Computing with silicon neurons: Scientists use artificial nerve cells to classify different types of data

Computing with silicon neurons: Scientists use artificial nerve cells to classify different types of data
The neuromorphic chip containing silicon neurons which the researchers used for their data-classifying network. Credit: Kirchoff Institute for Physics, Heidelberg University

Scientists from Berlin and Heidelberg use artificial nerve cells to classify different types of data. They can recognize handwritten numbers, or distinguish plant species based on their flowers.

A bakery assistant who takes the bread from the shelf just to give it to his boss who then hands it over to the customer? Rather unlikely. Instead, both work at the same time to sell the baked goods. Similarly, computer programs are more efficient if they process data in parallel rather than to calculate them one after the other. However, most programs that are applied still work in a serial manner.

Scientists from Freie Universität Berlin, the Bernstein Center Berlin, and Heidelberg University have now refined a new technology that is based on parallel . In the so-called neuromophic computing, made of silicon take over the computational work on special computer chips. The neurons are linked together in a similar fashion to the in our brain. If the assembly is fed with data, all silicon neurons work in parallel to solve the problem. The precise nature of their connections determines how the network processes the data. Once properly linked, the neuromorphic network operates almost by itself. The researchers have now designed a network-a neuromorphic "program"- for this chip that solves a fundamental computing problem: It can classify data with different features. It is able to recognize handwritten numbers, or may distinguish certain plant species based on flowering characteristics.

"The design of the network architecture has been inspired by the odor-processing nervous system of insects," explains Michael Schmuker, lead author of the study. "This system is optimized by nature for a highly parallel processing of the complex chemical world." Together with work group leader Martin Nawrot and Thomas Pfeil, Schmuker provided the proof of principle that a neuromorphic chip can solve such a complex task. For their study, the researchers used a chip with silicon neurons, which was developed at the Kirchhoff Institute for Physics of Heidelberg University.

Computer programs that can classify data are employed in various technical devices, such as smart phones. The neuromorphic network chip could also be applied in super-computers that are built on the model of the human brain to solve very complex tasks. Using their prototype, the Berlin scientists are now able to explore how networks must be designed to meet the specific requirements of these brain-like computer. A major challenge will be that not even two neurons are identical - neither in silicon nor in the brain.

More information: M. Schmuker, T. Pfeil & M.P. Nawrot (2014): A neuromorphic network for generic multivariate data classification. PNAS, published ahead of print January 27, DOI: 10.1073/pnas.1303053111

Related Stories

Chips that mimic the brain

date Jul 22, 2013

No computer works as efficiently as the human brain – so much so that building an artificial brain is the goal of many scientists. Neuroinformatics researchers from the University of Zurich and ETH Zurich have now made ...

Brain in a box: Computer R&D teams explore new models

date Jan 03, 2014

Beyond technology headlines announcing new wearable designs, curved displays and 3D printing machines, there is another research path. Researchers continue to explore how computers may learn from their own ...

Brain: Balancing old and new skills

date Dec 09, 2013

To learn new motor skills, the brain must be plastic: able to rapidly change the strengths of connections between neurons, forming new patterns that accomplish a particular task. However, if the brain were ...

Recommended for you

Changing activity in the ageing brain

date 10 minutes ago

Normal ageing affects our ability to carry out complex cognitive tasks. But exactly how our brain functions change during this process is largely unknown. Now, researchers in Malaysia have demonstrated that ...

Networking neurons thrive in 3-D human 'organoid'

date 41 minutes ago

A patient tormented by suicidal thoughts gives his psychiatrist a few strands of his hair. She derives stem cells from them to grow budding brain tissue harboring the secrets of his unique illness in a petri ...

Unlearning implicit social biases during sleep

date 18 hours ago

Can we learn to rid ourselves of our implicit biases regarding race and gender? A new Northwestern University study indicates that sleep may hold an important key to success in such efforts.

User comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.