Igniting scientific sparks: How public imagination drives research breakthroughs


The impact of public engagement on biological neuronal networks and reservoir computing research

Dr. Sumi, the first author of this research paper

In cutting-edge research, capturing the general audience’s imagination can lead to unexpected exposure and collaborations.

In a 2023 article, Sumi et al. from AIMR combined optogenetics, calcium imaging techniques, and reservoir computing modeling to investigate how the functional modularity of biological neuronal networks (BNNs) influenced their information processing capabilities—demonstrating that, when integrated into reservoir computing frameworks, BNNs can identify commonalities and patterns in diverse inputs, acting as general filters1.

Having received initial responses within the research community, the AIMR team followed up with a press release2 that triggered an unexpectedly enthusiastic reaction from the general public.

“In describing how we designed, grew, tested, and modeled our BNNs using everyday language and compelling figures, our press release resonated with the public, providing a futuristic image of the science we are doing,” says Sumi.

The response to the paper continued to grow, leading to an invitation for the researchers to appear on the Japanese science-documentary TV program Galileo X.

“When we wrote the press release, we did not expect to appear on television,” says Sumi. “In retrospect, the recent spread of technologies that mimic human behavior such as ChatGPT must have helped attract the interest in biomimetic computation.”

The increase in visibility further shaped the next steps of this research. A future direction involves a new collaboration with the Chiba lab at AIMR, aiming to elucidate the link between neuronal dynamics and functionality within the reservoir computing framework.

(Author: Patrick Han)


  1. Sumi T., Yamamoto H., Katori Y., Ito K., Konno T., Sato S. and Hirano-Iwata A. Biological neurons act as generalization filters in reservoir computing Proceedings of the National Academy of Sciences 120, e2217008120 (2023). | article
  2. Yamamoto H. (2023, June 29th). Artificially cultured brains improve processing of time series data [Press Release]. | article

This research highlight has been approved by the authors of the original article and all information and data contained within has been provided by said authors.