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Electronic Neuron Models as an Aid to Neurophysiological Research

Authors: F, JENIK;

Electronic Neuron Models as an Aid to Neurophysiological Research

Abstract

As is well known the time courses of many physiological and electrical phenomena are quite similar. Therefore electrical and electrochemical models can be used to simulate physiological processes [Bethe; Bonhoeffer; Burns; Druckrey and Kupfmuller; Eccles (1); Freygang; Hermann; Hodgkin and Huxley; Kupfmuller (1); Lillie; Tasaki].1 In modern automation and computer technology refined apparatus becomes necessary which is able to perform such complex functions as learning and pattern recognition, which seemed hitherto to have been restricted to organisms with highly developed nervous systems (Steinbuch; Wiener). The design of such apparatus being rather difficult, communication and electronic engineers are interested in how nature has solved the problems of information processing in the nervous system. The investigation of nervous systems is one of the tasks of biologists, and engineers hope that their questions can be answered by the biologists. However two difficulties arise: firstly, many biologists are not interested in engineering problems, and secondly, biologists and engineers do not approach problems from the same angle.

Related Organizations
Keywords

Neurons, Humans, Neurophysiology

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Average
Top 10%
Top 10%
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