Mind-body as a dualism coincides with Plato's "Ideas" or “Forms” as pure form, with an ontology different from that of matter. The immaterial Forms, seen by the intellect (nous), allow us to understand the world. On the other hand, mind-body as a monism can picture both sides of the mind-body distinction as pure physicalism, since information embodied in matter corresponds to a mere reorganization of the matter. This was Aristotle's more practical view. For him, Plato's Ideas were mere abstractions generalized from many existent particulars. Form without matter is empty, matter without form is inconceivable, unimaginable.

In De Anima (On the Soul, Peri Psyches), Book III, Parts 4 and 5, perhaps the most controversial and confusing part of his entire corpus, Aristotle says that the soul (psyche) or mind is immaterial. He was right. For Aristotle, Intellect (nous) is that part of the soul whose active thinking gives it a causal (aitia) power (dynamis) over the material (hyle) body (soma). This claim appears to anticipate the mind-body problem of René Descartes, how exactly does an immaterial thing or a mere property exert a causal force on the material body?

It is important to note that Descartes made the mind the locus of undetermined freedom. For him, the body is a deterministic mechanical system of tiny fibres causing movements in the brain (the afferent sensations), which then can pull on other fibres to activate the muscles (the efferent nerve impulses). This is the basis of stimulus and response theory in modern physiology (reflexology). It is also the basis behind connectionist theories of mind. An appropriate neural network (with all the necessary logical connections) need only connect the afferent to the efferent signals. No thinking mind is needed for animals.

Descartes' suggestion that animals are machines included the notion that man too is in part a machine - the human body obeys deterministic causal laws. But for Descartes man also has a soul or spirit that is exempt from determinism and thus from what is known today as "causal closure." But how, we must ask, can the mind both cause something physical to happen and yet itself be acausal, exempt from causal chains?

In The mid-1740s, French philosopher Julien Offray de La Mettrie declared Man a Machine. Two centuries later, in the mid-1940s, Warren McCulloch, a middle-aged neurosurgeon, and Walter Pitts, a self-educated symbolic logician speculated that the synapses in our neural networks might be doing binary calculations, i.e., the Brain is a Computer. It is now over eight decades since that first idea that the synaptic connections between brain neurons might be binary logic transmitting “all or nothing” action potentials along neurons (1's or 0's) to the next synapse and solving problems in propositional logic.

In 1943, a digital computer was still just an idea. True, it was seven years after Alan Turing in 1936 proposed his “universal computing machine.” However, the idea was a couple of years before the first digital computers were actually constructed (Colossus in the United Kingdom in 1945 and ENIAC in the United States in 1946).

Nevertheless, this 1943 idea that a brain might be doing computation has become the nearly universal opinion of “computational neuroscience” today: the brain is a digital computer.

The original idea that brain neurons might form logical networks was the work of 45-year-old McCulloch, who trained as a neurosurgeon in New York hospitals and had studied symbolic logic with Frederic Fitch, the Sterling professor of logic at Yale. McCulloch had a brilliant assistant in teenager Pitts, who had been reading Bertrand Russell and Alfred North Whitehead’s Principia Mathematica since he was 12 years old and had easily digested the math of Turing’s idea. When Pitts was just 15 years of age, he wrote to Russell, who invited Pitts to attend his upcoming visiting lectures at the University of Chicago and suggested that Pitts meet with Rudolf Carnap to discuss symbolic logic.

Pitts walked into Carnap’s office with a marked-up copy of Carnap’s famous text, “The Logical Syntax of Language,” and then left without telling Carnap how to contact him. It took Carnap months to locate the homeless Pitts and give him a minor job with a modest income. At that time, McCulloch was also in Chicago, a professor of psychiatry at the University of Illinois, and he met Pitts at seminars organized by Nicolas Rashevsky, the founder of Mathematical Biology and publisher of the Bulletin of Mathematical Biophysics, where McCulloch and Pitts published their landmark article, “A Logical Calculus of the Ideas Immanent in Nervous Activity”.

Also in Chicago at that time and attending Rashevsky seminars was Jerome Lettvin, studying for a medical degree at the University of Illinois. McCulloch invited Pitts and Lettvin to live in his large home where they spent long (alcohol-filled) nights discussing brain networks. Years later, when Cybernetics founder Norbert Wiener invited the three to M.I.T., these discussions led to their article “What the Frog’s Eye Tells the Frog’s Brain,” which appeared in the 1959 Proceedings of the IRE.

In their classic 1943 article, 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.” Their article also explicitly compared the behavior of neural networks to a Turing machine. “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… This is of interest as affording a psychological justification of the Turing definition of computability and its equivalents, Church’s definability and Kleene’s primitive recursiveness: if any number can be computed by an organism, it is computable by these definitions, and conversely”.

McCulloch and his young collaborator 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, such as John Conway’s “Game of Life” and the hypergraphs of ’s Mathematica. Their work was central to the thinking of Claude Shannon, John von Neumann, and Turing as they formulated the architecture of the first digital electronic computers.

Does the mind have a central processor, address buses, and digital data storage with representations of images? Or perhaps even parallel distributed processors (PDP) in different sections of the brain? Consider this opening paragraph from Christof Koch's 1999 book Biophysics of Computation: Information Processing in Single Neurons.

The brain computes! This is accepted as a truism by the majority of neuroscientists engaged in discovering the principles employed in the design and operation of nervous systems. What is meant here is that any brain takes the incoming sensory data, encodes them into various biophysical variables, such as the membrane potential or neuronal firing rates, and subsequently performs a large number of ill-specified operations, frequently termed computations, on these variables to extract relevant features from the input. The outcome of some of these computations can be stored for later access and will, ultimately, control the motor output of the animal in appropriate ways.

Biophysics of Computation. p,1

Just how neurons, their synapses, and their networks store and later reuse information has been a problem for decades. The problem is described as the search for the "neural correlates" of brain function, notably consciousness, but also of fundamental brain functions like vision.

An early theorist was Horace Barlow, who wrote in 1972...

5 Current concept of the single neuron
The cumulative effect of all the changes I have tried to outline above has been to make us realise that each single neuron can perform a much more complex and subtle task than had previously been thought. Neurons do not loosely and unreliably map the luminous intensities of the visual image onto our sensorium, but instead they detect pattern elements, discriminate the depth of objects, ignore irrelevant causes of variation, and are arranged in an intriguing hierarchy. Furthermore, there is evidence that they give prominence to what is informationally important, can respond with great reliability, and can have their pattern selectivity permanently modified by early visual experience.

This amounts to a revolution in our outlook. It is now quite inappropriate to regard unit activity as a noisy indication of more basic and reliable processes involved in mental operations; instead, we must regard single neurons as the prime movers of these mechanisms. Thinking is brought about by neurons, and we should not use phrases like 'unit activity reflects, reveals, or monitors thought processes', because the activities of neurons, quite simply, are thought processes. This revolution stemmed from physiological work and makes us realize that the activity of each single neuron may play a significant role in perception. I think that more clearly stated hypotheses are now needed about these roles in order to allow our psychological knowledge and intuitions about our perceptions to help us plan future experiments...

5 6.1 First dogma A description of that activity of a single nerve cell which is transmitted to and influences other nerve cells, and of a nerve cell's response to such influences from other cells, is a complete enough description for functional understanding of the nervous system. There is nothing else 'looking at' or controlling this activity, which must therefore provide a basis for understanding how the brain controls behaviour.

"Single Units and Sensation: A Neuron Doctrine for Perceptual Psychology?," Perception, 1972, 1(4), 371-394.

Barlow makes two things very clear. 1) The activities of neurons, quite simply, are thought processes, and 2) There is nothing else 'looking at' or controlling this activity, which must therefore provide a basis for understanding how the brain controls behaviour.

Ten years later, MIT cognitive scientist, neurobiologist, and physiologist David Marr made a dramatic turn toward computation, "representations," and "processing."

His book Vision: A computational investigation into the human representation and processing of visual information, was published posthumously by Marr's colleagues at MIT. He died of leukemia in 1980.

Marr wrote in his introduction to Vision that "vision is an information processing task," "that our brains must somehow be capable of representing this information," and that his work was "an inquiry into the nature of the internal representations by which we capture this information and thus make it available as a basis for decisions about our thoughts and actions." (p.3)

He also wrote that "the fundamental point is that in order to understand a device that performs an information processing task, one needs many different kings of explanations," that "each problem has to be addressed from several points of view — as a problem in representing information, as a computation capable of deriving the representation, and as a problem in the architecture of a computer capable of carrying out both things quickly and reliably." (pp.4-5)

Marr's "computational" vision was based on the earlier work of many MIT scientists who saw the brain as a logical machine capable of doing computations, starting with Warren McCulloch and Walter Pitts's 1943 paper "A Logical Calculus of the Ideas Immanent in Nervous Activity,"

In Marr's "Epilogue" to the Vision book, he wrote an imagined conversation between himself, his colleague Tomaso Poggio, and Francis Crick. He began with the work of Horace Barlow.

CONVERSATION

Can we begin with the levels-of-explanation idea, since you attribute so much importance to it? How is it related to ideas about feature detectors and in particular to Horace Barlow’s first dogma (1972, p. 380), which states, “A description of the activity of a single nerve cell which is transmitted to and influences other nerve cells, and of a nerve cell’s response to such influences from other cells, is a complete enough description for functional understanding of the nervous system ”?

Here, of course, I must disagree with Barlow’s formulation, although I do agree with one of the thoughts behind this dogma, namely, that there is nothing else looking at what the cells are doing — they are the ultimate correlates of perception. However, the dogma fails to take level one analysis — the level of the computational theory — into account.

Vision, p.336

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Part Four - Freedom

Part Six - Chance

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