How Neuromorphic Microstructures Control In Vitro Early-Stage Neuronal Outgrowth.
The 3 matches
- [1] § Experimental Section › Image Processing and Analysis › Analysis of Neurites Outgrowth ↔ preprocessing_bulk_vids.py, lines 881–941 · score 0.70 · distance matrix, custom distance, pairwise, DBSCAN, vector, pillar
- [2] § Experimental Section › Image Processing and Analysis › Analysis of Neurites Outgrowth ↔ post_processing_data_analysis_singlecsv.py, lines 398–483 · score 0.66 · movement dynamics, DataFrame, conversion factor, median, displacements, min
- [3] § Experimental Section › Image Processing and Analysis › Analysis of Neurites Outgrowth ↔ preprocessing_bulk_vids.py, lines 480–521 · score 0.56 · instantaneous velocities, vector, interval, displacements, min, Centroid
Paper
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The authors' code
Python · 1,596 lines · 74 KB · no license · 2 matches
preprocessing_bulk_vids.py at commit 9389c9a, no license · at the source
Overview
- Tissue Electronics, Istituto Italiano di Tecnologia, Naples, Italy
- Dipartimento di Chimica, Materiali e Produzione Industriale, Università di Napoli Federico II, Naples, Italy
- Neuroelectronic Interfaces, Faculty of Electrical Engineering and IT, RWTH Aachen, Aachen, Germany
- Institute for Biological Information Processing‐Bioelectronics (IBI‐3), Forschungszentrum Juelich, Juelich, Germany
Abstract
Neuromorphic biomaterials represent a novel class of materials designed to replicate the architecture and functionality of neuronal structures, offering new opportunities in tissue engineering and bioelectronics. By mimicking the complex microenvironment of native neural tissue, biomimetic microstructures provide physical scaffolding to support and guide neuronal processes, with potential applications in chip‐based platforms for monitoring and stimulating neuronal networks. However, achieving precise control over the morphology of neuromorphic materials and understanding their influence on early‐stage neuronal development are remaining challenges. In this study, we present biomimetic microstructure arrays, fabricated via two‐photon polymerization, that emulate the diverse morphologies and spatial arrangements of dendritic spines. These structures enable the investigation of neuronal responses at the early developmental stage, focusing on key processes such as cell adhesion, neuronal polarity, growth cone dynamics, and network formation.
Reproduced under the paper's license (CC BY), from the paper cited above.
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CHARLESProtocol2/Neurite-Growth-Analysis-Toolkit
9389c9a0d7707c3c47207ccda66ad36310333fd5, 26 November 2025Availability: 1 check, the latest on 28 September 2026: the link answers
- 28 September 2026: the link answers
8 files, not copied: shown from their source
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ator.py — Python, 237 lines, shown from its source - fluorescent_image_analys
is.py — Python, 535 lines, shown from its source - fluorescent_images_data_
analysis.py — Python, 713 lines, shown from its source - post_processing_data_ana
lysis_singlecsv.py — Python, 1,387 lines, 1 match, shown from its source - post_processing_mov_dyna
mics.py — Python, 1,998 lines, shown from its source - preprocessing_bulk_vids.
py — Python, 1,596 lines, 2 matches, shown from its source - preprocessing_helpers.py
— Python, 136 lines, shown from its source - README.md — Text, 84 lines, shown from its source
EstherMatamoros/ProteinExpression
1f3196f1d7c8c4d3dea63eb37b9d3b945402aa6c, 10 September 2024Availability: 1 check, the latest on 28 September 2026: the link answers
- 28 September 2026: the link answers
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alysis.py — Python, 66 lines, shown from its source - image_processing.py — Python, 440 lines, shown from its source
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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.
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Data
No dataset and no data link were found in the paper.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Reproduced under the paper's license (CC BY), from the paper cited above.
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Version 1, 28 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 5 keywords, 9 MeSH terms, 57 references.
Cite
This paper
Latte Bovio, C., Matamoros, E., Mollo, V., Mariano, A., Criscuolo, V., & Santoro, F. (2026). How Neuromorphic Microstructures Control In Vitro Early-Stage Neuronal Outgrowth. Advanced science (Weinheim, Baden-Wurttemberg, Germany), 13(33), e10822. https://
BibTeX
@article{lattebovio2026h
author = {Latte Bovio, Claudia and Matamoros, Esther and Mollo, Valentina and Mariano, Anna and Criscuolo, Valeria and Santoro, Francesca},
title = {{How Neuromorphic Microstructures Control In Vitro Early-Stage Neuronal Outgrowth}},
journal = {Advanced science (Weinheim, Baden-Wurttemberg, Germany)},
year = {2026},
month = may,
volume = {13},
number = {33},
pages = {e10822},
publisher = {Wiley},
issn = {2198-3844},
doi = {10.1002/
url = {https://
pmid = {42154454},
pmcid = {PMC13271619}
}
RIS
TY - JOUR
AU - Latte Bovio, Claudia
AU - Matamoros, Esther
AU - Mollo, Valentina
AU - Mariano, Anna
AU - Criscuolo, Valeria
AU - Santoro, Francesca
TI - How Neuromorphic Microstructures Control In Vitro Early-Stage Neuronal Outgrowth
T2 - Advanced science (Weinheim, Baden-Wurttemberg, Germany)
J2 - Adv Sci (Weinh)
PY - 2026
DA - 2026/
VL - 13
IS - 33
SP - e10822
SN - 2198-3844
PB - Wiley
DO - 10.1002/
UR - https://
LA - en
ER -
CSL-JSON
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