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Midbrain somatostatin-expressing cells control pain-suppression during defensive states.

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The authors' code

MATLAB · 137 lines · 5.2 KB · MIT

  1. % getThermoVIDFzIntervals:
  2. % Detect freezing periods from thermographic videos (TESTO 885).
  3. % Code used in "Brainstem somatostatin-expressing cells promote analgesia during negative emotional states". Winke, et al. 2022.
  4. % [v0.1, Daniel Jercog 2022, see: github.com/djercog/TestoFreez]
  5. %
  6. % function [fzIntervals,tm,areaChange,areaMouse]=getThermoVIDFzIntervals(videoFullpath,ffmpegBinPath)
  7. % function [fzIntervals,tm,areaChange,areaMouse]=getThermoVIDFzIntervals(videoFullpath,ffmpegBinPath,immobilityThreshold,minFzDur,minNonFzMerge)
  8. %
  9. % Input:
  10. % videoFullpath: full path to thermographic video (e.g, videoFullpath='E:\Videos\WT_FCA_IR\24-CSP.wmv';)
  11. % ffmpegBinPath: Path to ffmpeg/bin instalation folder (e.g., ffmpegBinPath='E:\ffmpeg\bin';)
  12. % immobilityThreshold: Threshold for immobility detection (default immobilityThreshold=0.003;)
  13. % minFzDur: Minimum immobility period duration to be considered freezing (default minFzDur=0.5;)
  14. % minNonFzMerge: Minimum non-freezing period to be merged between consecutive freezing periods (default minNonFzMerge=0.1;)
  15. %
  16. % Output:
  17. % fzIntervals: Freezing intervals detected.
  18. % tm: Time
  19. % areaChange: % pixels changed between consecutive video image frames within the ROI defined.
  20. % areaMouse: mouse area detected in pixels.
  21. %
  22. % Requires:
  23. % - videoframets (https://www.mathworks.com/matlabcentral/fileexchange/61235-video-frame-time-stamps)
  24. % - ffmpeg (https://ffmpeg.org/download.html)
  26. function [fzIntervals,tm,areaChange,areaMouse]=getThermoVIDFzIntervals(videoFullpath,ffmpegBinPath,immobilityThreshold,minFzDur,minNonFzMerge)
  28. if nargin < 3
  29. immobilityThreshold = 0.003;
  30. minFzDur=0.5;
  31. minNonFzMerge=0.1;
  32. else
  33. if (nargin~=5)
  34. error('Wrong number of input arguments.')
  35. end
  36. end
  38. %check if ffmpeg exists (for vidoframerets0
  39. if exist(ffmpegBinPath)==0
  40. error('ffmpeg directory not found.')
  41. end
  42. tm=videoframets(ffmpegBinPath,videoFullpath); %get video frame timestamps based on ffmpeg
  44. %set HP roi
  45. vidObj = VideoReader(videoFullpath);
  46. vidFramesAux = read(vidObj,4500);
  47. fAux=figure('color','w');
  48. ax=subplot(1,1,1);hold on;
  49. title('Define HP area:','fontsize',12);
  50. roiHP=roipoly(vidFramesAux);
  51. roiHP=double(roiHP);
  52. roiHP(roiHP==0)=nan;
  53. close(fAux);
  55. %Load entire video
  56. display('Loading video....')
  57. vidFramesAux = read(vidObj);
  59. %Calculate %area change within ROI between binarized downsampled video consecutive frames
  60. display('Processing video....');
  61. clear areaChange areaMouse;
  62. for j=2:length(vidFramesAux)
  63. %obtain 2 consecutive video frames
  64. auxF1=roiHP.*double(vidFramesAux(:,:,3,j-1)); %process blue channel only
  65. auxF2=roiHP.*double(vidFramesAux(:,:,3,j)); %process blue channel only
  66. thresh=min(auxF1(:))+ graythresh(auxF1)*(max(auxF1(:))-min(auxF1(:))); %Otsu's thresholding
  67. auxF1(auxF1<=thresh)=0;auxF1(auxF1>thresh)=1;
  68. thresh=min(auxF2(:))+ graythresh(auxF2)*(max(auxF2(:))-min(auxF2(:))); %Otsu's thresholding
  69. auxF2(auxF2<=thresh)=0;auxF2(auxF2>thresh)=1;
  70. %invert scale: 1 on mouse;
  71. indTo1=find(auxF1==0);indTo0=find(auxF1==1);auxF1(indTo1)=1;auxF1(indTo0)=0;
  72. indTo1=find(auxF2==0);indTo0=find(auxF2==1);auxF2(indTo1)=1;auxF2(indTo0)=0;
  73. areaMouse(j-1)=(length(find(auxF1==1))+length(find(auxF2==1)))/2; %avg between the 2 frames
  74. areaChange(j-1)=length(find(auxF2-auxF1==1 | auxF2-auxF1==-1))/length(find(roiHP==1)); % %change relative to ROI
  75. end
  77. %detecting freezing
  78. tm=tm(2:end);
  79. fzAux=zeros(length(areaChange),1);
  80. fzAux(find(areaChange<immobilityThreshold))=1;
  81. endFzPer=find(diff(fzAux)==-1);
  82. begFzPer=find(diff(fzAux)==1)+1;
  83. if ~isempty(begFzPer) && ~isempty(endFzPer)
  84. if endFzPer(1)<begFzPer(1)
  85. begFzPer=[1;begFzPer];
  86. end
  87. if begFzPer(end)>endFzPer(end)
  88. endFzPer=[endFzPer;length(fzAux)];
  89. end
  90. fzOns=tm(begFzPer);
  91. fzOffs=tm(endFzPer);
  92. else
  93. fzOns=[];
  94. fzOffs=[];
  95. end
  96. %remove short nFZ periods if neighboring periods are fz periods
  97. indAux=find(fzOns(2:end)-fzOffs(1:end-1)<=minNonFzMerge);
  98. toRemove=[];
  99. for s=1:length(indAux)
  100. %if (fzOffs(indAux(s)-1)-fzOns(indAux(s)-1)>minFzDur && fzOffs(1+indAux(s))-fzOns(1+indAux(s))>minFzDur)
  101. if (fzOffs(1+indAux(s))-fzOns(1+indAux(s))>minNonFzMerge)
  102. toRemove=[toRemove,indAux(s)];
  103. end
  104. end
  105. fzOffs(toRemove)=[];
  106. fzOns(toRemove+1)=[];
  107. %remove shor fz
  108. indAux=find(fzOffs-fzOns<=minFzDur);
  109. fzOns(indAux)=[];
  110. fzOffs(indAux)=[];
  111. fzIntervals=[fzOns,fzOffs];
  113. verifyDet = input('Verify detection? Y/N [N]:','s');
  114. if strcmp(verifyDet,'Y')
  115. % Verify detection
  116. f = figure('color','w');
  117. ax(1)=subplot(5,1,5);hold on;
  118. plot(tm,areaChange,'k');
  119. axis tight;ylim([-0.005,0.02]);
  120. plot(fzIntervals,[0.01,0.01],'r','linewidth',2);
  121. ylabel('% Area Change');xlabel('Time (s)');
  122. set(gca,'tickdir','out');
  123. ax(2)=subplot(5,1,1:4,'fontsize',5);hold on;
  124. title('Verify detection...','fontsize',14);
  125. axis ij;
  126. set(gca,'xtick',[],'ytick',[],'xcolor','w','ycolor','w');
  127. for i=1:size(vidFramesAux,4)-1
  128. if ishandle(f)
  129. im=imagesc(vidFramesAux(:,:,:,i));
  130. p=plot(ax(1),[tm(i),tm(i)],[-0.005,0.02],'m','linewidth',1);
  131. pause(0.02);
  132. delete(im);
  133. delete(p);
  134. end
  135. end
  136. close(f);
  137. end

getThermoVIDFzIntervals.m at commit d68940d, under MIT · at the source

Overview

Authors: Nanci Winke1,2, Frank Aby3, Daniel Jercog1,2, Coline Riffault1,2, Rabia Bouali-Benazzouz3, Juliette Viellard1,2,3, Delphine Girard1,2, Zoe Grivet3, Marc Landry3, Laia Castell4, Emmanuel Valjent4,5, Stephane Valerio1,2, Pascal Fossat3, Cyril Herry1,2
ORCID iDs: Coline Riffault, Emmanuel Valjent, Pascal Fossat, Cyril Herry
  1. Univ. Bordeaux, Neurocentre Magendie, Bordeaux, France
  2. INSERM, Neurocentre Magendie, Bordeaux, France
  3. Univ. Bordeaux, CNRS, Institute for Neurodegenerative Diseases, Bordeaux, France
  4. Université de Montpellier, Institut de génomique fonctionnelle (IGF), CNRS, Montpellier, France
  5. INM, Univ. Montpellier, Inserm, Montpellier, France
Institutions: Université de Bordeaux (France); Inserm (France); Neurocentre Magendie (France); Centre National de la Recherche Scientifique (France); Institut des Maladies Neurodégénératives (France); Institut Interdisciplinaire de Neuroscience (France); Centre Hospitalier Charles Perrens (France); Université de Montpellier (France); Institut de Génomique Fonctionnelle (France); Institute for Neurosciences of Montpellier (France)
Journal: eLife, volume 14, article RP106826
Dates: published online 10 November 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.7554/elife.106826 · PMID 43004867 · PMCID PMC13750795 · OpenAlex W4411577360
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: mouse (organism), pain (population), systems (subfield)
Methods: Preprocessing, Evoked potentials, Statistics
Keywords: Mouse
MeSH: Fear*, Mesencephalon*, Neurons*, Pain*, Periaqueductal Gray*, Somatostatin*, Analgesia, Animals, Behavior, Animal, Male, Mice, Optogenetics (* major topic)
Topic: Pain Mechanisms and Treatments (Physiology (medical), Medicine), according to OpenAlex
Funding: Fondation pour la Recherche Médicale (FRM-PhD); Agence Nationale de la Recherche (ANR-10-EQPX-08-optopath, 10.67599/anr-19-ce16-0016, 10.67599/anr-23-ce37-0015); French Society for the Study and Treatment of Pain (SFETD)
Citations: not cited yet (Europe PMC); 43 references in the paper

Abstract

In threatening situations, animals exhibit a broad range of behavioral and autonomic responses. As such, a crucial adaptive response is the inhibition of pain, which facilitates relevant defensive behaviors that promote survival. Whereas the structures and mechanisms involved in fear and pain behaviors are well documented, little is known about the precise neuronal mechanisms mediating the emotional regulation of endogenous pain-suppression. Here, we used a combination of behavioral, anatomical, optogenetic, and electrophysiological approaches to investigate, in male mice, the role of somatostatin-expressing cells in the ventrolateral periaqueductal gray matter (SST+ vlPAG cells) in the control of analgesia induced during defensive states. Our data indicate that optogenetic inhibition of SST+ vlPAG cells promotes analgesia irrespective of animal defensive state. In contrast, optogenetic activation of long-range SST+ vlPAG cells that project to the rostral ventromedial medulla (RVM) abolishes the analgesia mediated by fear behavior. Together, these results identify a novel circuit mechanism composed of long-range SST+ vlPAG cells projecting to the RVM that regulate analgesia elicited during defensive states.

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

Repository

Its files are read in the Code ↔ Paper reader above.

djercog/TestoFreez

License: MIT
State: the link answers, verified on 12 November 2026
Evidence: files inventoried
Commit: d68940d92134eb61d42ea267541ada195c9f1cb2, 5 October 2026
Languages: MATLAB (1)
Size: 3 files, 1 script
Software Heritage: not archived
Found in: the text, “Cued fear-conditioned analgesia”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Image Processing Toolbox (1 file)
Availability: 1 check, the latest on 12 November 2026: the link answers
  • 12 November 2026: the link answers
3 files
At the source: github.com/djercog/TestoFreez

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

Tracing map

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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 or analysed during this study, including the source data underlying every figure, have been deposited in the Dryad Digital Repository under DOI https://doi.org/10.5061/dryad.63xsj3vj3. Custom code used for the automated detection of freezing behaviour from thermographic recordings (TestoFreez) is available at https://github.com/djercog/TestoFreez (copy archived at Jercog, 2026) and released under the MIT licence.

The following dataset was generated:

Cyril H, Nanci W, Frank A, Daniel J, Coline R. 2026. Midbrain somatostatin-expressing cells control pain-suppression during defensive states. Dryad Digital Repository.

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

Versions

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Version 1, 12 November 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 14 authors, 1 keyword, 12 MeSH terms, 3 funders, 40 references.

Cite

This paper

Winke, N., Aby, F., Jercog, D., Riffault, C., Bouali-Benazzouz, R., Viellard, J., Girard, D., Grivet, Z., Landry, M., Castell, L., Valjent, E., Valerio, S., Fossat, P., & Herry, C. (2026). Midbrain somatostatin-expressing cells control pain-suppression during defensive states. eLife, 14, RP106826. https://doi.org/10.7554/elife.106826

BibTeX

@article{winke2026midbrain,
author = {Winke, Nanci and Aby, Frank and Jercog, Daniel and Riffault, Coline and Bouali-Benazzouz, Rabia and Viellard, Juliette and Girard, Delphine and Grivet, Zoe and Landry, Marc and Castell, Laia and Valjent, Emmanuel and Valerio, Stephane and Fossat, Pascal and Herry, Cyril},
title = {{Midbrain somatostatin-expressing cells control pain-suppression during defensive states}},
journal = {eLife},
year = {2026},
month = nov,
volume = {14},
pages = {RP106826},
publisher = {eLife Sciences Publications, Ltd},
issn = {2050-084X},
doi = {10.7554/elife.106826},
url = {https://doi.org/10.7554/elife.106826},
pmid = {43004867},
pmcid = {PMC13750795}
}

RIS

TY - JOUR
AU - Winke, Nanci
AU - Aby, Frank
AU - Jercog, Daniel
AU - Riffault, Coline
AU - Bouali-Benazzouz, Rabia
AU - Viellard, Juliette
AU - Girard, Delphine
AU - Grivet, Zoe
AU - Landry, Marc
AU - Castell, Laia
AU - Valjent, Emmanuel
AU - Valerio, Stephane
AU - Fossat, Pascal
AU - Herry, Cyril
TI - Midbrain somatostatin-expressing cells control pain-suppression during defensive states
T2 - eLife
J2 - eLife
PY - 2026
DA - 2026/11/10
VL - 14
SP - RP106826
SN - 2050-084X
PB - eLife Sciences Publications, Ltd
DO - 10.7554/elife.106826
UR - https://doi.org/10.7554/elife.106826
LA - en
ER -

CSL-JSON

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"id": "10.7554/elife.106826",
"type": "article-journal",
"title": "Midbrain somatostatin-expressing cells control pain-suppression during defensive states",
"container-title": "eLife",
"author": [
{
"family": "Winke",
"given": "Nanci"
},
{
"family": "Aby",
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},
{
"family": "Jercog",
"given": "Daniel"
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{
"family": "Riffault",
"given": "Coline"
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{
"family": "Bouali-Benazzouz",
"given": "Rabia"
},
{
"family": "Viellard",
"given": "Juliette"
},
{
"family": "Girard",
"given": "Delphine"
},
{
"family": "Grivet",
"given": "Zoe"
},
{
"family": "Landry",
"given": "Marc"
},
{
"family": "Castell",
"given": "Laia"
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{
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{
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"given": "Stephane"
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{
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"given": "Pascal"
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{
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"given": "Cyril"
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],
"container-title-short": "eLife",
"volume": "14",
"page": "RP106826",
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"language": "en",
"issued": {
"date-parts": [
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}

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