A diagram of a synapse receiving a signal from one of the connecting neurons. The new device is the first to mimic this process directly, without the need for software or complicated circuits. (Xiaojian Zhu, Nanoelectronics Group, U-M)
A new electronic device developed at U-M can directly model the behaviors of a synapse, which is a connection between two neurons. “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. These memristors could enable new platforms that process a vast number of signals in parallel and are capable of advanced machine learning.
Memristors are electrical resistors with memory that can store and process data simultaneously, which makes them a lot more efficient than traditional systems. However, 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.
