Applying Shannon’s information theory [32] to neuroscience started immediately after the significance of Shannon’s seminal paper was recognized, and different research directions began to use it (for a review, see [165]). Although Shannon warned [33] against the indiscriminate use of the theory and called attention to its valid scope: ”The hard core of information theory is, essentially, a branch of mathematics”, and it ”is not a trivial matter of translating words to a new domain”. The improper application of the information theory to neural communication is going on [166, 167].
Quotation:
”The ultimate aim of computational neuroscience is
to explain how electrical and chemical signals are used in the brain
to represent and process information”
[14] @1988.
”The fundamental task of the nervous system is to communicate and process information’ …”neurons convey
neural information by virtue of electrical and chemical signals’
[2]@1995.
”Information is carried within neurons and from
neurons to their target cells by electrical and chemical
signals. Transient electrical signals are particularly
important for carrying time-sensitive information rapidly and over long distances” [41], page 126. @2013
Quotation: ”In the terminology of communication theory and information theory, [a neuron] is a multiaccess, partially degraded broadcast channel that performs computations on data received at thousands of input terminals and transmits information to thousands of output terminals by means of a time-continuous version of pulse position. Moreover, [a neuron] engages in an extreme form of network coding; it does not store or forward the information it receives but rather fastidiously computes a certain functional of the union of all its input spike trains which it then conveys to a multiplicity of select recipients” [168]. @2010 Will be based on [16] [26] [28]
The theoretical model [16] described how the slow operation of biological objects explains biological phenomena, but due to the lack of dedicated measurements it could only indirectly underpin the theory’s correctness. Now, we give an exact quantitative explanation of the precise measurements [9, 83], which have not been correctly understood in the past decades due to the lack of understanding of the role of the finite interaction speed (conduction velocity) in neuronal operations.