or P11/12; corresponds to column 29) 32. fov 8: identifier for stalks and lateral processes paired by FOV (corresponds to column 29) 33. latency: time (seconds) between individual stalk ROI wave-associated responses and the median wave-associated transient timepoint for all responding lateral processes within the FOV (each row is one wave-associated stalk response) 34. drug 9: drug condition for latency measurements (corresponds to column 33) 35. iwi: interwave interval measured from voltage clamp recordings (seconds) 36. drug 10: drug condition corresponding to iwi measurements (corresponds to column 35) 37. id 10: identifier for matched cells recorded in acsf, gabazine, and gabazine + pirenzepine (corresponds to column 35) 38. epsc: magnitude of wave-associated EPSC (pA) 39. drug 11: drug condition corresponding to EPSC measurements (corresponds to column 38) 40. id 11: identifier for matched cells recorded in acsf, gabazine, and gabazine + pirenzepine (corresponds to column 38) 41. latency2: stalk-process latencies (seconds) with calcium indicator denoted in a subsequent row 42. drug2: drug condition for latency measurements in column 41 43. indicator: calcium indicator used for latency measurements in column 41 DATA-SPECIFIC INFORMATION FOR: 'Figure 5-source data 1.csv' 1. Number of variables: 5 2. Number of cases/rows: 16 3. Variable List: 1. motility category: motile, stable, or total 2. number processes: process counts in each category under various conditions 3. age: ages at which motility was measured with glutamate application (P9 or P24) 4. proportion stable per cell: proportion of total processes stable in control vs. drug 5. drug condition: agonist or antagonist used to perturb signaling during motility imaging (glutamate (col 1-9), BAPTA (col 10-15), carbachol (col 16-21), gabazine(col 22-27), TBOA (col. 28-33), pirenzepine (col. 34-39), DNQX/AP5 (col. 40-45)) DATA-SPECIFIC INFORMATION FOR: 'Figure 6-source data 1.csv' 1. Number of variables: 6 2. Number of cases/rows: 81 3. Variable List: 1. crossings: number of intersections at each Sholl radius 2. radius: distance from center point of Sholl profile (in microns for xy dimension; normalized from 0-1 by total IPL thickness for xz and yz dimensions). 3. genotype (geno): mouse genotype (wildtype/wt or B2KO/ko) 4. age: age of mouse used for glial Sholl analysis (young: P12, old: P30+) 5. id: cell identifier (measurements from same cell have same id) 6. dimension: axis in XYZ space in which Sholl analysis was done (XY, XZ, or YZ)