Scientists have fabricated a device that can mimic human brain cognitive actions
Figure: Scanning electron microscope image of the artificial synaptic network device resembling a bio-neural network. Associative learning is demonstrated by emulating Pavlov’s dog, where post-training the dog salivates by hearing the bell.
Scientists have fabricated a device that can mimic human brain cognitive actions and is more efficient than conventional techniques in emulating artificial intelligence, thus enhancing the computational speed and power consumption efficiency. Scientists from Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, an autonomous institute of the Department of Science & Technology, Government of India, devised a novel approach of fabricating an artificial synaptic network (ASN) resembling the biological neural network via a simple self-forming method (the device structure is formed by itself while heating). This work has been recently published in the journal ‘Materials Horizons’.
Aiming to develop a synaptic device for neuromorphic applications with a humble fabrication method, the JNCASR team explored a material system mimicking neuronal bodies and axonal network connectivity much like the biological system. In order to realize such a structure, they found that a self-forming process was easy, scalable, and cost-effective. In their research JNCASR team dewetted Silver (Ag) metal to form branched islands and nanoparticles with nanogap separations to resemble bio neurons and neurotransmitters where dewetting is a process of rupture of continuous film into disconnected/isolated islands or spherical particles. With such an architecture, several higher-order cognitive activities are emulated. The fabricated artificial synaptic network (ASN) consisted of Silver (Ag) agglomerates network separated by nanogaps filled with isolated nanoparticles. They found that dewetting Ag film at a higher temperature resulted in the formation of island structures separated by nanogaps resembling the bio-neural network.
Using programmed electrical signals as a real-world stimulus, this hierarchical structure emulated various learning activities such as short-term memory (STM), long-term memory (LTM), potentiation, depression, associative learning, interest-based learning, supervision, etc. Synaptic fatigue due to excessive learning and its self-recovery was also mimicked. Remarkably, all these behaviors were emulated in a single material system without the aid of external CMOS circuits. A prototype kit has been developed to emulate Pavlov’s dog behavior which demonstrates the potential of this device towards neuromorphic artificial intelligence. By organizing a nanomaterial resembling the biological neural substance, the JNCASR team has moved a step further in accomplishing advanced neuromorphic artificial intelligence.
Source: PIB release
