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Limited Detectability of Network Functional Alterations in a Tauopathy Model Using Mouse Primary Cortical Cultures.

Code ↔ Paper

3 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 3 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] § 2. Materials and Methods › 2.4. Spontaneous Activity Data Acquisition and Analysis › 2.4.2. Data Analysis and Event Detection ↔ internal/options/schmittOptions.m, the whole file · a weak match · score 0.71 · Schmitt trigger, lower threshold, upper threshold, detection, signal, train
  2. [2] § 2. Materials and Methods › 2.4. Spontaneous Activity Data Acquisition and Analysis › 2.4.2. Data Analysis and Event Detection ↔ internal/spikeInferenceSchmitt.m, lines 1–87 · score 0.70 · Schmitt trigger, lower threshold, upper threshold, detection, train, bursts
  3. [3] § 2. Materials and Methods › 2.4. Spontaneous Activity Data Acquisition and Analysis › 2.4.4. Effective Connectivity Analysis and Network Metrics ↔ internal/networkInference/Connectomics/cnn/gte.py, lines 14–133 · score 0.62 · Instant feedback, GTE, joint, vectors, bins, connection

Paper

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The authors' code

MATLAB · 32 lines · 1.3 KB · MIT · 1 match

  1. classdef schmittOptions < baseOptions
  2. % SCHMITTGOPTIONS Schmitt trigger options
  3. % Class containing the parameters to perform spike inference with a
  4. % schmitt trigger. It will identify a spike whenever the signal goes
  5. % above the upperThreshold and doesn't go below the lower threshold. It
  6. % will associate the spike with the average time between the rise and the
  7. % local maxima, and also store the duration and ampltiude in separated
  8. % variables.
  9. %
  10. % Copyright (C) 2016, Javier G. Orlandi <[email hidden]>
  11. %
  12. % See also Peeling, baseOptions, optionsWindow
  14. properties
  15. % First threshold for spike detection (signal has to go above this
  16. % value, see also threshold type)
  17. upperThreshold = 3;
  19. % Second threshold for spike detection (signal has to go below this
  20. % value, see also threshold type)
  21. lowerThreshold = 0.9;
  23. % ROI index used to check inference results with a single trace (only used in training mode)
  24. trainingROI = 1;
  26. % Type of threshold measure. Relative, means it will look for
  27. % multipliers of the standard deviation of the signal (above the mean).
  28. % Absolute will look for values directly above whatever the threshold
  29. % is.
  30. thresholdType = {'relative', 'absolute'};
  31. end
  32. end

schmittOptions.m, under MIT · at the source

Overview

Authors: Clara F López-León1,2, Julia Sala-Jarque3,4, José Antonio del Río4,5,6,7, Jordi Soriano1,2
ORCID iDs: Clara F López-León, Julia Sala-Jarque, José Antonio del Río, Jordi Soriano
  1. Departament de Física de la Matèria Condensada, Universitat de Barcelona, 08028 Barcelona, Spain
  2. Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, 08028 Barcelona, Spain
  3. Department of Molecular, Cellular, Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, CA 93106, USA
  4. Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
  5. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28031 Madrid, Spain
  6. Department of Cell Biology, Physiology and Immunology, Faculty of Biology, Universitat de Barcelona, 08028 Barcelona, Spain
  7. Institute of Neuroscience, University of Barcelona, 08028 Barcelona, Spain
Institutions: Universitat de Barcelona (Spain); University of California, Santa Barbara (United States); Barcelona Institute of Science and Technology (Spain); Institute for Bioengineering of Catalonia (Spain); Biomedical Research Networking Center on Neurodegenerative Diseases (Spain)
Journal: Biomedicines, volume 14, issue 8, article 1670
Dates: received 10 February 2026; accepted 19 July 2026; published online 24 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.3390/biomedicines14081670 · PMID 42652054 · PMCID PMC13510110 · OpenAlex W7171291620
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: optical imaging (calcium, voltage, 2-photon) (modality), mouse (organism), Alzheimer's / dementia (population)
Methods: Statistics, Evoked potentials, Connectivity, Graphs, fMRI & imaging, Single-unit activity, calcium imaging
Keywords: neuronal cultures, fluorescence calcium imaging, tauopathies, functional connectivity
Topic: Alzheimer's disease research and treatments (Physiology, Medicine), according to OpenAlex
Funding: Ministerio de Ciencia, Innovación y Universidades (PID2019-108842GB-C21, PID2022-137713NB-C22, PID2021-123714OB-I00, PLEC2022-009401, PDC2022-133268-I00, PID2024-162521OB-I00); Departament de Recerca i Universitats (SGR2021-00450, SGR2021-00453); CaixaBank (LCF-PR-HR19- 52160007)
Citations: not cited yet (Europe PMC); 81 references in the paper

Abstract

Background: Tauopathies are neurodegenerative disorders characterized by the abnormal hyperphosphorylation and aggregation of the microtubule-associated protein tau, leading to disrupted neuronal connectivity and progressive brain dysfunction. Despite their clinical relevance, most in vitro models have focused primarily on molecular and cellular aspects, with limited emphasis on alterations in network dynamics and functional connectivity. Methods: We developed an in vitro tauopathy model based on mouse primary neuronal cultures, enabling the investigation of network-level alterations under controlled conditions. We compared three experimental groups: untreated control cultures, cultures exposed to extracellular wild-type tau, and cultures treated with pathological tau (pTau) isolated from the sarkosyl-insoluble fraction of P301S (+/−) transgenic mice. To increase susceptibility to tau-induced pathology, all conditions were additionally transduced with adeno-associated viral vectors encoding human P301L tau. To quantify for damage, spontaneous neuronal activity was monitored throughout network maturation—from day in vitro (DIV) 7 to 16—using fluorescence calcium imaging, and multiple metrics describing network dynamics and functional organization were compared at DIV 12. Results: We observed that exposure to pTau did not induce overt cytotoxicity or major disruptions in global network dynamics, although a mild increase in network bursting activity was observed. Longitudinal analysis of network maturation further revealed largely similar developmental trajectories across experimental groups, with only subtle and persistent differences in bursting-related activity in pTau-treated cultures. Conclusions: We propose that the early developmental stage of the cultures, together with the intrinsic bursting and ongoing synaptic plasticity of primary neuronal networks, masks subtle pathological effects. This may limit the sensitivity of two-dimensional in vitro systems to detect network-level dysfunction, suggesting that more mature or structurally complex models, such as brain organoids, may be required to reveal robust functional deficits.

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 3 matches between paragraphs and lines of code.

Zenodo 1119025

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: the references
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (28 files), export_fig (22 files), Signal Processing Toolbox (19 files), Image Processing Toolbox (18 files), Optimization Toolbox (7 files), NumPy (6 files), Keras (4 files), Parallel Computing Toolbox (4 files), Curve Fitting Toolbox (2 files), scikit-learn (1 file), TensorFlow (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
949 files
At the source:

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;
  • 947 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 Statement

The data presented in this study are openly available in Zenodo at https://zenodo.org/records/18601917 (accessed on 10 February 2026), reference number 10.5281/zenodo.18601917.

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, 4 authors, 4 keywords, 3 funders, 81 references.

Cite

This paper

López-León, C. F., Sala-Jarque, J., del Río, J. A., & Soriano, J. (2026). Limited Detectability of Network Functional Alterations in a Tauopathy Model Using Mouse Primary Cortical Cultures. Biomedicines, 14(8), 1670. https://doi.org/10.3390/biomedicines14081670

BibTeX

@article{lopezleon2026limited,
author = {López-León, Clara F and Sala-Jarque, Julia and del Río, José Antonio and Soriano, Jordi},
title = {{Limited Detectability of Network Functional Alterations in a Tauopathy Model Using Mouse Primary Cortical Cultures}},
journal = {Biomedicines},
year = {2026},
month = jul,
volume = {14},
number = {8},
pages = {1670},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
issn = {2227-9059},
doi = {10.3390/biomedicines14081670},
url = {https://doi.org/10.3390/biomedicines14081670},
pmid = {42652054},
pmcid = {PMC13510110}
}

RIS

TY - JOUR
AU - López-León, Clara F
AU - Sala-Jarque, Julia
AU - del Río, José Antonio
AU - Soriano, Jordi
TI - Limited Detectability of Network Functional Alterations in a Tauopathy Model Using Mouse Primary Cortical Cultures
T2 - Biomedicines
J2 - Biomedicines
PY - 2026
DA - 2026/07/24
VL - 14
IS - 8
SP - 1670
SN - 2227-9059
PB - Multidisciplinary Digital Publishing Institute (MDPI)
DO - 10.3390/biomedicines14081670
UR - https://doi.org/10.3390/biomedicines14081670
LA - en
ER -

CSL-JSON

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