Bio-circuitry mimics synapses and neurons in a step toward sensory computing

October 17, 2019

Researchers at the Department of Energy's Oak Ridge National Laboratory, the University of Tennessee and Texas A&M University demonstrated bio-inspired devices that accelerate routes to neuromorphic, or brain-like, computing.

Results published in Nature Communications report the first example of a lipid-based "memcapacitor," a charge storage component with memory that processes information much like synapses do in the brain. Their discovery could support the emergence of computing networks modeled on biology for a sensory approach to machine learning.

"Our goal is to develop materials and computing elements that work like biological synapses and neurons--with vast interconnectivity and flexibility--to enable autonomous systems that operate differently than current computing devices and offer new functionality and learning capabilities," said Joseph Najem, a recent postdoctoral researcher at ORNL's Center for Nanophase Materials Sciences, a DOE Office of Science User Facility, and current assistant professor of mechanical engineering at Penn State.

The novel approach uses soft materials to mimic biomembranes and simulate the way nerve cells communicate with one another.

The team designed an artificial cell membrane, formed at the interface of two lipid-coated water droplets in oil, to explore the material's dynamic, electrophysiological properties. At applied voltages, charges build up on both sides of the membrane as stored energy, analogous to the way capacitors work in traditional electric circuits.

But unlike regular capacitors, the memcapacitor can "remember" a previously applied voltage and--literally--shape how information is processed. The synthetic membranes change surface area and thickness depending on electrical activity. These shapeshifting membranes could be tuned as adaptive filters for specific biophysical and biochemical signals.

"The novel functionality opens avenues for nondigital signal processing and machine learning modeled on nature," said ORNL's Pat Collier, a CNMS staff research scientist.

A distinct feature of all digital computers is the separation of processing and memory. Information is transferred back and forth from the hard drive and the central processor, creating an inherent bottleneck in the architecture no matter how small or fast the hardware can be.

Neuromorphic computing, modeled on the nervous system, employs architectures that are fundamentally different in that memory and signal processing are co-located in memory elements--memristors, memcapacitors and meminductors.

These "memelements" make up the synaptic hardware of systems that mimic natural information processing, learning and memory.

Systems designed with memelements offer advantages in scalability and low power consumption, but the real goal is to carve out an alternative path to artificial intelligence, said Collier.

Tapping into biology could enable new computing possibilities, especially in the area of "edge computing," such as wearable and embedded technologies that are not connected to a cloud but instead make on-the-fly decisions based on sensory input and past experience.

Biological sensing has evolved over billions of years into a highly sensitive system with receptors in cell membranes that are able to pick out a single molecule of a specific odor or taste. "This is not something we can match digitally," Collier said.

Digital computation is built around digital information, the binary language of ones and zeros coursing through electronic circuits. It can emulate the human brain, but its solid-state components do not compute sensory data the way a brain does.

"The brain computes sensory information pushed through synapses in a neural network that is reconfigurable and shaped by learning," said Collier. "Incorporating biology--using biomembranes that sense bioelectrochemical information--is key to developing the functionality of neuromorphic computing."

While numerous solid-state versions of memelements have been demonstrated, the team's biomimetic elements represent new opportunities for potential "spiking" neural networks that can compute natural data in natural ways.

Spiking neural networks are intended to simulate the way neurons spike with electrical potential and, if the signal is strong enough, pass it on to their neighbors through synapses, carving out learning pathways that are pruned over time for efficiency.

A bio-inspired version with analog data processing is a distant aim. Current early-stage research focuses on developing the components of bio-circuitry.

"We started with the basics, a memristor that can weigh information via conductance to determine if a spike is strong enough to be broadcast through a network of synapses connecting neurons," said Collier. "Our memcapacitor goes further in that it can actually store energy as an electric charge in the membrane, enabling the complex 'integrate and fire' activity of neurons needed to achieve dense networks capable of brain-like computation."

The team's next steps are to explore new biomaterials and study simple networks to achieve more complex brain-like functionalities with memelements.
-end-
The journal article is published as "Dynamical nonlinear memory capacitance in biomimetic membranes."

The research was conducted in part at the CNMS.

UT-Battelle manages ORNL for the DOE Office of Science. The single largest supporter of basic research in the physical sciences in the United States, the Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit https://www.energy.gov/science.

DOE/Oak Ridge National Laboratory

Related Neurons Articles from Brightsurf:

Paying attention to the neurons behind our alertness
The neurons of layer 6 - the deepest layer of the cortex - were examined by researchers from the Okinawa Institute of Science and Technology Graduate University to uncover how they react to sensory stimulation in different behavioral states.

Trying to listen to the signal from neurons
Toyohashi University of Technology has developed a coaxial cable-inspired needle-electrode.

A mechanical way to stimulate neurons
Magnetic nanodiscs can be activated by an external magnetic field, providing a research tool for studying neural responses.

Extraordinary regeneration of neurons in zebrafish
Biologists from the University of Bayreuth have discovered a uniquely rapid form of regeneration in injured neurons and their function in the central nervous system of zebrafish.

Dopamine neurons mull over your options
Researchers at the University of Tsukuba have found that dopamine neurons in the brain can represent the decision-making process when making economic choices.

Neurons thrive even when malnourished
When animal, insect or human embryos grow in a malnourished environment, their developing nervous systems get first pick of any available nutrients so that new neurons can be made.

The first 3D map of the heart's neurons
An interdisciplinary research team establishes a new technological pipeline to build a 3D map of the neurons in the heart, revealing foundational insight into their role in heart attacks and other cardiac conditions.

Mapping the neurons of the rat heart in 3D
A team of researchers has developed a virtual 3D heart, digitally showcasing the heart's unique network of neurons for the first time.

How to put neurons into cages
Football-shaped microscale cages have been created using special laser technologies.

A molecule that directs neurons
A research team coordinated by the University of Trento studied a mass of brain cells, the habenula, linked to disorders like autism, schizophrenia and depression.

Read More: Neurons News and Neurons Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.