We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement
New devices created that emulate human biological synapses
News

New devices created that emulate human biological synapses

New devices created that emulate human biological synapses
News

New devices created that emulate human biological synapses

Read time:
 

Want a FREE PDF version of This News Story?

Complete the form below and we will email you a PDF version of "New devices created that emulate human biological synapses"

First Name*
Last Name*
Email Address*
Country*
Company Type*
Job Function*
Would you like to receive further email communication from Technology Networks?

Technology Networks Ltd. needs the contact information you provide to us to contact you about our products and services. You may unsubscribe from these communications at any time. For information on how to unsubscribe, as well as our privacy practices and commitment to protecting your privacy, check out our Privacy Policy

Engineers at the University of Massachusetts (UMass) Amherst are leading a research team that is developing a new type of nanodevice for computer microprocessors that can mimic the functioning of a biological synapse—the place where a signal passes from one nerve cell to another in the body. The work is featured in the advance online publication of Nature Materials.


Such neuromorphic computing in which microprocessors are configured more like human brains is one of the most promising transformative computing technologies currently under study.


See Also: Brain-sensing technology allows monkeys to type with thoughts at a rate of 12 words per minute


J. Joshua Yang and Qiangfei Xia are professors in the electrical and computer engineering department in the UMass Amherst College of Engineering. Yang describes the research as part of collaborative work on a new type of memristive device.


Memristive devices are electrical resistance switches that can alter their resistance based on the history of applied voltage and current. These devices can store and process information and offer several key performance characteristics that exceed conventional integrated circuit technology.


"Memristors have become a leading candidate to enable neuromorphic computing by reproducing the functions in biological synapses and neurons in a neural network system, while providing advantages in energy and size," the researchers say.


Neuromorphic computing—meaning microprocessors configured more like human brains than like traditional computer chips—is one of the most promising transformative computing technologies currently under intensive study. Xia says, "This work opens a new avenue of neuromorphic computing hardware based on memristors."


They say that most previous work in this field with memristors has not implemented diffusive dynamics without using large standard technology found in integrated circuits commonly used in microprocessors, microcontrollers, static random access memory and other digital logic circuits.


Don't Miss: Blind lead the way in brave new world of tactile technology


The researchers say they proposed and demonstrated a bio-inspired solution to the diffusive dynamics that is fundamentally different from the standard technology for integrated circuits while sharing great similarities with synapses. They say, "Specifically, we developed a diffusive-type memristor where diffusion of atoms offers a similar dynamics and the needed time-scales as its bio-counterpart, leading to a more faithful emulation of actual synapses, i.e., a true synaptic emulator."


The researchers say, "The results here provide an encouraging pathway toward synaptic emulation using diffusive memristors for neuromorphic computing."


Note: Material may have been edited for length and content. For further information, please contact the cited source.


University of Massachusetts Amherst   press release


Publication

Wang Z et al. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing.   Nature Materials, Published Online September 26 2016. doi: 10.1038/nmat4756


Advertisement