OSCR

Meta-analytic evidence for distinct neural correlates of conditioned versus verbally induced placebo analgesia.

Code ↔ Paper

6 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 6 matches · 1 of them tie a paragraph to a whole file, not to given lines: a weak match, whose lines are not tinted
  1. [1] § Methods › Data acquisition ↔ A_Import/A_create_study_overview_table.m, lines 403–467 · score 0.87 · topical cream, nasal spray, sham acupuncture, intravenous, distension, electrical
  2. [2] § Methods › Mediation analysis ↔ imaging/meta-signflip_mean_signedquantile_studymod_ctrpain.ipynb, lines 347–442 · score 0.71 · generalized Pareto distribution, tail ratio, tail approximation, goodness, flipping, fitting
  3. [3] § Methods › Mediation analysis ↔ imaging/meta-signflip_mean_signedquantile_studymod_ctrpain_sex_interaction.ipynb, lines 317–411 · score 0.71 · generalized Pareto distribution, tail ratio, tail approximation, goodness, flipping, fitting
  4. [4] § Methods › CA3: Pain signatures ↔ GIV_functions/GIV_summary.m, the whole file · a weak match · score 0.70 · confidence intervals, activation changes, brain imaging, variations, scores, correlated
  5. [5] § Results › Brain mediators of the effect of induction type on behavioral placebo analgesia ↔ imaging/sensitivity_analysis.ipynb, lines 1–42 · score 0.61 · minimal detectable, detectability thresholds, MDE maps, sign flip, sensitivity, power
  6. [6] § Methods › CA2: Conjunction analysis ↔ plot/fig_pathConjunction_studymod_ctrpain.ipynb, lines 85–114 · score 0.56 · conjunction map, Nichols, condinst, log10, discovery, thresholds

Paper

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The authors' code

MATLAB · 597 lines · 13 KB · CC0-1.0 · 1 match

  1. function A_create_study_overview_table(datapath)
  3. %% Creates an overview table for study-level information
  4. % data collected from original publications, mat-files, and personal
  5. % communication
  7. study_ID={
  8. 'atlas'
  9. 'bingel06'
  10. 'bingel11'
  11. 'choi'
  12. 'eippert'
  13. 'ellingsen'
  14. 'elsenbruch'
  15. 'freeman'
  16. 'geuter'
  17. 'kessner'
  18. 'kong06'
  19. 'kong09'
  20. 'lui'
  21. 'ruetgen'
  22. 'schenk'
  23. 'theysohn'
  24. 'wager04a_princeton'
  25. 'wager04b_michigan'
  26. 'wrobel'
  27. 'zeidan'};
  29. n=[
  30. 21 %'atlas'
  31. 19 %'bingel06'
  32. 22 %'bingel11'
  33. 15%'choi'
  34. 40 %'eippert'
  35. 28 %'ellingsen'
  36. 36 %'elsenbruch'
  37. 24 %'freeman'
  38. 40 %'geuter'
  39. 39 %'kessner'
  40. 10 %'kong06'
  41. 12 %'kong09'
  42. 31 %'lui'
  43. 102 %'ruetgen'
  44. 32 %'schenk'
  45. 30 %'theysohn'
  46. 24 %'wager04a_princeton'
  47. 23 %'wager04b_michigan'
  48. 38 %'wrobel'
  49. 17]; %'zeidan'
  51. study_dir={
  52. 'Atlas_et_al_2012' %'atlas'
  53. 'Bingel_et_al_2006' %'bingel06'
  54. 'Bingel_et_al_2011' %'bingel11'
  55. 'Choi_et_al_2011' %'choi'
  56. 'Eippert_et_al_2009' %'eippert'
  57. 'Ellingsen_et_al_2013' %'ellingsen'
  58. 'Elsenbruch_et_al_2012' %'elsenbruch'
  59. 'Freeman_et_al_2015' %'freeman'
  60. 'Geuter_et_al_2013' %'geuter'
  61. 'Kessner_et_al_201314' %kessner
  62. 'Kong_et_al_2006' %'kong06'
  63. 'Kong_et_al_2009' %'kong009'
  64. 'Lui_et_al_2010' %'lui'
  65. 'Ruetgen_et_al_2015' %'ruetgen'
  66. 'Schenk_et_al_2014' %'schenk'
  67. 'Theysohn_et_al_2014' %'theysohn'
  68. 'Wager_et_al_2004a_Princeton_shock' %'wager04a'
  69. 'Wager_et_al_2004b_Michigan_heat' %'wager04b'
  70. 'Wrobel_et_al_2014' %'wrobel14'
  71. 'Zeidan_et_al_2015'}; %'zeidan'
  73. study_design={
  74. 'within' %'atlas'
  75. 'within' %'bingel06'
  76. 'within' %'bingel11'
  77. 'within' %'choi'
  78. 'within' %'eippert'
  79. 'within' %'ellingsen'
  80. 'within' %'elsenbruch'
  81. 'within' %'freeman'
  82. 'within' %'geuter'
  83. 'between' %'kessner' (mixed design, but "between-group" in respect to placebo conditioning)
  84. 'within' %'kong06'
  85. 'within' %'kong09'
  86. 'within' %'lui'
  87. 'between' %'ruetgen'
  88. 'within' %'schenk'
  89. 'within' %'theysohn'
  90. 'within' %'wager04a_princeton'
  91. 'within' %'wager04b_michigan'
  92. 'within' %'wrobel'
  93. 'within'}; %'zeidan'
  95. img_modality={
  96. 'fMRI' %'atlas'
  97. 'fMRI' %'bingel06'
  98. 'fMRI' %'bingel11'
  99. 'fMRI' %'choi'
  100. 'fMRI' %'eippert'
  101. 'fMRI' %'ellingsen'
  102. 'fMRI' %'elsenbruch'
  103. 'fMRI' %'freeman'
  104. 'fMRI' %'geuter'
  105. 'fMRI' %'kessner'
  106. 'fMRI' %'kong06'
  107. 'fMRI' %'kong09'
  108. 'fMRI' %'lui'
  109. 'fMRI' %'ruetgen'
  110. 'fMRI' %'schenk'
  111. 'fMRI' %'theysohn'
  112. 'fMRI' %'wager04a_princeton'
  113. 'fMRI' %'wager04b_michigan'
  114. 'fMRI' %'wrobel'
  115. 'ASL'}; %'zeidan'
  117. field_strength=[
  118. 1.5 %'atlas'
  119. 1.5 %'bingel06'
  120. 3.0 %'bingel11'
  121. 3.0 %'choi'
  122. 3.0 %'eippert'
  123. 3.0 %'ellingsen'
  124. 1.5 %'elsenbruch'
  125. 3.0 %'freeman'
  126. 3.0 %'geuter'
  127. 3.0 %'kessner'
  128. 3.0 %'kong06'
  129. 3.0 %'kong09'
  130. 3.0 %'lui'
  131. 3.0 %'ruetgen'
  132. 3.0 %'schenk'
  133. 1.5 %'theysohn'
  134. 3.0 %'wager04a_princeton'
  135. 3.0 %'wager04b_michigan'
  136. 3.0 %'wrobel'
  137. 3.0]; %'zeidan'
  139. TR=[
  140. 2000 %'atlas'
  141. 2600 %'bingel06'
  142. 3000 %'bingel11'
  143. 3000 %'choi'
  144. 2620 %'eippert'
  145. 2000 %'ellingsen'
  146. 3100 %'elsenbruch'
  147. 2000 %'freeman'
  148. 2580 %'geuter'
  149. 2580 %'kessner'
  150. 2000 %'kong06'
  151. 2000 %'kong09'
  152. 3014 %'lui'
  153. 1800 %'ruetgen'
  154. 2580 %'schenk'
  155. 2400 %'theysohn'
  156. 1800 %'wager04a_princeton'
  157. 1500 %'wager04b_michigan'
  158. 2580 %'wrobel'
  159. 4000]; %'zeidan'
  161. TE=[
  162. 34 %'atlas'
  163. 40 %'bingel06'
  164. 30 %'bingel11'
  165. 30 %'choi'
  166. 26 %'eippert'
  167. 30 %'ellingsen'
  168. 50 %'elsenbruch'
  169. 40 %'freeman'
  170. 26 %'geuter'
  171. 26 %'kessner'
  172. 40 %'kong06'
  173. 40 %'kong09'
  174. 35 %'lui'
  175. 33 %'ruetgen'
  176. 26 %'schenk'
  177. 26 %'theysohn'
  178. 22 %'wager04a_princeton'
  179. 20 %'wager04b_michigan'
  180. 25 %'wrobel'
  181. 12]; %'zeidan'
  183. voxel_size_at_acq=[
  184. 3.5 3.5 4.0 %'atlas'
  185. 3.3 3.3 4.0 %'bingel06'
  186. 3.5 3.5 3.0 %'bingel11'
  187. 3.8 3.8 4.0 %'choi'
  188. 2.0 2.0 3.0 %'eippert'
  189. 3.0 3.0 3.3 %'ellingsen'
  190. 3.8 3.8 3.3 %'elsenbruch'
  191. 3.1 3.1 5.0 %'freeman'
  192. 2.0 2.0 3.0 %'geuter'
  193. 2.0 2.0 3.0 %'kessner'
  194. 3.1 3.1 5.0 %'kong06'
  195. 3.1 3.1 5.0 %'kong09'
  196. 1.9 1.9 3.5 %'lui'
  197. 1.5 1.5 2.0 %'ruetgen'
  198. 2.0 2.0 2.0 %'schenk'
  199. 2.6 2.6 3.0 %'theysohn'
  200. 3.8 3.8 5.0 %'wager04a_princeton'
  201. 3.0 3.0 4.0 %'wager04b_michigan'
  202. 2.0 2.0 3.0 %'wrobel'
  203. 3.4 3.4 6.0]; %'zeidan'
  205. voxel_size_img=[
  206. 2.0 2.0 2.0 %'atlas'
  207. 3.0 3.0 3.0 %'bingel06'
  208. 2.0 2.0 2.0 %'bingel11'
  209. 2.0 2.0 2.0 %'choi'
  210. 2.0 2.0 2.0 %'eippert'
  211. 2.0 2.0 2.0 %'ellingsen'
  212. 2.0 2.0 2.0 %'elsenbruch'
  213. 2.0 2.0 2.0 %'freeman'
  214. 2.0 2.0 2.0 %'geuter'
  215. 2.0 2.0 2.0 %'kessner'
  216. 2.0 2.0 2.0 %'kong06'
  217. 2.0 2.0 2.0 %'kong09'
  218. 2.0 2.0 2.0 %'lui'
  219. 2.0 2.0 2.0 %'ruetgen'
  220. 2.0 2.0 2.0 %'schenk'
  221. 2.0 2.0 2.0 %'theysohn'
  222. 2.0 2.0 2.0 %'wager04a_princeton'
  223. 3.75 3.75 5.0 %'wager04b_michigan'
  224. 2.0 2.0 2.0 %'wrobel'
  225. 2.0 2.0 2.0]; %'zeidan'
  227. analysis_software={
  228. 'SPM5' %'atlas'
  229. 'SPM2' %'bingel06'
  230. 'SPM5' %'bingel11'
  231. 'FSL' %'choi'
  232. 'SPM5' %'eippert'
  233. 'FSL' %'ellingsen'
  234. 'SPM5' %'elsenbruch'
  235. 'SPM8' %'freeman'
  236. 'SPM8' %'geuter'
  237. 'SPM8' %'kessner'
  238. 'SPM2' %'kong06'
  239. 'SPM2' %'kong09'
  240. 'SPM5' %'lui'
  241. 'SPM12' %'ruetgen'
  242. 'SPM8' %'schenk'
  243. 'SPM8' %'theysohn'
  244. 'SPM99' %'wager04a_princeton'
  245. 'SPM99' %'wager04b_michigan'
  246. 'SPM8' %'wrobel'
  247. 'FSL'}; %'zeidan'
  249. slice_timing_correction=[
  250. 1 %'atlas'
  251. 0 %'bingel06'
  252. 1 %'bingel11'
  253. 0 %'choi'
  254. 1 %'eippert'
  255. 0 %'ellingsen'
  256. 0 %'elsenbruch'
  257. 0 %'freeman'
  258. 0 %'geuter'
  259. 1 %'kessner'
  260. 0 %'kong06'
  261. 0 %'kong09'
  262. 1 %'lui'
  263. 1 %'ruetgen'
  264. 0 %'schenk'
  265. 0 %'theysohn'
  266. 1 %'wager04a_princeton'
  267. 1 %'wager04b_michigan'
  268. 1 %'wrobel'
  269. NaN]; %'zeidan'
  271. spatial_smoothing_FWHM=[
  272. 8 8 8 %'atlas'
  273. 8 8 8 %'bingel06'
  274. 8 8 8 %'bingel11'
  275. 5 5 5 %'choi'
  276. 8 8 8 %'eippert'
  277. 5 5 5 %'ellingsen'
  278. 9 9 9 %'elsenbruch'
  279. 8 8 8 %'freeman'
  280. 6 6 6 %'geuter'
  281. 8 8 8 %'kessner'
  282. 8 8 8 %'kong06'
  283. 8 8 8 %'kong09'
  284. 4 4 8 %'lui'
  285. 6 6 6 %'ruetgen'
  286. 6 6 6 %'schenk'
  287. 8 8 8 %'theysohn'
  288. 6 6 6 %'wager04a_princeton'
  289. 9 9 9 %'wager04b_michigan'
  290. 8 8 8 %'wrobel'
  291. 9 9 9]; %'zeidan'
  293. temporal_high_pass_filter=[
  294. 180 %'atlas'
  295. 128 %'bingel06'
  296. 128 %'bingel11'
  297. 50 %'choi'
  298. 128 %'eippert'
  299. 120 %'ellingsen'
  300. 140 %'elsenbruch'
  301. 128 %'freeman'
  302. 128 %'geuter'
  303. 128 %'kessner'
  304. 128 %'kong06'
  305. 128 %'kong09'
  306. 128 %'lui'
  307. 128 %'ruetgen'
  308. 128 %'schenk'
  309. 120 %'theysohn'
  310. 128 %'wager04a_princeton'
  311. 100 %'wager04b_michigan'
  312. 128 %'wrobel'
  313. NaN]; %'zeidan'
  315. image_type={
  316. 'beta' %'atlas'
  317. 'con' %'bingel06'
  318. 'beta' %'bingel11'
  319. 'beta' %'choi'
  320. 'con' %'eippert'
  321. 'con' %'ellingsen'
  322. 'beta' %'elsenbruch'
  323. 'con' %'freeman'
  324. 'con' %'geuter'
  325. 'beta' %'kessner'
  326. 'con' %'kong06'
  327. 'con' %'kong09'
  328. 'con' %'lui'
  329. 'con' %'ruetgen'
  330. 'beta' %'schenk'
  331. 'beta' %'theysohn'
  332. 'con' %'wager04a_princeton'
  333. 'beta' %'wager04b_michigan'
  334. 'beta' %'wrobel'
  335. 'con'}; %'zeidan'
  337. contrast_imgs_only=[
  338. 0 %'atlas'
  339. 0 %'bingel06'
  340. 0 %'bingel11'
  341. 0 %'choi'
  342. 0 %'eippert'
  343. 0 %'ellingsen'
  344. 0 %'elsenbruch'
  345. 0 %'freeman'
  346. 0 %'geuter'
  347. 0 %'kessner'
  348. 0 %'kong06'
  349. 0 %'kong09'
  350. 0 %'lui'
  351. 0 %'ruetgen'
  352. 0 %'schenk'
  353. 0 %'theysohn'
  354. 1 %'wager04a_princeton'
  355. 0 %'wager04b_michigan'
  356. 0 %'wrobel'
  357. 1]; %'zeidan'
  359. modeled_stimulus_duration={
  360. 14.2 %'atlas'
  361. 0.0 %'bingel06'
  362. 6.0 %'bingel11'
  363. 15.0 %'choi'
  364. [10.0, 10.0] %'eippert' early+late
  365. 10.0 %'ellingsen'
  366. 31.0 %'elsenbruch'
  367. 7.0 %'freeman'
  368. [10.0, 10.0] %'geuter' early+late
  369. [10.0, 10.0] %'kessner' early+late
  370. 5.0 %'kong06'
  371. 7.0 %'kong09'
  372. 0 %'lui'
  373. 4.4 %'ruetgen'
  374. 20.0 %'schenk'
  375. 16.8 %'theysohn'
  376. 20.0 %'wager04a_princeton'
  377. 6.0 %'wager04b_michigan'
  378. [10.0, 10.0] %'wrobel'
  379. 12.0}; %'zeidan'
  381. stimulus_duration=[
  382. 10 %'atlas'
  383. 0.001 %'bingel06'
  384. 6 %'bingel11'
  385. 15 %'choi'
  386. 17 %'eippert'
  387. 10 %'ellingsen'
  388. 31 %'elsenbruch'
  389. 7 %'freeman'
  390. 16 %'geuter'
  391. 16 %'kessner'
  392. 5 %'kong06'
  393. 12 %'kong09'
  394. 0.005 %'lui'
  395. 0.5 %'ruetgen'
  396. 20 %'schenk'
  397. 16.8 %'theysohn'
  398. 6 %'wager04a_princeton'
  399. 17 %'wager04b_michigan'
  400. 17 %'wrobel'
  401. 12]; %'zeidan'
  403. stim_type={
  404. 'contact heat' %'atlas'
  405. 'laser' %'bingel06'
  406. 'contact heat' %'bingel11'
  407. 'electrical' %'choi'
  408. 'contact heat' %'eippert'
  409. 'contact heat' %'ellingsen'
  410. 'rectal distension' %'elsenbruch'
  411. 'contact heat' %'freeman'
  412. 'contact heat' %'geuter'
  413. 'contact heat' %'kessner'
  414. 'contact heat' %'kong06'
  415. 'contact heat' %'kong09'
  416. 'laser' %'lui'
  417. 'electrical' %'ruetgen'
  418. 'capsaicin & contact heat' %'schenk'
  419. 'rectal distension' %'theysohn'
  420. 'electrical' %'wager04a_princeton'
  421. 'contact heat' %'wager04b_michigan'
  422. 'contact heat' %'wrobel'
  423. 'contact heat'}; %'zeidan'
  425. stim_location={
  426. 'L forearm (v)' %'atlas'
  427. 'L & R hand (d)' %'bingel06'
  428. 'R calf (d)' %'bingel11'
  429. 'L hand (d)' %'choi'
  430. 'L forearm (v)' %'eippert'
  431. 'L forearm (d)' %'ellingsen'
  432. 'C rectal' %'elsenbruch'
  433. 'R forearm (v)' %'freeman'
  434. 'L forearm (v)' %'geuter'
  435. 'L forearm (v)' %'kessner'
  436. 'R forearm (v)' %'kong06'
  437. 'R forearm (v)' %'kong09'
  438. 'L or R foot (d)' %'lui'
  439. 'L hand (d)' %'ruetgen'
  440. 'L & R forearm (v)' %'schenk'
  441. 'C rectal' %'theysohn'
  442. 'R forearm (v)' %'wager04a_princeton'
  443. 'L forearm (v)' %'wager04b_michigan'
  444. 'L forearm (v)' %'wrobel'
  445. 'R leg (d)'}; %'zeidan'
  447. placebo_form={
  448. 'intravenous drip' %'atlas'
  449. 'topical cream/gel/patch' %'bingel06'
  450. 'intravenous drip' %'bingel11'
  451. 'intravenous drip' %'choi'
  452. 'topical cream/gel/patch' %'eippert'
  453. 'nasal spray' %'ellingsen'
  454. 'intravenous drip' %'elsenbruch'
  455. 'topical cream/gel/patch' %'freeman'
  456. 'topical cream/gel/patch' %'geuter'
  457. 'topical cream/gel/patch' %'kessner'
  458. 'sham acupuncture' %'kong06'
  459. 'sham acupuncture' %'kong09'
  460. 'sham TENS' %'lui'
  461. 'pill' %'ruetgen'
  462. 'topical cream/gel/patch' %'schenk'
  463. 'intravenous drip' %'theysohn'
  464. 'topical cream/gel/patch' %'wager04a_princeton'
  465. 'topical cream/gel/patch' %'wager04b_michigan'
  466. 'topical cream/gel/patch' %'wrobel'
  467. 'topical cream/gel/patch'}; %'zeidan'
  469. placebo_induction={
  470. 'suggestions' %'atlas'
  471. 'suggestions & conditioning' %'bingel06'
  472. 'suggestions & conditioning' %'bingel11'
  473. 'suggestions & conditioning' %'choi'
  474. 'suggestions & conditioning' %'eippert'
  475. 'suggestions' %'ellingsen'
  476. 'suggestions' %'elsenbruch'
  477. 'suggestions & conditioning' %'freeman'
  478. 'suggestions & conditioning' %'geuter'
  479. 'conditioning' %'kessner' >> within group also suggestions, but the between group contrast only involves conditioning differences
  480. 'suggestions & conditioning' %'kong06'
  481. 'suggestions & conditioning' %'kong09'
  482. 'suggestions & conditioning' %'lui'
  483. 'suggestions & conditioning' %'ruetgen'
  484. 'suggestions' %'schenk'
  485. 'suggestions' %'theysohn'
  486. 'suggestions' %'wager04a_princeton'
  487. 'suggestions & conditioning' %'wager04b_michigan'
  488. 'suggestions & conditioning' %'wrobel'
  489. 'suggestions & conditioning'}; %'zeidan'
  491. contrast_ratings_only=[
  492. 0 %'atlas'
  493. 0 %'bingel06'
  494. 0 %'bingel11'
  495. 0 %'choi'
  496. 0 %'eippert'
  497. 0 %'ellingsen'
  498. 0 %'elsenbruch'
  499. 0 %'freeman'
  500. 0 %'geuter'
  501. 0 %'kessner'
  502. 0 %'kong06'
  503. 0 %'kong09'
  504. 0 %'lui'
  505. 0 %'ruetgen'
  506. 0 %'schenk'
  507. 0 %'theysohn'
  508. 1 %'wager04a_princeton'
  509. 1 %'wager04b_michigan'
  510. 0 %'wrobel'
  511. 1]; %'zeidan'
  513. excluded_conservative_sample=logical([
  514. 0 %'atlas'
  515. 0 %'bingel06'
  516. 1 %'bingel11' due to fixed testing sequence of placebo and control
  517. 0 %'choi'
  518. 0 %'eippert'
  519. 0 %'ellingsen'
  520. 0 %'elsenbruch'
  521. 0 %'freeman'
  522. 0 %'geuter'
  523. 0 %'kessner'
  524. 1 %'kong06' due to missing data
  525. 0 %'kong09'
  526. 0 %'lui'
  527. 1 %'ruetgen' due to placebo responder selection
  528. 0 %'schenk'
  529. 0 %'theysohn'
  530. 0 %'wager04a_princeton'
  531. 1 %'wager04b_michigan' due to placebo responder selection
  532. 0 %'wrobel'
  533. 1]); %'zeidan' due to missing subjects and since this is the only ASL study
  535. study_citations={
  536. 'Atlas et al. 2012:';...
  537. 'Bingel et al. 2006:';...
  538. 'Bingel et al. 2011:';...
  539. 'Choi et al. 2011:';...
  540. 'Eippert et al. 2009:';...
  541. 'Ellingsen et al. 2013:';...
  542. 'Elsenbruch et al. 2012:';...
  543. 'Freeman et al. 2015:';...
  544. 'Geuter et al. 2013:';...
  545. 'Kessner et al. 2014:';...
  546. 'Kong et al. 2006:';...
  547. 'Kong et al. 2009:';...
  548. 'Lui et al. 2010';...
  549. 'Ruetgen et al. 2015:';...
  550. 'Schenk et al. 2015:';...
  551. 'Theysohn et al. 2009:';...
  552. 'Wager et al. 2004, Study 1:';...
  553. 'Wager et al. 2004, Study 2:';...
  554. 'Wrobel et al. 2014:';...
  555. 'Zeidan et al. 2015:';...
  556. };
  558. study_citations_conservative={
  559. 'Atlas et al. 2012:';...
  560. 'Bingel et al. 2006:';...
  561. 'Bingel et al. 2011:*';...
  562. 'Choi et al. 2011:';...
  563. 'Eippert et al. 2009:';...
  564. 'Ellingsen et al. 2013:';...
  565. 'Elsenbruch et al. 2012:';...
  566. 'Freeman et al. 2015:';...
  567. 'Geuter et al. 2013:';...
  568. 'Kessner et al. 2014:';...
  569. 'Kong et al. 2006:**';...
  570. 'Kong et al. 2009:';...
  571. 'Lui et al. 2010:';...
  572. 'Ruetgen et al. 2015:***'
  573. 'Schenk et al. 2015:'
  574. 'Theysohn et al. 2009:';...
  575. 'Wager et al. 2004, Study 1:';...
  576. 'Wager et al. 2004, Study 2:***';...
  577. 'Wrobel et al. 2014:'
  578. 'Zeidan et al. 2015:**';...
  579. };
  580. %* excluded due to fixed testing sequence
  581. %** excluded due to incomplete data-set
  582. %*** excluded due to pre-selection of placebo responders.
  585. raw=cell(length(study_ID),1); %placeholder for image data-tables
  587. df=table(study_ID,study_dir,n,study_design,...
  588. img_modality,field_strength,TR,TE,voxel_size_at_acq,...
  589. voxel_size_img,slice_timing_correction,temporal_high_pass_filter,spatial_smoothing_FWHM,...
  590. contrast_imgs_only,image_type,analysis_software,...
  591. modeled_stimulus_duration,stimulus_duration,stim_type,stim_location,...
  592. placebo_form, placebo_induction,contrast_ratings_only,...
  593. raw, excluded_conservative_sample, study_citations,...
  594. study_citations_conservative);
  596. save(fullfile(datapath,'data_frame.mat'), 'df');
  597. end

A_create_study_overview_table.m at commit 0f0467a, under CC0-1.0 · at the source

Overview

Authors: Tamas Spisak1, Helena Hartmann1,2, Matthias Zunhammer2, Balint Kincses1,2, Katja Wiech2,3, Tor D Wager4, Ulrike Bingel1,2
ORCID iDs: Tamas Spisak, Helena Hartmann, Matthias Zunhammer, Balint Kincses, Tor D Wager, Ulrike Bingel
  1. Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital Essen, Essen, Germany
  2. Department of Neurology, University Hospital Essen, Essen, Germany
  3. Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
  4. Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH USA
Institutions: Essen University Hospital (Germany); University of Oxford (United Kingdom); Wellcome Centre for Integrative Neuroimaging (United Kingdom); Dartmouth College (United States)
Journal: Nature communications, volume 17, issue 1, article 6538
Dates: received 20 May 2025; accepted 12 June 2026; published online 17 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41467-026-74743-0 · PMID 42469238 · PMCID PMC13379574 · OpenAlex W7169528866
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), pain (population)
Methods: Statistics
Keywords: Perception, Prefrontal cortex, Sensory processing, Classical conditioning
MeSH: Analgesia*, Brain*, Conditioning, Classical*, Pain*, Brain Mapping, Conditioning, Psychological, Humans, Magnetic Resonance Imaging, Placebo Effect (* major topic)
Topic: Pain Management and Placebo Effect (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: NIMH NIH HHS (R37 MH076136); Deutsche Forschungsgemeinschaft (German Research Foundation) (422744262 - TRR 289)
Citations: not cited yet (Europe PMC); 71 references in the paper

Abstract

Placebo analgesia demonstrates that belief and expectation can significantly alter pain, even without active treatment. Placebo analgesia can be induced through verbal suggestion, classical conditioning, or their combination, though the role of conditioned neural responses above and beyond effects of verbal instructions remains unclear. We conduct a systematic meta-analysis of individual participant data from 16 within-participant placebo neuroimaging studies (n = 409), employing univariate and multivariate analyses to identify shared and distinct mechanisms of placebo analgesia induced by suggestions alone versus suggestions combined with conditioning. Both techniques increase activity during pain in the dorsolateral prefrontal and inferior parietal cortices and decrease activation in the insula, putamen, and primary sensory areas. Adding conditioning enhances engagement of regions associated with context representation and pain modulation (e.g., dorsolateral/dorsomedial prefrontal cortices) and decreases in nociceptive regions (e.g., primary sensory and insular areas). Conditioning also strengthens the negative association between analgesia and nociceptive activity, as quantified by the Neurologic Pain Signature. Combining conditioning with instructions yields greater placebo analgesia, mediated by increased ventromedial prefrontal and dorsal caudate activity, alongside decreased sensory-nociceptive and cerebellar activity. These findings suggest the two strategies rely on partially distinct mechanisms in the brain.

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

Repositories

Its files are read in the Code ↔ Paper reader above, with 6 matches between paragraphs and lines of code.

pni-lab/placebo-conditioning-meta-analysis

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 475672df1e6156eb10b6d0d755e5901ae09a9460, 18 February 2026
Languages: Jupyter (29), MATLAB (6)
Size: 84 files, 35 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, license file, environment (requirements.txt), 29 notebooks
Not found: CITATION.cff, tests, continuous integration, documentation
Tools: NumPy (28 files), Matplotlib (27 files), pandas (26 files), seaborn (24 files), NiBabel (23 files), SciPy (23 files), Nilearn (17 files), scikit-learn (7 files), statsmodels (7 files), NetworkX (3 files), Statistics and Machine Learning Toolbox (2 files), Pingouin (2 files), Image Processing Toolbox (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
37 files
At the source: github.com/pni-lab/placebo-conditioning-meta-analysis

Zenodo 18837986

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
At the source:

mzunhammer/PlaceboImagingMetaAnalysis

License: CC0-1.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 0f0467a771ef58f6b674f9b57df9172f751e71ef, 11 April 2019
Languages: MATLAB (199), R (1)
Size: 263 files, 200 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (43 files), SPM (41 files), Image Processing Toolbox (2 files), FSL (1 file), ggplot2 (1 file), lme4 (1 file), lmerTest (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
202 files
At the source: github.com/mzunhammer/PlaceboImagingMetaAnalysis

Code availability

Analysis code for carrying out data cleaning is available at: https://github.com/mzunhammer/PlaceboImagingMetaAnalysis. The complete code for reproducing the analyses and figures presented in the manuscript are available at: https://github.com/pni-lab/placebo-conditioning-meta-analysis10.5281/zenodo.18837986).

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

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:

  • 3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 235 scripts, each with its path and the digest of its content;
  • 6 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

No dataset and no data link were found in the paper.

Data Availability Statement

The derivative/summary data generated in this study are publicly available on GitHub (https://github.com/pni-lab/placebo-conditioning-meta-analysis; 10.5281/zenodo.18837986). Individual-level raw data included in this meta-analysis are available only under restricted access due to legal and ethical constraints linked to the original studies (including participant-consent and ethics-approval limits). Access may be requested by contacting and providing a detailed description of the planned scientific research, including any reproducibility analyses. A response to data requests will be provided within 4 weeks. Upon approval of the proposed research plan, data may be shared under a data-use agreement.

Analysis code for carrying out data cleaning is available at: https://github.com/mzunhammer/PlaceboImagingMetaAnalysis. The complete code for reproducing the analyses and figures presented in the manuscript are available at: https://github.com/pni-lab/placebo-conditioning-meta-analysis10.5281/zenodo.18837986).

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, issue, pages, dates, 7 authors, 4 keywords, 9 MeSH terms, 2 funders, 67 references.

Cite

This paper

Spisak, T., Hartmann, H., Zunhammer, M., Kincses, B., Wiech, K., Wager, T. D., & Bingel, U. (2026). Meta-analytic evidence for distinct neural correlates of conditioned versus verbally induced placebo analgesia. Nature communications, 17(1), 6538. https://doi.org/10.1038/s41467-026-74743-0

BibTeX

@article{spisak2026meta,
author = {Spisak, Tamas and Hartmann, Helena and Zunhammer, Matthias and Kincses, Balint and Wiech, Katja and Wager, Tor D and Bingel, Ulrike},
title = {{Meta-analytic evidence for distinct neural correlates of conditioned versus verbally induced placebo analgesia}},
journal = {Nature communications},
year = {2026},
month = jul,
volume = {17},
number = {1},
pages = {6538},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-74743-0},
url = {https://doi.org/10.1038/s41467-026-74743-0},
pmid = {42469238},
pmcid = {PMC13379574}
}

RIS

TY - JOUR
AU - Spisak, Tamas
AU - Hartmann, Helena
AU - Zunhammer, Matthias
AU - Kincses, Balint
AU - Wiech, Katja
AU - Wager, Tor D
AU - Bingel, Ulrike
TI - Meta-analytic evidence for distinct neural correlates of conditioned versus verbally induced placebo analgesia
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/07/17
VL - 17
IS - 1
SP - 6538
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-74743-0
UR - https://doi.org/10.1038/s41467-026-74743-0
LA - en
ER -

CSL-JSON

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"id": "10.1038/s41467-026-74743-0",
"type": "article-journal",
"title": "Meta-analytic evidence for distinct neural correlates of conditioned versus verbally induced placebo analgesia",
"container-title": "Nature communications",
"author": [
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"family": "Spisak",
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"issue": "1",
"page": "6538",
"DOI": "10.1038/s41467-026-74743-0",
"PMID": "42469238",
"PMCID": "PMC13379574",
"ISSN": "2041-1723",
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"URL": "https://doi.org/10.1038/s41467-026-74743-0",
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"issued": {
"date-parts": [
[
2026,
7,
17
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]
}
}

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