Warren McCulloch spent most of his life saying that neurons in the brain are logic gates like those in digital computers and that the brain can be understood as a Turing machine (a universal digital computer). He said, “If you know theology at all, well, you’ll realize that the ideas in the mind of God are mathematics and logic.”
Dr. Warren McCulloch, the genius Yale Graduate, Neuropsychologist, Cybernetician, and MIT Researcher, proposed the first Neural Network in an MIT Research Lab in 1943. He was raised with the expectation of becoming a Christian minister but became fascinated with mathematics instead. He feels that mathematics represents the ideas of God and has pursued this interest throughout his scientific career.
He has always wanted to understand the concept of a number and how a person can truly know a number. He admits he has grasped part of this question but is still searching for a complete understanding.
Dr. McCulloch and his young collaborator Walter Pitts were thus the originators of today’s widely supported “computational model of the mind.” Their work inspired theories of “cellular automata,” in which individual cells live or die according to inputs from their surrounding cells.
In their 1943 paper, “A Logical Calculus of the Ideas Immanent in Nervous Activity,” Dr. McCulloch and Pitts 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
The McCulloch-Pitts article also compared the neurons’ behavior to that of a Turing Machine, which Alan Turing had proposed in a 1936 paper.
One more thing is to be remarked in conclusion. It is easily shown: first, that every net, if furnished with a tape, scanners connected to afferents, and suitable efferents to perform the necessary motor-operations, can compute only such numbers as can a Turing machine; second, that each of the latter numbers can be computed by such a net; and that nets with circles can be computed by such a net; and that nets with circles can compute, without scanners and a tape, some of the numbers the machine can, but no others, and not all of them. This is of interest as affording a psychological justification of the Turing definition of computability and its equivalents, Church’s λ-definability and Kleene’s primitive recursiveness: if any number can be computed by an organism, it is computable by these definitions, and conversely. —A Logical Calculus of the Ideas Immanent in Nervous Activity, p.99
In the 1930s, Dr. McCulloch studied logic at Yale in a course taught by Frederic Fitch, which was based on the important work “Principia Mathematica” by Bertrand Russell and Alfred North Whitehead. Fitch was also Ruth Barcan Marcus’s thesis adviser, and her ideas about the “necessity of identity” influenced Saul Kripke.
Even though information travels along neurons in the brain, the brain isn’t like a computer network. Brain processes aren’t algorithms, and there’s no central processing unit (CPU) or distributed parallel processing.
Simply put, humans are not machines, and the brain is not a computer. However, we can see McCulloch as the first thinker to suggest a solution to the mind-body problem that combines a non-physical logical mind with physical mechanical hardware, as indicated by the title of his 1965 book, “Embodiments of Mind.”
Dr. McCullough has conducted research, including studying the frog’s eye, to gain insights into the brain. He acknowledges that the human brain is extremely complex and that it will take a long time to fully understand it.
In 1959, Dr. McCulloch and Pitts worked with Jerome Lettvin and Humberto Maturana to write an important paper called “What the Frog’s Eye Tells the Frog’s Brain.” This paper was later included in McCulloch’s book, “Embodiments of Mind,” published in 1965.
Dr. McCulloch was disappointed by this work, and Pitts may have felt even worse. The reason for their disappointment was that a frog’s actions depend on the light patterns hitting its retina, which happens before the brain processes any information.
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The frog’s responses are part of its genetic makeup as a species. This shows how successful experiences from the frog’s ancestors are stored in its brain, allowing the frog to repeat successful actions (like catching a bug with its tongue) when it sees something similar.
From the paper: What are the consequences of this work? Fundamentally, it shows that the eye speaks to the brain in a language already highly organized and interpreted, instead of transmitting some more or less accurate copy of the distribution of light on the receptors.
The operations thus have much more the flavor of perception than of sensation if that distinction has any meaning now. That is to say that the language in which they are best described is the language of complex abstractions from the visual image. We have been tempted, for example, to call the convexity detectors “bug perceivers.” Such a fiber responds best when a dark object, smaller than a receptive field, enters that field, stops, and moves about intermittently thereafter. The response is not affected if the lighting changes or if the background (say a picture of grass and flowers) is moving, and is not there if only the background, moving or still, is in the field. Could one better describe a system for detecting an accessible bug?
Dr. McCulloch distinguishes the human nervous system from computers. Traditional computers process information step by step, meaning that an error in one step affects all subsequent steps. In contrast, some modern machines work in parallel, comparing results before proceeding. However, he proposes an even more advanced idea: a type of machine that processes information like a river, where different streams of information mix together before producing an output. He uses the term “anastomatic” to describe this intermingling of information.
Dr. McCulloch distinguishes the human nervous system from computers. Traditional computers process information step by step, meaning that an error in one step affects all subsequent steps. In contrast, some modern machines work in parallel, comparing results before proceeding.… pic.twitter.com/7BPvPeKjOf
— Vicky Verma (@Unexplained2020) October 19, 2024
Dr. McCullough mentioned that neurons (brain cells) die daily, especially after reaching a certain age. He noted that even though neurons die, we can still function well into old age, and he believed his research would address how the brain copes with this cell loss.
He speculated about the future, questioning whether we could create beings that might surpass humans. He believed that if machines were to survive humanity, they would continue in the direction humans were heading, but he thought they would lack true purpose once humans were gone.
He stated that machines would never have the same emotional connection to others that humans have and expressed skepticism that machines could genuinely feel love or attachment.
Despite his skepticism, he suggested that if he could clearly define the mechanisms of emotions, it might be possible to create machines that could replicate emotional connections.
In 1952, Dr. McCulloch moved to the Massachusetts Institute of Technology’s (MIT) Research Laboratory of Electronics, where he worked with other leading researchers such as Norbert Wiener and Claude Shannon. He also helped to organize the first ever conference on the topic of artificial intelligence, held at Dartmouth College in 1956.
Warren McCulloch’s contributions to the field of artificial intelligence and theoretical neuroscience have had a lasting impact on the field. His work laid the foundation for the development of artificial neural networks, and many of his ideas are still widely studied and applied in the field today.
