Neuron-derived neurotrophic factor-positive interneurons: a cellular target for anti-seizure therapies.

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Paper

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The authors' code

Shell · 2 lines · 114 B · GPL-3.0

#!/bin/bash
gnome-terminal -e "bash -c \"source activate pyecog2PySide; python -m pip install -e . ; exec bash\""

LinuxInstall.sh at commit 0199941, under GPL-3.0 · at the source

Overview

Authors: Amy Richardson¹, Marion S. Mercier¹, Yoshiteru Shimoda¹, Robert T. Graham¹, Marco Leite¹, Alejandro Garcia¹, Maud Muller¹, Suraya A. Bond¹, Maria Grozdanova¹, Qimin Wu¹, Andreas Lieb¹, Dimitri M. Kullmann¹, Vincent Magloire¹

ORCID iDs: Robert T. Graham, Marco Leite, Qimin Wu, Vincent Magloire

UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom

Institutions: UCL Queen Square Institute of Neurology (United Kingdom); University College London (United Kingdom)

Journal: EBioMedicine, volume 130, article 106362

Dates: received 15 December 2025; accepted 16 June 2026; published online 21 July 2026; in print August 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1016/j.ebiom.2026.106362 · PMID 42475878 · PMCID PMC13393760 · OpenAlex W7169785465

Open access: gold, a free copy (OpenAlex)

Status: code verified

Categories: mouse (organism), epilepsy (population)

Methods: Spectral & time-frequency, Connectivity, Statistics, Machine learning, Evoked potentials, fMRI & imaging, Single-unit activity, calcium imaging, Physiology & signal measures

Keywords: NDNF+ interneurons, Epilepsy, Inhibition, Anti-seizure therapies

MeSH: Interneurons*, Nerve Growth Factors*, Seizures*, Animals, Calcium, Chemogenetics, Disease Models, Animal, Hippocampus, Mice, Mice, Transgenic, Optogenetics, Pyramidal Cells (* major topic)

Topic: Nerve injury and regeneration (Cellular and Molecular Neuroscience, Neuroscience), according to OpenAlex

Funding: Epilepsy Research UK (F1901, 2303F); UK Medical Research Council (MR/V034758/1, MR/W005204/1); Wellcome Trust (212285/Z/18/Z); Gatsby Charitable Foundation (GAT3955); Rosetrees Trust (CSeedcorn2021\100113); Wellcome Career Development Award (227269/Z/23/Z); Japan Epilepsy Research Foundation

Citations: not cited yet (Europe PMC); 88 references in the paper

Research resources: Anti-vasoactive intestinal polypeptide RRID:AB_10730725, Anti-somatostatin RRID:AB_10903864, Alexafluor594 anti-rabbit RRID:AB_141359, Anti-reelin RRID:AB_1603148, Anti-neuropeptide Y RRID:AB_2307354, Alexafluor568 anti-rabbit RRID:AB_2534017, Alexafluor488 anti-mouse RRID:AB_2534069, Alexafluor568 anti-mouse RRID:AB_2534072, RRID:AB_3718175, Anti-parvalbumin RRID:AB_477329, pAAV-CAG-FLEX-ArchT-GFP RRID:Addgene_28307, RRID:Addgene_44361, RRID:Addgene_62725, RRID:Addgene_83899, RRID:IMSR_JAX_008069, RRID:IMSR_JAX_012569, 29 mice) and SOM::Cre RRID:IMSR_JAX_018973, RRID:IMSR_JAX_028536, RRID:SCR_001622, RRID:SCR_002798, RRID:SCR_008394, recorded using WinEDR RRID:SCR_014270, RRID:SCR_014713

Abstract

Background: Failure of epilepsy pharmacotherapy is common, justifying efforts to identify optimal cell targets for advanced therapies. Genetic manipulations of the inhibitory system in principle offer a finely tuned intervention that cannot be achieved with a broad reduction of pyramidal neuron excitability. In this context, neuron-derived neurotrophic factor-expressing (NDNF+) interneurons evoke long-lasting GABAA and GABAB receptor-mediated inhibition. However, their contribution to restraining hyperexcitability during epileptiform activity remains unexplored.

Methods: To address this, we employed calcium imaging, optogenetics, and chemogenetics in an NDNF-Cre mouse line to investigate how NDNF+ interneurons influence cortical and hippocampal hyperactivity and spontaneous seizures.

Findings: We show that NDNF+ interneurons are actively recruited during interictal spikes and focal seizures, although more slowly than parvalbumin-positive interneurons (mean difference: 2.8 s, p = 0.023). Optogenetic hyperpolarisation of NDNF+ interneurons exacerbates epileptic discharges (normalised seizure-duration mean difference: 0.23, p = 0.0474), whereas their depolarisation suppresses focal seizures, even when the optogenetic stimulus is delayed by several seconds from seizure onset (normalized seizure-duration mean difference: −0.27, p = 0.03). This effect is largely mediated by GABAB receptors. Additionally, chemogenetic depolarisation of NDNF+ interneurons has an important anti-seizure effect in the hippocampus both ex vivo (normalised seizure-duration mean difference: −0.92, p < 0.001) and in vivo.

Interpretation: Collectively, these findings establish NDNF+ neurons as key regulators of both cortical and hippocampal excitability even during epileptic activity, and identify them as promising cellular targets for the development of anti-seizure therapies.

Funding: Epilepsy Research UK, Wellcome, the Medical Research Council, the Gatsby Charitable Foundation, and The Rosetrees Trust.

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

Repository

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

KullmannLab/pyecog2

License: GPL-3.0

State: the link answers, verified on 27 September 2026

Evidence: files inventoried

Commit: 01999410e87c53f41c8b7d9d5ade0e70722dd057, 4 November 2025

Languages: Python (52), Jupyter (14), Shell (2)

Size: 134 files, 68 scripts

Software Heritage: not archived

Found in: “Data sharing statement”

Holds: README, license file, environment (setup.py), tests, 14 notebooks

Not found: CITATION.cff, continuous integration, documentation

Tools: NumPy (38 files), SciPy (17 files), Matplotlib (11 files), Numba (11 files), pandas (7 files), h5py (4 files), scikit-learn (1 file)

Availability: 1 check, the latest on 27 September 2026: the link answers

27 September 2026: the link answers

70 files

LinuxInstall.sh, Shell, 2 lines
LinuxLaunch.sh, Shell, 2 lines
Notebooks/Classifier Tests Multi animal.ipynb, Jupyter, 1,482 lines
Notebooks/Classifier Tests Original.ipynb, Jupyter, 521 lines
Notebooks/ClassifierCV.ipynb, Jupyter, 102 lines
Notebooks/Data Report.ipynb, Jupyter, 371 lines
Notebooks/Demo file creation 1.ipynb, Jupyter, 71 lines
Notebooks/Demo file creation.ipynb, Jupyter, 142 lines
Notebooks/FeatureExtractor tests.ipynb, Jupyter, 665 lines
Notebooks/License test.ipynb, Jupyter, 140 lines
Notebooks/Memap and demo file creation 1.ipynb, Jupyter, 149 lines
Notebooks/Multithreading examples.ipynb, Jupyter, 268 lines
Notebooks/Testing for gui 1.ipynb, Jupyter, 118 lines
Notebooks/Tests for annotations.ipynb, Jupyter, 842 lines
Notebooks/copy ndf fiels.ipynb, Jupyter, 53 lines
Notebooks/overlap add and overlap save tests.ipynb, Jupyter, 193 lines
UnitTestFiles/1.py, Python, 10 lines
pyecog2/ProjectClass.py, Python, 715 lines
pyecog2/__init__.py, Python, 1 line
pyecog2/__main__.py, Python, 2 lines
pyecog2/annotation_table_widget.py, Python, 625 lines
pyecog2/annotations_module.py, Python, 420 lines
pyecog2/classifier.py, Python, 554 lines
pyecog2/coding_tests/ParameterTreeExample.py, Python, 177 lines
pyecog2/coding_tests/ParameterTreeTest.py, Python, 109 lines
pyecog2/coding_tests/ParameterTreeTest2.py, Python, 121 lines
pyecog2/coding_tests/ProgressBarTests.py, Python, 36 lines
pyecog2/coding_tests/PySide_Test.py, Python, 22 lines
pyecog2/coding_tests/TableTests.py, Python, 63 lines
pyecog2/coding_tests/TableTests2.py, Python, 30 lines
pyecog2/coding_tests/WPTacquisition.py, Python, 176 lines
pyecog2/coding_tests/__init__.py, Python, 1 line
pyecog2/coding_tests/dock_tests.py, Python, 109 lines
pyecog2/coding_tests/logging_tests.py, Python, 19 lines
pyecog2/coding_tests/logging_tests_submodule.py, Python, 5 lines
pyecog2/coding_tests/pyqtgraph_examples.py, Python, 123 lines
pyecog2/coding_tests/save_settings.py, Python, 90 lines
pyecog2/coding_tests/testing_menu.py, Python, 32 lines
pyecog2/deprecated/__init__.py, Python, 1 line
pyecog2/deprecated/adafruit_notofications.py, Python, 132 lines
pyecog2/deprecated/gui_main.py, Python, 129 lines
pyecog2/deprecated/old__forref_PyecogCurvePlotItem.py, Python, 268 lines
pyecog2/feature_extractor.py, Python, 201 lines
pyecog2/h5loader.py, Python, 107 lines
pyecog2/hmm_pyecog.py, Python, 333 lines
pyecog2/license.py, Python, 159 lines
pyecog2/logging_aux.py, Python, 24 lines
pyecog2/main.py, Python, 850 lines
pyecog2/ndf_converter.py, Python, 761 lines
pyecog2/paired_graphics_view.py, Python, 739 lines
pyecog2/pyecog_plot_item.py, Python, 509 lines
pyecog2/pyqtgraph_classes.py, Python, 1 line
pyecog2/special_features.py, Python, 19 lines
pyecog2/spectrotools.py, Python, 241 lines
pyecog2/tree_model_and_nodes.py, Python, 431 lines
pyecog2/tree_widget.py, Python, 219 lines
pyecog2/ui_elements/AnnotationParameterTree.py, Python, 188 lines
pyecog2/ui_elements/ClassifierGUI.py, Python, 410 lines
pyecog2/ui_elements/FFTWidget.py, Python, 96 lines
pyecog2/ui_elements/FeatureExtractorGUI.py, Python, 251 lines
pyecog2/ui_elements/NDFConverterGUI.py, Python, 270 lines
pyecog2/ui_elements/PlotControlsWidget.py, Python, 132 lines
pyecog2/ui_elements/ProjectGUI.py, Python, 247 lines
pyecog2/ui_elements/VideoPlayerWidget.py, Python, 254 lines
pyecog2/ui_elements/WaveletWidget.py, Python, 489 lines
pyecog2/ui_elements/__init__.py, Python, 1 line
pyecog2/ui_elements/pyecogParameterTree.py, Python, 44 lines
setup.py, Python, 36 lines
LICENSE, License, 674 lines
README.md, Text, 29 lines

At the source: github.com/KullmannLab/pyecog2

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;
68 scripts, each with its path and the digest of its content;
no match between paragraphs and code yet;
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Data

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

Data sharing statement

The datasets generated and analysed during this study are available from the corresponding authors upon reasonable request (email: ; ; ). PyECoG software is available at: https://github.com/KullmannLab/pyecog2.

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 2, 28 September 2026

Authors: added Qimin Wu (0009-0003-8879-9119); Vincent Magloire (0000-0003-4006-7042); removed Qimin Wu; Vincent Magloire

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 13 authors, 4 keywords, 12 MeSH terms, 7 funders, 87 references, 23 RRIDs.

Cite

This paper

Richardson, A., Mercier, M. S., Shimoda, Y., Graham, R. T., Leite, M., Garcia, A., Muller, M., Bond, S. A., Grozdanova, M., Wu, Q., Lieb, A., Kullmann, D. M., & Magloire, V. (2026). Neuron-derived neurotrophic factor-positive interneurons: a cellular target for anti-seizure therapies. EBioMedicine, 130, 106362. https://doi.org/10.1016/j.ebiom.2026.106362

BibTeX

@article{richardson2026neuron, author = {Richardson, Amy and Mercier, Marion S. and Shimoda, Yoshiteru and Graham, Robert T. and Leite, Marco and Garcia, Alejandro and Muller, Maud and Bond, Suraya A. and Grozdanova, Maria and Wu, Qimin and Lieb, Andreas and Kullmann, Dimitri M. and Magloire, Vincent}, title = {{Neuron-derived neurotrophic factor-positive interneurons: a cellular target for anti-seizure therapies}}, journal = {EBioMedicine}, year = {2026}, month = jul, volume = {130}, pages = {106362}, publisher = {Elsevier}, issn = {2352-3964}, doi = {10.1016/j.ebiom.2026.106362}, url = {https://doi.org/10.1016/j.ebiom.2026.106362}, pmid = {42475878}, pmcid = {PMC13393760} }

RIS

TY - JOUR AU - Richardson, Amy AU - Mercier, Marion S. AU - Shimoda, Yoshiteru AU - Graham, Robert T. AU - Leite, Marco AU - Garcia, Alejandro AU - Muller, Maud AU - Bond, Suraya A. AU - Grozdanova, Maria AU - Wu, Qimin AU - Lieb, Andreas AU - Kullmann, Dimitri M. AU - Magloire, Vincent TI - Neuron-derived neurotrophic factor-positive interneurons: a cellular target for anti-seizure therapies T2 - EBioMedicine J2 - EBioMedicine PY - 2026 DA - 2026/07/21 VL - 130 SP - 106362 SN - 2352-3964 PB - Elsevier DO - 10.1016/j.ebiom.2026.106362 UR - https://doi.org/10.1016/j.ebiom.2026.106362 LA - en ER -

CSL-JSON

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