Brainoware: A Twist on Neuromorphic Computing

Saturday - December 16 2023, 10:10 UTC - 11 months ago

Brainoware is a revolutionary computer system that taps into 3D brain organoids—or "mini-brains." This setup provides an opportunity to better understand the brain’s inner workings while reducing energy costs and speeding up computation.

A tiny ball of brain cells hums with activity as it sits atop an array of electrodes. For two days, it receives a pattern of electrical zaps, each stimulation encoding the speech peculiarities of eight people. By day three, it can discriminate between speakers.

Dubbed Brainoware, the system raises the bar for biocomputing by tapping into 3D brain organoids, or "mini-brains." These models, usually grown from human stem cells, rapidly expand into a variety of neurons knitted into neural networks.

Like their biological counterparts, the blobs spark with electrical activity—suggesting they have the potential to learn, store, and process information. Scientists have long eyed them as a promising hardware component for brain-inspired computing.

This week, a team at Indiana University Bloomington turned theory into reality with Brainoware. They connected a brain organoid resembling the cortex—the outermost layer of the brain that supports higher cognitive functions—to a wafer-like chip densely packed with electrodes.

The mini-brain functioned like both the central processing unit and memory storage of a supercomputer. It received input in the form of electrical zaps and outputted its calculations through neural activity, which was subsequently decoded by an AI tool.

When trained on soundbites from a pool of people—transformed into electrical zaps—Brainoware eventually learned to pick out the "sounds" of specific people. In another test, the system successfully tackled a complex math problem that’s challenging for AI.

The system’s ability to learn stemmed from changes to neural network connections in the mini-brain—which is similar to how our brains learn every day. Although just a first step, Brainoware paves the way for increasingly sophisticated hybrid biocomputers that could lower energy costs and speed up computation.

The setup also allows neuroscientists to further unravel the inner workings of our brains.

"While computer scientists are trying to build brain-like silicon computers, neuroscientists are trying to understand the computations of brain cell cultures," wrote Drs. Lena Smirnova, Brian Caffo, and Erik C. Johnson at Johns Hopkins University who were not involved in the study. Brainoware could offer new insights into how we learn, how the brain develops, and even help test new therapeutics for when the brain falters.

A Twist on Neuromorphic Computing .

With its 200 billion neurons networked into hundreds of trillions of connections, the human brain is perhaps the most powerful computing hardware known.

Its setup is inherently different than classical computers, which have separate units for data processing and storage. Each task requires the computer shuttle data between the two, which dramatically increases computing time and energy. In contrast, both functions unite at the same physical spot in the brain.

Called synapses, these structures connect neurons into networks. Synapses learn by changing how strongly they connect with others—upping the connection strength with collaborators that help solve problems and storing the knowledge at the same spot.

The process may sound familiar. Artificial neomorphic computers, or neuromorphic devices, mimic this setup by using algorithms to change the physical structure of the computing device. And while much focus has been placed on silicon chips, brain organoids offer an exquisite form of neuromorphic hardware.