Researchers plan supercomputers that are powered by human brain cells
Johns Hopkins University researchers have outlined plans for a "bio-computer" that is highly feasible in our lifetime.
"Computing and artificial intelligence have been driving the technology revolution, but they are reaching a ceiling," Thomas Hartung, a professor of environmental health sciences at the Johns Hopkins Bloomberg School of Public Health and Whiting School of Engineering, who is spearheading the work, said in a statement.
"Biocomputing is an enormous effort of compacting computational power and increasing its efficiency to push past our current technological limits," he said.
The plans, involving a "bio-computer" powered by human brain cells, are detailed in the journal Frontiers in Science.
A futuristic computer built with brain organoids
Hartung and colleagues have been working with tiny brain organoids, lab-grown tissue that resembles fully-grown organs. Such research isn't new and has existed in the past two decades to experiment on kidneys, lungs, and other organs without resorting to human or animal testing.
Such work helps them hack the system, "doing things you cannot ethically do with human brains."
In 2012, Hartung began to grow and assemble brain cells into functional organoids using cells from human skin samples reprogrammed into an embryonic stem cell-like state. Each organoid contained about 50,000 cells. He sees a futuristic computer being built with such brain organoids.
"Computers that run on this "biological hardware" could in the next decade begin to alleviate energy-consumption demands of supercomputing that are becoming increasingly unsustainable," Hartung said.
Organoid intelligence is far away, but prep must begin now
Now, it will take decades before organoid intelligence can power systems as "smart as a mouse."
"Frontier, the latest supercomputer in Kentucky, is a $600 million, 6,800-square-foot installation. Only in June of last year, it exceeded for the first time the computational capacity of a single human brain — but using a million times more energy," said Hartung.
But scaling up the production of brain organoids and bolstering them with AI could someday help biocomputers support superior computing speed, processing power, data efficiency, and storage capabilities.
"It will take decades before we achieve the goal of something comparable to any type of computer," Hartung said. "But if we don't start creating funding programs for this, it will be much more difficult."
There's more to organoid intelligence. According to Lena Smirnova, a Johns Hopkins assistant professor of environmental health and engineering who co-leads the investigations, organoid intelligence could also revolutionize drug testing research for neurodevelopmental disorders and neurodegeneration.
"The tools we are developing towards biological computing are the same tools that will allow us to understand changes in neuronal networks specific for autism, without having to use animals or to access patients, so we can understand the underlying mechanisms of why patients have these cognition issues and impairments," she said.
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.
Researchers at Cedars-Sinai hospital in California have used single-neuron recording to discover two types of brain cells that establish boundaries between chunks of memory.