ArticleNature communications2023
Structural plasticity for neuromorphic networks with electropolymerized dendritic PEDOT connections.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
7 citing papers in PubMed.
- Analysis and Applications of Neuromorphic Memristors in Artificial Intelligence Computing.Nano-micro letters · 2026Review
- Materials and System Design for Self-Decision Bioelectronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Chemical control for the morphogenesis of conducting polymer dendrites in water.RSC applied polymers · 2026Article
- Electropolymerization of Organic Mixed Ionic-Electronic Conductors: Fundamentals and Applications in Bioelectronics.Chemical reviews · 2026Review
- Brain-Inspired Polymer Dendrite Networks for Morphology-Dependent Computing Hardware.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Memristive Ion Dynamics to Enable Biorealistic Computing.Chemical reviews · 2025Review
- Protein swarm-based cause-effect analysis: effects of microRNAs on cooperation networks linking COVID-19 infections, atherosclerosis, and Alzheimer's disease.Frontiers in cardiovascular medicine · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Neural networks are powerful tools for solving complex problems, but finding the right network topology for a given task remains an open question. Biology uses neurogenesis and structural plasticity to solve this problem. Advanced neural network algorithms are mostly relying on synaptic plasticity and learning. The main limitation in reconciling these two approaches is the lack of a viable hardware solution that could reproduce the bottom-up development of biological neural networks. Here, we show how the dendritic growth of PEDOT:PSS-based fibers through AC electropolymerization can implement structural plasticity during network development. We find that this strategy follows Hebbian principles and is able to define topologies that leverage better computing performances with sparse synaptic connectivity for solving non-trivial tasks. This approach is validated in software simulation, and offers up to 61% better network sparsity on classification and 50% in signal reconstruction tasks.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.