Scientists develop novel transistor that acts like human brain

Scientists have developed a vel transistor based on organic materials that has ability to learn, paving way for techlogy that mimics human brain.

transistor developed by scientists at Linkoping University in Sweden is equipped with both short-term and long-term memory. 

Until w, brains have been unique in being able to create connections where re were ne before. 

transistor, described in journal vanced Science, can create a new connection between an input and an output. 

Researchers have incorporated transistor into an electronic circuit that learns how to link a certain stimulus with an output signal, in same way that a dog learns that sound of a food bowl being prepared means that dinner is on way.

A rmal transistor acts as a valve that amplifies or dampens output signal, depending on characteristics of input signal. 

In organic electrochemical transistor that researchers have developed, channel in transistor consists of an electropolymerised conducting polymer. 

channel can be formed, grown or shrunk, or completely eliminated during operation. It can also be trained to react to a certain stimulus, a certain input signal, such that transistor channel becomes more conductive and output signal larger.

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"It is first time that real time formation of new electronic components is shown in neuromorphic devices," said Simone Fabia, from Linkoping University.

channel is grown by increasing degree of polymerisation of material in transistor channel, reby increasing number of polymer chains that conduct signal.

Alternatively, material may be overoxidised (by applying a high volt) and channel becomes inactive. Temporary changes of conductivity can also be achieved by doping or dedoping material.

"We have shown that we can induce both short-term and permanent changes to how transistor processes information, which is vital if one wants to mimic ways that brain cells communicate with each or," said Jennifer Gerasimov, from Linkoping University.

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By changing input signal, strength of transistor response can be modulated across a wide range, and connections can be created where ne previously existed.

This gives transistor a behaviour that is comparable with that of synapse, or communication interface between two brain cells.

It is also a major step towards machine learning using organic electronics. Software-based artificial neural networks are currently used in machine learning to achieve what is kwn as "deep learning".

Software requires that signals are transmitted between a huge number of des to simulate a single synapse, which takes considerable computing power and thus consumes considerable energy.

"We have developed hardware that does same thing, using a single electronic component," said Gerasimov.

"Our organic electrochemical transistor can refore carry out work of thousands of rmal transistors with an energy consumption that approaches energy consumed when a human brain transmits signals between two cells," said Fabia.