Evidence map›Paper›PMID 36925616›Full record

ReviewFrontiers in artificial intelligence2023

First Organoid Intelligence (OI) workshop to form an OI community.

Itzy E Morales Pantoja, Lena Smirnova, Alysson R Muotri, Karl J Wahlin, Jeffrey Kahn, J Lomax Boyd, David H Gracias, Timothy D Harris, Tzahi Cohen-Karni, Brian S Caffo and 32 more

Open access · goldFull text readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in artificial intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
7.6field-weighted citation impact, top 2% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Harnessing Intelligence from Brain Cells In Vitro.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2025
    Review
  5. Article
  6. Review
  7. Article
  8. Opportunities and Challenges of Brain-on-a-Chip Interfaces.Cyborg and bionic systems (Washington, D.C.) · 2025
    Review
  9. Review
  10. Engineering signalling pathways in mammalian cells.Nature biomedical engineering · 2024
    Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

42 authors at 20 institutions in 6 countries.

Itzy E Morales PantojaCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Lena SmirnovaCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Alysson R MuotriDepartment of Pediatrics and Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, San Diego, CA, United States.
Karl J WahlinViterbi Family Department of Ophthalmology & the Shiley Eye Institute, UC San Diego, La Jolla, CA, United States.
Jeffrey KahnBerman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, United States.
J Lomax BoydBerman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, United States.
David H GraciasDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States.
Timothy D HarrisDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Tzahi Cohen-KarniDepartments of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States.
Brian S CaffoDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
Alexander S SzalayDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Fang HanDepartment of Statistics and Economics, University of Washington, Seattle, WA, United States.
Donald J ZackDepartment of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Ralph Etienne-CummingsDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States.
Akwasi AkwaboahDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States.
July Carolina RomeroCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Dowlette-Mary Alam El DinCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Jesse D PlotkinCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Barton L PaulhamusDepartment of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Erik C JohnsonDepartment of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Frederic GilbertPhilosophy Program, School of Humanities, University of Tasmania, Hobart, TAS, Australia.
J Lowry CurleyAxoSim Inc., New Orleans, LA, United States.
Ben CappielloAxoSim Inc., New Orleans, LA, United States.
Jens C SchwambornLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Eric J HillSchool of Biosciences, College of Health and Life Sciences, Aston University, Birmingham, United Kingdom.
Paul RoachDepartment of Chemistry, School of Science, Loughborough University, Loughborough, Leicestershire, United Kingdom.
Daniel TorneroDepartment of Biomedical Sciences, Institute of Neuroscience, University of Barcelona, Barcelona, Spain.
Caroline KrallCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Rheinallt ParriAston Pharmacy School, College of Health and Life Sciences, Aston University, Birmingham, United Kingdom.
Fenna SilléCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Andre LevchenkoDepartment of Biomedical Engineering, Yale Systems Biology Institute, Yale University, New Haven, CT, United States.
Rabih E JabbourDepartment of Bioscience and Biotechnology, University of Maryland Global Campus, Rockville, MD, United States.
Brett J KaganCortical Labs, Melbourne, VIC, Australia.
Cynthia A BerlinickeDepartment of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Qi HuangDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States.
Alexandra MaertensCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Kathrin HerrmannCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Katya TsaiounCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Raha DastgheybDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States.
Christa Whelan HabelaDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States.
Joshua T VogelsteinDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Thomas HartungCenter for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.
Johns Hopkins University · USAston University · GBAxoSim (United States) · USJohns Hopkins University Applied Physics Laboratory · USCarnegie Mellon University · USFleet Science Center · USFoundation Center · USJanelia Research Campus · USJohns Hopkins Berman Institute of Bioethics · USJohns Hopkins Medicine · USLoughborough University · GBSidney Kimmel Comprehensive Cancer Center · USUniversitat de Barcelona · ESUniversity of California, San Diego · USUniversity of Konstanz · DEUniversity of Luxembourg · LUUniversity of Maryland Global Campus · USUniversity of Tasmania · AUUniversity of Washington · USYale University · US

Funding

Traning Program in Environmental Health SciencesT32ES007141 · NIEHS · JOHNS HOPKINS UNIVERSITY · PI Marsha Wills-Karp · 1985 to 2026
$22.2M
Statistical methods for structural and functional integration in multi-modal neuroimaging dataR01EB029977 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI CAFFO, BRIAN SCOTT · 2021 to 2024
$1.9M
NIBIB NIH HHS R01 EB029977NIEHS NIH HHS T32 ES007141
6 · The paper itself

Abstract

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Indexed as

artificial intelligencebiological computingbraincognitionelectrophysiologymicrophysiological systemsOrganoid Intelligence

Identifiers

PMID36925616
PMCPMC10013972
OpenAlexW4323309926

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read4
Read underepoch 390

Registered trials

None linked

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.