Information flow in cultured neuronal networks by transfer entropy.

Overview

Authors: Wataru Minoshima^1,2, Yumi Segawa¹, Chie Hosokawa¹

Department of Chemistry, Graduate School of Science, Osaka Metropolitan University, Osaka, Japan
Advanced ICT Research Institute (Kobe), National Institute of Information and Communications Technology, Kobe, Japan

Institutions: Osaka Metropolitan University (Japan); National Institute of Information and Communications Technology (Japan)

Journal: Biophysical reports, volume 6, issue 3, article 100278

Dates: received 22 May 2026; accepted 17 July 2026; published online 20 July 2026; in print September 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1016/j.bpr.2026.100278 · PMID 42476453 · PMCID PMC13476481 · OpenAlex W7169777988

Open access: gold, a free copy (OpenAlex)

Status: code on request (how the code is found and verified)

Categories: rat (organism), cellular / molecular (subfield)

Methods: Spectral & time-frequency, Statistics, Connectivity, Single-unit activity, calcium imaging

MeSH: Entropy*, Nerve Net*, Neurons*, Action Potentials, Animals, Cells, Cultured, Hippocampus, Microelectrodes, Rats (* major topic)

Topic: Neural dynamics and brain function (Cognitive Neuroscience, Neuroscience), according to OpenAlex

Funding: JSPS; JST

Citations: not cited yet (Europe PMC); 61 references in the paper

Abstract

Neurons form functional connections in neuronal networks of the brain. Neurotransmission refers to the information flow of electrical signals between neurons, and changes in the strength of this flow characterize brain functions. An evaluation method for neuronal information flow strength is necessary to elucidate the basic principles of brain function. To analyze the strength of information flow, identifying information transmission between time series of electrical spikes in neuronal networks, such as spike trains, is required. In this study, we evaluated the information flow strength in neuronal networks using transfer entropy (TE), an analysis method based on information theory, to elucidate causal relationships between two spike trains. Cultured rat hippocampal neuronal networks were used as living brain models, and extracellular monitoring of action potentials (expressed as spikes) was performed using microelectrode arrays. Spike trains of spontaneous activity and stimulus-evoked responses were measured in multiple neurons, and the causal relationship between electrode pairs was evaluated as an index of information flow between neurons using TE. From the results of spontaneous activity and evoked responses, it was suggested that TE values between electrodes increased with culture days and that the information flow strength was enhanced by network maturation. Furthermore, the correlation between TE values and neuronal population distance was evaluated using TE analysis. We found that neurons that received strong inputs slightly overlapped in their spontaneous activity and evoked responses. These findings suggest that spontaneous activity and evoked responses exhibit similar patterns in neuronal networks. In the graph theoretical analysis based on TE values, the network topology exhibited changes that strengthened information flow over 70 days in culture. Therefore, TE analysis is an effective tool for estimating the information flow between neurons based on neuronal electrical activity recorded at multiple sites.

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

Code

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Data and code availability

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 9 MeSH terms, 2 funders, 59 references.

Cite

This paper

Minoshima, W., Segawa, Y., & Hosokawa, C. (2026). Information flow in cultured neuronal networks by transfer entropy. Biophysical reports, 6(3), 100278. https://doi.org/10.1016/j.bpr.2026.100278

BibTeX

@article{minoshima2026information, author = {Minoshima, Wataru and Segawa, Yumi and Hosokawa, Chie}, title = {{Information flow in cultured neuronal networks by transfer entropy}}, journal = {Biophysical reports}, year = {2026}, month = jul, volume = {6}, number = {3}, pages = {100278}, publisher = {Elsevier}, issn = {2667-0747}, doi = {10.1016/j.bpr.2026.100278}, url = {https://doi.org/10.1016/j.bpr.2026.100278}, pmid = {42476453}, pmcid = {PMC13476481} }

RIS

TY - JOUR AU - Minoshima, Wataru AU - Segawa, Yumi AU - Hosokawa, Chie TI - Information flow in cultured neuronal networks by transfer entropy T2 - Biophysical reports J2 - Biophys Rep (N Y) PY - 2026 DA - 2026/07/20 VL - 6 IS - 3 SP - 100278 SN - 2667-0747 PB - Elsevier DO - 10.1016/j.bpr.2026.100278 UR - https://doi.org/10.1016/j.bpr.2026.100278 LA - en ER -

CSL-JSON

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