Bio Computers
Context:
- Johns Hopkins University researchers recently revealed their ambitions for “organoid intelligence,” or OI, a potentially revolutionary new branch of study that aims to create “biocomputers” (JHU).
About biocomputers:
- When brain cultures created in the lab are coupled with actual sensors and input/output devices, we can use real human brain cells to make computing “more brain-like”.
- The biological hardware that powers computational systems in biocomputers is called organoids, or groups of living tissue created from stem cells that act like organs.
This technology’s underlying principle is:
- It has proven difficult to fully understand how the human brain works. Rat brains have historically been used to study various neurological conditions that affect humans. Rodents and humans have significantly diverse brain structures and functions, as well as very varied cognitive capacities, even though rats provide a more approachable and straightforward model for understanding the brain than humans.
- Scientists are developing brain organoids, or 3D cultures of brain tissue, in the lab in an effort to develop systems that are more applicable to humans. These “mini-brains” (up to 4 mm in size) mimic many of the structural and functional features of a developing human brain and are created from human stem cells. Researchers are now using them to test drugs and look into how the human brain develops.
- Because the human brain also requires other sensory inputs (touch, smell, vision, etc.) to mature into the complex organ that it is, brain organoids made in the lab are not sophisticated enough. Also, the organoids’ current lack of blood circulation limits their capacity to grow.
OI and biocomputers’ relevance
- According to experts, it will enable more complex learning than a conventional computer, resulting in richer feedback and better decision-making than AI. The technology can understand the biological basis of human cognition, learning, and many neurological disorders by utilising the brain’s processing power.
With regards to the newest “bio-computer”:
- JHU researchers intend to create “bio-computers” by merging brain organoids with cutting-edge computing methods. They plan to combine the organoids with machine learning by growing the organoids inside flexible structures coupled with multiple electrodes (similar to the ones used to take EEG readings from the brain).
- These structures will be able to record the neural firing patterns as well as deliver electrical stimulation to mimic sensory experiences. The response pattern of the neurons and their influence on human behaviour or biology will next be examined using machine learning techniques.
- A microelectrode array that can record and stimulate human neurons was created recently by researchers. By providing either positive or negative electric feedback from the sensors, they were able to train the neurons to produce an electrical pattern that would be generated if the neurons were playing table tennis.
Potential applications of “bio-computers”
- Despite being slower than computers, for example, at elementary mathematics, human brains do better than machines when processing sophisticated information.
- Brain organoids can also be made using stem cells from people who have cognitive or neurodegenerative disorders. By contrasting the information on brain structure, connections, and signalling between “healthy” and “patient-derived” organoids, one can learn about the basic foundations of human cognition, learning, and memory.
- They may also help with the biology of and treatment development for severe neurodegenerative and neuro developmental diseases like Parkinson’s disease and microcephaly.
Advancing the use of commercial biocomputers:
- Today’s brain organoids have an average cell count of less than 100,000 and a diameter of less than 1 mm, making them around three millionths the size of a real human brain. So, expanding the brain’s organoid and introducing non-neuronal cells involved in biological learning will both improve the brain’s computational capacity.
- Microfluidic systems will also need to be developed by researchers to transport nutrients, trash, and oxygen. To store and analyse the massive amounts of data (i.e., brain recordings from each neuron and link) that these hybrid systems would generate, researchers will need to deploy “Big Data” infrastructure.
- They will also need to create and use cutting-edge analytical techniques to link the structural and functional changes in the brain organoids to the many output variables (with the aid of machines).
- The present challenge for this technology is the development of long-term memory. The use of these to patient-derived brain organoids, such as donors for autism and Alzheimer’s disease, is then already envisaged. Drug development could gain in this decade.
Conclusion:
- OI and biocomputers are emerging technologies that face similar challenges. It is also advised to form an ethics team to identify, examine, and assess moral dilemmas when they arise in relation to this technology.
