Electronic synapse (NSF and NRI)
We are developing nanoscale electronic devices and circuits to emulate the functions of the synapses and neurons of the brain. The goal is to use nanoscale electronic devices to do information processing using algorithms and methods inspired by how the brain works. Currently, we are using phase change memory and metal oxide RRAM to perform gray-scale analog programming of the resistance values. These electronic emulations of the synapse are then connected in a neural network to process information and achieve simple learning behavior.
In the past few years, we have been able to emulate a variety of spike-timing dependent plasticity (STDP) behaviors of the biological synapse using these nanoscale electronic devices. Using larger arrays of electronic synapses, we experimentally demonstrated brain-like associative learning. This electronic synaptic grid allows us to study how device variations affect system performance. The stochastic nature of the switching process of these devices has a rich set of properties that may be utilized for many applications.
In the future, it may be possible to use these nanoscale electronic devices to study how the brain works, by interfacing these devices directly with biological entities. Besides, they might allow realization of intelligent machines in a more energy efficient way.