Behavioral and 2P Calcium Imaging Data for "A neural circuit architecture for rapid learning in goal-directed navigation"

<b>Behavioral and 2P calcium imaging data for the following paper:</b>Dan C, Hulse BK, Kappagantula R, +Jayaraman V &amp; +Hermundstad AM (2024), A neural circuit architecture for rapid learning in goal-directed navigation<i>.</i><b>Data files for different groups of flies:</b><b>Preproc_*_FlightBehaviorData.mat: </b>preprocessed behavioral data<b>Preproc_*_CAImaging_FlightBehaviorData.mat: </b>preprocessed behavioral data and raw calcium imaging data<b>Segmented_*_FlightBehaviorData.mat: </b>processed behavioral data segmented into fixations and saccades<b>ProcJumpData_*.mat:</b> processed Calcium imaging data to track jumps in the compass heading over time<b>File descriptors</b><b>:</b><b>Punishment</b> ('Laser'; 'NoLaser'): indicates whether or not flies underwent laser training<b>Genotype</b> ('WT', 'SS00090 Parent/Kir', 'SS00096 Parent/Kir', '60D05')<b>File organization:</b>Each file contains MATLAB data structures indexed by fly <i>i</i> and trial <i>j</i><b>PreProcData*.fly(i).trial(j) </b>contains the following fields:<b>x:</b> frame position of visual scene in arena (can take values from 0 to 95, which span 360deg)<b>wba:</b> difference in wing-beat amplitude between left and right wings<b>wbf:</b> wingbeat frequency<b>time:</b> time in seconds<b>laser:</b> binary number indicating whether laser punishment was delivered<b>puff: </b>binary number indicating whether an airpuff was delivered<b>trialType: </b>'naive', 'train', or 'probe'<b>bgsubF:</b> background-subtracted fluorescence (only for 60D05 flies)<b>SegData*.fly(i).trial(j) </b>contains the following fields:<b>saccades: </b>structure containing properties of saccades<b>fixations:</b> structure containing properties of fixations<b>drift:</b> structure containing properties of drift periods that were not classifies as either fixations or saccades<b>PI:</b> performance score for trial<b>PIinds: </b>indices of timepoints used to compute PI scores and other behavioral measures<b>nlaser: </b>number of timepoints at which laser punishment was delivered.<b>residency: </b>number of timepoints spent at each of 48 frame positions (i.e., collapsed across the two-fold symmetry of the visual scene)<b>shifted: </b>data structure containing data aligned to the preferred heading of each fly, defined over the 48 frame positions in the collapsed span of the arena<b>residencyFull: </b>number of timepoints spent at each of 96 frame positions<b>shiftedFull:</b> data structure containing data aligned to the preferred heading of each fly, defined over all 96 frame positions<b>tSeriesProcAll(i).jumpData(j)</b> contains the following fields:<b>dffMat: </b>fluorescence for 32 wedges in the ellipsoid body, tracked across time<b>arena: </b>orientation of visual scene in arena, defined from -pi to pi radians<b>correctedPVA_EB: </b>original population vector average (PVA) of activity in the EB after correcting for multiple offsets<b>origPVA_EB: </b>original population vector average (PVA) of activity in the EB, without correcting for multiple offsets<b>PVA_EB_strength: </b>strength of corrected PVA<b>FRmaps.FRMapHeading:</b> average fluorescence in each of 32 wedges of the EB for each of 48 orientations of the visual scene (i.e., collapsed across the two-fold symmetry of the visual scene)<b>bumpjumps:</b> structure containing properties of offset between the compass bump and the visual scene<i>the following fields are copied over from the data structures above:</i><b>saccades: </b>structure containing properties of saccades (copied from SegData*.fly(i).trial(j))<b>fixations:</b> structure containing properties of fixations (copied from SegData*.fly(i).trial(j))<b>setpoint:</b> preferred arena heading, defined from 0 to 95 pixels<b>PIinds: </b>indices of timepoints used to compute PI scores and other behavioral measures<b>x:</b> frame position of visual scene in arena (can take values from 0 to 95, which span 360deg)<b>wba:</b> difference in wing-beat amplitude between left and right wings<b>wbf:</b> wingbeat frequency<b>time:</b> time in seconds<b>trialType: </b>'naive', 'train', or 'probe'<br><b>Associated code:</b>Code for FPGA camera-based wingbeat analyzer is available at: https://github.com/ChuntaoDan/FPGA_WingbeatAnalyzer (DOI: 10.5281/zenodo.11060747)Code for all behavioral analyses, calcium imaging analyses, modeling, and plotting is available at https://github.com/HermundstadLab/flyVisualLearning (DOI: 10.5281/zenodo.11062515)<br>