We can trace the origin of the idea of the brain as a computer to a paper written seven years after Alan Turing had proposed his "universal computing machine," and just a few years before the first digital computer was built (ENIAC, 1946).

In their 1943 paper, "A Logical Calculus of the Ideas Immanent in Nervous Activity," twenty-year old Walter Pitts and his older colleague Warren McCulloch wrote

Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes. It is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under the other and gives the same results, although perhaps not in the same time. Various applications of the calculus are discussed.

"A Logical Calculus of the Ideas Immanent in Nervous Activity," p.99

McCulloch said his ideas that neural networks are similar to arguments in propositional logic and thus to computer networks dates back many years.

Many years ago one of us, by considerations impertinent to this argument, was led to conceive of the response of any neuron as factually equivalent to a proposition which proposed its adequate stimulus. He therefore attempted to record the behavior of complicated nets in the notation of the symbolic logic of propositions. The “all-or-none” law of nervous activity is sufficient to insure that the activity of any neuron may be represented as a proposition. Physiological relations existing among nervous activities correspond, of course, to relations among the propositions; and the utility of the representation depends upon the identity of these relations with those of the logic of propositions. To each reaction of any neuron there is a corresponding assertion of a simple proposition. This, in turn, implies either some other simple proposition or the disjunction of the conjunction, with or without negation, of similar propositions, according to the configuration of the synapses upon and the threshold of the neuron in question.

"A Logical Calculus of the Ideas Immanent in Nervous Activity," p.99

Psychology struggled for decades to establish a "science of the mind," first by "introspecting" what is going on inside the mind (William James), then adopting "behaviorism" which denies the existence of the unobservable immaterial mind and allows only verifiable "observations of human behavior (John Watson, B.F.Skinner).

John B. Watson was the creator of behaviorism, He proposed to replace the "science of the mind" with the "science of human behavior."

Psychology had studied the mind and consciousness by introspection. Watson claimed that subjective internal states of mind and consciousness are unobservable, unmeasurable, and even nonexistent. Psychology should only study the measurable, objective, external behaviors of man and animals.

B.F.Skinner added the idea of reinforcement schedules to Watson's conditioning techniques. His work led to "mind" and "consciousness" becoming unspeakable concepts in many psychology departments. A survey of today’s four leading textbooks on psychology has only one that defines psychology as “the science of mind.” Another has for its main index entry, “mind, theory of, see theory of mind. A third has “mind, see brain.” And the last has no entry at all under “mind.” The historian of psychology A.A.Roback said psychology had lost its mind. Can there be psychology without a psyche?

Behavorism was replaced with "cognitive science" in the 1950's, especially at the Massachusetts Institute of Technology, where an important meeting of cognitive scientists took place. George A. Miller presented his "The Magical Number Seven, Plus or Minus Two" paper while Noam Chomsky, Allen Newell, and Herbert Simon presented their findings on computer science. Ulric Neisser, the "father of cognitive psychology," commented on many of the findings at this meeting in his 1967 book Cognitive Psychology.

Behaviorists such as Miller began to focus on the representation of language rather than general behavior. Vision scientist David Marr concluded that one should understand any cognitive process at three levels of analysis. These levels include the computational, the algorithmic/representational, and physical levels of analysis.

Since the foundational ideas of Warren McCulloch and Walter Pitts in the 1940's, a number of major textbooks were devoted to cognitive science or cognitive psychology, developing the idea that the brain is an information processing system like a computer. Out of all these excellent books, we can quote an article from the early 1990's by two of the major players in computational neuroscience, Patricia S. Churchland and Terrence Sejnowski, authors of The Computational Brain.

Cognition essentially involves representations and computations. Representations are, in general, symbolic structures, and computations are, in general, rules (such as rules of logic) for manipulating those symbolic structures.

A good model for understanding mind-brain functions is the computer - that is, a machine based on the same logical foundations as a Turing machine and the von Neumann architecture for a digital computer. Such machines are ideally suited for the manipulation of symbols according to rules. The computer metaphor suggests that the mind-brain, at the information processing level, can be understood as a kind of digital computer; the problem for cognitive psychology is to determine the program that our brains run.

"Neural Representation and Neural Computation," (1990) Philosophical Perspectives, 4, 343-382.

We can list the major functions of a digital computer that computational neuroscience hopes to locate somewhere in the brain/mind.

Digital Computer Functions

• A central logic processing unit or distributed parallel processors
• Systems for input and output of data (information)
• Data storage of digital bits - 1s or 0s
• In the von Neumann architecture, the programs are stored in the same meory as other data
• Algorithms to recall that data to create a representation of the information
• Circuits to communicate information (messages) from place to place
• Processors to prepare and transmit messages and to receive and interpret them

Neurons as the Logical Elements of Computation

Bibliography

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