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Local inhibitory dynamics underpin temporal integration and functional segregation between barrels and septa in the mouse barrel cortex.

Code ↔ Paper

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  1. [1] § Results › Progressive multi- over single-whisker response divergence in septal populations is abolished in Elfn1 KO mice ↔ eLife-VOR-RA-2025-107099/Source Code 3.m, lines 803–926 · score 0.59 · 7–20, KO SW, 1–20, KO MW, Layer, ratio
  2. [2] § Methods › t-SNE analysis ↔ eLife-VOR-RA-2025-107099/Source Code 3.m, lines 2352–2408 · score 0.52 · t-SNE, barneshut, exaggeration, gscatter, perplexity, algorithm
  3. [3] § Methods › t-SNE analysis ↔ eLife-VOR-RA-2025-107099/Source Code 5.m, the whole file · a weak match · score 0.51 · t-SNE, barneshut, exaggeration, gscatter, perplexity, algorithm

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The authors' code

MATLAB · 2,922 lines · 131 KB · no license · 2 matches

  1. %% Ali Özgür Argunşah, June, 2026
  2. %% https://doi.org/10.7554/eLife.107099.3
  3. %% Figure 1 and 4 and Supplements
  5. % Load Data
  6. clear all
  8. %%
  9. load('/Users/aargun/Documents/My Papers/Barrel-Septa/Elife_Revision/VOR_June25_2026/Data/Silicon Probe/NeighbourData_Sep2022.mat');
  10. load('/Users/aargun/Documents/My Papers/Barrel-Septa/Elife_Revision/VOR_June25_2026/Data/Silicon Probe/AllData_May2023.mat');
  11. load stim_raw.mat;
  13. saveFolder = '/Users/aargun/Documents/My Papers/Barrel-Septa/Elife_Revision/VOR_June25_2026/Exported';
  15. % Whisker Stim
  16. stimvec = stim(:,2)-mean(stim(1:100,2));
  17. stimvec_norm = stimvec/max(stimvec);
  18. begin = (2610-round(4000/5));
  19. stimvec_norm_synch = stimvec_norm(begin:begin+9199);
  21. t1 = (1:2200)/1000;
  22. t2 = (1:9200)/4182;
  24. stimvec_norm_synch_Fs1000 = interp1(t2',stimvec_norm_synch,t1','spline');
  26. %% Figure 1A - Waveform
  28. figure , plot((1:2200)/1000,100*stimvec_norm_synch_Fs1000,'LineWidth',1,'Color','k');
  29. title('Figure 1A - Waveform');
  31. figure , plot((1:9200)/4182,100*stimvec_norm_synch,'LineWidth',1,'Color','r');
  33. baselineTimes = 1:190;
  35. tempstim = stimvec_norm_synch_Fs1000;
  36. tempstim(tempstim>0.4*ones(2200,1)) = 0;
  37. [pks,locs] = findpeaks(tempstim,'MinPeakHeight',0.2);
  39. % beglocs = locs(1:2:end);
  40. % New BegLocs
  41. beglocs = [205 306 406 506 606 706 806 905 1004 1104 1204 1304 1404 1502 1602 1702 1802 1902 2000 2100 ];
  44. %%
  45. colorBarrel = [50,50,50]/255;%[31,120,180]/255;%[252 216 134]/255;
  46. colorSepta = [206,18,86]/255;%[51,160,44]/255;%[235 38 31]/255;
  47. colorNeigh = [8,81,156]/255;%[227,26,28]/255;%[188 128 219]/255;
  49. colorBarrelKO = [150,150,150]/255;%[177,89,40]/255;%[247 136 154]/255;
  50. colorSeptaKO = [201,148,199]/255;%[106,61,154]/255;%[31 38 235]/255;
  51. colorNeighKO = [78,179,211]/255;%[245,225,75]/255;%[162 238 135]/255;
  53. colorBarrel_MW = colorBarrel/2;%color1/2;%[252 216 134]/255;
  54. colorSepta_MW = colorSepta/2;%color2/2;%[235 38 31]/255;
  55. colorNeigh_MW = [];%color3/2;%[188 128 219]/255;
  57. colorBarrelKO_MW = colorBarrelKO/2;%color1ko/2;%[247 136 154]/255;
  58. colorSeptaKO_MW = colorSeptaKO/2;%color2ko/2;%[31 38 235]/255;
  59. colorNeighKO_MW = [];%color3ko/2;%[162 238 135]/255;
  61. %% MW Data Etraction
  63. counter = 1;
  64. temp_L23_WT_MW = [];
  65. for i = 1:size(jenqData.wt.barrel.L23.multi.spktimes,2)
  66. for j = 1:20
  67. temp = zeros(1,2200);
  68. temp(jenqData.wt.barrel.L23.multi.spktimes{i}{j}) = 1;
  69. temp_L23_WT_MW(counter,:) = temp;
  70. counter = counter + 1;
  71. end
  72. end
  74. counter = 1;
  75. temp_L4_WT_MW = [];
  76. for i = 1:size(jenqData.wt.barrel.L4.multi.spktimes,2)
  77. for j = 1:20
  78. temp = zeros(1,2200);
  79. temp(jenqData.wt.barrel.L4.multi.spktimes{i}{j}) = 1;
  80. temp_L4_WT_MW(counter,:) = temp;
  81. counter = counter + 1;
  82. end
  83. end
  85. counter = 1;
  86. temp_L5_WT_MW = [];
  87. for i = 1:size(jenqData.wt.barrel.L5.multi.spktimes,2)
  88. for j = 1:20
  89. temp = zeros(1,2200);
  90. temp(jenqData.wt.barrel.L5.multi.spktimes{i}{j}) = 1;
  91. temp_L5_WT_MW(counter,:) = temp;
  92. counter = counter + 1;
  93. end
  94. end
  96. counter = 1;
  97. temp_L23_WT_MW_septa = [];
  98. for i = 1:size(jenqData.wt.septa.L23.multi.spktimes,2)
  99. for j = 1:20
  100. temp = zeros(1,2200);
  101. temp(jenqData.wt.septa.L23.multi.spktimes{i}{j}) = 1;
  102. temp_L23_WT_MW_septa(counter,:) = temp;
  103. counter = counter + 1;
  104. end
  105. end
  107. counter = 1;
  108. temp_L4_WT_MW_septa = [];
  109. for i = 1:size(jenqData.wt.septa.L4.multi.spktimes,2)
  110. for j = 1:20
  111. temp = zeros(1,2200);
  112. temp(jenqData.wt.septa.L4.multi.spktimes{i}{j}) = 1;
  113. temp_L4_WT_MW_septa(counter,:) = temp;
  114. counter = counter + 1;
  115. end
  116. end
  118. counter = 1;
  119. temp_L5_WT_MW_septa = [];
  120. for i = 1:size(jenqData.wt.septa.L5.multi.spktimes,2)
  121. for j = 1:20
  122. temp = zeros(1,2200);
  123. temp(jenqData.wt.septa.L5.multi.spktimes{i}{j}) = 1;
  124. temp_L5_WT_MW_septa(counter,:) = temp;
  125. counter = counter + 1;
  126. end
  127. end
  129. counter = 1;
  130. temp_L23_KO_MW = [];
  131. for i = 1:size(jenqData.ko.barrel.L23.multi.spktimes,2)
  132. for j = 1:20
  133. temp = zeros(1,2200);
  134. temp(jenqData.ko.barrel.L23.multi.spktimes{i}{j}) = 1;
  135. temp_L23_KO_MW(counter,:) = temp;
  136. counter = counter + 1;
  137. end
  138. end
  140. counter = 1;
  141. temp_L4_KO_MW = [];
  142. for i = 1:size(jenqData.ko.barrel.L4.multi.spktimes,2)
  143. for j = 1:20
  144. temp = zeros(1,2200);
  145. temp(jenqData.ko.barrel.L4.multi.spktimes{i}{j}) = 1;
  146. temp_L4_KO_MW(counter,:) = temp;
  147. counter = counter + 1;
  148. end
  149. end
  151. counter = 1;
  152. temp_L5_KO_MW = [];
  153. for i = 1:size(jenqData.ko.barrel.L5.multi.spktimes,2)
  154. for j = 1:20
  155. temp = zeros(1,2200);
  156. temp(jenqData.ko.barrel.L5.multi.spktimes{i}{j}) = 1;
  157. temp_L5_KO_MW(counter,:) = temp;
  158. counter = counter + 1;
  159. end
  160. end
  162. counter = 1;
  163. temp_L23_KO_MW_septa = [];
  164. for i = 1:size(jenqData.ko.septa.L23.multi.spktimes,2)
  165. for j = 1:20
  166. temp = zeros(1,2200);
  167. temp(jenqData.ko.septa.L23.multi.spktimes{i}{j}) = 1;
  168. temp_L23_KO_MW_septa(counter,:) = temp;
  169. counter = counter + 1;
  170. end
  171. end
  173. counter = 1;
  174. temp_L4_KO_MW_septa = [];
  175. for i = 1:size(jenqData.ko.septa.L4.multi.spktimes,2)
  176. for j = 1:20
  177. temp = zeros(1,2200);
  178. temp(jenqData.ko.septa.L4.multi.spktimes{i}{j}) = 1;
  179. temp_L4_KO_MW_septa(counter,:) = temp;
  180. counter = counter + 1;
  181. end
  182. end
  184. counter = 1;
  185. temp_L5_KO_MW_septa = [];
  186. for i = 1:size(jenqData.ko.septa.L5.multi.spktimes,2)
  187. for j = 1:20
  188. temp = zeros(1,2200);
  189. temp(jenqData.ko.septa.L5.multi.spktimes{i}{j}) = 1;
  190. temp_L5_KO_MW_septa(counter,:) = temp;
  191. counter = counter + 1;
  192. end
  193. end
  195. %% Spontaneous Analysis
  196. LFP_Barrel_WT_L23_SW = cat(1,jenqData.wt.barrel.L23.single.LFP,jenqData.wt.barrel.L23.multi.LFP);
  198. MUA_Barrel_WT_L23_SW = cat(2,jenqData.wt.barrel.L23.single.MUA,jenqData.wt.barrel.L23.multi.MUA);
  199. MUA_Barrel_KO_L23_SW = cat(2,jenqData.ko.barrel.L23.single.MUA,jenqData.ko.barrel.L23.multi.MUA);
  200. MUA_Septa_WT_L23_SW = cat(2,jenqData.wt.septa.L23.single.MUA,jenqData.wt.septa.L23.multi.MUA);
  201. MUA_Septa_KO_L23_SW = cat(2,jenqData.ko.septa.L23.single.MUA,jenqData.ko.septa.L23.multi.MUA);
  203. MUA_Barrel_WT_L4_SW = cat(2,jenqData.wt.barrel.L4.single.MUA,jenqData.wt.barrel.L4.multi.MUA);
  204. MUA_Barrel_KO_L4_SW = cat(2,jenqData.ko.barrel.L4.single.MUA,jenqData.ko.barrel.L4.multi.MUA);
  205. MUA_Septa_WT_L4_SW = cat(2,jenqData.wt.septa.L4.single.MUA,jenqData.wt.septa.L4.multi.MUA);
  206. MUA_Septa_KO_L4_SW = cat(2,jenqData.ko.septa.L4.single.MUA,jenqData.ko.septa.L4.multi.MUA);
  208. MUA_Barrel_WT_L5_SW = cat(2,jenqData.wt.barrel.L5.single.MUA,jenqData.wt.barrel.L5.multi.MUA);
  209. MUA_Barrel_KO_L5_SW = cat(2,jenqData.ko.barrel.L5.single.MUA,jenqData.ko.barrel.L5.multi.MUA);
  210. MUA_Septa_WT_L5_SW = cat(2,jenqData.wt.septa.L5.single.MUA,jenqData.wt.septa.L5.multi.MUA);
  211. MUA_Septa_KO_L5_SW = cat(2,jenqData.ko.septa.L5.single.MUA,jenqData.ko.septa.L5.multi.MUA);
  213. ranksum(mean(MUA_Barrel_WT_L23_SW(1:200,:),1),mean(MUA_Barrel_KO_L23_SW(1:200,:),1))
  214. ranksum(mean(MUA_Septa_WT_L23_SW(1:200,:),1),mean(MUA_Septa_KO_L23_SW(1:200,:),1))
  216. ranksum(mean(MUA_Barrel_WT_L4_SW(1:200,:),1),mean(MUA_Barrel_KO_L4_SW(1:200,:),1))
  217. ranksum(mean(MUA_Septa_WT_L4_SW(1:200,:),1),mean(MUA_Septa_KO_L4_SW(1:200,:),1))
  219. ranksum(mean(MUA_Barrel_WT_L23_SW(1:200,:),1),mean(MUA_Septa_WT_L23_SW(1:200,:),1))
  220. ranksum(mean(MUA_Barrel_KO_L23_SW(1:200,:),1),mean(MUA_Septa_KO_L23_SW(1:200,:),1))
  222. %% Remove Baseline
  223. noBase_temp_L23_WT = temp_L23_WT-repmat(mean(temp_L23_WT(:,1:200),2),1,2200);
  224. noBase_temp_L23_WT_neigh = temp_L23_WT_neigh-repmat(mean(temp_L23_WT_neigh(:,1:200),2),1,2201);
  225. noBase_temp_L23_WT_septa = temp_L23_WT_septa-repmat(mean(temp_L23_WT_septa(:,1:200),2),1,2200);
  227. noBase_temp_L23_ko = temp_L23_ko-repmat(mean(temp_L23_ko(:,1:200),2),1,2200);
  228. noBase_temp_L23_KO_neigh = temp_L23_KO_neigh-repmat(mean(temp_L23_KO_neigh(:,1:200),2),1,2201);
  229. noBase_temp_L23_ko_septa = temp_L23_ko_septa-repmat(mean(temp_L23_ko_septa(:,1:200),2),1,2200);
  231. noBase_temp_L23_WT_MW = temp_L23_WT_MW-repmat(mean(temp_L23_WT_MW(:,1:200),2),1,2200);
  232. noBase_temp_L23_WT_MW_septa = temp_L23_WT_MW_septa-repmat(mean(temp_L23_WT_MW_septa(:,1:200),2),1,2200);
  234. noBase_temp_L23_KO_MW = temp_L23_KO_MW-repmat(mean(temp_L23_KO_MW(:,1:200),2),1,2200);
  235. noBase_temp_L23_KO_MW_septa = temp_L23_KO_MW_septa-repmat(mean(temp_L23_KO_MW_septa(:,1:200),2),1,2200);
  237. noBase_temp_L4_WT = temp_L4_WT-repmat(mean(temp_L4_WT(:,1:200),2),1,2200);
  238. noBase_temp_L4_WT_neigh = temp_L4_WT_neigh-repmat(mean(temp_L4_WT_neigh(:,1:200),2),1,2201);
  239. noBase_temp_L4_WT_septa = temp_L4_WT_septa-repmat(mean(temp_L4_WT_septa(:,1:200),2),1,2200);
  241. noBase_temp_L4_ko = temp_L4_ko-repmat(mean(temp_L4_ko(:,1:200),2),1,2200);
  242. noBase_temp_L4_KO_neigh = temp_L4_KO_neigh-repmat(mean(temp_L4_KO_neigh(:,1:200),2),1,2201);
  243. noBase_temp_L4_ko_septa = temp_L4_ko_septa-repmat(mean(temp_L4_ko_septa(:,1:200),2),1,2200);
  245. noBase_temp_L4_WT_MW = temp_L4_WT_MW-repmat(mean(temp_L4_WT_MW(:,1:200),2),1,2200);
  246. noBase_temp_L4_WT_MW_septa = temp_L4_WT_MW_septa-repmat(mean(temp_L4_WT_MW_septa(:,1:200),2),1,2200);
  248. noBase_temp_L4_KO_MW = temp_L4_KO_MW-repmat(mean(temp_L4_KO_MW(:,1:200),2),1,2200);
  249. noBase_temp_L4_KO_MW_septa = temp_L4_KO_MW_septa-repmat(mean(temp_L4_KO_MW_septa(:,1:200),2),1,2200);
  251. noBase_temp_L5_WT = temp_L5_WT-repmat(mean(temp_L5_WT(:,1:200),2),1,2200);
  252. noBase_temp_L5_WT_neigh = temp_L5_WT_neigh-repmat(mean(temp_L5_WT_neigh(:,1:200),2),1,2201);
  253. noBase_temp_L5_WT_septa = temp_L5_WT_septa-repmat(mean(temp_L5_WT_septa(:,1:200),2),1,2200);
  255. noBase_temp_L5_ko = temp_L5_ko-repmat(mean(temp_L5_ko(:,1:200),2),1,2200);
  256. noBase_temp_L5_KO_neigh = temp_L5_KO_neigh-repmat(mean(temp_L5_KO_neigh(:,1:200),2),1,2201);
  257. noBase_temp_L5_ko_septa = temp_L5_ko_septa-repmat(mean(temp_L5_ko_septa(:,1:200),2),1,2200);
  259. noBase_temp_L5_WT_MW = temp_L5_WT_MW-repmat(mean(temp_L5_WT_MW(:,1:200),2),1,2200);
  260. noBase_temp_L5_WT_MW_septa = temp_L5_WT_MW_septa-repmat(mean(temp_L5_WT_MW_septa(:,1:200),2),1,2200);
  262. noBase_temp_L5_KO_MW = temp_L5_KO_MW-repmat(mean(temp_L5_KO_MW(:,1:200),2),1,2200);
  263. noBase_temp_L5_KO_MW_septa = temp_L5_KO_MW_septa-repmat(mean(temp_L5_KO_MW_septa(:,1:200),2),1,2200);
  265. %% Figures
  267. % Figure 1 Figure Supplement 3A - Barrel
  268. figure , bar(mean(temp_L23_WT),2,'FaceColor',colorBarrel,'LineWidth',15);
  269. set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  270. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_Barrel_spikes.png'),"Resolution",600);
  272. % Figure 1 Figure Supplement 3A - Septa
  273. figure, bar(smooth(mean(temp_L23_WT_septa),3),3,'FaceColor',...
  274. colorSepta,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  275. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_Septa_spikes.png'),"Resolution",600);
  277. % Figure 1D - Barrel
  278. figure , bar(smooth(mean(temp_L4_WT),3),3,'FaceColor',...
  279. colorBarrel,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  280. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_Barrel_spikes.png'),"Resolution",600);
  282. % Figure 1D - Septa
  283. figure, bar(smooth(mean(temp_L4_WT_septa),3),3,'FaceColor',...
  284. colorSepta,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  285. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_Septa_spikes.png'),"Resolution",600);
  287. % Figure 1D - Neighbour
  288. figure, bar(smooth(mean(temp_L4_WT_neigh),3),3,'FaceColor',...
  289. colorNeigh,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  290. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_Neighbour_spikes.png'),"Resolution",600);
  292. % Figure 4B - Barrel
  293. figure , bar(smooth(mean(temp_L4_ko),3),3,'FaceColor',...
  294. colorBarrelKO,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  295. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_Barrel_spikes.png'),"Resolution",600);
  297. % Figure 4B - Septa
  298. figure, bar(smooth(mean(temp_L4_ko_septa),3),3,'FaceColor',...
  299. colorSeptaKO,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  300. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_Septa_spikes.png'),"Resolution",600);
  302. % Figure 4B - Neighbour
  303. figure, bar(smooth(mean(temp_L4_KO_neigh),3),3,'FaceColor',...
  304. colorNeighKO,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  305. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_Neighbour_spikes.png'),"Resolution",600);
  307. % Figure 1 Figure Supplement 3B - Barrel
  308. figure , bar(mean(temp_L23_WT_MW),2,'FaceColor',colorBarrel,'LineWidth',15);
  309. set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  310. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_Barrel_spikes_MW.png'),"Resolution",600);
  312. % Figure 1 Figure Supplement 3B - Septa
  313. figure, bar(smooth(mean(temp_L23_WT_MW_septa),3),3,'FaceColor',...
  314. colorSepta,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  315. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_Septa_spikes_MW.png'),"Resolution",600);
  317. % Figure 1F - Barrel
  318. figure , bar(smooth(mean(temp_L4_WT_MW),3),3,'FaceColor',...
  319. colorBarrel,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  320. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_Barrel_spikes_MW.png'),"Resolution",600);
  322. % Figure 1F - Septa
  323. figure, bar(smooth(mean(temp_L4_WT_MW_septa),3),3,'FaceColor',...
  324. colorSepta,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  325. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_Septa_spikes_MW.png'),"Resolution",600);
  327. % Figure 4D - Barrel
  328. figure , bar(smooth(mean(temp_L4_KO_MW),3),3,'FaceColor',...
  329. colorBarrelKO,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  330. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_Barrel_spikes_MW.png'),"Resolution",600);
  332. % Figure 4D - Septa
  333. figure, bar(smooth(mean(temp_L4_KO_MW_septa),3),3,'FaceColor',...
  334. colorSeptaKO,'LineWidth',15); set(gca,'visible','off'); set(gcf,'Position',[100 100 500 250]);
  335. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_Septa_spikes_MW.png'),"Resolution",600);
  337. % Data Rearrabgement
  339. clear stimtrials_L23_WT;
  340. clear stimtrialsAverage_L23_WT;
  341. clear diff_stimtrialsAverage_L23_WT;
  342. % figure; hold on;
  343. rgbColors = zeros(3,20);
  344. rgbColors(3,:) = linspace(1,255,20)/255;
  345. rgbColors(2,:) = linspace(1,155,20)/255;
  346. for s = 1:20
  347. stimtrials_L23_WT(:,:,s) = temp_L23_WT(:,beglocs(s):beglocs(s)+94);
  348. stimtrials_L4_WT(:,:,s) = temp_L4_WT(:,beglocs(s):beglocs(s)+94);
  349. stimtrials_L5_WT(:,:,s) = temp_L5_WT(:,beglocs(s):beglocs(s)+94);
  351. stimtrials_L23_WT_septa(:,:,s) = temp_L23_WT_septa(:,beglocs(s):beglocs(s)+94);
  352. stimtrials_L4_WT_septa(:,:,s) = temp_L4_WT_septa(:,beglocs(s):beglocs(s)+94);
  353. stimtrials_L5_WT_septa(:,:,s) = temp_L5_WT_septa(:,beglocs(s):beglocs(s)+94);
  355. stimtrials_L23_WT_neigh(:,:,s) = temp_L23_WT_neigh(:,beglocs(s):beglocs(s)+94);
  356. stimtrials_L4_WT_neigh(:,:,s) = temp_L4_WT_neigh(:,beglocs(s):beglocs(s)+94);
  357. stimtrials_L5_WT_neigh(:,:,s) = temp_L5_WT_neigh(:,beglocs(s):beglocs(s)+94);
  359. stimtrials_L23_KO(:,:,s) = temp_L23_ko(:,beglocs(s):beglocs(s)+94);
  360. stimtrials_L4_KO(:,:,s) = temp_L4_ko(:,beglocs(s):beglocs(s)+94);
  361. stimtrials_L5_KO(:,:,s) = temp_L5_ko(:,beglocs(s):beglocs(s)+94);
  363. stimtrials_L23_KO_septa(:,:,s) = temp_L23_ko_septa(:,beglocs(s):beglocs(s)+94);
  364. stimtrials_L4_KO_septa(:,:,s) = temp_L4_ko_septa(:,beglocs(s):beglocs(s)+94);
  365. stimtrials_L5_KO_septa(:,:,s) = temp_L5_ko_septa(:,beglocs(s):beglocs(s)+94);
  367. stimtrials_L23_KO_neigh(:,:,s) = temp_L23_KO_neigh(:,beglocs(s):beglocs(s)+94);
  368. stimtrials_L4_KO_neigh(:,:,s) = temp_L4_KO_neigh(:,beglocs(s):beglocs(s)+94);
  369. stimtrials_L5_KO_neigh(:,:,s) = temp_L5_KO_neigh(:,beglocs(s):beglocs(s)+94);
  370. end
  372. % Normalized
  373. for s = 1:20
  374. norm_stimtrials_L23_WT(:,:,s) = temp_L23_WT(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L23_WT(:,201:230)));
  375. norm_stimtrials_L4_WT(:,:,s) = temp_L4_WT(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L4_WT(:,201:230)));
  376. norm_stimtrials_L5_WT(:,:,s) = temp_L5_WT(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L5_WT(:,201:230)));
  378. norm_stimtrials_L23_WT_septa(:,:,s) = temp_L23_WT_septa(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L23_WT_septa(:,201:230)));
  379. norm_stimtrials_L4_WT_septa(:,:,s) = temp_L4_WT_septa(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L4_WT_septa(:,201:230)));
  380. norm_stimtrials_L5_WT_septa(:,:,s) = temp_L5_WT_septa(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L5_WT_septa(:,201:230)));
  382. norm_stimtrials_L23_WT_neigh(:,:,s) = temp_L23_WT_neigh(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L23_WT_neigh(:,201:230)));
  383. norm_stimtrials_L4_WT_neigh(:,:,s) = temp_L4_WT_neigh(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L4_WT_neigh(:,201:230)));
  384. norm_stimtrials_L5_WT_neigh(:,:,s) = temp_L5_WT_neigh(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L5_WT_neigh(:,201:230)));
  386. norm_stimtrials_L23_KO(:,:,s) = temp_L23_ko(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L23_ko(:,201:230)));
  387. norm_stimtrials_L4_KO(:,:,s) = temp_L4_ko(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L4_ko(:,201:230)));
  388. norm_stimtrials_L5_KO(:,:,s) = temp_L5_ko(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L5_ko(:,201:230)));
  390. norm_stimtrials_L23_KO_septa(:,:,s) = temp_L23_ko_septa(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L23_ko_septa(:,201:230)));
  391. norm_stimtrials_L4_KO_septa(:,:,s) = temp_L4_ko_septa(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L4_ko_septa(:,201:230)));
  392. norm_stimtrials_L5_KO_septa(:,:,s) = temp_L5_ko_septa(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L5_ko_septa(:,201:230)));
  394. norm_stimtrials_L23_KO_neigh(:,:,s) = temp_L23_KO_neigh(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L23_KO_neigh(:,201:230)));
  395. norm_stimtrials_L4_KO_neigh(:,:,s) = temp_L4_KO_neigh(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L4_KO_neigh(:,201:230)));
  396. norm_stimtrials_L5_KO_neigh(:,:,s) = temp_L5_KO_neigh(:,beglocs(s):beglocs(s)+94)/max(mean(temp_L5_KO_neigh(:,201:230)));
  397. end
  399. % MW
  400. for s = 1:20
  402. %
  403. stimtrials_MW_L23_WT(:,:,s) = temp_L23_WT_MW(:,beglocs(s):beglocs(s)+94);
  404. stimtrials_MW_L4_WT(:,:,s) = temp_L4_WT_MW(:,beglocs(s):beglocs(s)+94);
  405. stimtrials_MW_L5_WT(:,:,s) = temp_L5_WT_MW(:,beglocs(s):beglocs(s)+94);
  407. stimtrials_MW_L23_WT_septa(:,:,s) = temp_L23_WT_MW_septa(:,beglocs(s):beglocs(s)+94);
  408. stimtrials_MW_L4_WT_septa(:,:,s) = temp_L4_WT_MW_septa(:,beglocs(s):beglocs(s)+94);
  409. stimtrials_MW_L5_WT_septa(:,:,s) = temp_L5_WT_MW_septa(:,beglocs(s):beglocs(s)+94);
  411. stimtrials_MW_L23_KO(:,:,s) = temp_L23_KO_MW(:,beglocs(s):beglocs(s)+94);
  412. stimtrials_MW_L4_KO(:,:,s) = temp_L4_KO_MW(:,beglocs(s):beglocs(s)+94);
  413. stimtrials_MW_L5_KO(:,:,s) = temp_L5_KO_MW(:,beglocs(s):beglocs(s)+94);
  415. stimtrials_MW_L23_KO_septa(:,:,s) = temp_L23_KO_MW_septa(:,beglocs(s):beglocs(s)+94);
  416. stimtrials_MW_L4_KO_septa(:,:,s) = temp_L4_KO_MW_septa(:,beglocs(s):beglocs(s)+94);
  417. stimtrials_MW_L5_KO_septa(:,:,s) = temp_L5_KO_MW_septa(:,beglocs(s):beglocs(s)+94);
  418. end
  421. %% Peak Comparison L2/3 WT
  423. % Figure 1D Figure Supplement 3A - Image - Barrel
  424. figure; set(gcf,'Position',[100 100 350 300]);
  425. imagesc(squeeze(mean(stimtrials_L23_WT,1))',[0 0.35]);
  426. colormap turbo; colorbar;
  427. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  428. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  429. set(gca,'FontSize',18); set(gca,'TickDir','out');
  430. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  431. exportgraphics(gcf,fullfile(saveFolder,'L23_Barrel_WT_Image.png'),"Resolution",600);
  433. % Figure 1D Figure Supplement 3A - Image - Septa
  434. figure; set(gcf,'Position',[100 100 500 300]);
  435. imagesc(squeeze(mean(stimtrials_L23_WT_septa,1))',[0 0.35]);
  436. colormap turbo; colorbar;
  437. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  438. xlabel('Time (ms)','FontSize',24); xticks([1 20 40 60 80]);
  439. set(gca,'FontSize',24); set(gca,'TickDir','out');
  440. ylabel('Pulse Number','FontSize',22); yticks([1 5 10 15 20]);
  441. exportgraphics(gcf,fullfile(saveFolder,'L23_Septa_WT_Image.png'),"Resolution",600);
  443. % Figure 1D - Image - Barrel
  444. figure; set(gcf,'Position',[100 100 350 300]);
  445. imagesc(squeeze(mean(stimtrials_L4_WT,1))',[0 0.35]);
  446. colormap turbo; colorbar;
  447. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  448. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  449. set(gca,'FontSize',18); set(gca,'TickDir','out');
  450. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  451. exportgraphics(gcf,fullfile(saveFolder,'L4_Barrel_WT_Image.png'),"Resolution",600);
  453. % Figure 1D - Image - Septa
  454. figure; set(gcf,'Position',[100 100 350 300]);
  455. imagesc(squeeze(mean(stimtrials_L4_WT_septa,1))',[0 0.35]);
  456. colormap turbo; colorbar;
  457. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  458. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  459. set(gca,'FontSize',18); set(gca,'TickDir','out');
  460. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  461. exportgraphics(gcf,fullfile(saveFolder,'L4_Septa_WT_Image.png'),"Resolution",600);
  463. % Figure 1D - Image - Neighbour
  464. figure; set(gcf,'Position',[100 100 350 300]);
  465. imagesc(squeeze(mean(stimtrials_L4_WT_neigh,1))',[0 0.35]);
  466. colormap turbo; colorbar;
  467. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  468. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  469. set(gca,'FontSize',18); set(gca,'TickDir','out');
  470. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  471. exportgraphics(gcf,fullfile(saveFolder,'L4_Neigh_WT_Image.png'),"Resolution",600);
  473. % Figure 4B - Image - Barrel
  474. figure; set(gcf,'Position',[100 100 350 300]);
  475. imagesc(squeeze(mean(stimtrials_L4_KO,1))',[0 0.35]);
  476. colormap turbo; colorbar;
  477. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  478. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  479. set(gca,'FontSize',18); set(gca,'TickDir','out');
  480. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  481. exportgraphics(gcf,fullfile(saveFolder,'L4_Barrel_KO_Image.png'),"Resolution",600);
  483. % Figure 4B - Image - Septa
  484. figure; set(gcf,'Position',[100 100 350 300]);
  485. imagesc(squeeze(mean(stimtrials_L4_KO_septa,1))',[0 0.35]);
  486. colormap turbo; colorbar;
  487. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  488. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  489. set(gca,'FontSize',18); set(gca,'TickDir','out');
  490. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  491. exportgraphics(gcf,fullfile(saveFolder,'L4_Septa_KO_Image.png'),"Resolution",600);
  493. % Figure 4B - Image - Neighbour
  494. figure; set(gcf,'Position',[100 100 350 300]);
  495. imagesc(squeeze(mean(stimtrials_L4_KO_neigh,1))',[0 0.35]);
  496. colormap turbo; colorbar;
  497. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  498. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  499. set(gca,'FontSize',18); set(gca,'TickDir','out');
  500. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  501. exportgraphics(gcf,fullfile(saveFolder,'L4_Neigh_KO_Image.png'),"Resolution",600);
  504. % Figure 1 Figure Supplement 3B - Image - Barrel
  505. figure; set(gcf,'Position',[100 100 500 300]);
  506. imagesc(squeeze(mean(stimtrials_MW_L23_WT,1))',[0 0.35]);
  507. colormap turbo; colorbar;
  508. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  509. xlabel('Time (ms)','FontSize',24); xticks([1 20 40 60 80]);
  510. set(gca,'FontSize',24); set(gca,'TickDir','out');
  511. ylabel('Pulse Number','FontSize',22); yticks([1 5 10 15 20]);
  512. exportgraphics(gcf,fullfile(saveFolder,'L23_Barrel_WT_Image_MW.png'),"Resolution",600);
  514. % Figure 1 Figure Supplement 3B - Image - Septa
  515. figure; set(gcf,'Position',[100 100 500 300]);
  516. imagesc(squeeze(mean(stimtrials_MW_L23_WT_septa,1))',[0 0.35]);
  517. colormap turbo; colorbar;
  518. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  519. xlabel('Time (ms)','FontSize',24); xticks([1 20 40 60 80]);
  520. set(gca,'FontSize',24); set(gca,'TickDir','out');
  521. ylabel('Pulse Number','FontSize',22); yticks([1 5 10 15 20]);
  522. exportgraphics(gcf,fullfile(saveFolder,'L23_Septa_WT_Image_MW.png'),"Resolution",600);
  524. % Figure 1F - Image - Barrel
  525. figure; set(gcf,'Position',[100 100 350 300]);
  526. imagesc(squeeze(mean(stimtrials_MW_L4_WT,1))',[0 0.35]);
  527. colormap turbo; colorbar;
  528. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  529. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  530. set(gca,'FontSize',18); set(gca,'TickDir','out');
  531. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  532. exportgraphics(gcf,fullfile(saveFolder,'L4_Barrel_WT_Image_MW.png'),"Resolution",600);
  534. % Figure 1F - Image - Septa
  535. figure; set(gcf,'Position',[100 100 350 300]);
  536. imagesc(squeeze(mean(stimtrials_MW_L4_WT_septa,1))',[0 0.35]);
  537. colormap turbo; colorbar;
  538. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  539. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  540. set(gca,'FontSize',18); set(gca,'TickDir','out');
  541. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  542. exportgraphics(gcf,fullfile(saveFolder,'L4_Septa_WT_Image_MW.png'),"Resolution",600);
  544. % Figure 4D - Image - Barrel
  545. figure; set(gcf,'Position',[100 100 350 300]);
  546. imagesc(squeeze(mean(stimtrials_MW_L4_KO,1))',[0 0.35]);
  547. colormap turbo; colorbar;
  548. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  549. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  550. set(gca,'FontSize',18); set(gca,'TickDir','out');
  551. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  552. exportgraphics(gcf,fullfile(saveFolder,'L4_Barrel_KO_Image_MW.png'),"Resolution",600);
  554. % Figure 4D - Image - Septa
  556. figure; set(gcf,'Position',[100 100 350 300]);
  557. imagesc(squeeze(mean(stimtrials_MW_L4_KO_septa,1))',[0 0.35]);
  558. colormap turbo; colorbar;
  559. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  560. xlabel('Time (ms)','FontSize',18); xticks([1 20 40 60 80]);
  561. set(gca,'FontSize',18); set(gca,'TickDir','out');
  562. ylabel('Pulse Number','FontSize',18); yticks([1 5 10 15 20]);
  563. exportgraphics(gcf,fullfile(saveFolder,'L4_Septa_KO_Image_MW.png'),"Resolution",600);
  565. %% MW/SW Extraction
  566. for i = 1:size(temp_L4_WT,1)
  567. temp_L4_WT_smooth(i,:) = smooth(temp_L4_WT(i,:),3);
  568. temp_L4_WT_MW_smooth(i,:) = smooth(temp_L4_WT_MW(i,:),3);
  569. end
  570. c = 1;
  571. for t = 1:20:size(temp_L4_WT,1)
  572. temp_L4_WT_smooth_trials(c,:) = mean(temp_L4_WT_smooth(t:t+19,:),1);
  573. temp_L4_WT_MW_smooth_trials(c,:) = mean(temp_L4_WT_MW_smooth(t:t+19,:),1);
  574. c = c + 1;
  575. end
  576. for i = 1:size(temp_L4_WT_septa,1)
  577. temp_L4_WT_septa_smooth(i,:) = smooth(temp_L4_WT_septa(i,:),3);
  578. temp_L4_WT_MW_septa_smooth(i,:) = smooth(temp_L4_WT_MW_septa(i,:),3);
  579. end
  580. c = 1;
  581. for t = 1:20:size(temp_L4_WT_septa,1)
  582. temp_L4_WT_septa_smooth_trials(c,:) = mean(temp_L4_WT_septa_smooth(t:t+19,:),1);
  583. temp_L4_WT_MW_septa_smooth_trials(c,:) = mean(temp_L4_WT_MW_septa_smooth(t:t+19,:),1);
  584. c = c + 1;
  585. end
  586. for b = 1:size(temp_L4_WT_smooth_trials,1)
  587. for s = 1:20
  588. L4_WT_SW_Barrel_Max(b,s) = trapz(nanmean(temp_L4_WT_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  589. L4_WT_MW_Barrel_Max(b,s) = trapz(nanmean(temp_L4_WT_MW_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  590. end
  591. end
  592. for b = 1:size(temp_L4_WT_septa_smooth_trials,1)
  593. for s = 1:20
  594. L4_WT_SW_Septa_Max(b,s) = trapz(nanmean(temp_L4_WT_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  595. L4_WT_MW_Septa_Max(b,s) = trapz(nanmean(temp_L4_WT_MW_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  596. end
  597. end
  599. L4_WT_MW_div_SW_Barrel_mean = 100*mean(L4_WT_MW_Barrel_Max./L4_WT_SW_Barrel_Max);
  600. L4_WT_MW_div_SW_Barrel_sem = 100*std(L4_WT_MW_Barrel_Max./L4_WT_SW_Barrel_Max,[],1)/sqrt(size(L4_WT_MW_Barrel_Max,1));
  601. L4_WT_MW_div_SW_Septa_mean = 100*mean(L4_WT_MW_Septa_Max./L4_WT_SW_Septa_Max);
  602. L4_WT_MW_div_SW_Septa_sem = 100*std(L4_WT_MW_Septa_Max./L4_WT_SW_Septa_Max,[],1)/sqrt(size(L4_WT_MW_Septa_Max,1));
  604. for i = 1:size(temp_L4_ko,1)
  605. temp_L4_KO_smooth(i,:) = smooth(temp_L4_ko(i,:),3);
  606. temp_L4_KO_MW_smooth(i,:) = smooth(temp_L4_KO_MW(i,:),3);
  607. end
  608. c = 1;
  609. for t = 1:20:size(temp_L4_ko,1)
  610. temp_L4_KO_smooth_trials(c,:) = mean(temp_L4_KO_smooth(t:t+19,:),1);
  611. temp_L4_KO_MW_smooth_trials(c,:) = mean(temp_L4_KO_MW_smooth(t:t+19,:),1);
  612. c = c + 1;
  613. end
  614. for i = 1:size(temp_L4_ko_septa,1)
  615. temp_L4_KO_septa_smooth(i,:) = smooth(temp_L4_ko_septa(i,:),3);
  616. temp_L4_KO_MW_septa_smooth(i,:) = smooth(temp_L4_KO_MW_septa(i,:),3);
  617. end
  618. c = 1;
  619. for t = 1:20:size(temp_L4_ko_septa,1)
  620. temp_L4_KO_septa_smooth_trials(c,:) = mean(temp_L4_KO_septa_smooth(t:t+19,:),1);
  621. temp_L4_KO_MW_septa_smooth_trials(c,:) = mean(temp_L4_KO_MW_septa_smooth(t:t+19,:),1);
  622. c = c + 1;
  623. end
  624. for b = 1:size(temp_L4_KO_smooth_trials,1)
  625. for s = 1:20
  626. L4_KO_SW_Barrel_Max(b,s) = trapz(nanmean(temp_L4_KO_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  627. L4_KO_MW_Barrel_Max(b,s) = trapz(nanmean(temp_L4_KO_MW_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  628. end
  629. end
  630. for b = 1:size(temp_L4_KO_septa_smooth_trials,1)
  631. for s = 1:20
  632. L4_KO_SW_Septa_Max(b,s) = trapz(nanmean(temp_L4_KO_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  633. L4_KO_MW_Septa_Max(b,s) = trapz(nanmean(temp_L4_KO_MW_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  634. end
  635. end
  637. L4_KO_MW_div_SW_Barrel_mean = 100*mean(L4_KO_MW_Barrel_Max./L4_KO_SW_Barrel_Max);
  638. L4_KO_MW_div_SW_Barrel_sem = 100*std(L4_KO_MW_Barrel_Max./L4_KO_SW_Barrel_Max,[],1)/sqrt(size(L4_KO_MW_Barrel_Max,1));
  639. L4_KO_MW_div_SW_Septa_mean = 100*mean(L4_KO_MW_Septa_Max./L4_KO_SW_Septa_Max);
  640. L4_KO_MW_div_SW_Septa_sem = 100*std(L4_KO_MW_Septa_Max./L4_KO_SW_Septa_Max,[],1)/sqrt(size(L4_KO_MW_Septa_Max,1));
  642. % Figure 1H
  643. figure; set(gcf,'Position',[500 500 610 400]);
  644. hold on; errorbar(1:20,L4_WT_MW_div_SW_Barrel_mean,L4_WT_MW_div_SW_Barrel_sem,'LineWidth',3,'Color',colorBarrel);
  645. hold on; errorbar(1:20,L4_WT_MW_div_SW_Septa_mean,L4_WT_MW_div_SW_Septa_sem,'LineWidth',3,'Color',colorSepta);
  646. plot(1:20,100*ones(1,20),'--','Color',[.1 .1 .1]);
  647. xlim([0 21]); ylim([50 225]);
  648. yticks(0:50:250);
  649. xticks([1:20]); ylabel('AUC_{MW}/AUC_{SW}','FontWeight','normal'); xlabel('Pulse Number','FontSize',22);
  650. set(gca,'FontSize',18); set(gca,'TickDir','out');
  651. legend('Barrel WT','Septa WT','Location','NorthWest');
  652. title('L4 Multi/Single','FontWeight','normal');
  653. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_div_SW_Barrel.png'),"Resolution",600);
  655. % Figure 4F
  656. figure; set(gcf,'Position',[500 500 610 400]);
  657. hold on; errorbar(1:20,L4_KO_MW_div_SW_Barrel_mean,L4_KO_MW_div_SW_Barrel_sem,'LineWidth',3,'Color',colorBarrelKO);
  658. hold on; errorbar(1:20,L4_KO_MW_div_SW_Septa_mean,L4_KO_MW_div_SW_Septa_sem,'LineWidth',3,'Color',colorSeptaKO);
  659. plot(1:20,100*ones(1,20),'--','Color',[.1 .1 .1]);
  660. xlim([0 21]); ylim([50 225]);
  661. yticks(0:50:250);
  662. xticks([1:20]); ylabel('AUC_{MW}/AUC_{SW}','FontWeight','normal'); xlabel('Pulse Number','FontSize',22);
  663. set(gca,'FontSize',18); set(gca,'TickDir','out');
  664. legend('Barrel KO','Septa KO','Location','NorthWest');
  665. title('L4 Multi/Single','FontWeight','normal');
  666. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_div_SW_Barrel.png'),"Resolution",600);
  668. % Figure 1I - 1-20 Pulses
  669. all_L4_WT_ratio_Barrel = 100*mean(L4_WT_MW_Barrel_Max./L4_WT_SW_Barrel_Max,2);
  670. all_L4_WT_ratio_Septa = 100*mean(L4_WT_MW_Septa_Max./L4_WT_SW_Septa_Max,2);
  671. all_L4_KO_ratio_Barrel = 100*mean(L4_KO_MW_Barrel_Max./L4_KO_SW_Barrel_Max,2);
  672. all_L4_KO_ratio_Septa = 100*mean(L4_KO_MW_Septa_Max./L4_KO_SW_Septa_Max,2);
  674. t1 = all_L4_WT_ratio_Barrel;
  675. t2 = all_L4_WT_ratio_Septa;
  676. ranksum((t1),(t2))
  677. ranksum(rmoutliers(t1),rmoutliers(t2))
  678. figure; set(gcf,'Position',[1200 100 300 400]); hold on;
  679. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  680. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  681. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  682. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  683. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  684. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  686. hold on; plot([1 2],[200 200],'LineWidth',3,'Color','k');
  687. text(1.5,205,'*','HorizontalAlignment','center','FontSize',48);
  689. axis([0.5 2.5 0 270]);
  690. yticks(0:50:250);
  691. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC(MW/SW)%'); title('1-20');
  692. set(gca,'FontSize',30); set(gca,'TickDir','out');
  693. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_div_SW_Barrel_Septa_AllPulses.png'),"Resolution",600);
  695. % Figure 4G - 1-20 Pulses
  696. t1 = all_L4_KO_ratio_Barrel;
  697. t2 = all_L4_KO_ratio_Septa;
  698. ranksum((t1),(t2))
  699. ranksum(rmoutliers(t1),rmoutliers(t2))
  700. figure; set(gcf,'Position',[1200 100 300 400]); hold on;
  701. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  702. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  703. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  704. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  705. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  706. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  708. axis([0.5 2.5 0 270]);
  709. yticks(0:50:250);
  710. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC(MW/SW)%'); title('1-20');
  711. set(gca,'FontSize',30); set(gca,'TickDir','out');
  712. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_div_SW_Barrel_Septa_AllPulses.png'),"Resolution",600);
  714. % Figure 1I - 1-6 Pulses
  715. all_L4_WT_ratio_Barrel = 100*mean(L4_WT_MW_Barrel_Max(:,1:6)./L4_WT_SW_Barrel_Max(:,1:6),2);
  716. all_L4_WT_ratio_Septa = 100*mean(L4_WT_MW_Septa_Max(:,1:6)./L4_WT_SW_Septa_Max(:,1:6),2);
  717. all_L4_KO_ratio_Barrel = 100*mean(L4_KO_MW_Barrel_Max(:,1:6)./L4_KO_SW_Barrel_Max(:,1:6),2);
  718. all_L4_KO_ratio_Septa = 100*mean(L4_KO_MW_Septa_Max(:,1:6)./L4_KO_SW_Septa_Max(:,1:6),2);
  720. t1 = all_L4_WT_ratio_Barrel;
  721. t2 = all_L4_WT_ratio_Septa;
  722. ranksum((t1),(t2))
  723. ranksum(rmoutliers(t1),rmoutliers(t2))
  724. figure; set(gcf,'Position',[1200 100 300 400]); hold on;
  725. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  726. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  727. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  728. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  729. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  730. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  732. axis([0.5 2.5 0 270]);
  733. yticks(0:50:250);
  734. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC(MW/SW)%'); title('1-6');
  735. set(gca,'FontSize',30); set(gca,'TickDir','out');
  736. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_div_SW_Barrel_Septa_Pulses1_6.png'),"Resolution",600);
  738. % Figure 4G - 1-6 Pulses
  739. t1 = all_L4_KO_ratio_Barrel;
  740. t2 = all_L4_KO_ratio_Septa;
  741. ranksum((t1),(t2))
  742. ranksum(rmoutliers(t1),rmoutliers(t2))
  743. figure; set(gcf,'Position',[1200 100 300 400]); hold on;
  744. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  745. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  746. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  747. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  748. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  749. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  751. axis([0.5 2.5 0 270]);
  752. yticks(0:50:250);
  753. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC(MW/SW)%'); title('1-6');
  754. set(gca,'FontSize',30); set(gca,'TickDir','out');
  755. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_div_SW_Barrel_Septa_Pulses1_6.png'),"Resolution",600);
  757. % Figure 1I - 7-20 Pulses
  758. all_L4_WT_ratio_Barrel = 100*mean(L4_WT_MW_Barrel_Max(:,7:20)./L4_WT_SW_Barrel_Max(:,7:20),2);
  759. all_L4_WT_ratio_Septa = 100*mean(L4_WT_MW_Septa_Max(:,7:20)./L4_WT_SW_Septa_Max(:,7:20),2);
  760. all_L4_KO_ratio_Barrel = 100*mean(L4_KO_MW_Barrel_Max(:,7:20)./L4_KO_SW_Barrel_Max(:,7:20),2);
  761. all_L4_KO_ratio_Septa = 100*mean(L4_KO_MW_Septa_Max(:,7:20)./L4_KO_SW_Septa_Max(:,7:20),2);
  763. t1 = all_L4_WT_ratio_Barrel;
  764. t2 = all_L4_WT_ratio_Septa;
  765. ranksum((t1),(t2))
  766. ranksum(rmoutliers(t1),rmoutliers(t2))
  767. figure; set(gcf,'Position',[1200 100 300 400]); hold on;
  768. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  769. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  770. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  771. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  772. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  773. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  775. hold on; plot([1 2],[200 200],'LineWidth',3,'Color','k');
  776. text(1.5,205,'**','HorizontalAlignment','center','FontSize',48);
  778. axis([0.5 2.5 0 270]);
  779. yticks(0:50:250);
  780. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC(MW/SW)%'); title('7-20');
  781. set(gca,'FontSize',30); set(gca,'TickDir','out');
  782. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_div_SW_Barrel_Septa_Pulses7_20.png'),"Resolution",600);
  784. % Figure 4G - 7-20 Pulses
  785. t1 = all_L4_KO_ratio_Barrel;
  786. t2 = all_L4_KO_ratio_Septa;
  787. ranksum((t1),(t2))
  788. ranksum(rmoutliers(t1),rmoutliers(t2))
  789. figure; set(gcf,'Position',[1200 100 300 400]); hold on;
  790. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  791. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  792. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  793. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  794. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  795. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  797. axis([0.5 2.5 0 270]);
  798. yticks(0:50:250);
  799. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC(MW/SW)%'); title('7-20');
  800. set(gca,'FontSize',30); set(gca,'TickDir','out');
  801. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_div_SW_Barrel_Septa_Pulses7_20.png'),"Resolution",600);
  803. %% WT L23
  804. for i = 1:size(temp_L23_WT,1)
  805. temp_L23_WT_smooth(i,:) = smooth(temp_L23_WT(i,:),3);
  806. temp_L23_WT_MW_smooth(i,:) = smooth(temp_L23_WT_MW(i,:),3);
  807. end
  808. c = 1;
  809. for t = 1:20:size(temp_L23_WT,1)
  810. temp_L23_WT_smooth_trials(c,:) = mean(temp_L23_WT_smooth(t:t+19,:),1);
  811. temp_L23_WT_MW_smooth_trials(c,:) = mean(temp_L23_WT_MW_smooth(t:t+19,:),1);
  812. c = c + 1;
  813. end
  814. for i = 1:size(temp_L23_WT_septa,1)
  815. temp_L23_WT_septa_smooth(i,:) = smooth(temp_L23_WT_septa(i,:),3);
  816. temp_L23_WT_MW_septa_smooth(i,:) = smooth(temp_L23_WT_MW_septa(i,:),3);
  817. end
  818. c = 1;
  819. for t = 1:20:size(temp_L23_WT_septa,1)
  820. temp_L23_WT_septa_smooth_trials(c,:) = mean(temp_L23_WT_septa_smooth(t:t+19,:),1);
  821. temp_L23_WT_MW_septa_smooth_trials(c,:) = mean(temp_L23_WT_MW_septa_smooth(t:t+19,:),1);
  822. c = c + 1;
  823. end
  824. for b = 1:size(temp_L23_WT_smooth_trials,1)
  825. for s = 1:20
  826. L23_WT_SW_Barrel_Max(b,s) = trapz(nanmean(temp_L23_WT_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  827. L23_WT_MW_Barrel_Max(b,s) = trapz(nanmean(temp_L23_WT_MW_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  828. end
  829. end
  830. for b = 1:size(temp_L23_WT_septa_smooth_trials,1)
  831. for s = 1:20
  832. L23_WT_SW_Septa_Max(b,s) = trapz(nanmean(temp_L23_WT_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  833. L23_WT_MW_Septa_Max(b,s) = trapz(nanmean(temp_L23_WT_MW_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  834. end
  835. end
  837. % KO L23
  838. for i = 1:size(temp_L23_ko,1)
  839. temp_L23_KO_smooth(i,:) = smooth(temp_L23_ko(i,:),3);
  840. temp_L23_KO_MW_smooth(i,:) = smooth(temp_L23_KO_MW(i,:),3);
  841. end
  842. c = 1;
  843. for t = 1:20:size(temp_L23_ko,1)
  844. temp_L23_KO_smooth_trials(c,:) = mean(temp_L23_KO_smooth(t:t+19,:),1);
  845. temp_L23_KO_MW_smooth_trials(c,:) = mean(temp_L23_KO_MW_smooth(t:t+19,:),1);
  846. c = c + 1;
  847. end
  848. for i = 1:size(temp_L23_ko_septa,1)
  849. temp_L23_KO_septa_smooth(i,:) = smooth(temp_L23_ko_septa(i,:),3);
  850. temp_L23_KO_MW_septa_smooth(i,:) = smooth(temp_L23_KO_MW_septa(i,:),3);
  851. end
  852. c = 1;
  853. for t = 1:20:size(temp_L23_ko_septa,1)
  854. temp_L23_KO_septa_smooth_trials(c,:) = mean(temp_L23_KO_septa_smooth(t:t+19,:),1);
  855. temp_L23_KO_MW_septa_smooth_trials(c,:) = mean(temp_L23_KO_MW_septa_smooth(t:t+19,:),1);
  856. c = c + 1;
  857. end
  858. for b = 1:size(temp_L23_KO_smooth_trials,1)
  859. for s = 1:20
  860. L23_KO_SW_Barrel_Max(b,s) = trapz(nanmean(temp_L23_KO_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  861. L23_KO_MW_Barrel_Max(b,s) = trapz(nanmean(temp_L23_KO_MW_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  862. end
  863. end
  864. for b = 1:size(temp_L23_KO_septa_smooth_trials,1)
  865. for s = 1:20
  866. L23_KO_SW_Septa_Max(b,s) = trapz(nanmean(temp_L23_KO_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  867. L23_KO_MW_Septa_Max(b,s) = trapz(nanmean(temp_L23_KO_MW_septa_smooth_trials(b,beglocs(s):beglocs(s)+49),1));
  868. end
  869. end
  871. L23_WT_MW_div_SW_Barrel_mean = 100*mean(L23_WT_MW_Barrel_Max./L23_WT_SW_Barrel_Max);
  872. L23_WT_MW_div_SW_Barrel_sem = 100*std(L23_WT_MW_Barrel_Max./L23_WT_SW_Barrel_Max,[],1)/sqrt(size(L23_WT_MW_Barrel_Max,1));
  873. L23_WT_MW_div_SW_Septa_mean = 100*mean(L23_WT_MW_Septa_Max./L23_WT_SW_Septa_Max);
  874. L23_WT_MW_div_SW_Septa_sem = 100*std(L23_WT_MW_Septa_Max./L23_WT_SW_Septa_Max,[],1)/sqrt(size(L23_WT_MW_Septa_Max,1));
  876. L23_KO_MW_div_SW_Barrel_mean = 100*mean(L23_KO_MW_Barrel_Max./L23_KO_SW_Barrel_Max);
  877. L23_KO_MW_div_SW_Barrel_sem = 100*std(L23_KO_MW_Barrel_Max./L23_KO_SW_Barrel_Max,[],1)/sqrt(size(L23_KO_MW_Barrel_Max,1));
  878. L23_KO_MW_div_SW_Septa_mean = 100*mean(L23_KO_MW_Septa_Max./L23_KO_SW_Septa_Max);
  879. L23_KO_MW_div_SW_Septa_sem = 100*std(L23_KO_MW_Septa_Max./L23_KO_SW_Septa_Max,[],1)/sqrt(size(L23_KO_MW_Septa_Max,1));
  881. % Figure 1 Figure SUpplement 3C
  882. figure; set(gcf,'Position',[500 500 610 400]);
  883. hold on; errorbar(1:20,L23_WT_MW_div_SW_Barrel_mean,L23_WT_MW_div_SW_Barrel_sem,'LineWidth',3,'Color',colorBarrel);
  884. hold on; errorbar(1:20,L23_WT_MW_div_SW_Septa_mean,L23_WT_MW_div_SW_Septa_sem,'LineWidth',3,'Color',colorSepta);
  885. plot(1:20,100*ones(1,20),'--','Color',[.1 .1 .1]);
  886. xlim([0 21]); ylim([50 400]);
  887. yticks(0:50:350);
  888. xticks([1:20]); ylabel('AUC_{MW}/AUC_{SW}','FontWeight','normal'); xlabel('Pulse Number','FontSize',22);
  889. set(gca,'FontSize',18); set(gca,'TickDir','out');
  890. legend('Barrel WT','Septa WT','Location','NorthWest');
  891. title('Layer_{2/3} Multi/Single','FontWeight','normal');
  892. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_MW_div_SW_Barrel.png'),"Resolution",600);
  894. figure; set(gcf,'Position',[500 500 610 400]);
  895. hold on; errorbar(1:20,L23_KO_MW_div_SW_Barrel_mean,L23_KO_MW_div_SW_Barrel_sem,'LineWidth',3,'Color',colorBarrelKO);
  896. hold on; errorbar(1:20,L23_KO_MW_div_SW_Septa_mean,L23_KO_MW_div_SW_Septa_sem,'LineWidth',3,'Color',colorSeptaKO);
  897. plot(1:20,100*ones(1,20),'--','Color',[.1 .1 .1]);
  898. xlim([0 21]); ylim([50 400]);
  899. yticks(0:50:350);
  900. xticks([1:20]); ylabel('AUC_{MW}/AUC_{SW}','FontWeight','normal'); xlabel('Pulse Number','FontSize',22);
  901. set(gca,'FontSize',18); set(gca,'TickDir','out');
  902. legend('Barrel KO','Septa KO','Location','NorthWest');
  903. title('Layer_{2/3} Multi/Single','FontWeight','normal');
  904. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_MW_div_SW_Barrel.png'),"Resolution",600);
  906. % % Figure 4G - 7-20 Pulses
  907. %
  908. % t1 = all_L4_KO_ratio_Barrel;
  909. % t2 = all_L4_KO_ratio_Septa;
  910. % ranksum(t1,t2)
  911. % figure; set(gcf,'Position',[1200 100 200 300]); hold on;
  912. % bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  913. % plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  914. % plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  915. % bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  916. % plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  917. % plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  918. %
  919. % hold on; plot([1 2],[240 240],'LineWidth',3,'Color','w');
  920. % text(1.5,245,'NS','HorizontalAlignment','center','FontSize',64,'Color','w');
  921. %
  922. % axis([0.5 2.5 0 270]);
  923. % yticks(0:50:250);
  924. % xticks([1 2]); xticklabels({'B' 'S'}); ylabel('Peak(MW/SW)%');
  925. % set(gca,'FontSize',30); set(gca,'TickDir','out');
  926. % exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_div_SW_Barrel_Septa.png'),"Resolution",600);
  928. %%
  929. %% Statistical Comparisons
  930. %% L2/3 WT
  931. tempB = []; tempS = []; tempN = [];
  932. for ii = 1:size(stimtrials_L23_WT,1)
  933. for jj = 1:20
  934. tempB(ii,jj) = trapz(1:50,stimtrials_L23_WT(ii,1:50,jj));
  935. end
  936. end
  937. for ii = 1:size(stimtrials_L23_WT_septa,1)
  938. for jj = 1:20
  939. tempS(ii,jj) = trapz(1:50,stimtrials_L23_WT_septa(ii,1:50,jj));
  940. end
  941. end
  942. for ii = 1:size(stimtrials_L23_WT_neigh,1)
  943. for jj = 1:20
  944. tempN(ii,jj) = trapz(1:50,stimtrials_L23_WT_neigh(ii,1:50,jj));
  945. end
  946. end
  948. %%
  949. %% All Pulse Stats
  951. for p = 1:20
  952. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  953. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  954. t3 = mean(reshape(tempN(:,p),20,length(tempN(:,20))/20),1);
  956. pValues(1,p) = ranksum(t1,t2);
  957. pValues(2,p) = ranksum(t1,t3);
  958. pValues(3,p) = ranksum(t2,t3);
  959. end
  961. colorMapDiscrete = [];
  962. colorMapDiscrete = hot(10);
  964. figure; set(gcf,'Position',[100 100 250 800]);
  965. imagesc(pValues',[0 0.1]); colormap(flipud(colorMapDiscrete)); colorbar;
  966. set(gca,'FontSize',20); set(gca,'TickDir','out');
  967. ylabel('Pulse Number','FontSize',20); yticks((1:20));
  968. xlabel('Stats','FontSize',20); xticks([1 2 3]); xticklabels({'BS','BN','SN'}); xtickangle(90);
  969. exportgraphics(gcf,fullfile(saveFolder,'L23_BSN_WT_Stats_SW.png'),"Resolution",600);
  971. % First Pulse
  972. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  973. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  974. t3 = mean(reshape(tempN(:,1),20,length(tempN(:,20))/20),1);
  975. %
  976. % clc;
  977. % ranksum(t1,t2)
  978. % ranksum(t1,t3)
  979. % ranksum(t2,t3)
  980. %
  981. % figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  982. % bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  983. % plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  984. % plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  985. % bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  986. % plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  987. % plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  988. % bar(3, mean(t3), 'FaceColor', colorNeigh, 'EdgeColor', 'none', 'BarWidth', 0.6);
  989. % plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  990. % plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeigh/2);
  991. %
  992. % plot([2 3],[19 19],'LineWidth',3,'Color','k');
  993. % text(2.5,19.1,'*','HorizontalAlignment','center','FontSize',64);
  994. %
  995. % axis([0.5 3.5 0 20]);
  996. % yticks(0:4:20);
  997. % xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  998. % set(gca,'FontSize',30); set(gca,'TickDir','out');
  999. % exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_first_pulse.png'),"Resolution",600);
  1000. %
  1001. % % Second Pulse
  1002. % t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  1003. % t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  1004. % t3 = mean(reshape(tempN(:,2),20,length(tempN(:,20))/20),1);
  1005. %
  1006. % clc;
  1007. % ranksum(t1,t2)
  1008. % ranksum(t1,t3)
  1009. % ranksum(t2,t3)
  1010. %
  1011. % figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1012. % bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1013. % plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1014. % plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1015. % bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1016. % plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1017. % plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1018. % bar(3, mean(t3), 'FaceColor', colorNeigh, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1019. % plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1020. % plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeigh/2);
  1021. %
  1022. % % plot([2 3],[19 19],'LineWidth',3,'Color','k');
  1023. % % text(2.5,19.1,'*','HorizontalAlignment','center','FontSize',64);
  1024. %
  1025. % axis([0.5 3.5 0 20]);
  1026. % yticks(0:4:20);
  1027. % xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  1028. % set(gca,'FontSize',30); set(gca,'TickDir','out');
  1029. % exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_second_pulse.png'),"Resolution",600);
  1030. %
  1031. % % Third Pulse
  1032. % t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  1033. % t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  1034. % t3 = mean(reshape(tempN(:,3),20,length(tempN(:,20))/20),1);
  1035. %
  1036. % clc;
  1037. % ranksum(t1,t2)
  1038. % ranksum(t1,t3)
  1039. % ranksum(t2,t3)
  1040. %
  1041. % figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1042. % bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1043. % plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1044. % plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1045. % bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1046. % plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1047. % plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1048. % bar(3, mean(t3), 'FaceColor', colorNeigh, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1049. % plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1050. % plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeigh/2);
  1051. %
  1052. % plot([1 2],[12 12],'LineWidth',3,'Color','k');
  1053. % text(1.5,12.1,'*','HorizontalAlignment','center','FontSize',64);
  1054. %
  1055. % axis([0.5 3.5 0 20]);
  1056. % yticks(0:4:20);
  1057. % xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  1058. % set(gca,'FontSize',30); set(gca,'TickDir','out');
  1059. % exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_third_pulse.png'),"Resolution",600);
  1060. %
  1061. % % 20th Pulse
  1062. % t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  1063. % t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  1064. % t3 = mean(reshape(tempN(:,20),20,length(tempN(:,20))/20),1);
  1065. %
  1066. % clc;
  1067. % ranksum(t1,t2)
  1068. % ranksum(t1,t3)
  1069. % ranksum(t2,t3)
  1070. %
  1071. % figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1072. % bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1073. % plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1074. % plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1075. % bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1076. % plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1077. % plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1078. % bar(3, mean(t3), 'FaceColor', colorNeigh, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1079. % plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1080. % plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeigh/2);
  1081. %
  1082. % plot([1 2],[7.5 7.5],'LineWidth',3,'Color','k');
  1083. % text(1.5,7.7,'**','HorizontalAlignment','center','FontSize',64);
  1084. % plot([2 3],[5.5 5.5],'LineWidth',3,'Color','k');
  1085. % text(2.5,5.7,'*','HorizontalAlignment','center','FontSize',64);
  1086. %
  1087. % axis([0.5 3.5 0 20]);
  1088. % yticks(0:4:20);
  1089. % xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  1090. % set(gca,'FontSize',30); set(gca,'TickDir','out');
  1091. % exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_20th_pulse.png'),"Resolution",600);
  1093. %% L4 WT
  1094. tempB = []; tempS = []; tempN = [];
  1095. for ii = 1:size(stimtrials_L4_WT,1)
  1096. for jj = 1:20
  1097. tempB(ii,jj) = trapz(1:50,stimtrials_L4_WT(ii,1:50,jj));
  1098. end
  1099. end
  1100. for ii = 1:size(stimtrials_L4_WT_septa,1)
  1101. for jj = 1:20
  1102. tempS(ii,jj) = trapz(1:50,stimtrials_L4_WT_septa(ii,1:50,jj));
  1103. end
  1104. end
  1105. for ii = 1:size(stimtrials_L4_WT_neigh,1)
  1106. for jj = 1:20
  1107. tempN(ii,jj) = trapz(1:50,stimtrials_L4_WT_neigh(ii,1:50,jj));
  1108. end
  1109. end
  1111. %% All Pulse Stats
  1112. for p = 1:20
  1113. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1114. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1115. t3 = mean(reshape(tempN(:,p),20,length(tempN(:,20))/20),1);
  1117. pValues(1,p) = ranksum(t1,t2);
  1118. pValues(2,p) = ranksum(t1,t3);
  1119. pValues(3,p) = ranksum(t2,t3);
  1120. end
  1122. colorMapDiscreteTemp = [];
  1123. colorMapDiscreteTemp = hot(10);
  1124. colorMapDiscrete(10,:) = colorMapDiscreteTemp(10,:);
  1125. colorMapDiscrete(9,:) = colorMapDiscreteTemp(8,:);
  1126. colorMapDiscrete(8,:) = colorMapDiscreteTemp(6,:);
  1127. colorMapDiscrete(7,:) = colorMapDiscreteTemp(4,:);
  1128. colorMapDiscrete(6,:) = colorMapDiscreteTemp(2,:);
  1129. colorMapDiscrete(5,:) = colorMapDiscreteTemp(1,:);
  1130. colorMapDiscrete(4,:) = colorMapDiscreteTemp(1,:);
  1131. colorMapDiscrete(3,:) = colorMapDiscreteTemp(1,:);
  1132. colorMapDiscrete(2,:) = colorMapDiscreteTemp(1,:);
  1133. colorMapDiscrete(1,:) = [0 0 0];
  1135. colorMapDiscrete = 1-colorMapDiscrete;
  1137. % Figure 1E
  1138. figure; set(gcf,'Position',[100 100 1000 200]);
  1139. imagesc(pValues,[0 0.05]); cmap = colormap(flipud(colorMapDiscrete)); cbh = colorbar;
  1140. cbh.Ticks = [0, 0.01, 0.05]; cbh.TickLabels = {'0','0.01','>0.05'} ;
  1141. set(gca,'FontSize',20); set(gca,'TickDir','out');
  1142. xlabel('Pulse Number','FontSize',20); xticks((1:20));
  1143. yticks([1 2 3]); yticklabels({'B vs S','B vs N','S vs N'}); %xtickangle(45);
  1144. exportgraphics(gcf,fullfile(saveFolder, 'L4_BSN_WT_Stats_SW.png'),"Resolution",300);
  1146. %% MW Stats
  1147. %% L2/3 WT MW
  1148. tempB = []; tempS = []; tempN = [];
  1149. for ii = 1:size(stimtrials_MW_L23_WT,1)
  1150. for jj = 1:20
  1151. tempB(ii,jj) = trapz(1:50,stimtrials_MW_L23_WT(ii,1:50,jj));
  1152. end
  1153. end
  1154. for ii = 1:size(stimtrials_MW_L23_WT_septa,1)
  1155. for jj = 1:20
  1156. tempS(ii,jj) = trapz(1:50,stimtrials_MW_L23_WT_septa(ii,1:50,jj));
  1157. end
  1158. end
  1160. pValuesL23 = [];
  1161. for p = 1:20
  1162. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1163. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1165. pValuesL23(p) = ranksum(t1,t2);
  1166. end
  1168. figure; set(gcf,'Position',[100 100 150 800]);
  1169. imagesc(pValues',[0 0.05]); colormap gray; colorbar;
  1170. colorbar('Ticks',[0 0.01 0.05],'TickLabels',{'***','**','*'});
  1171. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1172. ylabel('Pulse Number','FontSize',28); yticks((1:20));
  1173. xlabel('pValue','FontSize',22); xticks([1]); xticklabels({'BS'});
  1174. exportgraphics(gcf,fullfile(saveFolder,'L23_BS_WT_Stats_MW.png'),"Resolution",600);
  1175. % First Pulse
  1176. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  1177. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  1179. clc;
  1180. ranksum(t1,t2)
  1182. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1183. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1184. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1185. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1186. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1187. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1188. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1190. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1191. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1193. axis([0.5 2.5 0 13]);
  1194. yticks(0:4:20);
  1195. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1196. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1197. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_MW_BSN_stat_first_pulse.png'),"Resolution",600);
  1199. % Second Pulse
  1200. t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  1201. t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  1203. clc;
  1204. ranksum(t1,t2)
  1206. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1207. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1208. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1209. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1210. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1211. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1212. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1214. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1215. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1217. axis([0.5 2.5 0 13]);
  1218. yticks(0:4:20);
  1219. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1220. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1221. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_MW_BSN_stat_second_pulse.png'),"Resolution",600);
  1223. % Third Pulse
  1224. t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  1225. t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  1227. clc;
  1228. ranksum(t1,t2)
  1230. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1231. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1232. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1233. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1234. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1235. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1236. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1238. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1239. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1241. axis([0.5 2.5 0 13]);
  1242. yticks(0:4:20);
  1243. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1244. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1245. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_MW_BSN_stat_third_pulse.png'),"Resolution",600);
  1247. % 20th Pulse
  1248. t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  1249. t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  1251. clc;
  1252. ranksum(t1,t2)
  1254. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1255. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1256. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1257. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1258. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1259. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1260. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1262. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1263. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1265. axis([0.5 2.5 0 13]);
  1266. yticks(0:4:20);
  1267. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1268. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1269. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_MW_BSN_stat_20th_pulse.png'),"Resolution",600);
  1271. %% L4 WT MW
  1273. %%
  1274. tempB = []; tempS = [];
  1275. for ii = 1:size(stimtrials_MW_L4_WT,1)
  1276. for jj = 1:20
  1277. tempB(ii,jj) = trapz(1:50,stimtrials_MW_L4_WT(ii,1:50,jj));
  1278. end
  1279. end
  1280. for ii = 1:size(stimtrials_MW_L4_WT_septa,1)
  1281. for jj = 1:20
  1282. tempS(ii,jj) = trapz(1:50,stimtrials_MW_L4_WT_septa(ii,1:50,jj));
  1283. end
  1284. end
  1286. for p = 1:20
  1287. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1288. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1290. pValuesMW(p) = ranksum(t1,t2);
  1291. end
  1293. % colorMapDiscrete = [];
  1294. % colorMapDiscrete = hot(10);
  1296. figure; set(gcf,'Position',[100 100 100 700]); set(gcf,'OuterPosition',[100 100 180 700]);
  1297. imagesc(pValuesMW',[0 0.1]); colormap(flipud(colorMapDiscrete)); colorbar;
  1298. set(gca,'FontSize',20); set(gca,'TickDir','out');
  1299. ylabel('Pulse Number','FontSize',20); yticks((1:20));
  1300. xlabel('Stats','FontSize',20); xticks([1]); xticklabels({'B vs S'});
  1301. exportgraphics(gcf,fullfile(saveFolder, 'L4_BSN_WT_Stats_MW.png'),"Resolution",300);
  1304. %%
  1305. pValuesL4 = [];
  1306. for p = 1:20
  1307. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1308. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1310. pValuesL4(p) = ranksum(t1,t2);
  1311. end
  1313. figure; set(gcf,'Position',[100 100 150 800]);
  1314. imagesc(pValues',[0 0.05]); colormap gray; colorbar;
  1315. colorbar('Ticks',[0 0.01 0.05],'TickLabels',{'***','**','*'});
  1316. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1317. ylabel('Pulse Number','FontSize',28); yticks((1:20));
  1318. xlabel('pValue','FontSize',22); xticks([1]); xticklabels({'BS'});
  1319. exportgraphics(gcf,fullfile(saveFolder,'L4_BS_WT_Stats_MW.png'),"Resolution",600);
  1321. % Figure 1G - First Pulse
  1322. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  1323. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  1325. clc;
  1326. ranksum(t1,t2)
  1328. figure; set(gcf,'Position',[1200 100 200 400]); hold on;
  1329. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1330. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1331. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1332. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1333. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1334. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1335. axis([0.5 2.5 0 13]);
  1336. yticks(0:4:20);
  1337. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1338. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1339. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_BSN_stat_first_pulse.png'),"Resolution",600);
  1341. % Figure 1G - Second Pulse
  1342. t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  1343. t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  1345. clc;
  1346. ranksum(t1,t2)
  1348. figure; set(gcf,'Position',[1200 100 200 400]); hold on;
  1349. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1350. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1351. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1352. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1353. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1354. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1356. plot([1 2],[12 12],'LineWidth',3,'Color','k');
  1357. text(1.5,12.1,'**','HorizontalAlignment','center','FontSize',64);
  1359. axis([0.5 2.5 0 13]);
  1360. yticks(0:4:20);
  1361. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1362. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1363. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_BSN_stat_second_pulse.png'),"Resolution",600);
  1365. % Figure 1G - Third Pulse
  1366. t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  1367. t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  1369. clc;
  1370. ranksum(t1,t2)
  1372. figure; set(gcf,'Position',[1200 100 200 400]); hold on;
  1373. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1374. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1375. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1376. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1377. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1378. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1380. plot([1 2],[11 11],'LineWidth',3,'Color','k');
  1381. text(1.5,11.1,'**','HorizontalAlignment','center','FontSize',64);
  1383. axis([0.5 2.5 0 13]);
  1384. yticks(0:4:20);
  1385. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1386. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1387. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_BSN_stat_third_pulse.png'),"Resolution",600);
  1389. % Figure 1G - 20th Pulse
  1390. t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  1391. t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  1393. clc;
  1394. ranksum(t1,t2)
  1396. figure; set(gcf,'Position',[1200 100 200 400]); hold on;
  1397. bar(1, mean(t1), 'FaceColor', colorBarrel, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1398. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1399. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrel/2);
  1400. bar(2, mean(t2), 'FaceColor', colorSepta, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1401. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1402. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSepta/2);
  1404. plot([1 2],[9.3 9.3],'LineWidth',3,'Color','k');
  1405. text(1.5,9.4,'**','HorizontalAlignment','center','FontSize',64);
  1407. axis([0.5 2.5 0 13]);
  1408. yticks(0:4:20);
  1409. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1410. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1411. exportgraphics(gcf,fullfile(saveFolder,'L4_WT_MW_BSN_stat_20th_pulse.png'),"Resolution",600);
  1413. %% MW Stats - KO
  1414. %% L2/3 KO MW
  1415. tempB = []; tempS = []; tempN = [];
  1416. for ii = 1:size(stimtrials_MW_L23_KO,1)
  1417. for jj = 1:20
  1418. tempB(ii,jj) = trapz(1:50,stimtrials_MW_L23_KO(ii,1:50,jj));
  1419. end
  1420. end
  1421. for ii = 1:size(stimtrials_MW_L23_KO_septa,1)
  1422. for jj = 1:20
  1423. tempS(ii,jj) = trapz(1:50,stimtrials_MW_L23_KO_septa(ii,1:50,jj));
  1424. end
  1425. end
  1427. pValuesL23KO = [];
  1428. for p = 1:20
  1429. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1430. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1432. pValuesL23KO(p) = ranksum(t1,t2);
  1433. end
  1435. figure; set(gcf,'Position',[100 100 150 800]);
  1436. imagesc(pValues',[0 0.05]); colormap gray; colorbar;
  1437. colorbar('Ticks',[0 0.01 0.05],'TickLabels',{'***','**','*'});
  1438. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1439. ylabel('Pulse Number','FontSize',28); yticks((1:20));
  1440. xlabel('pValue','FontSize',22); xticks([1]); xticklabels({'BS'});
  1441. exportgraphics(gcf,fullfile(saveFolder,'L23_BS_KO_Stats_MW.png'),"Resolution",600);
  1443. % First Pulse
  1444. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  1445. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  1447. clc;
  1448. ranksum(t1,t2)
  1450. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1451. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1452. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1453. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1454. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1455. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1456. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1458. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1459. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1461. axis([0.5 2.5 0 13]);
  1462. yticks(0:4:20);
  1463. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1464. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1465. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_MW_BSN_stat_first_pulse.png'),"Resolution",600);
  1467. % Second Pulse
  1468. t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  1469. t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  1471. clc;
  1472. ranksum(t1,t2)
  1474. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1475. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1476. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1477. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1478. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1479. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1480. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1482. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1483. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1485. axis([0.5 2.5 0 13]);
  1486. yticks(0:4:20);
  1487. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1488. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1489. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_MW_BSN_stat_second_pulse.png'),"Resolution",600);
  1491. % Third Pulse
  1492. t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  1493. t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  1495. clc;
  1496. ranksum(t1,t2)
  1498. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1499. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1500. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1501. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1502. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1503. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1504. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1506. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1507. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1509. axis([0.5 2.5 0 13]);
  1510. yticks(0:4:20);
  1511. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1512. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1513. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_MW_BSN_stat_third_pulse.png'),"Resolution",600);
  1515. % 20th Pulse
  1516. t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  1517. t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  1519. clc;
  1520. ranksum(t1,t2)
  1522. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1523. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1524. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1525. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1526. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1527. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1528. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1530. % plot([1 2],[8 8],'LineWidth',3,'Color','k');
  1531. % text(1.5,8.1,'***','HorizontalAlignment','center','FontSize',64);
  1533. axis([0.5 2.5 0 13]);
  1534. yticks(0:4:20);
  1535. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1536. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1537. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_MW_BSN_stat_20th_pulse.png'),"Resolution",600);
  1539. %% L4 KO MW
  1540. tempB = []; tempS = []; tempN = [];
  1541. for ii = 1:size(stimtrials_MW_L4_KO,1)
  1542. for jj = 1:20
  1543. tempB(ii,jj) = trapz(1:50,stimtrials_MW_L4_KO(ii,1:50,jj));
  1544. end
  1545. end
  1546. for ii = 1:size(stimtrials_MW_L4_KO_septa,1)
  1547. for jj = 1:20
  1548. tempS(ii,jj) = trapz(1:50,stimtrials_MW_L4_KO_septa(ii,1:50,jj));
  1549. end
  1550. end
  1552. pValuesL4KO = [];
  1553. for p = 1:20
  1554. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1555. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1557. pValuesL4KO(p) = ranksum(t1,t2);
  1558. end
  1560. figure; set(gcf,'Position',[100 100 150 800]);
  1561. imagesc(pValues',[0 0.05]); colormap gray; colorbar;
  1562. colorbar('Ticks',[0 0.01 0.05],'TickLabels',{'***','**','*'});
  1563. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1564. ylabel('Pulse Number','FontSize',28); yticks((1:20));
  1565. xlabel('pValue','FontSize',22); xticks([1]); xticklabels({'BS'});
  1566. exportgraphics(gcf,fullfile(saveFolder,'L4_BS_KO_Stats_MW.png'),"Resolution",600);
  1568. % Figure 4E - First Pulse
  1569. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  1570. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  1572. clc;
  1573. ranksum(t1,t2)
  1575. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1576. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1577. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1578. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1579. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1580. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1581. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1583. axis([0.5 2.5 0 13]);
  1584. yticks(0:4:20);
  1585. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1586. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1587. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_BSN_stat_first_pulse.png'),"Resolution",600);
  1589. % Figure 4E - Second Pulse
  1590. t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  1591. t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  1593. clc;
  1594. ranksum(t1,t2)
  1596. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1597. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1598. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1599. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1600. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1601. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1602. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1604. axis([0.5 2.5 0 13]);
  1605. yticks(0:4:20);
  1606. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1607. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1608. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_BSN_stat_second_pulse.png'),"Resolution",600);
  1610. % Figure 4E - Third Pulse
  1611. t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  1612. t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  1614. clc;
  1615. ranksum(t1,t2)
  1617. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1618. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1619. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1620. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1621. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1622. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1623. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1625. axis([0.5 2.5 0 13]);
  1626. yticks(0:4:20);
  1627. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1628. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1629. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_BSN_stat_third_pulse.png'),"Resolution",600);
  1631. % Figure 4E - 20th Pulse
  1632. t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  1633. t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  1635. clc;
  1636. ranksum(t1,t2)
  1638. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1639. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1640. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1641. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1642. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1643. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1644. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1646. plot([1 2],[10 10],'LineWidth',3,'Color','k');
  1647. text(1.5,10.1,'**','HorizontalAlignment','center','FontSize',64);
  1649. axis([0.5 2.5 0 13]);
  1650. yticks(0:4:20);
  1651. xticks([1 2]); xticklabels({'B' 'S'}); ylabel('AUC');
  1652. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1653. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_MW_BSN_stat_20th_pulse.png'),"Resolution",600);
  1655. %% L4 KO
  1656. tempB = []; tempS = []; tempN = [];
  1657. for ii = 1:size(stimtrials_L4_KO,1)
  1658. for jj = 1:20
  1659. tempB(ii,jj) = trapz(1:50,stimtrials_L4_KO(ii,1:50,jj));
  1660. end
  1661. end
  1662. for ii = 1:size(stimtrials_L4_KO_septa,1)
  1663. for jj = 1:20
  1664. tempS(ii,jj) = trapz(1:50,stimtrials_L4_KO_septa(ii,1:50,jj));
  1665. end
  1666. end
  1667. for ii = 1:size(stimtrials_L4_KO_neigh,1)
  1668. for jj = 1:20
  1669. tempN(ii,jj) = trapz(1:50,stimtrials_L4_KO_neigh(ii,1:50,jj));
  1670. end
  1671. end
  1673. % Figure 4C
  1674. for p = 1:20
  1675. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1676. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1677. t3 = mean(reshape(tempN(:,p),20,length(tempN(:,20))/20),1);
  1679. pValues(1,p) = ranksum(t1,t2);
  1680. pValues(2,p) = ranksum(t1,t3);
  1681. pValues(3,p) = ranksum(t2,t3);
  1682. end
  1685. colorMapDiscreteTemp = [];
  1686. colorMapDiscreteTemp = hot(10);
  1687. colorMapDiscrete(10,:) = colorMapDiscreteTemp(10,:);
  1688. colorMapDiscrete(9,:) = colorMapDiscreteTemp(8,:);
  1689. colorMapDiscrete(8,:) = colorMapDiscreteTemp(6,:);
  1690. colorMapDiscrete(7,:) = colorMapDiscreteTemp(4,:);
  1691. colorMapDiscrete(6,:) = colorMapDiscreteTemp(2,:);
  1692. colorMapDiscrete(5,:) = colorMapDiscreteTemp(1,:);
  1693. colorMapDiscrete(4,:) = colorMapDiscreteTemp(1,:);
  1694. colorMapDiscrete(3,:) = colorMapDiscreteTemp(1,:);
  1695. colorMapDiscrete(2,:) = colorMapDiscreteTemp(1,:);
  1696. colorMapDiscrete(1,:) = [0 0 0];
  1698. colorMapDiscrete = 1-colorMapDiscrete;
  1700. figure; set(gcf,'Position',[100 100 1000 200]);
  1701. imagesc(pValues,[0 0.05]); cmap = colormap(flipud(colorMapDiscrete)); cbh = colorbar;
  1702. cbh.Ticks = [0, 0.01, 0.05]; cbh.TickLabels = {'0','0.01','>0.05'} ;
  1703. set(gca,'FontSize',20); set(gca,'TickDir','out');
  1704. xlabel('Pulse Number','FontSize',20); xticks((1:20));
  1705. yticks([1 2 3]); yticklabels({'B vs S','B vs N','S vs N'}); %xtickangle(45);
  1706. exportgraphics(gcf,fullfile(saveFolder, 'L4_BSN_KO_Stats_SW.png'),"Resolution",300);
  1708. %% WT vs KO SW and MW p Values
  1709. tempB_WT = []; tempB_KO = [];
  1710. for ii = 1:size(stimtrials_L5_WT,1)
  1711. for jj = 1:20
  1712. tempB_WT(ii,jj) = trapz(1:50,stimtrials_L5_WT(ii,1:50,jj));
  1713. end
  1714. end
  1715. for ii = 1:size(stimtrials_L5_KO,1)
  1716. for jj = 1:20
  1717. tempB_KO(ii,jj) = trapz(1:50,stimtrials_L5_KO(ii,1:50,jj));
  1718. end
  1719. end
  1721. tempS_WT = []; tempS_KO = [];
  1722. for ii = 1:size(stimtrials_L5_WT_septa,1)
  1723. for jj = 1:20
  1724. tempS_WT(ii,jj) = trapz(1:50,stimtrials_L5_WT_septa(ii,1:50,jj));
  1725. end
  1726. end
  1727. for ii = 1:size(stimtrials_L5_KO_septa,1)
  1728. for jj = 1:20
  1729. tempS_KO(ii,jj) = trapz(1:50,stimtrials_L5_KO_septa(ii,1:50,jj));
  1730. end
  1731. end
  1733. tempN_WT = []; tempN_KO = [];
  1734. for ii = 1:size(stimtrials_L5_WT_neigh,1)
  1735. for jj = 1:20
  1736. tempN_WT(ii,jj) = trapz(1:50,stimtrials_L5_WT_neigh(ii,1:50,jj));
  1737. end
  1738. end
  1739. for ii = 1:size(stimtrials_L5_KO_neigh,1)
  1740. for jj = 1:20
  1741. tempN_KO(ii,jj) = trapz(1:50,stimtrials_L5_KO_neigh(ii,1:50,jj));
  1742. end
  1743. end
  1744. %% All Pulse Stats
  1745. for p = 1:20
  1746. t1 = mean(reshape(tempB_WT(:,p),20,length(tempB_WT(:,20))/20),1);
  1747. t2 = mean(reshape(tempB_KO(:,p),20,length(tempB_KO(:,20))/20),1);
  1749. t3 = mean(reshape(tempS_WT(:,p),20,length(tempS_WT(:,20))/20),1);
  1750. t4 = mean(reshape(tempS_KO(:,p),20,length(tempS_KO(:,20))/20),1);
  1752. t5 = mean(reshape(tempN_WT(:,p),20,length(tempN_WT(:,20))/20),1);
  1753. t6 = mean(reshape(tempN_KO(:,p),20,length(tempN_KO(:,20))/20),1);
  1755. pValues(1,p) = ranksum(t1,t2);
  1756. pValues(2,p) = ranksum(t3,t4);
  1757. pValues(3,p) = ranksum(t5,t6);
  1758. end
  1760. figure; hold on;
  1761. plot(pValues(1,:)','Color',(colorBarrel+colorBarrelKO)/2,'LineWidth',3);
  1762. plot(pValues(2,:)','Color',(colorSepta+colorSeptaKO)/2,'LineWidth',3);
  1763. plot(pValues(3,:)','Color',(colorNeigh+colorNeighKO)/2,'LineWidth',3);
  1764. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1765. legend({'Barrel','Septa','Neighbor'},'FontSize',14,'AutoUpdate','off');
  1766. plot(0:21,0.05*ones(1,22),'Color','r','LineWidth',1)
  1767. xlabel('Pulse Number','FontSize',24);
  1768. ylabel('p','FontSize',24);
  1769. title('WT vs KO','FontSize',24); axis([1 20 0 1]);
  1770. saveas(gcf, fullfile(saveFolder,'L5_p_WT_vs_KO_1-50ms.png','epsc'));
  1772. %% MW
  1773. tempB_WT = []; tempB_KO = [];
  1774. for ii = 1:size(stimtrials_MW_L23_WT,1)
  1775. for jj = 1:20
  1776. tempB_WT(ii,jj) = trapz(1:50,stimtrials_MW_L23_WT(ii,1:50,jj));
  1777. end
  1778. end
  1779. for ii = 1:size(stimtrials_MW_L23_KO,1)
  1780. for jj = 1:20
  1781. tempB_KO(ii,jj) = trapz(1:50,stimtrials_MW_L23_KO(ii,1:50,jj));
  1782. end
  1783. end
  1785. tempS_WT = []; tempS_KO = [];
  1786. for ii = 1:size(stimtrials_MW_L23_WT_septa,1)
  1787. for jj = 1:20
  1788. tempS_WT(ii,jj) = trapz(1:50,stimtrials_MW_L23_WT_septa(ii,1:50,jj));
  1789. end
  1790. end
  1791. for ii = 1:size(stimtrials_MW_L23_KO_septa,1)
  1792. for jj = 1:20
  1793. tempS_KO(ii,jj) = trapz(1:50,stimtrials_MW_L23_KO_septa(ii,1:50,jj));
  1794. end
  1795. end
  1797. %% All Pulse Stats
  1798. for p = 1:20
  1799. t1 = mean(reshape(tempB_WT(:,p),20,length(tempB_WT(:,20))/20),1);
  1800. t2 = mean(reshape(tempB_KO(:,p),20,length(tempB_KO(:,20))/20),1);
  1802. t3 = mean(reshape(tempS_WT(:,p),20,length(tempS_WT(:,20))/20),1);
  1803. t4 = mean(reshape(tempS_KO(:,p),20,length(tempS_KO(:,20))/20),1);
  1805. pValues(1,p) = ranksum(t1,t2);
  1806. pValues(2,p) = ranksum(t3,t4);
  1807. end
  1809. figure; hold on;
  1810. plot(pValues(1,:)','Color',(colorBarrel+colorBarrelKO)/2,'LineWidth',3);
  1811. plot(pValues(2,:)','Color',(colorSepta+colorSeptaKO)/2,'LineWidth',3);
  1812. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1813. legend({'Barrel','Septa'},'FontSize',14,'AutoUpdate','off');
  1814. plot(0:21,0.05*ones(1,22),'Color','r','LineWidth',1)
  1815. xlabel('Pulse Number','FontSize',24);
  1816. ylabel('p','FontSize',24);
  1817. title('WT vs KO','FontSize',24); axis([1 20 0 1]);
  1818. saveas(gcf, fullfile(saveFolder,'L23_p_WT_vs_KO_MW_1-50ms.png','epsc'));
  1820. %%
  1821. one = squeeze(mean(stimtrials_L23_WT_neigh,1))';
  1822. two = squeeze(mean(stimtrials_L23_KO_neigh,1))';
  1824. [ds,ix,iy] = dtw(one,two);
  1826. onewarp = one(:,ix);
  1827. twowarp = two(:,iy);
  1829. figure; set(gcf,'Position',[100 100 500 300]);
  1830. imagesc(onewarp,[0 0.35]);
  1831. colormap turbo; colorbar;
  1832. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  1833. xlabel('Time (ms)','FontSize',24); xticks([1 20 40 60 80]);
  1834. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1835. ylabel('Pulse Number','FontSize',22); yticks([1 5 10 15 20]);
  1836. exportgraphics(gcf,fullfile(saveFolder,'L23_Neigh_WT_Image_Warped.png'),"Resolution",600);
  1838. figure; set(gcf,'Position',[100 100 500 300]);
  1839. imagesc(twowarp,[0 0.35]);
  1840. colormap turbo; colorbar;
  1841. colorbar('Ticks',[0 0.1 0.2 0.3 0.4],'TickLabels',{'0','0.1','0.2','0.3','0.4'});
  1842. xlabel('Time (ms)','FontSize',24); xticks([1 20 40 60 80]);
  1843. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1844. ylabel('Pulse Number','FontSize',22); yticks([1 5 10 15 20]);
  1845. exportgraphics(gcf,fullfile(saveFolder,'L23_Neigh_KO_Image_Warped.png'),"Resolution",600);
  1847. %% L2/3 KO
  1848. tempB = []; tempS = []; tempN = [];
  1849. for ii = 1:size(stimtrials_L23_KO,1)
  1850. for jj = 1:20
  1851. tempB(ii,jj) = trapz(1:50,stimtrials_L23_KO(ii,1:50,jj));
  1852. end
  1853. end
  1854. for ii = 1:size(stimtrials_L23_KO_septa,1)
  1855. for jj = 1:20
  1856. tempS(ii,jj) = trapz(1:50,stimtrials_L23_KO_septa(ii,1:50,jj));
  1857. end
  1858. end
  1859. for ii = 1:size(stimtrials_L23_KO_neigh,1)
  1860. for jj = 1:20
  1861. tempN(ii,jj) = trapz(1:50,stimtrials_L23_KO_neigh(ii,1:50,jj));
  1862. end
  1863. end
  1865. for p = 1:20
  1866. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  1867. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  1868. t3 = mean(reshape(tempN(:,p),20,length(tempN(:,20))/20),1);
  1870. pValues(1,p) = ranksum(t1,t2);
  1871. pValues(2,p) = ranksum(t1,t3);
  1872. pValues(3,p) = ranksum(t2,t3);
  1873. end
  1875. figure; set(gcf,'Position',[100 100 250 800]);
  1876. imagesc(pValues',[0 0.05]); colormap gray; colorbar;
  1877. colorbar('Ticks',[0 0.01 0.05],'TickLabels',{'***','**','*'});
  1878. set(gca,'FontSize',24); set(gca,'TickDir','out');
  1879. ylabel('Pulse Number','FontSize',28); yticks((1:20));
  1880. xlabel('pValue','FontSize',22); xticks([1 2 3]); xticklabels({'BS','BN','SN'});
  1881. exportgraphics(gcf,fullfile(saveFolder,'L23_BSN_KO_Stats_SW.png'),"Resolution",600);
  1883. % First Pulse
  1884. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  1885. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  1886. t3 = mean(reshape(tempN(:,1),20,length(tempN(:,20))/20),1);
  1888. clc;
  1889. ranksum(t1,t2)
  1890. ranksum(t1,t3)
  1891. ranksum(t2,t3)
  1893. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1894. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1895. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1896. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1897. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1898. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1899. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1900. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1901. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1902. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  1904. plot([2 3],[17.8 17.8],'LineWidth',3,'Color','k');
  1905. text(2.5,17.8,'*','HorizontalAlignment','center','FontSize',64);
  1906. plot([1 3],[19 19],'LineWidth',3,'Color','k');
  1907. text(2,19,'*','HorizontalAlignment','center','FontSize',64);
  1909. axis([0.5 3.5 0 20]);
  1910. yticks(0:4:20);
  1911. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  1912. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1913. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_BSN_stat_first_pulse.png'),"Resolution",600);
  1915. % Second Pulse
  1916. t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  1917. t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  1918. t3 = mean(reshape(tempN(:,2),20,length(tempN(:,20))/20),1);
  1920. clc;
  1921. ranksum(t1,t2)
  1922. ranksum(t1,t3)
  1923. ranksum(t2,t3)
  1925. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1926. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1927. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1928. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1929. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1930. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1931. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1932. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1933. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1934. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  1936. % plot([2 3],[19 19],'LineWidth',3,'Color','k');
  1937. % text(2.5,19.1,'*','HorizontalAlignment','center','FontSize',64);
  1939. axis([0.5 3.5 0 20]);
  1940. yticks(0:4:20);
  1941. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  1942. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1943. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_BSN_stat_second_pulse.png'),"Resolution",600);
  1945. % Third Pulse
  1946. t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  1947. t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  1948. t3 = mean(reshape(tempN(:,3),20,length(tempN(:,20))/20),1);
  1950. clc;
  1951. ranksum(t1,t2)
  1952. ranksum(t1,t3)
  1953. ranksum(t2,t3)
  1955. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1956. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1957. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1958. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1959. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1960. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1961. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1962. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1963. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1964. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  1966. % plot([1 2],[12 12],'LineWidth',3,'Color','k');
  1967. % text(1.5,12.1,'*','HorizontalAlignment','center','FontSize',64);
  1969. axis([0.5 3.5 0 20]);
  1970. yticks(0:4:20);
  1971. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  1972. set(gca,'FontSize',30); set(gca,'TickDir','out');
  1973. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_BSN_stat_third_pulse.png'),"Resolution",600);
  1975. % 20th Pulse
  1976. t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  1977. t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  1978. t3 = mean(reshape(tempN(:,20),20,length(tempN(:,20))/20),1);
  1980. clc;
  1981. ranksum(t1,t2)
  1982. ranksum(t1,t3)
  1983. ranksum(t2,t3)
  1985. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  1986. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1987. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  1988. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  1989. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1990. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  1991. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  1992. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  1993. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  1994. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  1996. % plot([1 2],[7.5 7.5],'LineWidth',3,'Color','k');
  1997. % text(1.5,7.7,'**','HorizontalAlignment','center','FontSize',64);
  1998. % plot([2 3],[5.5 5.5],'LineWidth',3,'Color','k');
  1999. % text(2.5,5.7,'*','HorizontalAlignment','center','FontSize',64);
  2001. axis([0.5 3.5 0 20]);
  2002. yticks(0:4:20);
  2003. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  2004. set(gca,'FontSize',30); set(gca,'TickDir','out');
  2005. exportgraphics(gcf,fullfile(saveFolder,'L23_KO_BSN_stat_20th_pulse.png'),"Resolution",600);
  2007. %% L4 KO
  2008. tempB = []; tempS = []; tempN = [];
  2009. for ii = 1:size(stimtrials_L4_KO,1)
  2010. for jj = 1:20
  2011. tempB(ii,jj) = trapz(1:50,stimtrials_L4_KO(ii,1:50,jj));
  2012. end
  2013. end
  2014. for ii = 1:size(stimtrials_L4_KO_septa,1)
  2015. for jj = 1:20
  2016. tempS(ii,jj) = trapz(1:50,stimtrials_L4_KO_septa(ii,1:50,jj));
  2017. end
  2018. end
  2019. for ii = 1:size(stimtrials_L4_KO_neigh,1)
  2020. for jj = 1:20
  2021. tempN(ii,jj) = trapz(1:50,stimtrials_L4_KO_neigh(ii,1:50,jj));
  2022. end
  2023. end
  2025. for p = 1:20
  2026. t1 = mean(reshape(tempB(:,p),20,length(tempB(:,20))/20),1);
  2027. t2 = mean(reshape(tempS(:,p),20,length(tempS(:,20))/20),1);
  2028. t3 = mean(reshape(tempN(:,p),20,length(tempN(:,20))/20),1);
  2030. pValues(1,p) = ranksum(t1,t2);
  2031. pValues(2,p) = ranksum(t1,t3);
  2032. pValues(3,p) = ranksum(t2,t3);
  2033. end
  2035. figure; set(gcf,'Position',[100 100 250 800]);
  2036. imagesc(pValues',[0 0.05]); colormap gray; colorbar;
  2037. colorbar('Ticks',[0 0.01 0.05],'TickLabels',{'***','**','*'});
  2038. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2039. ylabel('Pulse Number','FontSize',28); yticks((1:20));
  2040. xlabel('pValue','FontSize',22); xticks([1 2 3]); xticklabels({'BS','BN','SN'});
  2041. exportgraphics(gcf,fullfile(saveFolder,'L4_BSN_KO_Stats_SW.png'),"Resolution",600);
  2043. % First Pulse
  2044. t1 = mean(reshape(tempB(:,1),20,length(tempB(:,20))/20),1);
  2045. t2 = mean(reshape(tempS(:,1),20,length(tempS(:,20))/20),1);
  2046. t3 = mean(reshape(tempN(:,1),20,length(tempN(:,20))/20),1);
  2048. clc;
  2049. ranksum(t1,t2)
  2050. ranksum(t1,t3)
  2051. ranksum(t2,t3)
  2053. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2054. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2055. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2056. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  2057. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2058. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2059. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  2060. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2061. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2062. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  2064. plot([2 3],[15 15],'LineWidth',3,'Color','k');
  2065. text(2.5,15.1,'*','HorizontalAlignment','center','FontSize',64);
  2066. plot([1 3],[17 17],'LineWidth',3,'Color','k');
  2067. text(2,17.1,'*','HorizontalAlignment','center','FontSize',64);
  2069. axis([0.5 3.5 0 20]);
  2070. yticks(0:4:20);
  2071. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  2072. set(gca,'FontSize',30); set(gca,'TickDir','out');
  2073. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_BSN_stat_first_pulse.png'),"Resolution",600);
  2075. % Second Pulse
  2076. t1 = mean(reshape(tempB(:,2),20,length(tempB(:,20))/20),1);
  2077. t2 = mean(reshape(tempS(:,2),20,length(tempS(:,20))/20),1);
  2078. t3 = mean(reshape(tempN(:,2),20,length(tempN(:,20))/20),1);
  2080. clc;
  2081. ranksum(t1,t2)
  2082. ranksum(t1,t3)
  2083. ranksum(t2,t3)
  2085. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2086. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2087. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2088. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  2089. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2090. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2091. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  2092. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2093. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2094. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  2096. % plot([2 3],[19 19],'LineWidth',3,'Color','k');
  2097. % text(2.5,19.1,'*','HorizontalAlignment','center','FontSize',64);
  2099. axis([0.5 3.5 0 20]);
  2100. yticks(0:4:20);
  2101. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  2102. set(gca,'FontSize',30); set(gca,'TickDir','out');
  2103. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_BSN_stat_second_pulse.png'),"Resolution",600);
  2105. % Third Pulse
  2106. t1 = mean(reshape(tempB(:,3),20,length(tempB(:,20))/20),1);
  2107. t2 = mean(reshape(tempS(:,3),20,length(tempS(:,20))/20),1);
  2108. t3 = mean(reshape(tempN(:,3),20,length(tempN(:,20))/20),1);
  2110. clc;
  2111. ranksum(t1,t2)
  2112. ranksum(t1,t3)
  2113. ranksum(t2,t3)
  2115. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2116. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2117. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2118. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  2119. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2120. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2121. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  2122. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2123. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2124. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  2126. % plot([1 2],[12.5 12.5],'LineWidth',3,'Color','k');
  2127. % text(1.5,12.7,'**','HorizontalAlignment','center','FontSize',64);
  2129. axis([0.5 3.5 0 20]);
  2130. yticks(0:4:20);
  2131. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  2132. set(gca,'FontSize',30); set(gca,'TickDir','out');
  2133. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_BSN_stat_third_pulse.png'),"Resolution",600);
  2135. % 20th Pulse
  2136. t1 = mean(reshape(tempB(:,20),20,length(tempB(:,20))/20),1);
  2137. t2 = mean(reshape(tempS(:,20),20,length(tempS(:,20))/20),1);
  2138. t3 = mean(reshape(tempN(:,20),20,length(tempN(:,20))/20),1);
  2140. clc;
  2141. ranksum(t1,t2)
  2142. ranksum(t1,t3)
  2143. ranksum(t2,t3)
  2145. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2146. bar(1, mean(t1), 'FaceColor', colorBarrelKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2147. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2148. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorBarrelKO/2);
  2149. bar(2, mean(t2), 'FaceColor', colorSeptaKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2150. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2151. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorSeptaKO/2);
  2152. bar(3, mean(t3), 'FaceColor', colorNeighKO, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2153. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2154. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',colorNeighKO/2);
  2156. plot([1 2],[12 12],'LineWidth',3,'Color','k');
  2157. text(1.5,12.2,'*','HorizontalAlignment','center','FontSize',64);
  2158. plot([1 3],[14 14],'LineWidth',3,'Color','k');
  2159. text(2,14.2,'*','HorizontalAlignment','center','FontSize',64);
  2161. axis([0.5 3.5 0 20]);
  2162. yticks(0:4:20);
  2163. xticks([1 2 3]); xticklabels({'B' 'S' 'N'}); ylabel('AUC');
  2164. set(gca,'FontSize',30); set(gca,'TickDir','out');
  2165. exportgraphics(gcf,fullfile(saveFolder,'L4_KO_BSN_stat_20th_pulse.png'),"Resolution",600);
  2167. %% ANOVA Calculations - July 2025
  2169. % Compate WT Barrel vs Septa
  2170. % SW
  2171. tempB_perBarrel = convertTrialtoPerBarrel(stimtrials_L4_WT);
  2172. tempS_perBarrel = convertTrialtoPerBarrel(stimtrials_L4_WT_septa);
  2173. tempN_perBarrel = convertTrialtoPerBarrel(stimtrials_L4_WT_neigh);
  2175. [rm, ranovaResults, timeResults] = calculate3ANOVA(tempB_perBarrel,tempS_perBarrel,tempN_perBarrel)
  2176. size(tempB_perBarrel)
  2177. size(tempS_perBarrel)
  2178. size(tempN_perBarrel)
  2180. % MW
  2181. tempB_MW_perBarrel = convertTrialtoPerBarrel(stimtrials_MW_L4_WT);
  2182. tempS_MW_perBarrel = convertTrialtoPerBarrel(stimtrials_MW_L4_WT_septa);
  2184. [rm, ranovaResults, timeResults] = calculateANOVA(tempB_MW_perBarrel,tempS_MW_perBarrel)
  2185. size(tempB_MW_perBarrel)
  2186. size(tempS_MW_perBarrel)
  2188. % MW_SW
  2189. mw_sw_L4_WT_Barrel = (tempB_MW_perBarrel./tempB_perBarrel);
  2190. mw_sw_L4_WT_Septa = (tempS_MW_perBarrel./tempS_perBarrel);
  2192. [rm, ranovaResults, timeResults] = calculateANOVA(mw_sw_L4_WT_Barrel,mw_sw_L4_WT_Septa)
  2193. size(mw_sw_L4_WT_Barrel)
  2194. size(mw_sw_L4_WT_Septa)
  2196. % Compate KO Barrel vs Septa
  2197. % SW
  2198. tempB_perBarrel = convertTrialtoPerBarrel(stimtrials_L4_KO);
  2199. tempS_perBarrel = convertTrialtoPerBarrel(stimtrials_L4_KO_septa);
  2200. tempN_perBarrel = convertTrialtoPerBarrel(stimtrials_L4_KO_neigh);
  2202. [rm, ranovaResults, timeResults] = calculate3ANOVA(tempB_perBarrel,tempS_perBarrel,tempN_perBarrel)
  2203. size(tempB_perBarrel)
  2204. size(tempS_perBarrel)
  2205. size(tempN_perBarrel)
  2207. % MW
  2208. tempB_MW_perBarrel = convertTrialtoPerBarrel(stimtrials_MW_L4_KO);
  2209. tempS_MW_perBarrel = convertTrialtoPerBarrel(stimtrials_MW_L4_KO_septa);
  2211. [rm, ranovaResults, timeResults] = calculateANOVA(tempB_MW_perBarrel,tempS_MW_perBarrel)
  2212. size(tempB_MW_perBarrel)
  2213. size(tempS_MW_perBarrel)
  2215. % MW_SW
  2216. mw_sw_L4_KO_Barrel = (tempB_MW_perBarrel./tempB_perBarrel);
  2217. mw_sw_L4_KO_Septa = (tempS_MW_perBarrel./tempS_perBarrel);
  2219. [rm, ranovaResults, timeResults] = calculateANOVA(mw_sw_L4_KO_Barrel,mw_sw_L4_KO_Septa)
  2220. size(mw_sw_L4_KO_Barrel)
  2221. size(mw_sw_L4_KO_Septa)
  2223. %% ANOVA Stats June 2025
  2224. all_L4_WT_ratio_Barrel_Combined = (L4_WT_MW_Barrel_Max./L4_WT_SW_Barrel_Max);
  2225. all_L4_WT_ratio_Septa_Combined = (L4_WT_MW_Septa_Max./L4_WT_SW_Septa_Max);
  2226. all_L4_KO_ratio_Barrel_Combined = (L4_KO_MW_Barrel_Max./L4_KO_SW_Barrel_Max);
  2227. all_L4_KO_ratio_Septa_Combined = (L4_KO_MW_Septa_Max./L4_KO_SW_Septa_Max);
  2229. dataA = all_L4_WT_ratio_Barrel_Combined; % Condition A : 14 Barrels, 20 time points
  2230. dataB = all_L4_WT_ratio_Septa_Combined; % Condition B : 9 Septa, 20 time points
  2231. data = [dataA; dataB]; % Combine : 23 BS x 20 time points
  2233. condition = [repmat({'A'}, 13, 1); repmat({'B'}, 8, 1)];
  2235. % Create table
  2236. timeNames = arrayfun(@(x) sprintf('Time%d', x), 1:20, 'UniformOutput', false);
  2237. T = array2table(data, 'VariableNames', timeNames);
  2238. T.Condition = condition;
  2240. % Define within-subject factor
  2241. withinDesign = table((1:20)', 'VariableNames', {'Time'});
  2242. withinDesign.Time = categorical(withinDesign.Time);
  2244. % Fit repeated measures model
  2245. rm = fitrm(T, 'Time1-Time20 ~ Condition', 'WithinDesign', withinDesign);
  2247. % Run ANOVA
  2248. ranovaResults = ranova(rm, 'WithinModel', 'Time');
  2249. disp(ranovaResults);
  2251. % Post-hoc tests (if needed)
  2252. timeResults = multcompare(rm, 'Time', 'By', 'Condition');
  2253. disp(timeResults);
  2255. % Post-hoc test for Condition at each Time point
  2256. rm = fitrm(T, 'Time1-Time20 ~ Condition', 'WithinDesign', table(categorical(1:20)', 'VariableNames', {'Time'}));
  2257. timeResults = multcompare(rm, 'Condition', 'By', 'Time');
  2258. disp(timeResults);
  2260. %%
  2261. dataA = all_L4_KO_ratio_Barrel_Combined; % Condition A: 13 subjects, 20 time points
  2262. dataB = all_L4_KO_ratio_Septa_Combined; % Condition B: 8 subjects, 20 time points
  2263. data = [dataA; dataB]; % Combine: 21 subjects x 20 time points
  2265. condition = [repmat({'A'}, size(dataA,1), 1); repmat({'B'}, size(dataB,1), 1)];
  2267. % Create table
  2268. timeNames = arrayfun(@(x) sprintf('Time%d', x), 1:20, 'UniformOutput', false);
  2269. T = array2table(data, 'VariableNames', timeNames);
  2270. T.Condition = condition;
  2272. % Define within-subject factor
  2273. withinDesign = table((1:20)', 'VariableNames', {'Time'});
  2274. withinDesign.Time = categorical(withinDesign.Time);
  2276. % Fit repeated measures model
  2277. rm = fitrm(T, 'Time1-Time20 ~ Condition', 'WithinDesign', withinDesign);
  2279. % Run ANOVA
  2280. ranovaResults = ranova(rm, 'WithinModel', 'Time');
  2281. disp(ranovaResults);
  2283. % Post-hoc tests (if needed)
  2284. timeResults = multcompare(rm, 'Time', 'By', 'Condition');
  2285. disp(timeResults);
  2287. % Post-hoc test for Condition at each Time point
  2288. rm = fitrm(T, 'Time1-Time20 ~ Condition', 'WithinDesign', table(categorical(1:20)', 'VariableNames', {'Time'}));
  2289. timeResults = multcompare(rm, 'Condition', 'By', 'Time');
  2290. disp(timeResults);
  2292. %% SW_MW Ratios
  2294. %%
  2296. for s = 1:20
  2297. stimtrials_L23_WT(:,:,s) = temp_L23_WT(:,beglocs(s):beglocs(s)+94);
  2298. stimtrials_L23_WT_septa(:,:,s) = temp_L23_WT_septa(:,beglocs(s):beglocs(s)+94);
  2299. stimtrials_L23_WT_neigh(:,:,s) = temp_L23_WT_neigh(:,beglocs(s):beglocs(s)+94);
  2300. end
  2302. tempB = []; tempS = []; tempN = [];
  2303. for ii = 1:size(noBase_stimtrials_L23_WT,1)
  2304. for jj = 1:20
  2305. tempB(ii,jj) = trapz(1:94,stimtrials_L23_WT(ii,1:94,jj));
  2306. end
  2307. end
  2308. for ii = 1:size(noBase_stimtrials_L23_WT_septa,1)
  2309. for jj = 1:20
  2310. tempS(ii,jj) = trapz(1:94,stimtrials_L23_WT_septa(ii,1:94,jj));
  2311. end
  2312. end
  2313. for ii = 1:size(noBase_stimtrials_L23_WT_neigh,1)
  2314. for jj = 1:20
  2315. tempN(ii,jj) = trapz(1:94,stimtrials_L23_WT_neigh(ii,1:94,jj));
  2316. end
  2317. end
  2319. figure , errorbar((1:20)+rand(1,20)/5,mean(tempB),std(temp,[],1)/sqrt(size(noBase_stimtrials_L23_WT,1)/20),'Color',colorBarrel,'LineWidth',4);
  2320. hold on , errorbar((1:20)+rand(1,20)/5,mean(tempS),std(temp3,[],1)/sqrt(size(noBase_stimtrials_L23_WT_septa,1)/20),'Color',colorSepta,'LineWidth',4);
  2321. hold on , errorbar((1:20)+rand(1,20)/5,mean(tempN),std(temp2,[],1)/sqrt(size(noBase_stimtrials_L23_WT_neigh,1)/20),'Color',colorNeigh,'LineWidth',4);
  2322. legend({'Barrel','Septa','Neighbour'},'FontSize',20);
  2323. axis([0.5 20.5 0 1.1]);
  2324. yticks([0 0.05 0.1 0.15 0.20]); yticklabels({'0','0.05','0.10','0.15','0.20'});
  2325. xticks([1 5 10 15 20]); ylabel('MUA'); xlabel('Pulse Number');
  2326. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2327. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN.png'),"Resolution",600);
  2329. %% Average of Everything
  2330. m1 = squeeze(mean(mean(stimtrials_L4_WT(:,:,1:20),3),1));
  2331. m1 = m1 - m1(1); m1 = m1/max(m1);
  2332. m2 = squeeze(mean(mean(stimtrials_L4_WT_septa(:,:,1:20),3),1));
  2333. m2 = m2 - m2(1); m2 = m2/max(m2);
  2334. m3 = squeeze(mean(mean(stimtrials_L4_WT_neigh(:,:,1:20),3),1));
  2335. m3 = m3 - m3(1); m3 = m3/max(m3);
  2337. figure , plot(m1,'Color',colorBarrel,'LineWidth',4);
  2338. hold on, plot(m2,'Color',colorSepta,'LineWidth',4);
  2339. hold on, plot(m3,'Color',colorNeigh,'LineWidth',4);
  2341. m1ko = squeeze(mean(mean(stimtrials_L4_KO(:,:,1:20),3),1));
  2342. m1ko = m1ko - m1ko(1); m1ko = m1ko/max(m1ko);
  2343. m2ko = squeeze(mean(mean(stimtrials_L4_KO_septa(:,:,1:20),3),1));
  2344. m2ko = m2ko - m2ko(1); m2ko = m2ko/max(m2ko);
  2345. m3ko = squeeze(mean(mean(stimtrials_L4_KO_neigh(:,:,1:20),3),1));
  2346. m3ko = m3ko - m3ko(1); m3ko = m3ko/max(m3ko);
  2348. figure , plot(m1ko,'Color',colorBarrelKO,'LineWidth',4);
  2349. hold on, plot(m2ko,'Color',colorSeptaKO,'LineWidth',4);
  2350. hold on, plot(m3ko,'Color',colorNeighKO,'LineWidth',4);
  2352. %% T-SNE PLOTS December 2024
  2353. dataset1 = stimtrials_L4_WT(:,1:45,:);
  2354. dataset2 = stimtrials_L4_WT_septa(:,1:45,:);
  2355. dataset3 = stimtrials_L4_WT_neigh(:,1:45,:);
  2356. dataset4 = stimtrials_L4_KO(:,1:45,:);
  2357. dataset5 = stimtrials_L4_KO_septa(:,1:45,:);
  2358. dataset6 = stimtrials_L4_KO_neigh(:,1:45,:);
  2360. ds1 = []; ds2 = []; ds3 = []; ds4 = []; ds5 = []; ds6 = [];
  2362. ch = 1;
  2363. for h = 1:20:size(dataset1,1)
  2364. temp1 = mean(dataset1(h:h+19,:,:),1);
  2365. ds1(ch,:) = temp1(:);
  2366. ch = ch + 1;
  2367. end
  2369. ch = 1;
  2370. for h = 1:20:size(dataset2,1)
  2371. temp2 = mean(dataset2(h:h+19,:,:),1);
  2372. ds2(ch,:) = temp2(:);
  2373. ch = ch + 1;
  2374. end
  2376. ch = 1;
  2377. for h = 1:20:size(dataset3,1)
  2378. temp3 = mean(dataset3(h:h+19,:,:),1);
  2379. ds3(ch,:) = temp3(:);
  2380. ch = ch + 1;
  2381. end
  2383. ch = 1;
  2384. for h = 1:20:size(dataset4,1)
  2385. temp4 = mean(dataset4(h:h+19,:,:),1);
  2386. ds4(ch,:) = temp4(:);
  2387. ch = ch + 1;
  2388. end
  2390. ch = 1;
  2391. for h = 1:20:size(dataset5,1)
  2392. temp5 = mean(dataset5(h:h+19,:,:),1);
  2393. ds5(ch,:) = temp5(:);
  2394. ch = ch + 1;
  2395. end
  2397. ch = 1;
  2398. for h = 1:20:size(dataset6,1)
  2399. temp6 = mean(dataset6(h:h+19,:,:),1);
  2400. ds6(ch,:) = temp6(:);
  2401. ch = ch + 1;
  2402. end
  2404. Y = tsne([ds1; ds2; ds3; ds4; ds5; ds6],...
  2405. 'Algorithm','barneshut','Perplexity',3,'NumPCAComponents',2,'Exaggeration',6);
  2406. genotype = [ones(1,size(ds1,1)) 2*ones(1,size(ds2,1)) 3*ones(1,size(ds3,1))...
  2407. 4*ones(1,size(ds4,1)) 5*ones(1,size(ds5,1)) 6*ones(1,size(ds6,1))];
  2408. figure; gscatter(Y(:,1),Y(:,2),genotype);
  2409. %%
  2410. m1 = squeeze(mean(mean(stimtrials_MW_L4_WT_septa(:,:,1:20),3),1));
  2411. m1 = m1 - m1(1); m1 = m1/max(m1);
  2412. m2 = squeeze(mean(mean(stimtrials_MW_L4_KO_septa(:,:,1:20),3),1));
  2413. m2 = m2 - m2(1); m2 = m2/max(m2);
  2415. figure , plot(m1,'Color',colorSepta,'LineWidth',4);
  2416. hold on, plot(m2,'Color',colorSepta/2,'LineWidth',4);
  2420. %% L2/3 WT
  2421. temp = [];
  2422. temp2 = [];
  2423. temp3 = [];
  2425. for ii = 1:size(stimtrials_L23_WT,1)
  2426. for jj = 1:20
  2427. temp(ii,jj) = max(stimtrials_L23_WT(ii,1:25,jj));
  2428. end
  2429. end
  2430. for ii = 1:size(stimtrials_L23_WT_neigh,1)
  2431. for jj = 1:20
  2432. temp2(ii,jj) = max(stimtrials_L23_WT_neigh(ii,1:25,jj));
  2433. end
  2434. end
  2435. for ii = 1:size(stimtrials_L23_WT_septa,1)
  2436. for jj = 1:20
  2437. temp3(ii,jj) = max(stimtrials_L23_WT_septa(ii,1:25,jj));
  2438. end
  2439. end
  2441. figure , errorbar((1:20)+rand(1,20)/5,mean(temp) ,std(temp,[],1)/sqrt(size(stimtrials_L23_WT,1)/20),'Color',colorBarrel,'LineWidth',4);
  2442. hold on , errorbar((1:20)+rand(1,20)/5,mean(temp3),std(temp3,[],1)/sqrt(size(stimtrials_L23_WT_septa,1)/20),'Color',colorSepta,'LineWidth',4);
  2443. hold on , errorbar((1:20)+rand(1,20)/5,mean(temp2),std(temp2,[],1)/sqrt(size(stimtrials_L23_WT_neigh,1)/20),'Color',colorNeigh,'LineWidth',4);
  2444. legend({'Barrel','Septa','Neighbour'},'FontSize',20);
  2445. axis([0.5 20.5 0 0.245]);
  2446. yticks([0 0.05 0.1 0.15 0.20]); yticklabels({'0','0.05','0.10','0.15','0.20'});
  2447. xticks([1 5 10 15 20]); ylabel('MUA'); xlabel('Pulse Number');
  2448. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2449. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN.png'),"Resolution",600);
  2451. figure , bar(mean(temp_L23_WT),5,'FaceColor',color1,'LineWidth',15); set(gca,'visible','off');
  2452. hold on, bar(mean(temp_L23_WT_neigh),5,'FaceColor',color2,'LineWidth',15);
  2453. hold on, bar(mean(temp_L23_WT_septa),5,'FaceColor',color3,'LineWidth',15);
  2454. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_spikes.png'),"Resolution",600);
  2456. % First Pulse
  2458. t1 = mean(reshape(temp(:,1),20,length(temp(:,20))/20),1);
  2459. t2 = mean(reshape(temp2(:,1),20,length(temp2(:,20))/20),1);
  2460. t3 = mean(reshape(temp3(:,1),20,length(temp3(:,20))/20),1);
  2462. clc;
  2463. ranksum(t1,t2)
  2464. ranksum(t1,t3)
  2465. ranksum(t2,t3)
  2467. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2468. bar(1, mean(t1), 'FaceColor', color1, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2469. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2470. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color1/2);
  2471. bar(2, mean(t2), 'FaceColor', color2, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2472. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2473. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color2/2);
  2474. bar(3, mean(t3), 'FaceColor', color3, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2475. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2476. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color3/2);
  2478. % legend({'Barrel','Neighbour','Septa'},'FontSize',24);
  2479. axis([0.5 3.5 0 0.45]);
  2480. yticks([0 0.05 0.1 0.15 0.20 0.25 0.30 0.35 0.40]); yticklabels({'0' '0.05' '0.10' '0.15' '0.20' '0.25' '0.30' '0.35' '0.40'});
  2481. yticks([0 0.05 0.1 0.15 0.20 0.25 0.30 0.35 0.40]); yticklabels({'0' '0.05' '0.10' '0.15' '0.20' '0.25' '0.30' '0.35' '0.40'}); xticks([1 2 3]); xticklabels({'B' 'N' 'S'}); ylabel('MUA'); %xlabel('Pulse Number');
  2482. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2483. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_first_pulse.png'),"Resolution",600);
  2485. % Second Pulse
  2487. t1 = mean(reshape(temp(:,2),20,length(temp(:,20))/20),1);
  2488. t2 = mean(reshape(temp2(:,2),20,length(temp2(:,20))/20),1);
  2489. t3 = mean(reshape(temp3(:,2),20,length(temp3(:,20))/20),1);
  2491. clc;
  2492. ranksum(t1,t2)
  2493. ranksum(t1,t3)
  2494. ranksum(t2,t3)
  2496. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2497. bar(1, mean(t1), 'FaceColor', color1, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2498. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2499. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color1/2);
  2500. bar(2, mean(t2), 'FaceColor', color2, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2501. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2502. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color2/2);
  2503. bar(3, mean(t3), 'FaceColor', color3, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2504. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2505. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color3/2);
  2507. plot([1 2],[0.27 0.27],'LineWidth',3,'Color','k');
  2508. text(1.5,0.271,'***','HorizontalAlignment','center','FontSize',64);
  2509. % plot([1 3],[0.27 0.27],'LineWidth',3,'Color','k');
  2510. % text(2,0.271,'*','HorizontalAlignment','center','FontSize',64);
  2511. % legend({'Barrel','Neighbour','Septa'},'FontSize',24);
  2512. axis([0.5 3.5 0 0.3]);
  2513. yticks([0 0.05 0.1 0.15 0.20 0.25 0.30 0.35 0.40]); yticklabels({'0' '0.05' '0.10' '0.15' '0.20' '0.25' '0.30' '0.35' '0.40'}); xticks([1 2 3]); xticklabels({'B' 'N' 'S'}); ylabel('MUA'); %xlabel('Pulse Number');
  2514. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2515. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_second_pulse.png'),"Resolution",600);
  2517. % Third Pulse
  2519. t1 = mean(reshape(temp(:,3),20,length(temp(:,20))/20),1);
  2520. t2 = mean(reshape(temp2(:,3),20,length(temp2(:,20))/20),1);
  2521. t3 = mean(reshape(temp3(:,3),20,length(temp3(:,20))/20),1);
  2523. clc;
  2524. ranksum(t1,t2)
  2525. ranksum(t1,t3)
  2526. ranksum(t2,t3)
  2528. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2529. bar(1, mean(t1), 'FaceColor', color1, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2530. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2531. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color1/2);
  2532. bar(2, mean(t2), 'FaceColor', color2, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2533. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2534. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color2/2);
  2535. bar(3, mean(t3), 'FaceColor', color3, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2536. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2537. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color3/2);
  2539. plot([1 2],[0.27 0.27],'LineWidth',3,'Color','k');
  2540. text(1.5,0.271,'***','HorizontalAlignment','center','FontSize',64);
  2541. % plot([1 3],[0.27 0.27],'LineWidth',3,'Color','k');
  2542. % text(2,0.271,'*','HorizontalAlignment','center','FontSize',64);
  2543. % legend({'Barrel','Neighbour','Septa'},'FontSize',24);
  2544. axis([0.5 3.5 0 0.3]);
  2545. yticks([0 0.05 0.1 0.15 0.20 0.25 0.30 0.35 0.40]); yticklabels({'0' '0.05' '0.10' '0.15' '0.20' '0.25' '0.30' '0.35' '0.40'}); xticks([1 2 3]); xticklabels({'B' 'N' 'S'}); ylabel('MUA'); %xlabel('Pulse Number');
  2546. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2547. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_second_pulse.png'),"Resolution",600);
  2549. % Last Pulse
  2551. t1 = mean(reshape(temp(:,20),20,length(temp(:,20))/20),1);
  2552. t2 = mean(reshape(temp2(:,20),20,length(temp2(:,20))/20),1);
  2553. t3 = mean(reshape(temp3(:,20),20,length(temp3(:,20))/20),1);
  2555. clc;
  2556. ranksum(t1,t2)
  2557. ranksum(t1,t3)
  2558. ranksum(t2,t3)
  2560. figure; set(gcf,'Position',[1200 100 300 500]); hold on;
  2561. bar(1, mean(t1), 'FaceColor', color1, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2562. plot([1 1],[mean(t1)-std(t1)/sqrt(length(t1)) mean(t1)+std(t1)/sqrt(length(t1))],'LineWidth',5,'Color','k');
  2563. plot(ones(1,length(t1))-0.1+rand(1,length(t1))/5,t1,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color1/2);
  2564. bar(2, mean(t2), 'FaceColor', color2, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2565. plot([2 2],[mean(t2)-std(t2)/sqrt(length(t2)) mean(t2)+std(t2)/sqrt(length(t2))],'LineWidth',5,'Color','k');
  2566. plot(2*ones(1,length(t2))-0.1+rand(1,length(t2))/5,t2,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color2/2);
  2567. bar(3, mean(t3), 'FaceColor', color3, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2568. plot([3 3],[mean(t3)-std(t3)/sqrt(length(t3)) mean(t3)+std(t3)/sqrt(length(t3))],'LineWidth',5,'Color','k');
  2569. plot(3*ones(1,length(t3))-0.1+rand(1,length(t3))/5,t3,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color3/2);
  2571. plot([1 2],[0.25 0.25],'LineWidth',3,'Color','k');
  2572. text(1.5,0.251,'***','HorizontalAlignment','center','FontSize',64);
  2573. plot([1 3],[0.27 0.27],'LineWidth',3,'Color','k');
  2574. text(2,0.271,'*','HorizontalAlignment','center','FontSize',64);
  2575. % legend({'Barrel','Neighbour','Septa'},'FontSize',24);
  2576. axis([0.5 3.5 0 0.3]);
  2577. yticks([0 0.05 0.1 0.15 0.20 0.25 0.30 0.35 0.40]); yticklabels({'0' '0.05' '0.10' '0.15' '0.20' '0.25' '0.30' '0.35' '0.40'}); xticks([1 2 3]); xticklabels({'B' 'N' 'S'}); ylabel('MUA'); %xlabel('Pulse Number');
  2578. set(gca,'FontSize',24); set(gca,'TickDir','out');
  2579. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_last_pulse.png'),"Resolution",600);
  2581. t1_sw = mean(reshape(temp(:,1),20,length(temp(:,20))/20),1);
  2582. t2_sw = mean(reshape(temp2(:,1),20,length(temp2(:,20))/20),1);
  2583. t3_sw = mean(reshape(temp3(:,1),20,length(temp3(:,20))/20),1);
  2585. t1_mw = 100-100*mean(reshape(temp(:,20),20,length(temp(:,20))/20),1)./t1_sw;
  2586. t2_mw = 100-100*mean(reshape(temp2(:,20),20,length(temp2(:,20))/20),1)./t2_sw;
  2587. t3_mw = 100-100*mean(reshape(temp3(:,20),20,length(temp3(:,20))/20),1)./t3_sw;
  2589. signrank(t1_sw,t1_mw)
  2590. signrank(t2_sw,t2_mw)
  2591. signrank(t3_sw,t3_mw)
  2593. figure; set(gcf,'Position',[1200 100 450 400]); hold on;
  2594. bar(1, mean(t1_mw), 'FaceColor', color1, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2595. plot([1 1],[mean(t1_mw)-std(t1_mw)/sqrt(length(t1_mw)) mean(t1_mw)+std(t1_mw)/sqrt(length(t1_mw))],'LineWidth',5,'Color','k');
  2596. plot(ones(1,length(t1_mw))-0.1+rand(1,length(t1_mw))/5,t1_mw,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color1/2);
  2597. bar(2, mean(t2_mw), 'FaceColor', color2, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2598. plot([2 2],[mean(t2_mw)-std(t2_mw)/sqrt(length(t2_mw)) mean(t2_mw)+std(t2_mw)/sqrt(length(t2_mw))],'LineWidth',5,'Color','k');
  2599. plot(2*ones(1,length(t2_mw))-0.1+rand(1,length(t2_mw))/5,t2_mw,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color2/2);
  2600. bar(3, mean(t3_mw), 'FaceColor', color3, 'EdgeColor', 'none', 'BarWidth', 0.6);
  2601. plot([3 3],[mean(t3_mw)-std(t3_mw)/sqrt(length(t3_mw)) mean(t3_mw)+std(t3_mw)/sqrt(length(t3_mw))],'LineWidth',5,'Color','k');
  2602. plot(3*ones(1,length(t3_mw))-0.1+rand(1,length(t3_mw))/5,t3_mw,'Marker','.','MarkerSize',38,'LineStyle','none','Color',color3/2);
  2604. text(1,30,'***','HorizontalAlignment','center','FontSize',52,'Color','w');
  2605. text(2,30,'***','HorizontalAlignment','center','FontSize',52,'Color','w');
  2606. text(3,30,'**','HorizontalAlignment','center','FontSize',52,'Color','w');
  2608. % legend({'Barrel','Neighbour','Septa'},'FontSize',24);
  2609. axis([0.5 3.5 0 100]);
  2610. yticks(0:20:100);
  2611. xticks([1 2 3]); xticklabels({'B' 'N' 'S'}); ylabel('%Adaptation'); %xlabel('Pulse Number');
  2612. set(gca,'FontSize',36); set(gca,'TickDir','out');
  2613. exportgraphics(gcf,fullfile(saveFolder,'L23_WT_BSN_stat_Adaptation.png'),"Resolution",600);
  2617. %%
  2618. allPred_WT_L23 = [];
  2619. for stimNum = 1:20
  2620. d_WT = stimtrials_L23_WT(:,:,stimNum);
  2621. d_WT_Septa = stimtrials_L23_WT_septa(:,:,stimNum);
  2622. d_WT_Neigh = stimtrials_L23_WT_neigh(:,:,stimNum);
  2624. y1 = ones(1,size(d_WT,1));
  2625. y2 = 2*ones(1,size(d_WT_Septa,1));
  2626. y3 = 3*ones(1,size(d_WT_Neigh,1));
  2628. labelVector = repelem([{'Barrel'}, {'Septa'}, {'Neighbor'}],...
  2629. [size(d_WT,1) size(d_WT_Septa,1) size(d_WT_Neigh,1)])';
  2631. Y = labelVector;
  2632. X = [d_WT; d_WT_Septa; d_WT_Neigh];
  2634. tmp = templateEnsemble('GentleBoost',100,templateTree('surrogate','on'));
  2635. opt = statset('UseParallel',true);
  2636. ecoc = fitcecoc(X,Y,'Coding','onevsall','Learners',tmp,...
  2637. 'Prior','uniform','Options',opt);
  2638. cvecoc = crossval(ecoc,'Options',opt);
  2639. Yhat = kfoldPredict(cvecoc,'Options',opt);
  2641. figure;
  2642. ConfMat = confusionchart(Y,Yhat,'Title',sprintf('Pulse Number: %d',stimNum), ...
  2643. 'RowSummary','row-normalized', ...
  2644. 'ColumnSummary','column-normalized');
  2645. ConfMat.InnerPosition = [0.20 0.15 0.75 0.75];
  2646. ConfMat.FontSize = 24;
  2648. saveas(gcf, fullfile(saveFolder,sprintf('L23_WT_BSN_Decode_%d.png',stimNum),"Resolution",600));
  2649. close all;
  2651. allPred_WT_L23(:,:,stimNum) = confusionmat(Y,Yhat);
  2652. end
  2654. allPred_KO_L23 = [];
  2655. for stimNum = 1:20
  2656. d_WT = stimtrials_L23_KO(:,:,stimNum);
  2657. d_WT_Septa = stimtrials_L23_KO_septa(:,:,stimNum);
  2658. d_WT_Neigh = stimtrials_L23_KO_neigh(:,:,stimNum);
  2660. y1 = ones(1,size(d_WT,1));
  2661. y2 = 2*ones(1,size(d_WT_Septa,1));
  2662. y3 = 3*ones(1,size(d_WT_Neigh,1));
  2664. labelVector = repelem([{'Barrel'}, {'Septa'}, {'Neighbor'}],...
  2665. [size(d_WT,1) size(d_WT_Septa,1) size(d_WT_Neigh,1)])';
  2667. Y = labelVector;
  2668. X = [d_WT; d_WT_Septa; d_WT_Neigh];
  2670. tmp = templateEnsemble('GentleBoost',100,templateTree('surrogate','on'));
  2671. opt = statset('UseParallel',true);
  2672. ecoc = fitcecoc(X,Y,'Coding','onevsall','Learners',tmp,...
  2673. 'Prior','uniform','Options',opt);
  2674. cvecoc = crossval(ecoc,'Options',opt);
  2675. Yhat = kfoldPredict(cvecoc,'Options',opt);
  2677. figure;
  2678. ConfMat = confusionchart(Y,Yhat,'Title',sprintf('Pulse Number: %d',stimNum), ...
  2679. 'RowSummary','row-normalized', ...
  2680. 'ColumnSummary','column-normalized');
  2681. ConfMat.InnerPosition = [0.20 0.15 0.75 0.75];
  2682. ConfMat.FontSize = 24;
  2684. saveas(gcf, fullfile(saveFolder,sprintf('L23_KO_BSN_Decode_%d.png',stimNum),"Resolution",600));
  2685. close all;
  2687. allPred_KO_L23(:,:,stimNum) = confusionmat(Y,Yhat);
  2688. end
  2690. allPred_WT_L4 = [];
  2691. for stimNum = 1:20
  2692. d_WT = stimtrials_L4_WT(:,:,stimNum);
  2693. d_WT_Septa = stimtrials_L4_WT_septa(:,:,stimNum);
  2694. d_WT_Neigh = stimtrials_L4_WT_neigh(:,:,stimNum);
  2696. y1 = ones(1,size(d_WT,1));
  2697. y2 = 2*ones(1,size(d_WT_Septa,1));
  2698. y3 = 3*ones(1,size(d_WT_Neigh,1));
  2700. labelVector = repelem([{'Barrel'}, {'Septa'}, {'Neighbor'}],...
  2701. [size(d_WT,1) size(d_WT_Septa,1) size(d_WT_Neigh,1)])';
  2703. Y = labelVector;
  2704. X = [d_WT; d_WT_Septa; d_WT_Neigh];
  2706. tmp = templateEnsemble('GentleBoost',100,templateTree('surrogate','on'));
  2707. opt = statset('UseParallel',true);
  2708. ecoc = fitcecoc(X,Y,'Coding','onevsall','Learners',tmp,...
  2709. 'Prior','uniform','Options',opt);
  2710. cvecoc = crossval(ecoc,'Options',opt);
  2711. Yhat = kfoldPredict(cvecoc,'Options',opt);
  2713. figure;
  2714. ConfMat = confusionchart(Y,Yhat,'Title',sprintf('Pulse Number: %d',stimNum), ...
  2715. 'RowSummary','row-normalized', ...
  2716. 'ColumnSummary','column-normalized');
  2717. ConfMat.InnerPosition = [0.20 0.15 0.75 0.75];
  2718. ConfMat.FontSize = 24;
  2720. saveas(gcf, fullfile(saveFolder,sprintf('L4_WT_BSN_Decode_%d.png',stimNum),"Resolution",600));
  2721. close all;
  2723. allPred_WT_L4(:,:,stimNum) = confusionmat(Y,Yhat);
  2724. end
  2726. allPred_KO_L4 = [];
  2727. for stimNum = 1:20
  2728. d_WT = stimtrials_L4_KO(:,:,stimNum);
  2729. d_WT_Septa = stimtrials_L4_KO_septa(:,:,stimNum);
  2730. d_WT_Neigh = stimtrials_L4_KO_neigh(:,:,stimNum);
  2732. y1 = ones(1,size(d_WT,1));
  2733. y2 = 2*ones(1,size(d_WT_Septa,1));
  2734. y3 = 3*ones(1,size(d_WT_Neigh,1));
  2736. labelVector = repelem([{'Barrel'}, {'Septa'}, {'Neighbor'}],...
  2737. [size(d_WT,1) size(d_WT_Septa,1) size(d_WT_Neigh,1)])';
  2739. Y = labelVector;
  2740. X = [d_WT; d_WT_Septa; d_WT_Neigh];
  2742. tmp = templateEnsemble('GentleBoost',100,templateTree('surrogate','on'));
  2743. opt = statset('UseParallel',true);
  2744. ecoc = fitcecoc(X,Y,'Coding','onevsall','Learners',tmp,...
  2745. 'Prior','uniform','Options',opt);
  2746. cvecoc = crossval(ecoc,'Options',opt);
  2747. Yhat = kfoldPredict(cvecoc,'Options',opt);
  2749. figure;
  2750. ConfMat = confusionchart(Y,Yhat,'Title',sprintf('Pulse Number: %d',stimNum), ...
  2751. 'RowSummary','row-normalized', ...
  2752. 'ColumnSummary','column-normalized');
  2753. ConfMat.InnerPosition = [0.20 0.15 0.75 0.75];
  2754. ConfMat.FontSize = 24;
  2756. saveas(gcf, fullfile(saveFolder,sprintf('L4_KO_BSN_Decode_%d.png',stimNum),"Resolution",600));
  2757. close all;
  2759. allPred_KO_L4(:,:,stimNum) = confusionmat(Y,Yhat);
  2760. end
  2762. allPred_WT_L5 = [];
  2763. for stimNum = 1:20
  2764. d_WT = stimtrials_L5_WT(:,:,stimNum);
  2765. d_WT_Septa = stimtrials_L5_WT_septa(:,:,stimNum);
  2766. d_WT_Neigh = stimtrials_L5_WT_neigh(:,:,stimNum);
  2768. y1 = ones(1,size(d_WT,1));
  2769. y2 = 2*ones(1,size(d_WT_Septa,1));
  2770. y3 = 3*ones(1,size(d_WT_Neigh,1));
  2772. labelVector = repelem([{'Barrel'}, {'Septa'}, {'Neighbor'}],...
  2773. [size(d_WT,1) size(d_WT_Septa,1) size(d_WT_Neigh,1)])';
  2775. Y = labelVector;
  2776. X = [d_WT; d_WT_Septa; d_WT_Neigh];
  2778. tmp = templateEnsemble('GentleBoost',100,templateTree('surrogate','on'));
  2779. opt = statset('UseParallel',true);
  2780. ecoc = fitcecoc(X,Y,'Coding','onevsall','Learners',tmp,...
  2781. 'Prior','uniform','Options',opt);
  2782. cvecoc = crossval(ecoc,'Options',opt);
  2783. Yhat = kfoldPredict(cvecoc,'Options',opt);
  2785. figure;
  2786. ConfMat = confusionchart(Y,Yhat,'Title',sprintf('Pulse Number: %d',stimNum), ...
  2787. 'RowSummary','row-normalized', ...
  2788. 'ColumnSummary','column-normalized');
  2789. ConfMat.InnerPosition = [0.20 0.15 0.75 0.75];
  2790. ConfMat.FontSize = 24;
  2792. saveas(gcf, fullfile(saveFolder,sprintf('L5_WT_BSN_Decode_%d.png',stimNum),"Resolution",600));
  2793. close all;
  2795. allPred_WT_L5(:,:,stimNum) = confusionmat(Y,Yhat);
  2796. end
  2798. allPred_KO_L5 = [];
  2799. for stimNum = 1:20
  2800. d_WT = stimtrials_L5_KO(:,:,stimNum);
  2801. d_WT_Septa = stimtrials_L5_KO_septa(:,:,stimNum);
  2802. d_WT_Neigh = stimtrials_L5_KO_neigh(:,:,stimNum);
  2804. y1 = ones(1,size(d_WT,1));
  2805. y2 = 2*ones(1,size(d_WT_Septa,1));
  2806. y3 = 3*ones(1,size(d_WT_Neigh,1));
  2808. labelVector = repelem([{'Barrel'}, {'Septa'}, {'Neighbor'}],...
  2809. [size(d_WT,1) size(d_WT_Septa,1) size(d_WT_Neigh,1)])';
  2811. Y = labelVector;
  2812. X = [d_WT; d_WT_Septa; d_WT_Neigh];
  2814. tmp = templateEnsemble('GentleBoost',100,templateTree('surrogate','on'));
  2815. opt = statset('UseParallel',true);
  2816. ecoc = fitcecoc(X,Y,'Coding','onevsall','Learners',tmp,...
  2817. 'Prior','uniform','Options',opt);
  2818. cvecoc = crossval(ecoc,'Options',opt);
  2819. Yhat = kfoldPredict(cvecoc,'Options',opt);
  2821. figure;
  2822. ConfMat = confusionchart(Y,Yhat,'Title',sprintf('Pulse Number: %d',stimNum), ...
  2823. 'RowSummary','row-normalized', ...
  2824. 'ColumnSummary','column-normalized');
  2825. ConfMat.InnerPosition = [0.20 0.15 0.75 0.75];
  2826. ConfMat.FontSize = 24;
  2828. saveas(gcf, fullfile(saveFolder,sprintf('L5_KO_BSN_Decode_%d.png',stimNum),"Resolution",600));
  2829. close all;
  2831. allPred_KO_L5(:,:,stimNum) = confusionmat(Y,Yhat);
  2832. end
  2835. figure , plot(allPred_WT_L23(:));
  2836. hold on, plot(allPred_KO_L23(:));
  2838. figure; hold on;
  2839. for i = 1:9
  2840. plot(allPred_WT_L23(i,:));
  2841. end
  2843. figure , plot(squeeze(allPred_WT_L23(1,1,:))/allPred_WT_L23(1,1,1),'Color',colorBarrel,'LineWidth',3);
  2844. hold on, plot(squeeze(allPred_WT_L23(2,2,:))/allPred_WT_L23(2,2,1),'Color',colorNeigh ,'LineWidth',3);
  2845. hold on, plot(squeeze(allPred_WT_L23(3,3,:))/allPred_WT_L23(3,3,1),'Color',colorSepta ,'LineWidth',3);
  2847. figure , plot(squeeze(allPred_KO_L23(1,1,:))/allPred_KO_L23(1,1,1),'Color',colorBarrelKO,'LineWidth',3);
  2848. hold on, plot(squeeze(allPred_KO_L23(2,2,:))/allPred_KO_L23(2,2,1),'Color',colorNeighKO ,'LineWidth',3);
  2849. hold on, plot(squeeze(allPred_KO_L23(3,3,:))/allPred_KO_L23(3,3,1),'Color',colorSeptaKO ,'LineWidth',3);
  2850. %%
  2855. [Y2, scores] = kfoldPredict(cvecoc,'Options',opt);
  2857. %% plot ROCs
  2859. figure; hold on;
  2860. for i = 1:length(ecoc.ClassNames)
  2861. [xr, yr, ~, auc] = perfcurve(Y2,scores(:, i), ecoc.ClassNames(i));
  2862. auc
  2863. plot(xr, yr, 'linewidth', 1);
  2864. legends{i} = sprintf('AUC for %s class: %.3f', ecoc.ClassNames(i), auc);
  2865. end
  2867. legend(legends, 'location', 'southeast')
  2868. line([0 1], [0 1], 'linestyle', ':', 'color', 'k');
  2869. xlabel('FPR'), ylabel('TPR')
  2870. title('ROC for Iris Classification (1 vs Others)')
  2871. axis square
  2873. [~,score_nb] = resubPredict(ecoc);
  2874. mdlSVM = fitPosterior(ecoc);
  2875. [Xnb,Ynb,Tnb,AUCnb] = perfcurve(Y,score_nb(:,ecoc.ClassNames),'true');
  2877. [X,Y,T,AUC] = perfcurve(species(51:end,:),scores,'virginica');
  2879. figure , plot(squeeze(allPred_WT(1,1,:)),'Color',colorBarrel,'LineWidth',3);
  2880. hold on, plot(squeeze(allPred_WT(2,2,:)),'Color',colorSepta,'LineWidth',3);
  2881. hold on, plot(squeeze(allPred_WT(3,3,:)),'Color',colorNeigh,'LineWidth',3);
  2883. figure , plot(squeeze(allPred_KO(1,1,:)),'Color',colorBarrelKO,'LineWidth',3);
  2884. hold on, plot(squeeze(allPred_KO(2,2,:)),'Color',colorSeptaKO,'LineWidth',3);
  2885. hold on, plot(squeeze(allPred_KO(3,3,:)),'Color',colorNeighKO,'LineWidth',3);
  2886. %%
  2887. figure , plot(squeeze(mean(norm_stimtrials_L23_WT(:,:,1),1)),'LineWidth',2);
  2888. hold on, plot(squeeze(mean(norm_stimtrials_L23_WT_septa(:,:,1),1)),'LineWidth',2);
  2889. hold on, plot(squeeze(mean(norm_stimtrials_L23_WT_neigh(:,:,1),1)),'LineWidth',2);
  2891. figure , plot(squeeze(mean(norm_stimtrials_L23_WT(:,:,2),1)),'LineWidth',2);
  2892. hold on, plot(squeeze(mean(norm_stimtrials_L23_WT_septa(:,:,2),1)),'LineWidth',2);
  2893. hold on, plot(squeeze(mean(norm_stimtrials_L23_WT_neigh(:,:,2),1)),'LineWidth',2);
  2895. figure , plot(squeeze(mean(norm_stimtrials_L23_KO(:,:,1),1)),'LineWidth',2);
  2896. hold on, plot(squeeze(mean(norm_stimtrials_L23_KO_septa(:,:,1),1)),'LineWidth',2);
  2897. hold on, plot(squeeze(mean(norm_stimtrials_L23_KO_neigh(:,:,1),1)),'LineWidth',2);
  2899. figure , plot(squeeze(mean(norm_stimtrials_L23_KO(:,:,2),1)),'LineWidth',2);
  2900. hold on, plot(squeeze(mean(norm_stimtrials_L23_KO_septa(:,:,2),1)),'LineWidth',2);
  2901. hold on, plot(squeeze(mean(norm_stimtrials_L23_KO_neigh(:,:,2),1)),'LineWidth',2);
  2902. %%
  2904. figure , imagesc(squeeze(mean(norm_stimtrials_L23_WT,1))',[0 0.5]); colormap hot;
  2905. hold on, imagesc(squeeze(mean(norm_stimtrials_L23_WT_septa,1))',[0 0.5]); colormap hot;
  2906. hold on, imagesc(squeeze(mean(norm_stimtrials_L23_WT_neigh,1))',[0 0.5]); colormap hot;
  2908. figure, imagesc(squeeze(mean(norm_stimtrials_L23_KO,1))'-squeeze(mean(norm_stimtrials_L23_WT,1))',[-0.25 0.25]); colormap hot;
  2909. figure, imagesc(squeeze(mean(norm_stimtrials_L4_KO,1))'-squeeze(mean(norm_stimtrials_L4_WT,1))',[-0.25 0.25]); colormap hot;
  2910. figure, imagesc(squeeze(mean(norm_stimtrials_L5_KO,1))'-squeeze(mean(norm_stimtrials_L5_WT,1))',[-0.25 0.25]); colormap hot;
  2912. figure, imagesc((squeeze(mean(norm_stimtrials_L23_KO,1))'-squeeze(mean(norm_stimtrials_L23_WT,1))')...
  2913. -(squeeze(mean(norm_stimtrials_L4_KO,1))'-squeeze(mean(norm_stimtrials_L4_WT,1))'),[-0.25 0.25]); colormap hot;
  2915. gprMdl = fitrgp((1:96)',squeeze(mean(norm_stimtrials_L23_KO(:,:,1),1)),'Basis','linear',...
  2916. 'FitMethod','exact','PredictMethod','exact');
  2918. ypred = resubPredict(gprMdl);
  2919. figure;
  2920. plot(1:96,squeeze(mean(norm_stimtrials_L23_KO(:,:,1),1))','b.');
  2921. hold on;
  2922. plot(1:96,ypred,'r','LineWidth',1.5);

Source Code 3.m, no license · at the source

Overview

Authors: Ali Özgür Argunşah1,2, Tevye Jason Stachniak1,2,3, Jenq-Wei Yang1,2, Linbi Cai1,2, Alexander van der Bourg1,2, Rahel Kastli1,2,4, Theofanis Karayannis1,2,5
ORCID iDs: Ali Özgür Argunşah, Tevye Jason Stachniak, Linbi Cai, Rahel Kastli, Theofanis Karayannis
  1. Laboratory of Neural Circuit Assembly, Brain Research Institute, University of Zurich Winterthurerstrasse, Zurich, Switzerland
  2. Neuroscience Center Zurich, University of Zurich and ETH Zurich, Winterthurerstrasse, Zurich, Switzerland
  3. Division of Biomedical Sciences, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Canada
  4. Department of Stem Cell & Regenerative Biology, Harvard University, Cambridge, United States
  5. University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zurich, Switzerland
Institutions: University of Zurich (Switzerland); ETH Zurich (Switzerland); Memorial University of Newfoundland (Canada); Harvard University (United States)
Journal: eLife, volume 14, article RP107099
Dates: published online 18 August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.7554/elife.107099 · PMID 42610441 · PMCID PMC13485306 · OpenAlex W4411340734
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.7554/elife.107099.3
Status: code verified
Categories: mouse (organism), systems (subfield)
Methods: Spectral & time-frequency, Statistics, Smoothing, state filtering, decompositions, Machine learning, Evoked potentials, fMRI & imaging, Single-unit activity, calcium imaging
Keywords: Mouse
MeSH: Somatosensory Cortex*, Touch Perception*, Vibrissae*, Animals, Interneurons, Mice, Mice, Knockout (* major topic)
Topic: Neural dynamics and brain function (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: European Research Council (10.3030/679175, 679175); Swiss National Science Foundation (S-41260-01-01)
Citations: cited by 1 paper (Europe PMC); 80 references in the paper
Research resources: C57BL6J RRID:IMSR_JAX:000664, Ai14 RRID:IMSR_JAX:007914, VIP-IRES-Cre RRID:IMSR_JAX:010908, SST-IRES-Cre RRID:IMSR_JAX:013044, MATLAB RRID:SCR_001622, Fiji RRID:SCR_002285, Imaris RRID:SCR_007370, Icy RRID:SCR_010587, ScanImage RRID:SCR_014307, MC Rack RRID:SCR_014955, Agarose (type III-A) RRID:SCR_028585

Abstract

Mice, like humans, enhance tactile perception through repeated sampling of spatially segregated sensory inputs. In the whisker system, individual whisker identity is preserved along the whisker-brainstem-thalamus-cortex pathway, culminating in distinct cortical domains: barrels and septa. Using simultaneous in vivo recordings from barrel and septal domains, we identify a progressive divergence in spiking activity during repeated single- and multi-whisker stimulation. While the multi- to single-whisker response ratio remains stable in barrels, it increases progressively in septa, suggesting recruitment of local inhibitory circuits. Genetic fate mapping and tissue clearing revealed distinct laminar and regional distributions of SST+ and VIP+ interneurons in barrel and septal domains. Calcium imaging showed that both interneuron types respond to whisker stimulation, but SST+ interneurons were preferentially recruited during repeated multi-whisker stimulation. Deletion of Elfn1, a regulator of excitatory synaptic dynamics onto SST+ interneurons, abolished the progressive increase in septal multi- to single-whisker response ratios. Temporal decoding analyses further demonstrated a loss of barrel-septa functional segregation in Elfn1 knockout mice. Finally, viral tracing combined with whole-brain clearing revealed distinct projection patterns from barrels and septa to secondary somatosensory (S2) and motor (M1) cortices. Together, these findings support a model in which Elfn1-dependent recruitment of SST+ interneurons contributes to preferential multi-whisker integration and functional specialization within the mouse somatosensory cortex.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Tools: Statistics and Machine Learning Toolbox (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
1 file
At the source: pmc-oa-opendata.s3.amazonaws.com/PMC13485306.1/elife-107099-code6.zip

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 5 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 5 scripts, each with its path and the digest of its content;
  • 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

All data generated and analyzed during this study are available in the Dryad Digital Repository at https://doi.org/10.5061/dryad.4qrfj6qt8. Custom MATLAB scripts used for data processing, statistical analysis, decoding, and figure generation are provided as Supplementary Source Code files.

The following dataset was generated:

Argunşah A, Stachniak T, Yang J, Cai L, van der Bourg A, Kastli R, Karayannis T. 2026. Data from: Local inhibitory dynamics underpin temporal integration and functional segregation between barrels and septa in the mouse barrel cortex. Dryad Digital Repository.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 7 authors, 1 keyword, 7 MeSH terms, 2 funders, 80 references, 11 RRIDs.

Cite

This paper

Argunşah, A. Ö., Stachniak, T. J., Yang, J.-W., Cai, L., van der Bourg, A., Kastli, R., & Karayannis, T. (2026). Local inhibitory dynamics underpin temporal integration and functional segregation between barrels and septa in the mouse barrel cortex. eLife, 14, RP107099. https://doi.org/10.7554/elife.107099

BibTeX

@article{argunsah2026local,
author = {Argunşah, Ali Özgür and Stachniak, Tevye Jason and Yang, Jenq-Wei and Cai, Linbi and van der Bourg, Alexander and Kastli, Rahel and Karayannis, Theofanis},
title = {{Local inhibitory dynamics underpin temporal integration and functional segregation between barrels and septa in the mouse barrel cortex}},
journal = {eLife},
year = {2026},
month = aug,
volume = {14},
pages = {RP107099},
publisher = {eLife Sciences Publications, Ltd},
issn = {2050-084X},
doi = {10.7554/elife.107099},
url = {https://doi.org/10.7554/elife.107099},
pmid = {42610441},
pmcid = {PMC13485306}
}

RIS

TY - JOUR
AU - Argunşah, Ali Özgür
AU - Stachniak, Tevye Jason
AU - Yang, Jenq-Wei
AU - Cai, Linbi
AU - van der Bourg, Alexander
AU - Kastli, Rahel
AU - Karayannis, Theofanis
TI - Local inhibitory dynamics underpin temporal integration and functional segregation between barrels and septa in the mouse barrel cortex
T2 - eLife
J2 - Elife
PY - 2026
DA - 2026/08/18
VL - 14
SP - RP107099
SN - 2050-084X
PB - eLife Sciences Publications, Ltd
DO - 10.7554/elife.107099
UR - https://doi.org/10.7554/elife.107099
LA - en
ER -

CSL-JSON

{
"id": "10.7554/elife.107099",
"type": "article-journal",
"title": "Local inhibitory dynamics underpin temporal integration and functional segregation between barrels and septa in the mouse barrel cortex",
"container-title": "eLife",
"author": [
{
"family": "Argunşah",
"given": "Ali Özgür"
},
{
"family": "Stachniak",
"given": "Tevye Jason"
},
{
"family": "Yang",
"given": "Jenq-Wei"
},
{
"family": "Cai",
"given": "Linbi"
},
{
"family": "van der Bourg",
"given": "Alexander"
},
{
"family": "Kastli",
"given": "Rahel"
},
{
"family": "Karayannis",
"given": "Theofanis"
}
],
"container-title-short": "Elife",
"volume": "14",
"page": "RP107099",
"DOI": "10.7554/elife.107099",
"PMID": "42610441",
"PMCID": "PMC13485306",
"ISSN": "2050-084X",
"publisher": "eLife Sciences Publications, Ltd",
"URL": "https://doi.org/10.7554/elife.107099",
"language": "en",
"issued": {
"date-parts": [
[
2026,
8,
18
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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