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Artificial intelligence: a chip has been developed that mimics brain activity
Last reviewed: 01.07.2025
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For decades, scientists have dreamed of creating a computer system that could replicate the human brain's talent for learning new problems.
Scientists at the Massachusetts Institute of Technology have now taken a major step toward achieving this goal by developing a computer chip that mimics the way the brain's neurons adapt in response to new information. This phenomenon, known as plasticity, is thought to underlie many brain functions, including learning and memory.
With about 400 transistors, the silicon chip can mimic the activity of a single brain synapse - the connection between two neurons that facilitates the transfer of information from one neuron to another. The researchers expect the chip to help neuroscientists learn much more about how the brain works, and could also be used to develop neural prostheses such as artificial retinas, says project leader Chi-Sang Poon.
Modeling synapses
There are about 100 billion neurons in the brain, each of which forms synapses with many other neurons. A synapse is the space between two neurons (presynaptic and postsynaptic neurons). The presynaptic neuron releases neurotransmitters such as glutamate and GABA, which bind to receptors on the cell's postsynaptic membrane, activating ion channels. The opening and closing of these channels causes the cell's electrical potential to change. If the potential changes dramatically enough, the cell fires an electrical impulse called an action potential.
All synaptic activity depends on ion channels, which control the flow of charged ions such as sodium, potassium, and calcium. These channels are also key in two processes known as long-term potentiation (LTP) and long-term depression (LTD), which strengthen and weaken synapses, respectively.
The scientists designed their computer chip so that the transistors can mimic the activity of different ion channels. While most chips operate in a binary on/off mode, the electrical currents on the new chip flow through the transistors in an analog mode. A gradient of electrical potential causes the current to flow through the transistors in the same way that ions flow through ion channels in a cell.
"We can tune the parameters of the circuit to focus on a particular ion channel," Poon says. "Now we have a way to capture every ion process that happens in a neuron."
The new chip represents "a significant advance in efforts to study biological neurons and synaptic plasticity on a CMOS [complementary metal-oxide-semiconductor] chip," says Dean Buonomano, a professor of neurobiology at the University of California, Los Angeles, adding that "the level of biological realism is impressive.
The scientists plan to use their chip to create systems for simulating specific neural functions, such as the visual processing system. Such systems could be much faster than digital computers. Even high-performance computer systems take hours or days to simulate simple brain circuits. With the chip's analog system, the simulations are faster than in biological systems.
Another potential use for these chips is to customize interactions with biological systems, such as artificial retinas and brains. In the future, these chips could become building blocks for artificial intelligence devices, Poon says.