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A brain stem circuit integrating reflexive and anticipatory salivation.

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  1. [1] § STAR★METHODS › METHOD DETAILS › Fiber photometry and stimuli presentation ↔ pMAT v1-2 MATLAB/Debleach v2/FP_DEBLEACHED.m, the whole file · a weak match · score 0.50 · Fiber Photometry, calcium, median, bin, signals, window

Paper

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The authors' code

MATLAB · 78 lines · 3.3 KB · GPL-3.0 · 1 match

  1. function [DF_norm, DF_MAD] = FP_DEBLEACHED(DeltaFlour,Window, ITERATIONS)
  2. %% By David Estrin & David Barker for the Barker Laboratory
  3. % Code is written for ____ et al., 2020
  4. % The purpose of this code is to take a calcium trace from fiber
  5. % photometry and detrend/debleach the trace.
  7. %% The following are Inputs:
  8. % 1--DeltaFlour- Experimental Channel
  9. % 2--Threshold-Enter Manual Threshold Value. This will change depending on if you are
  10. % using normal Z Score or the Robust Z Score (DF_MAD).
  11. % 3--Window- Change the amount of time to bin and debleach.
  12. % 4--ITERATIONS- Number of times this code will calculate a debleached
  13. % calcium signal. These interations will be averaged at the end.
  15. %% The following are Outputs:
  16. % 1--DF_norm- The de-bleached Z score normal line
  17. % 2--DF_MAD- The de-bleached robuse Z score line
  19. %% Example use of this function:
  20. %
  21. % [Fiber_Photometry_Trace]=DeltaF(Ch490,Ch405); Get trace
  22. %
  23. % [Fiber_Photometry_Trace_Debleached_1, Fiber_Photometry_Trace_Debleached_2] = ...
  24. % FP_DEBLEACHED(Fiber_Photometry_Trace, 15, 100); Get debleached
  25. % trace
  26. %
  29. DF=DeltaFlour;
  30. Parse=Window*1000; % 15000 Miliseconds (15 Seconds) is what we are dividing data into.
  31. cuts=round(Parse/ITERATIONS);
  33. for l=1:Parse:length(DF) % Loop through Percentiles
  34. if l+Parse>length(DF) %Based on the parsing, cut off some of the data at end of recording, typicall few points
  35. MEAN=mean(DF(l:end)); % Find mean of moving window
  36. DF_Transpose(l:length(DF),1)=(DF(l:length(DF),1)-MEAN); %This will be the rescalled version of DF
  38. MEDIAN=median(DF(l:end)); %% Median Absolute Deviation
  39. DF_MAD(l:length(DF),1)=((DF(l:length(DF),1)-MEDIAN)); %% Median Absolute Deviation
  41. break
  42. end
  43. MEAN=mean(DF(l:(l+Parse))); % Find mean of moving window
  44. DF_Transpose(l:(l+Parse),1)=(DF(l:(l+Parse),1)-MEAN); %This will be the rescalled version of DF
  45. MEDIAN=median(DF(l:(l+Parse))); %% Median Absolute Deviation
  46. DF_MAD(l:(l+Parse),1)=((DF(l:(l+Parse),1)-MEDIAN)); %% Median Absolute Deviation
  47. end
  48. MAD_MATRIX(:,1)=DF_MAD;
  49. clear DF_MAD;
  51. tic
  52. matrix=zeros(length(DF), ITERATIONS);
  53. parfor k=1:(ITERATIONS-1)
  54. DF_MAD=zeros(length(DF),1);
  55. for l=(k*cuts):Parse:length(DF) % Loop through Percentiles
  56. if l+Parse>length(DF) %Based on the parsing, cut off some of the data at end of recording, typicall few points
  57. MEDIAN=median(DF(l:end)); %% Median Absolute Deviation
  58. DF_MAD(l:length(DF),1)=((DF(l:length(DF))-MEDIAN)); %% Median Absolute Deviation
  59. break
  60. end
  61. if l==(k*cuts)
  62. MEDIAN=median(DF(1:l)); %% Median Absolute Deviation
  63. DF_MAD(1:l,1)=((DF(1:l,1)-MEDIAN)); %% Median Absolute Deviation
  64. end
  65. MEDIAN=median(DF(l:(l+Parse))); %% Median Absolute Deviation
  66. DF_MAD(l:(l+Parse),1)=((DF(l:(l+Parse),1)-MEDIAN)); %% Median Absolute Deviation
  67. end
  68. matrix(:,k)=DF_MAD;
  69. end
  70. VeryMad=median(matrix');
  71. toc
  72. clear matrix DF_MAD matrix2 DF_Z DF_Slope matrix3;
  73. VeryMad=VeryMad';
  74. VeryMad=VeryMad./mad(VeryMad); %De-bleached Robust Normalized Delta F
  75. DF_MAD=VeryMad;
  76. DF_norm=DF_Transpose./std(DF_Transpose); %De-bleached Normalized Delta F.
  77. end

FP_DEBLEACHED.m at commit 320c349, under GPL-3.0 · at the source

Overview

Authors: Gyujin Park1, Hojoon Lee1,2,3
ORCID iDs: Gyujin Park, Hojoon Lee
  1. Department of Neurobiology, Northwestern University, Evanston, IL, USA
  2. Senior author
  3. Lead contact
Institutions: Northwestern University (United States)
Journal: Cell reports, volume 45, issue 3, article 117067
Dates: published online 14 March 2026; in print 24 March 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1016/j.celrep.2026.117067 · PMID 41832958 · PMCID PMC13056588 · OpenAlex W7135167357
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: mouse (organism), systems (subfield)
Methods: Preprocessing, Statistics, Single-unit activity, calcium imaging
Keywords: Brain stem, Taste, Salivation, Pavlovian Conditioning, Sensorimotor Integration, Gustatory Cortex, Cp: Neuroscience, Salivatory Nucleus
MeSH: Brain Stem*, Salivation*, Animals, Conditioning, Classical, Male, Mice, Mice, Inbred C57BL, Neurons, Taste (* major topic)
Topic: Olfactory and Sensory Function Studies (Sensory Systems, Neuroscience), according to OpenAlex
Funding: National Center for Complementary and Integrative Health (R01AT013056); Whitehall Foundation; National Institutes of Health; NIDCD NIH HHS (R21 DC022726); National Institute on Deafness and Other Communication Disorders (R21DC022726); National Institute of Biomedical Imaging and Bioengineering (R21EB036732); NIBIB NIH HHS (R21 EB036732); NCCIH NIH HHS (R01 AT013056)
Citations: cited by 1 paper (Europe PMC); 53 references in the paper
Research resources: Anti-fluorogold primary antibody RRID:AB_2632408, RRID:SCR_017767

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

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djamesbarker/pMAT

License: GPL-3.0
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 320c349fe5068ae1104ce8ba6f862e151459075e, 26 July 2021
Languages: MATLAB (33)
Size: 104 files, 33 scripts
Software Heritage: not archived
Found in: “KEY RESOURCES TABLE”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Signal Processing Toolbox (2 files), Statistics and Machine Learning Toolbox (2 files)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
35 files
At the source: github.com/djamesbarker/pMAT

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

Tracing map

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  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 33 scripts, each with its path and the digest of its content;
  • 1 match between paragraphs of the paper and lines of the code (method lexical-v1);
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Data

Datasets cited

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it points to the authors' code: djamesbarker/pMAT
  • it says that the data are available on request
  • it says that the code is available on request

Read it in the paper: doi.org/10.1016/j.celrep.2026.117067.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 8 keywords, 9 MeSH terms, 8 funders, 46 references, 2 RRIDs.

Cite

This paper

Park, G., & Lee, H. (2026). A brain stem circuit integrating reflexive and anticipatory salivation. Cell reports, 45(3), 117067. https://doi.org/10.1016/j.celrep.2026.117067

BibTeX

@article{park2026brain,
author = {Park, Gyujin and Lee, Hojoon},
title = {{A brain stem circuit integrating reflexive and anticipatory salivation}},
journal = {Cell reports},
year = {2026},
month = mar,
volume = {45},
number = {3},
pages = {117067},
publisher = {Cell Press},
issn = {2211-1247},
doi = {10.1016/j.celrep.2026.117067},
url = {https://doi.org/10.1016/j.celrep.2026.117067},
pmid = {41832958},
pmcid = {PMC13056588}
}

RIS

TY - JOUR
AU - Park, Gyujin
AU - Lee, Hojoon
TI - A brain stem circuit integrating reflexive and anticipatory salivation
T2 - Cell reports
J2 - Cell Rep
PY - 2026
DA - 2026/03/14
VL - 45
IS - 3
SP - 117067
SN - 2211-1247
PB - Cell Press
DO - 10.1016/j.celrep.2026.117067
UR - https://doi.org/10.1016/j.celrep.2026.117067
LA - en
ER -

CSL-JSON

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"volume": "45",
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"page": "117067",
"DOI": "10.1016/j.celrep.2026.117067",
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"ISSN": "2211-1247",
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