Organoid intelligence (OI): the new frontier in biocomputing and intelligence-in-a-dish

Organoid intelligence (OI): the new frontier in biocomputing and intelligence-in-a-dish. Smirnova, L., Caffo, B. S., Gracias, D. H., Huang, Q., Morales Pantoja, I. E., Tang, B., Zack, D. J., Berlinicke, C. A., Boyd, J. L., Harris, T. D., Johnson, E. C., Kagan, B. J., Kahn, J., Muotri, A. R., Paulhamus, B. L., Schwamborn, J. C., Plotkin, J., Szalay, A. S., Vogelstein, J. T., Worley, P. F., & Hartung, T. Frontiers in Science, 2023.

Paper doi abstract bibtex

Recent advances in human stem cell-derived brain organoids promise to replicate critical molecular and cellular aspects of learning and memory and possibly aspects of cognition in vitro. Coining the term “organoid intelligence” (OI) to encompass these developments, we present a collaborative program to implement the vision of a multidisciplinary field of OI. This aims to establish OI as a form of genuine biological computing that harnesses brain organoids using scientific and bioengineering advances in an ethically responsible manner. Standardized, 3D, myelinated brain organoids can now be produced with high cell density and enriched levels of glial cells and gene expression critical for learning. Integrated microfluidic perfusion systems can support scalable and durable culturing, and spatiotemporal chemical signaling. Novel 3D microelectrode arrays permit high-resolution spatiotemporal electrophysiological signaling and recording to explore the capacity of brain organoids to recapitulate the molecular mechanisms of learning and memory formation and, ultimately, their computational potential. Technologies that could enable novel biocomputing models via stimulus-response training and organoid-computer interfaces are in development. We envisage complex, networked interfaces whereby brain organoids are connected with real-world sensors and output devices, and ultimately with each other and with sensory organ organoids (e.g. retinal organoids), and are trained using biofeedback, big-data warehousing, and machine learning methods. In parallel, we emphasize an embedded ethics approach to analyze the ethical aspects raised by OI research in an iterative, collaborative manner involving all relevant stakeholders. The many possible applications of this research urge the strategic development of OI as a scientific discipline. We anticipate OI-based biocomputing systems to allow faster decision-making, continuous learning during tasks, and greater energy and data efficiency. Furthermore, the development of “intelligence-in-a-dish” could help elucidate the pathophysiology of devastating developmental and degenerative diseases (such as dementia), potentially aiding the identification of novel therapeutic approaches to address major global unmet needs.

@article{smirnova23_organ_oi,
  author =	 {Smirnova, Lena and Caffo, Brian S. and Gracias, David H. and
                  Huang, Qi and Morales Pantoja, Itzy E. and Tang, Bohao and
                  Zack, Donald J. and Berlinicke, Cynthia A. and Boyd, J. Lomax
                  and Harris, Timothy D. and Johnson, Erik C. and Kagan, Brett
                  J. and Kahn, Jeffrey and Muotri, Alysson R. and Paulhamus,
                  Barton L. and Schwamborn, Jens C. and Plotkin, Jesse and
                  Szalay, Alexander S. and Vogelstein, Joshua T. and Worley,
                  Paul F. and Hartung, Thomas},
  title =	 {Organoid intelligence (OI): the new frontier in biocomputing
                  and intelligence-in-a-dish},
  journal =	 {Frontiers in Science},
  volume =	 1,
  year =	 2023,
  url =
                  {https://www.frontiersin.org/articles/10.3389/fsci.2023.1017235},
  doi =		 {10.3389/fsci.2023.1017235},
  issn =	 {2813-6330},
  abstract =	 {Recent advances in human stem cell-derived brain organoids
                  promise to replicate critical molecular and cellular aspects
                  of learning and memory and possibly aspects of cognition in
                  vitro. Coining the term “organoid intelligence” (OI) to
                  encompass these developments, we present a collaborative
                  program to implement the vision of a multidisciplinary field
                  of OI. This aims to establish OI as a form of genuine
                  biological computing that harnesses brain organoids using
                  scientific and bioengineering advances in an ethically
                  responsible manner. Standardized, 3D, myelinated brain
                  organoids can now be produced with high cell density and
                  enriched levels of glial cells and gene expression critical
                  for learning. Integrated microfluidic perfusion systems can
                  support scalable and durable culturing, and spatiotemporal
                  chemical signaling. Novel 3D microelectrode arrays permit
                  high-resolution spatiotemporal electrophysiological signaling
                  and recording to explore the capacity of brain organoids to
                  recapitulate the molecular mechanisms of learning and memory
                  formation and, ultimately, their computational
                  potential. Technologies that could enable novel biocomputing
                  models via stimulus-response training and organoid-computer
                  interfaces are in development. We envisage complex, networked
                  interfaces whereby brain organoids are connected with
                  real-world sensors and output devices, and ultimately with
                  each other and with sensory organ organoids (e.g. retinal
                  organoids), and are trained using biofeedback, big-data
                  warehousing, and machine learning methods. In parallel, we
                  emphasize an embedded ethics approach to analyze the ethical
                  aspects raised by OI research in an iterative, collaborative
                  manner involving all relevant stakeholders. The many possible
                  applications of this research urge the strategic development
                  of OI as a scientific discipline. We anticipate OI-based
                  biocomputing systems to allow faster decision-making,
                  continuous learning during tasks, and greater energy and data
                  efficiency. Furthermore, the development of
                  “intelligence-in-a-dish” could help elucidate the
                  pathophysiology of devastating developmental and degenerative
                  diseases (such as dementia), potentially aiding the
                  identification of novel therapeutic approaches to address
                  major global unmet needs.}
}

Downloads: 0