New Artificial Synapse Communicates with Living Cells

In 2017, Stanford University researchers created an artificial version of a synapse. In 2019, the team assembled nine of their artificial synapses together in an array, showing that they could be simultaneously programmed to mimic the parallel operation of the brain. Now, in a paper published today in Nature Materials, they have tested the first biohybrid version of their artificial synapse and demonstrated that it can communicate with living cells.

"This paper really highlights the unique strength of the materials that we use in being able to interact with living matter," said Alberto Salleo, co-senior author of the paper. "The cells are happy sitting on the soft polymer. But the compatibility goes deeper: These materials work with the same molecules neurons use naturally."

While other brain-integrated devices require an electrical signal to detect and process the brain's messages, the communications between this device and living cells occur through electrochemistry—as though the material were just another neuron receiving messages from its neighbor.

The biohybrid artificial synapse consists of two soft polymer electrodes, separated by a trench filled with electrolyte solution—which plays the part of the synaptic cleft that separates communicating neurons in the brain. When living cells are placed on top of one electrode, neurotransmitters that those cells release can react with that electrode to produce ions. Those ions travel across the trench to the second electrode and modulate the conductive state of this electrode. Some of that change is preserved, simulating the learning process occurring in nature.

"In a biological synapse, essentially everything is controlled by chemical interactions at the synaptic junction. Whenever the cells communicate with one another, they're using chemistry," said Scott Keene, co-lead author of the paper. "Being able to interact with the brain's natural chemistry gives the device added utility."

This process mimics the same kind of learning seen in biological synapses, which is highly efficient in terms of energy because computing and memory storage happen in one action. In more traditional computer systems, the data is processed first and then later moved to storage.

Now that the researchers have successfully tested their design, they are figuring out the best paths for future research, which could include work on brain-inspired computers, brain-machine interfaces, medical devices or new research tools for neuroscience. Already, they are working on how to make the device function better in more complex biological settings that contain different kinds of cells and neurotransmitters.