src=”/wp-content/uploads/prucnal-portrait.jpg” title=”Paul Prucnal, a Princeton
professor of electrical engineering, is leading a collaboration between researchers at the University and
Lockheed Martin, the aerospace and defense technology corporation, to develop a “photonic neuron,”
a device that uses fiber-optic circuits that transmit information a billion times faster than a human
neuron. Photo by Brian Wilson” width=”162″ />The name of the project — “photonic
neuron” — was catchy enough, but what really caught Mitchell Nahmias’ attention was the
opportunity to combine his interests in engineering and neuroscience.
Nahmias became one of seven Princeton undergraduate students to participate in a research
collaboration between the University and Lockheed Martin, the aerospace and defense technology corporation,
to produce fiber-optic-based computational devices that work similarly to neurons, but are a billion times
“I’m an electrical engineering major, but I really like biology and cognitive
science,” said Nahmias, a member of the class of 2012. “This is a cool project, a really
interesting confluence of a bunch of fields.”
If the project is successful, the new technology could allow for computer circuits that are capable
of making nearly instantaneous calculations in life-or-death situations, such as locating a terrorist from a
radio signal or deciding whether to eject a fighter pilot from a jet.
It might also allow speedy processing of huge amounts of data, such as the video signals that
currently guide the movements of robotic cars or scans of genetic data for clues to fighting diseases.
title=”Prucnal meets with the students on the research team every week to share developments on the
project and brainstorm new ideas on the laboratory whiteboard. Here he talks with Nicole Rafidi, a rising
senior. (Photo by Frank Wojciechowski)” width=”500″ />
The research is led by Paul”>http://www.princeton.edu/ee/people/display_person/?netid=prucnal”>Paul
Prucnal, a Princeton professor of electrical”>http://www.princeton.edu/ee/”>electrical
engineering, and David Rosenbluth, a neuroscientist and principle engineer at Lockheed Martin’s
Advance Technology Laboratory, in Cherry Hill, N.J. It is funded by Lockheed Martin and Princeton’s
Stuart M. Essig ’83 and Erin S. Enright ’82 Fund for Innovation in Engineering and
The project, which started in 2008, seeks to overcome the inherent speed constraints of electrical
circuits, which are ultimately limited by the time it takes electricity to flow through wires. Instead of
electrical wires, the team is using clear fiber-optic cables, through which information travels at nearly
the speed of light.
The “photonic” half of the project’s name derives from photons, which are
the fundamental unit of light, just as electrons are the fundamental unit of electricity. In conventional
fiber-optic communications, photons speed information along great distances but are converted back to
electrons once they reach a destination and the information needs to be processed. In Prucnal’s lab,
the processing occurs while the information is still encoded in light.
In addition to harnessing the ultimate speediness of light, the researchers are borrowing
computational concepts used by the neural circuits that help humans and other organisms make ultrafast
Each neuron, whether in the brain or peripheral circuits of the nervous system, is connected to
other neurons, which communicate through electrochemical pulses known as action potentials, or,
colloquially, as “spikes.” Based on the pattern of incoming spikes, a neuron decides
whether to send out its own signal to convey information to the rest of the network. This function is the
basis for neural computing.
title=”The project uses fiber-optic devices that make ultrafast calculations with photons of light
instead of the electrons used by electricity-based computers circuits. (Photo by Frank Wojciechowski)”
The ability to make such decisions rapidly comes in handy in many situations. A gazelle being
pursued by a cheetah, for instance, has to decide extremely quickly — and correctly — whether to dart left
or right. A baseball player at bat has to decide to swing or not swing based on a number of cues that arrive
a fraction of a second before the decision must be made.
The way that neural networks compute in do-or-die situations offers clues as to how computational
devices based on light could function.
“We are transposing learning, inhibition and other behaviors typical of neural processing
onto fiber-optic circuits,” Rosenbluth said. “But I don’t think of it as trying to
reproduce something in the brain. It’s a hybrid between the analog computing done in the brain and
the purely digital systems used by most computers.”
When Prucnal and Rosenbluth first began talking about the possibility of studying blending
fiber-optic signal processing and neuroscience, they noticed that although the mathematical equations used
to model neural and fiber-optic networks used different variables, they were very similar in their overall
“We put the equations side-by-side and it was really an ‘aha!’ moment for
us,” Prucnal said. “It was pretty exciting that it might actually work.”
In addition to Nahmias, undergraduates who have worked on the project include 2011 graduate Vinayak
Venkataraman, rising seniors Will Herlands, Nicole Rafidi and Alex Tait, and rising juniors Abdulrahman
Mahmoud and Dolly Xu, all electrical engineering students. Yue Tian, a graduate student in electrical
engineering, is focusing on the project as part of his doctoral research.