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Induced epileptic seizures in larval zebrafish reveal a synaptic modulation associated with the post-ictal state.

Code ↔ Paper

5 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 5 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] § Materials and methods › Analysis of ExM images of glycinergic synapses on the M cells ↔ ExM GlyR Imaging/receptor_segmentation_simple_anlaysis.m, lines 49–73 · score 0.65 · bilateral filter, image stack, smoothing, MATLAB, segmentation, receptor
  2. [2] § Materials and methods › Analysis of ExM images of glycinergic synapses on the M cells ↔ ExM GlyR Imaging/extrapolate_and_dilate.m, lines 1–28 · score 0.64 · original image resolution, 0.59 um, 0.1625 um, dilated, dimensions, mask
  3. [3] § Materials and methods › Analysis of neural activity in response to startling stimuli ↔ Neural Activity Imaging/main.m, lines 48–55 · score 0.53 · EZCalcium, CaImAn, ROI, neurons, neural activity
  4. [4] § Materials and methods › Analysis of neural activity in response to startling stimuli ↔ Neural Activity Imaging/FindActiveInt_LF.m, the whole file · a weak match · score 0.52 · standard deviation, prominent, peaks, raw, segmented, stimulus
  5. [5] § Materials and methods › Analysis of ExM images of glycinergic synapses on the M cells ↔ ExM GlyR Imaging/receptor_segmentation_simple_anlaysis.m, lines 49–73 · score 0.52 · image stack, Bilateral, filtering, smooth, MATLAB, segmentation

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

MATLAB · 113 lines · 4.4 KB · no license · 2 matches

  1. clc;
  2. clear all;
  3. close all;
  5. % work on a single dataset
  7. data_directory = 'data_directory'; % Provide a path to a directory containing a .tif file with a cropped image of an M cell, horizontally oriented
  8. original_data_fname = 'original_data_fname.tif'; % Provide the name of the .tif file from above, with stained GlyRs
  10. results_directory = 'results_directory'; % Provide a path to a directory that will contain receptor quantifications for all fish and M cells
  12. Mauthner_ID = '161224_E3_E3R'; % Provide an identified for the fish and M cell being analyzed - for subsequent pooling of results together
  13. save([results_directory '\' Mauthner_ID],'data_directory','original_data_fname');
  15. options.overwrite = true;
  17. mask_mat = double(tiffreadVolume([data_directory 'dilated_mask.tiff']));
  18. data_mat = double(tiffreadVolume([data_directory original_data_fname]));
  20. %% interpolation - upsample in z to get a uniform sampling rate in all dimensions
  22. % TO DO: make the masked_data_mat smaller, its boundaries in 3D should be tight
  23. % around masked pixels
  25. dx = 0.1625;
  26. dy = dx;
  27. dz = 0.59;
  29. x = (0:size(data_mat, 2)-1)'*dx;
  30. y = (0:size(data_mat, 1)-1)'*dy;
  31. z = (0:size(data_mat, 3)-1)'*dz;
  32. [X,Y,Z] = meshgrid (x,y,z);
  34. xq = x;
  35. yq = y;
  36. zq = 0:dx:z(end);
  37. [Xq,Yq,Zq] = meshgrid (xq,yq,zq);
  39. unmasked_mat = interp3(X,Y,Z,data_mat,Xq,Yq,Zq);
  41. % if exists
  42. % unmasked_mat = double(tiffreadVolume([data_directory 'interp_data_mat.tif']));
  44. mat = unmasked_mat.*mask_mat;
  46. saveastiff(uint16(mat),[data_directory 'interp_masked_data_mat.tif'],options);
  47. saveastiff(uint16(unmasked_mat),[data_directory 'interp_data_mat.tif'],options);
  49. %% bilateral filtering
  51. % if starting here
  52. % mat = double(tiffreadVolume([data_directory 'interp_masked_data_mat.tif']));
  54. max_mat = max(mat(:));
  55. mat_norm = mat./max_mat; % normalization with maximal M cell value
  57. % using a 3D bilateral filter on the image stack, value of smoothing was
  58. % chosen as a compromize between the minimum std value of the data and the
  59. % value that was computed based on MATLAB suggestions (see below)
  61. filt_img = unmasked_mat./max_mat; % normalizing by the maximal value within the M cell such that the filter parameters will be appropriate
  62. for itr=1:2
  63. for j = 1:size(mat,3)
  64. filt_img(:,:, j) = imbilatfilt(filt_img(:, :, j),0.001,5);
  65. end
  66. end
  68. filt_unmasked_img = filt_img;
  69. filt_img = filt_img.*mask_mat;
  71. options.overwrite = true;
  72. saveastiff(filt_img,[data_directory 'filt_inflated_masked_img.tif'],options); % saving a double as a double preserves actual values
  73. % saveastiff(filt_unmasked_img,[data_directory 'filt_inflated_img.tif'],options); % saving a double as a double preserves actual values
  75. %% using hysteresis to generate a binary mask of all synapses
  77. % if exists
  78. % filt_img = double(tiffreadVolume([data_directory 'filt_inflated_masked_img.tif']));
  80. undilated_Mcell_mask = double(tiffreadVolume([data_directory 'exterp_mask.tif']));
  81. exterp_undilated_Mcell_mask = interp3(X,Y,Z,undilated_Mcell_mask,Xq,Yq,Zq);
  83. signal_level = mean(filt_img((exterp_undilated_Mcell_mask==0)&(filt_img~=0)));
  84. signal_std = std(filt_img((exterp_undilated_Mcell_mask==0)&(filt_img~=0)));
  86. % LF - switching to signal mean and std based values
  87. t1 = signal_level+signal_std;
  88. t2 = signal_level+2*signal_std;
  89. [~,hys]=hysteresis3d(filt_img,t1,t2,26);
  91. saveastiff(uint16(hys),[data_directory sprintf('hysteresis3d_%.3f_%.3f.tif',t1,t2)], options);
  93. med_im_bw = medfilt3(hys);
  95. saveastiff(uint16(med_im_bw),[data_directory 'med_filt_hyst_mask.tiff'],options);
  97. %% final output - binary receptor and M cell masks
  99. % if exists and starting here
  100. % med_im_bw = double(tiffreadVolume([data_directory 'med_filt_hyst_mask.tiff']));
  101. % undilated_Mcell_mask = double(tiffreadVolume([data_directory 'exterp_mask.tif']));
  103. % interpolate to original resolution
  104. rec_mask = interp3(Xq,Yq,Zq,double(med_im_bw),X,Y,Z);
  105. saveastiff(uint16(rec_mask),[data_directory 'rec_mask.tiff'],options);
  107. dilated_Mcell_mask = interp3(Xq,Yq,Zq,double(mask_mat),X,Y,Z);
  108. saveastiff(uint16(dilated_Mcell_mask),[data_directory 'Mcell_mask.tiff'],options);
  110. Mcell_membrane_inds = find((dilated_Mcell_mask==1)&(undilated_Mcell_mask==0));
  111. Mcell_membrane_mask = zeros(size(undilated_Mcell_mask));
  112. Mcell_membrane_mask(Mcell_membrane_inds)=1;
  113. saveastiff(uint16(Mcell_membrane_mask),[data_directory 'Mcell_membrane_mask.tiff'],options);

receptor_segmentation_simple_anlaysis.m, no license · at the source

Overview

Authors: Dor Meron1, Yarden Levinsky1, Milagros Prendes1, Inbar Brosh1, Moti Freiman1, Limor Freifeld1
ORCID iDs: Limor Freifeld
  1. Biomedical Engineering Department, Technion—Israel Institute of Technology, Haifa 32000, Israel
Institutions: Technion – Israel Institute of Technology (Israel)
Journal: Brain communications, volume 8, issue 5, article fcag323
Dates: received 24 November 2025; accepted 10 August 2026; published online 8 September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag323 · PMID 42712917 · PMCID PMC13550772 · OpenAlex W7211970064
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: histology / microscopy (modality), human (organism), zebrafish (organism), epilepsy (population), cellular / molecular (subfield)
Methods: Statistics, fMRI & imaging, Single-unit activity, calcium imaging
Keywords: epilepsy, larval zebrafish, neural activity imaging, expansion microscopy, glycinergic synapses
Topic: Zebrafish Biomedical Research Applications (Cell Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Zuckerman STEM leadership program
Citations: not cited yet (Europe PMC); 126 references in the paper

Abstract

Epilepsy patients suffer from spontaneous and recurrent seizures. In some cases, after seizures, a transient post-ictal state associated with cognitive deficits develops. Moreover, seizure-induced alterations in brain structure and function may give rise to neurological comorbidities associated with epilepsy. Nevertheless, the mechanisms underlying neurological comorbidities in epilepsy broadly and the post-ictal state specifically are not well understood. Here we used a well-established model of acutely induced seizures in larval zebrafish to reveal how seizures modulate a neural circuit implementing a specific sensorimotor transformation, the escape response. Using in vivo calcium imaging, we found that the responsivity of Mauthner cells, hindbrain command-like neurons that normally evoke fast and strong escape responses, to startling stimuli was reduced following seizures. Moreover, we observed a global reduction in post-seizure responsivity of neurons to the stimuli and in spontaneous neural activity. To identify structural correlates of these changes, we used expansion microscopy to characterize synaptic inputs to the Mauthner cells. Using this approach, we discovered that seizures increased the density of receptors in glycinergic inhibitory synapses onto these cells, expected to increase synaptic strength. This enhancement may compensate for the lack of GABAergic inhibition during the seizure. In addition, inducing the disassembly of glycinergic synapses by post-seizure strychnine treatment, reversed the effect of reduced neural responsivity. Put together, these data show that, at both the synaptic and circuit levels, inhibitory drive is strengthened after seizure termination, giving rise to a post-ictal state similar to that defined in humans. Consequently, sensory sensitivity is reduced, and post-seizure behavioural deficits are expected. These results reveal a potential target for pharmacological interventions that may mitigate neurological deficits in epilepsy when the seizures themselves cannot be prevented.

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

Repository

Its files are read in the Code ↔ Paper reader above, with 5 matches between paragraphs and lines of code.

OSF sd5jy

License: none: the authors keep all their rights
State: the link answers, verified on 26 September 2026
Evidence: files inventoried
Languages: MATLAB (24)
Size: 26 files, 24 scripts
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Image Processing Toolbox (5 files), Parallel Computing Toolbox (1 file), Signal Processing Toolbox (1 file)
Availability: 1 check, the latest on 26 September 2026: the link answers (HTTP 200)
  • 26 September 2026: the link answers (HTTP 200)
24 files
At the source: osf.io/sd5jy/overview?view_only=996dc66dbec64cabaf5db26496197fca

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:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 24 scripts, each with its path and the digest of its content;
  • 5 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

The data that support the findings of this study are available from the corresponding author upon request. The code that was used for neural activity imaging and ExM data analysis can be freely downloaded from the Open Science Framework using this link: https://osf.io/sd5jy/overview?view_only=996dc66dbec64cabaf5db26496197fca.

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, 6 authors, 5 keywords, 1 funder, 121 references.

Cite

This paper

Meron, D., Levinsky, Y., Prendes, M., Brosh, I., Freiman, M., & Freifeld, L. (2026). Induced epileptic seizures in larval zebrafish reveal a synaptic modulation associated with the post-ictal state. Brain communications, 8(5), fcag323. https://doi.org/10.1093/braincomms/fcag323

BibTeX

@article{meron2026induced,
author = {Meron, Dor and Levinsky, Yarden and Prendes, Milagros and Brosh, Inbar and Freiman, Moti and Freifeld, Limor},
title = {{Induced epileptic seizures in larval zebrafish reveal a synaptic modulation associated with the post-ictal state}},
journal = {Brain communications},
year = {2026},
month = sep,
volume = {8},
number = {5},
pages = {fcag323},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag323},
url = {https://doi.org/10.1093/braincomms/fcag323},
pmid = {42712917},
pmcid = {PMC13550772}
}

RIS

TY - JOUR
AU - Meron, Dor
AU - Levinsky, Yarden
AU - Prendes, Milagros
AU - Brosh, Inbar
AU - Freiman, Moti
AU - Freifeld, Limor
TI - Induced epileptic seizures in larval zebrafish reveal a synaptic modulation associated with the post-ictal state
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/09/08
VL - 8
IS - 5
SP - fcag323
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag323
UR - https://doi.org/10.1093/braincomms/fcag323
LA - en
ER -

CSL-JSON

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"title": "Induced epileptic seizures in larval zebrafish reveal a synaptic modulation associated with the post-ictal state",
"container-title": "Brain communications",
"author": [
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"family": "Meron",
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"PMID": "42712917",
"PMCID": "PMC13550772",
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"issued": {
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8
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}
}

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