Emotions are nerve impulses. The feel of paper and
flush of shame. Feelings and emotions are relayed as nerve impulses. Nerve endings or sensors report on feelings from tissues all over body. These sensations include sharp pain, burning pain, cool or warm temperature, itching, muscle contraction, joint movements, soft touch, mechanical stress, tickling, flushing, hunger and thirst. Electrical excitation of certain parts of temporal lobe, cause intense fear to be produced in patients. Excitation of other parts caused feelings of isolation, loneliness, disgust, or even pleasure. The mind differentiated finely between these nerve impulses - to feel tired, hungry or much else. But, how could “pleasant, or unpleasant” quality of nerve impulses be explained? Why should universal experience of pain be wretched and pleasure agreeable? What kind of code could mind use to differentiate between nice and awful? The book, The Intuitive Algorithm (IA), explains how mere nerve impulses could achieve this. That view is founded on crucial IA evidence that instant pattern recognition – intuition - could underpin processes of mind.
A seamless pattern recognition system.
Over ages, science had speculated on nature of human intelligence. The IA concept was a new view. That wisdom of mind relied on massive memories of nerve cells for combinations. The mind used intuition, a pattern recognition process. It was a logical elimination routine, which could instantly sift a single contextual answer from its immense knowledge base. It was this process, which enabled you to reach into your pocket and identify a key. Just by touch. Nerve cells could finely differentiate between combinations of sensations to recognize objects and events. Recognition was enabled by a combinatorial coding process by neurons. Such a recognition process was recently accepted by science and a Nobel Prize acknowledged that discovery in 2004. So, at input end, kaleidoscopic combinations of millions of sensations were received. From these, mind instantly recognized events. Recognized events triggered contextual feelings. Feelings triggered allied drives. Drives fired sequences of remembered muscle movements. The circuit closed. All this was enabled by massive memories in neurons and, intuition. 100 billion nerve cells recognized events and delivered motor output, within a bare span of 20 milliseconds. The time between shadow and scream. So, from input to output, mind was a seamless pattern recognition system.
Intelligent drives.
The current feeling dictated purpose at highest levels. A hierarchy of intelligences followed through. At second level, learned movements were inserted. At lowest level, fine motor coordination delivered final output – whether a spoken word, or a written line. A feeling expressed a purpose. A feeling of fear could dictate an escape drive, whose purpose was to achieve safety. That demanded instant responses, varying across species. A deer bounded away. A bird took flight. A fish swam off. While activities of running, flying and swimming differed, they achieved same objective of escaping. Such activities could not be stupid. Escape was hardly possible by heading into predator. Increasing distance from danger demanded uncommon cleverness. That objective could even be achieved by slipping into a safe sanctuary, inaccessible to predator. Like underside of a rock. The system received intelligent contributions down to lowest levels. Purpose was expressed as feelings at highest level and remembered drives operated at lower levels.
A drive, which assembled combinatorial memories of context
The nerve cell memories, which powered these intelligences were both inherited and acquired. The IA concept of nerve cell memories was supported by research. The study of cortical activity, while learning skills, presented a mystery to science. PET scans revealed that as a person learned a skill, cortical activity was initially high. But, with learning, it gradually reduced. Why did practiced effort require less cortical activity? Why should practice need less neural interactions? Surely, highly skilled activities should have more neural traffic? Science remained in dark. However, mastering a skill needed attention. Landmarks had to be identified and remembered. Attention increased cortical activity. Those combinations of context were recorded by drive channel. The IA concept suggested that learning involved memory at lower levels. The cortex laboured to teach drive channel. The memories of drive channel neurons later responded appropriately, without cortical intervention.
