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Blueprint for an artificial brain
Date:2/26/2013

-efficient and robust processors that are able to learn by themselves.' Based on his own experiments and research findings from biology and physics, his article is the first to summarize which principles taken from nature need to be transferred to technological systems if such a neuromorphic (nerve like) computer is to function. Such principles are that memristors, just like synapses, have to 'note' earlier impulses, and that neurons react to an impulse only when it passes a certain threshold.

Thanks to these properties, synapses can be used to reconstruct the brain process responsible for learning, says Andy Thomas. He takes the classic psychological experiment with Pavlov's dog as an example. The experiment shows how you can link the natural reaction to a stimulus that elicits a reflex response with what is initially a neutral stimulus this is how learning takes place. If the dog sees food, it reacts by salivating. If the dog hears a bell ring every time it sees food, this neutral stimulus will become linked to the stimulus eliciting a reflex response. As a result, the dog will also salivate when it hears only the bell ringing and no food is in sight. The reason for this is that the nerve cells in the brain that transport the stimulus eliciting a reflex response have strong synaptic links with the nerve cells that trigger the reaction.

If the neutral bell-ringing stimulus is introduced at the same time as the food stimulus, the dog will learn. The control mechanism in the brain now assumes that the nerve cells transporting the neutral stimulus (bell ringing) are also responsible for the reaction the link between the actually 'neutral' nerve cell and the 'salivation' nerve cell also becomes stronger. This link can be trained by repeatedly bringing together the stimulus eliciting a reflex response and the neutral stimulus. 'You can also construct such a circuit with memristors this is a first step towards a neuromorphic processor,' says And
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Contact: Andy Thomas
andy.thomas@uni-bielefeld.de
49-521-106-2540
University of Bielefeld
Source:Eurekalert  

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Blueprint for an artificial brain
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