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Can a bacteria brain play Ping-pong and Go?

   Department of Biomedical Engineering

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Although initial discussions regarding bioelectricity and its role in the fundamental understanding of various cellular behaviours took place in the 1970s, the bioelectrical view of cells as a more general concept has remained limited to the fringes of biological research for five decades. Recent studies in diverse systems have shown that bioelectrical signals are at the core of cell–cell communication in micro-organisms, plants and animals. Bioelectricity can underpin efficient growth and antibiotic resistance in bacterial biofilms and organisation, morphogenesis and regeneration in mammalian and plant tissues. These findings, together with the bioengineering solution that externally-applied electric fields can modulate multicellular processes have resulted in the recent proposition that microorganisms and multicellular organisation more broadly should be studied as a bioelectrical paradigm. In a bacteria colony, individual bacteria cells can send electric signals, sharing information from the surrounding environment, and regulate their metabolic cycles and control the morphology (body) of a whole colony.

Those principles in bioelectricity have been used in Artificial Intelligence (AI), a strong paradigm which can convert data streams into problem-solving and decision-making machines of the human mind.

Using a bacteria colony, we aim to develop a bacteria brain which can play a Ping-pong game and Go (surrounding stone game).

To this end, electric signals from the bacteria are recorded to generate a series of commands to play the games, and information from the games is feedback to the colony in the form of electric stimulation. Closing the input-output loops around the bacteria colony, we hypothesise that pathways of information processing will emerge, due to self-organisation and the free energy principle of neuronal systems.

Furthermore, we will pave a way to finding a universal algorithm of biological systems for learning how to process information to solve problems.

Electric communication in bacterial communities

Bacterial communities respond to environmental factors to survive in a changing environment. Demonstrating rich spatial patterns (body morphology), a bacterial community can control its shape as a whole colony to optimise nutrition intake or minimise the effect of antibiotics. Recent studies have shown that responding to nutrition levels, bacteria cells at the periphery send electric signals to the centre of the colony aggregation, altering the membrane potential to suppress their metabolic cycles. In other words, they electrically communicate with each other to pass sufficient nutrition to the centre, avoiding its depletion around the centre. In summary, individual bacteria cells can sense environmental factors, send electric signals to and from each other, and a whole colony goes through a decision-making process to choose a body morphology for adaptation.

Dr. Hayashi’s research spans the areas of complex physical systems, behavioural science and neuroscience, with specific expertise in: 1) non-equilibrium dynamics governing adaptive behaviour in physical and living systems; 2) neural/behavioural mechanisms of the closed brain-body loop for various living systems; and 3) mathematical models underpinning behaviour and activity of neural networks. Techniques include physio-chemical experiments, microbiological experiments, machine learning, electroencephalogram (EEG) measurement, and mathematical modelling. His lab’s website is https://www.sites.google.com/site/complexlivingmachineslab/.

School of Biological Sciences, University of Reading: 

The University of Reading, located west of London, England, provides world-class research education programs. The University’s main Whiteknights Campus is set in 130 hectares of beautiful parkland, a 30-minute train ride to central London and 40 minutes from London Heathrow airport. 

Our School of Biological Sciences conducts high-impact research, tackling current global challenges faced by society and the planet. Our research ranges from understanding and improving human health and combating disease, through to understanding evolutionary processes and uncovering new ways to protect the natural world. In 2020, we moved into a stunning new ~£60 million Health & Life Sciences building. This state-of-the-art facility is purpose-built for science research and teaching. It houses the Cole Museum of Zoology, a café and social spaces.


Applicants should have a good degree (minimum of a UK Upper Second (2:1) undergraduate degree or equivalent) in System/Synthetic Biology, Engineering and Biomedical Engineering, Nonequilibrium Physics, Physics of Complex Systems, AI, or a related discipline. Applicants will also need to meet the University’s English Language requirements. We offer pre-sessional courses that can help with meeting these requirements.

How to apply:

Submit an application for a PhD in Biological Sciences at http://www.reading.ac.uk/pgapply.


Further information:




Dr. Yoshikatsu Hayashi, email:    

The supervisory team comprises Dr Hayashi and Dr Munehiro Asally from the University of Warwick.

Funding Notes

We welcome applications from self-funded students worldwide for this project.
If you are applying to an international funding scheme, we encourage you to get in contact as we may be able to support you in your application.


(1) Schofield, Z., Meloni, G. N., Tran, P., Zerfass, C., Sena, G., Hayashi, Y., Grant, M., Contera, S. A., Minteer, S. D., Kim, M., Prindle, A., Rocha, P., Djamgoz, M. B. A., Pilizota, T., Unwin, P. R., Asally, M. and Soyer, O. S. (2020) Bioelectrical understanding and engineering of cell biology. Journal of the Royal Society Interface, 17 (166). 20200013. ISSN 1742-5662 doi: https://doi.org/10.1098/rsif.2020.0013
(2) Stratford, J. P., Edwards, C. L. A., Ghanshyam, M. J., Malyshev, D., Delise, M. A., Hayashi, Y. and Asally, M. (2019) Electrically induced bacterial membrane-potential dynamics correspond to cellular proliferation capacity. Proceedings of the National Academy of Sciences of the United States of America, 116 (19). pp. 9552-9557. ISSN 1091-6490 doi: https://doi.org/10.1073/pnas.1901788116

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