ArticleMicrosystems & nanoengineering2026
Analysis and dynamic modeling of firing synchronization in electrically interconnected dual-compartment neuronal networks.
Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
In vitro cultured neuronal networks offer controllable experimental models for investigating neuronal information processing mechanisms and network plasticity. However, research into synchronization and functional connectivity transitions following physical electrical interconnection between isolated compartments remains elusive. This study presents a microsystem that includes a compartmentalized microchamber neuron chip (CMNC) with programmable electrical interconnection and multichannel electrophysiological recording capabilities. The microsystem is utilized to establish artificial electrical interconnection between dual-compartment neuronal networks (DCNNs). We quantitatively evaluated network functional connectivity throughout control, interconnection, and post-disconnection phases, focusing on three key dimensions: spike timing synchrony, firing activity correlation and phase coherence. The experimental data showed that the electrical interconnection had sustained effects on firing synchrony and phase coherence across the DCNNs. After disconnection, synchrony decreased but remained significantly higher than control levels, suggesting a plastic response of the neuronal networks to the electrical coupling. To bridge experimental observations with mechanistic insights, we developed an Electrical-Interconnection Wilson-Cowan Model (EI-WCM), which quantitatively links physical coupling parameters (K) to network-level integration dynamics. The integrated microsystem and dynamical model presented here provide a stable, controllable platform and approach for studying functional connectivity, synergetic interactions and plasticity of neuronal networks, demonstrating significant potential for applications in brain-computer interfaces and neuronal information processing.
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.