Nanotechnology's road to artificial brains

(Nanowerk Spotlight) If you think that building an artificial human brain is science fiction, you are probably right – for now. But don't think for a moment that researchers are not working hard on laying the foundations for what is called neuromorphic engineering – a new interdisciplinary discipline that includes nanotechnologies and whose goal is to design artificial neural systems with physical architectures similar to biological nervous systems.

One of the key components of any neuromorphic effort is the design of artificial synapses. The human brain contains vastly more synapses than neurons – by a factor of about 10,000 – and therefore it is necessary to develop a nanoscale, low power, synapse-like device if scientists want to scale neuromorphic circuits towards the human brain level.

Recently, we reported the development of a hybrid nanoparticle-organic transistor that can mimic the main functionalities of a synapse ("Scientists use nanotechnology to try building computers modeled after the brain").

New research now suggests that memristor devices are capable of emulating the biological synapses with properly designed CMOS neuron components. A memristor is a two-terminal electronic device whose conductance can be precisely modulated by charge or flux through it. It has the special property that its resistance can be programmed (resistor) and subsequently remains stored (memory). Researchers at the University of Michigan (UM) have now demonstrated that a memristor can connect conventional circuits and support a process that is the basis for memory and learning in biological systems. This work was part of a DARPA-sponsored project with HRL Laboratories being the lead institution on the UM team.

"In a mammalian brain the computing units, neurons, are connected to each other through programmable junctions called synapses," Wei Lu, an assistant professor in the Department of Electrical Engineering and Computer Science, explains to Nanowerk. "The synaptic weight modulates how signals are transmitted between neurons and can in turn be precisely adjusted by the ionic flow through the synapse. A memristor by definition is a resistive device with inherent memory. It is in fact very similar to a synapse – they are both two-terminal devices whose conductance can be modulated by external stimuli with the ability to store (memorize) the new information."

Reporting their findings in a recent issue of Nano Letters ("Nanoscale Memristor Device as Synapse in Neuromorphic Systems"), Lu and his group fabricated a nanoscale silicon-based memristor to mimic a synapse.