A new electronic device can developed at the University of Michigan can directly model the behaviors of a synapse, which is a connection between two neurons.
For the first time, the way that neurons share or compete for resources can be explored in hardware without the need for complicated circuits.
"Neuroscientists have argued that competition and cooperation behaviors among synapses are very important. Our new memristive devices allow us to implement a faithful model of these behaviors in a solid-state system," said Wei Lu, U-M professor of electrical and computer engineering and senior author of the study in Nature Materials.
Memristors are electrical resistors with memory—advanced electronic devices that regulate current based on the history of the voltages applied to them. They can store and process data simultaneously, which makes them a lot more efficient than traditional systems. They could enable new platforms that process a vast number of signals in parallel and are capable of advanced machine learning.
The memristor is a good model for a synapse. It mimics the way that the connections between neurons strengthen or weaken when signals pass through them. But the changes in conductance typically come from changes in the shape of the channels of conductive material within the memristor. These channels—and the memristor's ability to conduct electricity—could not be precisely controlled in previous devices.
Now, the U-M team has made a memristor in which they have better command of the conducting pathways.They developed a new material out of the semiconductor molybdenum disulfide—a "two-dimensional" material that can be peeled into layers just a few atoms thick. Lu's team injected lithium ions into the gaps between molybdenum disulfide layers.