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cjgabriecjgabrie
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Update to version 1.6
- Fixed bug causing crash when using multiple ROIs - Fixed bug causing saved GUI settings to not be applied (despite showing on GUI) - Fixed bug causing multiple incorrect tracking points during image registration - Changed naming in single mode to remove video extension on resulting analysis folder
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-17
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‎BehaviorDEPOT_GUI_v1_6.mlapp‎

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‎BehaviorDEPOTv1.6.mlappinstall‎

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‎BehaviorDEPOTv1.6.prj‎

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<deployment-project plugin="plugin.apptool" plugin-version="1.0">
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<configuration build-checksum="2926307672" file="C:\BehaviorDEPOT\BehaviorDEPOTv1.6.prj" location="C:\BehaviorDEPOT" name="BehaviorDEPOTv1.6" target="target.mlapps" target-name="Package App">
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<param.appname>BehaviorDEPOTv1.6</param.appname>
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<param.authnamewatermark>C. Gabriel, Z. Zeidler, B. Jin, L. DeNardo</param.authnamewatermark>
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<param.email />
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<param.company />
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<param.icon />
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<param.icons />
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<param.summary>BehaviorDEPOT v1.6 application for analyzing top-down rodent DLC/SLEAP tracking and automatic behavior classification</param.summary>
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<param.description />
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<param.screenshot>C:\Users\chris\AppData\Local\Temp\tpe03402fa_0134_443d_97fe_253027d8a554.png</param.screenshot>
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<param.version>1.6</param.version>
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<param.products.name>
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<item>MATLAB</item>
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<item>Curve Fitting Toolbox</item>
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<item>Parallel Computing Toolbox</item>
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<item>Signal Processing Toolbox</item>
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<item>Statistics and Machine Learning Toolbox</item>
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</param.products.name>
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<param.products.id>
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<item>1</item>
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<item>60</item>
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<item>80</item>
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<item>8</item>
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<item>19</item>
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</param.products.id>
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<param.products.version>
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<item>9.12</item>
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<item>3.7</item>
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<item>7.6</item>
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<item>9.0</item>
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<item>12.3</item>
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</param.products.version>
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<param.platforms />
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<param.output>${PROJECT_ROOT}</param.output>
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<param.guid>c70783ed-8870-4f9e-b919-45aa12649ba7</param.guid>
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<unset>
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<param.email />
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<param.company />
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<param.icon />
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<param.icons />
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<param.description />
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<param.platforms />
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<param.output />
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</unset>
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<fileset.main>
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<file>${PROJECT_ROOT}\BehaviorDEPOT_GUI_v1_6.mlapp</file>
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</fileset.main>
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<fileset.depfun />
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<fileset.resources>
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<file>${PROJECT_ROOT}\code</file>
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</fileset.resources>
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<fileset.package />
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<build-deliverables>
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<file location="C:\" name="BehaviorDEPOT" optional="false">C:\BehaviorDEPOT</file>
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</build-deliverables>
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<workflow />
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<matlab>
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<root>C:\Program Files\MATLAB\R2022a</root>
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<toolboxes />
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</matlab>
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<platform>
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<unix>false</unix>
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<mac>false</mac>
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<windows>true</windows>
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<win2k>false</win2k>
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<winxp>false</winxp>
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<vista>false</vista>
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<linux>false</linux>
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<solaris>false</solaris>
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<osver>10.0</osver>
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<os32>false</os32>
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<os64>true</os64>
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<arch>win64</arch>
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<matlab>true</matlab>
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</platform>
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</configuration>
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</deployment-project>

‎code/BehDEPOT_mainscript.m‎

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if P.batchSession == 1
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analyzed_folder_name = strcat(P.basedir, addSlash(), P.video_folder_list(j), addSlash(), P.video_folder_list(j), '_analyzed');
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else
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analyzed_folder_name = strcat(P.video_file,"_analyzed");
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[~,vid_no_ext] = fileparts(P.video_file);
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analyzed_folder_name = strcat(vid_no_ext, "_analyzed");
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end
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saveDataPrep(analyzed_folder_name, Params, Tracking, Metrics);

‎code/classifiers/calculateTMaze.m‎

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% T-Maze Classifier
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% C.G. 3/1/22
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% Contact: [email protected]
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%INPUT: Params, Tracking, Metrics (from BehaviorDEPOT output)
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%OUTPUT: TMaze Structure
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% INPUT: Params, Metrics (from BehaviorDEPOT output)
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% OUTPUT: TMaze Structure
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% FUNCTION: Classify total & percent time (in s), distance traveled (in cm), and number of
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% entries into each ROI
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% PARAMS:
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% 1) windowWidth: for convolving inROI vectors
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% 2) countThreshold: for convolving inROI vectors
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% 3) ROI_Labels:
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all_ROIs{i} = convolveFrames(all_ROIs{i}, Params.TMaze.windowWidth, Params.TMaze.countThreshold);
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end
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%% Analysis
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%% TMaze Analysis
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% Collect frame-wise distance traveled
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dist_traveled_frame = Metrics.Movement.DistanceTraveled;
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for i = 1:length(all_ROIs)
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% Calculate percent time in each arm (o1, o2, c1, c2) + center
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TMaze.(roi_names{i}).Bouts = findStartStop(all_ROIs{i});
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TMaze.(roi_names{i}).Vector = all_ROIs{i};

‎code/functions/drawROIs.m‎

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if r > 1
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hold on;
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for nroi = 1:(r-1)
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plot(polyshape(P.roi_limits{nroi}), 'FaceAlpha', 0.25)
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plot(polyshape(roi_limits{nroi}), 'FaceAlpha', 0.25)
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end
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end
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‎code/functions/videoInterface.m‎

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P.Video.location = video_name;
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% Collect 5 random frames
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frame_idx = randi(vid.numFrame,1, 5); % take random frame to verify tracking
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frame_idx = randi(vid.numFrame, 1, 5); % take random frame to verify tracking
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Frame = struct();
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‎code/gui_settings.mat‎

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‎code/modules/BD_dataPrep.m‎

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%% BehaviorDEPOT Data Prep Module
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% C.G. 2/24/22
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% PURPOSE: Import user input from BehaviorDEPOT GUI (stored in P) and apply
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% to run 'j'; performs pose registration, ROI drawing interface, data smoothing/interpolation, and metric calculation
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% INPUTS:
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% P: Structure array of user parameters imported from GUI
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% j: Counting variable (integer) for batch analysis runs
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% OUTPUTS:
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% Params: Structure array of parameters for current run
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% Tracking: Structure array of raw and smoothed pose tracking data
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% Metrics: Structure array of extracted metrics from registered animal
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% P: User input structure to be run on future runs; includes updates for
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% reused-ROI and part registration
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function [Params, Tracking, Metrics, P] = BD_dataPrep(P, j)
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%% Select current dataset

‎code/plotting/plotPointTracking.m‎

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%plotPointTracking
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%INPUT: Tracking, Params, frame, frame index
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%OUTPUT: Behavior.Freezing structure
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%FUNCTION: calculate the freezing frames via transformation of data from
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%the Metrics structure and save into Behavior structure
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% Future: Calculate average velocity of body; test in place of
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% RearBackVelocity
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function pointValidation = plotPointTracking(Tracking, Params, frame, frame_idx)
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% visual verification of point tracking and body part indexing
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frame_idx = str2num(frame_idx(2:end));
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part_names = Params.part_names;
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leg = {};
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figure('Name','Example point alignment and body part indexing');

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