Artificial Intelligence, Science, Technology
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Artificial synapse said to rival biological synapses in energy consumption and function

This article is lifted from the KurzweilAI site. Link:
neuronal-network-ONW-STSchematic of biological neuronal network and an organic nanowire (ONW) synaptic transistor (ST) that emulates a biological synapse. The yellow conductive lines and probe (A′) mimic an axon (A) that delivers presynaptic spikes from a pre-neuron to the presynaptic membrane. The mobile ions in the ion gel move in the electrical field, analogous to the biological neuron transmitters in the synaptic cleft; the field later induces an excitatory postsynaptic current (EPSC, light blue line) in the biological dendrite (B). An ONW (B′) combined with a drain electrode (yellow surface) mimics a biological dendrite (B). EPSC (light green line) is generated in the ONW in response to presynaptic spikes and is delivered to a post-neuron through connections to the drain electrode. (credit: Wentao Xu et al./Science Advances)

A human synapse consumes an extremely small amount of energy (~10 fJ or femtojoules** per synaptic event).

The researchers have fabricated an organic nanofiber (ONF), or organic nanowire (ONW), electronic device that emulates the important working principles and energy consumption of biological synapses while requiring only ~1 fJ per synaptic event. The ONW also emulates the morphology (form) of a synapse. 

The morphology of ONFs is similar to that of nerve fibers, which form crisscrossing grids to enable the high memory density of a human brain. The researchers say the highly-aligned ONFs can be massively produced with precise control over alignment and dimension; and this morphology may make possible the future construction of the high-density memory of a neuromorphic (brain-form-emulating) system.****

The researchers say they have emulated important working principles of a biological synapse, such as paired-pulse facilitation (PPF), short-term plasticity (STP), long-term plasticity (LTP), spike-timing dependent plasticity (STDP), and spike-rate dependent plasticity (SRDP).

The artificial synapse devices provide a new research direction in neuromorphic electronics and open a new era of organic electronics with high memory density and low energy consumption, the researchers claim. Potential applications include neuromorphic computing systems, AI systems for self-driving cars, analysis of big data, cognitive systems, robot control, medical diagnosis, stock-trading analysis, remote sensing, and other smart human-interactive systems and machines in the future, they suggest.

This research was supported by the Pioneer Research Center Program and Center for Advanced Soft-Electronics as a Global Frontier Project, funded by the Korean Ministry of Science, ICT, and Future Planning.

The research was published an open-access paper in Science Advances, a new sister journal of Science.

* Prof. Tae-Woo Lee, Wentao Xu, and Sung-Yong Min, PhD, with the Dept. of Materials Science and Engineering at POSTECH

** A fJ (femtojoule) is 10-15 Joule (one watt-second). 

*** ~1014 synapses.

**** Previous attempts to realize synaptic functions in single electronic devices include resistive random access memory (RRAM), phase change memory (PCM), conductive bridges, and synaptic transistors.

Editor strongly suggests interested readers go to the original article for other diagrams and captions. and also to read the very interesting comments that follow the article. Again, here is that link:



I made my bones as an advertising copywriter. My TV, radio and print ads have amused millions of people and helped sell tons of cleaning products, coffee, macadamia nuts and other goodies. But I prefer that other kind of fiction: short stories and novels. My first published novel, Mindclone, is a near-future look at the amusing and serious consequences of brain-uploading. It’s garnered mostly five star reviews. The sequel is percolating in my brain even now. Stay tuned.

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