While Roger Penrose suggested that a computer could never mimic the mind, Walter Freeman described the seemingly impossible obstacle to doing it. Yet, a simple algorithm, used in a Diagnostic Expert System could explain the instant pattern recognition process followed by the mind. This Article explains the algorithm. And, how through a combinatorial memory and the use of inhibition, nerve cells could achieve the miracles of the mind.

ARTIFICIAL INTELLIGENCE AND THE MIND

Intuition. While in his book, The Emperor's New Mind, Roger Penrose held that the mind could never be algorithmic, this article suggests that the mind used a pattern recognition algorithm - intuition. Such recognition propelled information through many neural regions like a lightning streak. Data moved from input to output in a reported 20 milliseconds. The mind saw, recognized, interpreted and acted. In the blink of an eye. Myriad processes converted light, sound, touch and smell instantly into nerve impulses. A dedicated region recognized those impulses as objects and events. The limbic system, another region, interpreted those events to generate emotions. A fourth region responded to those emotions with actions. Perception, identification, evaluation and action. Half a second between the shadow and the scream. And, intuition used an algorithm.

Instant holistic evaluation. The system had over a hundred billion neurons. Yet, it processed all your knowledge in half a second. Walter Freeman, the famous neurobiologist, defined this amazing ability. "The cognitive guys think it's just impossible to keep throwing everything you've got into the computation every time. But, that is exactly what the brain does. Consciousness is about bringing your entire history to bear on ... your next moment." The mind was holistic. It evaluated all its knowledge for the next activity. How could so much information be stored and processed instantly? Could it be pattern recognition?

Exponential growth of the search path. Recognition of subtle patterns was a formidable problem for computers. The difficulty in the diagnosis of diseases was typical. Normally, many shared symptoms were presented by a multitude of diseases. For example, pain, or fever could be indicated by many diseases. Each such symptom pointed to several diseases. The objective was to recognize a single pattern among many overlapping patterns. When searching for the target disease, the first selected ailment with the first presented symptom could lack the second symptom. So, back and forth searches expanded exponentially as the database of diseases increased in size. That made the process absurdly tedious - theoretically, even years of search, for extensive databases. So, in spite of their speed, rapid and subtle computer pattern recognition remained unthinkable.

The Intuitive Algorithm. But, industry strength pattern recognition was feasible. The following algorithm could instantly recognize patterns in extended databases. The relationship of each and every member of the database was coded for each question.

Is pain a symptom of the disease?

Y = Yes: N = No: U = Uncertain

The key was to use elimination to evaluate the database, not selection. Every member of the database was individually coded for elimination in the context of each answer.

Is pain a symptom of the disease? Answer: YES

All "N" Diseases eliminated.

For disease recognition, if an answer indicated a symptom, IA eliminated all diseases devoid of the symptom. Every answer eliminated, narrowing the search to reach diagnosis.

Is pain a symptom of the disease? Answer: NO

All "Y" Diseases eliminated.

If the symptom was absent, IA eliminated all diseases which always exhibited the symptom. Diseases, which randomly presented the symptom were retained in both cases. So the process handled uncertainty – the "Maybe" answer, which normal computer programs could not handle.

A sequence of questions narrows down to Disease - 18 - the answer.

If all diseases are eliminated, the disease is unknown.

Instant pattern recognition. The algorithm had powered Expert Systems acting with the speed of a simple recalculation on a spreadsheet, to recognize a disease, identify a case law or diagnose the problems of a complex machine. It was instant, holistic, and logical. If several parallel answers could be presented, as in the multiple parameters of a power plant, recognition was instant. For the mind, where millions of parameters were simultaneously presented, real time pattern recognition was practical. And elimination was the key.

Elimination = Switching off. Elimination was switching off - inhibition. Nerve cells were known to extensively inhibit the activities of other cells to highlight context. With access to millions of sensory inputs, the nervous system instantly inhibited – eliminated trillions of combinations to zero in on the right pattern. The process stoutly used "No" answers. If a patient did not have pain, thousands of possible diseases could be ignored. If a patient could just walk into the surgery, a doctor could overlook a wide range of illnesses. But, how could this process of elimination be applied to nerve cells? Where could the wealth of knowledge be stored?

Combinatorial coding. The mind received kaleidoscopic combinations of millions of sensations. Of these, smells were reported to be recognized through a combinatorial coding process, where nerve cells recognized combinations.

This recognition process was recently reported by science for olfactory neurons. In the experiment scientists reported that even slight changes in chemical structure activated different combinations of receptors. Thus, octanol smelled like oranges, but the similar compound octanoic acid smelled like sweat. A Nobel Prize acknowledged that discovery in 2004.

Galactic nerve cell memories. Combinatorial codes were extensively used by nature. The four "letters" in the genetic code – A, C, G and T – were used in combinations for the creation of a nearly infinite number of genetic sequences. This coding discovery has deeper implications. Dogs could quickly sniff a few footprints of a person and determine accurately which way the person was walking. The animal's nose could detect the relative odour strength difference between footprints only a few feet apart, to determine the direction of a trail. Smell was identified through remembered combinations. If a nerve cell had just 26 inputs from A to Z, it could receive millions of possible combinations of inputs. The average neuron had thousands of inputs. It was galactic memories for combinations which enabled animals to remember and recall millions of smells. Each cell could be a single member of a database, eliminating itself (becoming inhibited) for unrecognized combinations of inputs.

Elimination the key. Elimination was the special key, which evaluated vast combinatorial memories. Medical texts reported that the mind had a hierarchy of intelligences, which performed dedicated tasks. For example, there was an association region, which recognized a pair of scissors using the context of its feel. If you injured this region, you could still feel the scissors with your eyes closed, but you would not recognize it as scissors. You still felt the context, but without recognition of the object. So, intuition enabled nerve cells in association regions to use perception to recognize objects. Medical research reported many such recognition regions.

Seamless pattern recognition. Intuition enabled the finite intelligences in the minds of living things to respond holistically within the 20 millisecond time span. These intelligences acted serially. The first intelligence converted the combinations of sensory perceptions into nerve impulses. The second intelligence recognized these impulses as objects and events. The third intelligence translated the recognized events into feelings. A fourth translated feelings into intelligent drives. Half a second for a 100 billion nerve cells to use context to eliminate irrelevance and deliver motor output. The mind was a seamless pattern recognition machine, powered by the key secret of intuition – contextual elimination, from massive acquired and inherited nerve cell memories.

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