The Internet has been buzzing this week with the story of researchers in France developing a “hybrid nanoparticle-organic transistor that can mimic the main functionalities of a synapse.”
You may have seen a number of different versions of this story this week, but I recommend Nanowerk’s coverage of it, which I quoted above. Nanowerk manages to bring some context to the research and how nanotechnologies have been used to try and duplicate some of the functions of the human brain and apply them to computer science, most notably DARPA’s SyNAPSE project.
In addition, Nanowerk has an interview with the lead researcher, Dominique Vuillaume, a research director at CNRS and head of the Molecular Nanostructures & Devices group at the Institute for Electronics Microelectronics and Nanotechnology (IEMN) that reveals it as a far more significant piece of research that I had originally thought when I read the first news accounts.
The researchers have dubbed their device NOMFET (Nanoparticle Organic Memory Field-Effect Transistor), and as the name indicates it is an organic transistor, based on pentacene and gold nanoparticles.
The details of how the transistor work as described in the Nanowerk article explains the ingenious way that the researchers were able to mimic the “short-term plasticity” of a synapse.
While this is a remarkable development it would not be quite as significant to the development of neuron-inspired computer systems if it were not for its big improvement on silicon-based CMOS chips in duplicating neural networks.
As quoted in the article, Vuillaume says “…even if silicon CMOS chips have been designed and fabricated to emulate the brain behaviors, this approach is limited because it takes several – at least seven – silicon transistors to build an electronic synapse. Here, we did the same job with a single device."
When one considers that there are 10,000 synapses for every neuron in the human brain, reducing size becomes increasingly important if your aim is duplicating the architecture of the human brain.