The search to reveal a mystery
Research laboratories around the world sought the location of human memory. The research had followed diverse leads. One clue related to the branched inputs of nerve cells, called dendrites. Branch growth was assisted by a protein called cypin. Some memory disabilities were related to deficits in cypin. So, one possibility was that nerve cells grew new branches to store memory. New branches could represent added memory. But, human memory was immense. People were reported to be able to recognize, with 99.5% accuracy, any one of 2,500 images shown to them at one second intervals. Each of those images contained millions of pixels of specific information. When the size and scale of human memory was considered, the idea of branches, however microscopic, growing to add memories sounded perilously cancerous.
LTP was another possibility. High frequency stimulation of the dendrites of a neuron were known to improve the sensitivity of the synaptic nerve junctions. Such activity was seen to be “remembered” by the cell through greater sensitivity at specific inputs. Neurochemicals at the synaptic junctions were also known to increase such sensitivity. But, while the process enhanced memory, LTP failed to offer a global hypothesis about how memory could be stored.
The hippocampus was also mentioned in connection with memory research. Damage to this organ, a component of a region of the brain called the limbic system, was known to cause patients to forget ongoing events within a few seconds. But, incidents from childhood and early adult life were still remembered. Memory had faded from a couple of years prior to the event that caused damage to the hippocampus. Older memories were still retained by the patient even without the hippocampus. Evidently, the organ did not store such memories. It could play a role, but the actual storage of memory remained enigmatic. In the end, all science did know was that memory resided all over the system and that one particular organ helped the formation of memories.
Yet, the answer to the memory enigma had been staring them in the face for years. That happened, when science acknowledged the use of combinatorial coding by nerve cells in the olfactory system. Combinatorial coding sounded confusing and complex. But, in the context of nerve cells, combinatorial coding only meant that a nerve cell recognized combinations. If a nerve cell had dendritic inputs, identified as A, B, C and so on to Z, it could then fire, when it received inputs at ABD, ABP, or XYZ. It recognized those combinations. ABD, ABP, or XYZ. The cell could identify ABD from ABP. Subtle differences. Such 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.
Highly developed skill
It was combinatorial coding, which enabled nerve cells of reptilian nosebrains to recognize smells and make crucial life decisions since the beginnings of history. Such sensory power had been developed in animals to a remarkable degree. Research showed that dogs could register the parameters of a smell and then pick it out from millions of competing smells. The animals could detect a human scent on a glass slide that had been lightly fingerprinted and left outdoors for as much as two weeks. They 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 odor strength difference between footprints only a few feet apart, to determine the direction of a trail. Recording and recognizing ABD and DEF enabled animals to record and recall a single smell to differentiate it from millions of other smells. Inherited memories of millions of smells decided whether food was edible, or inedible, or whether a spoor was life threatening. The system had both newly recorded and inherited memories, which enabled them to recognize smells in the environment.
Inherited and acquired memories
While such remarkable odor recognition skills were known for ages, it was only in the late nineties that science discovered combinatorial coding. A Nobel Prize was awarded for the discovery of the use combinatorial coding by the olfactory system in 2004. The olfactory system used the coding to enable a relatively small number of olfactory receptors to recognize different odors. Science discovered that particular combinations could fire to trigger recognition. 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. We remembered the smell of oranges. Even the smell of sweat. Which meant that the system remembered those combinations. But science failed to recognize the true significance of combinatorial coding when they searched for the location of human memory. Millions of combinations were possible for the nerve cell with inputs from A to Z. But nerve cells had thousands of inputs. If nerve cells remembered combinations, then that could be the location of a galactic nervous system memory.
Combinatorial coding could provide immense intelligence to the nervous system. The wonder of nature was the enormous scale, scope and sensitivity of its reporting systems. The mind had this vast army of scouts, reporting back on millions of tiny sensations – the heat of sun and the hardness of rock. Pain on the skin too was a report. When their impulses were received in the cortex, you felt pain. In the earlier example, with combinatorial coding, a cell could fire for ABD and be inhibited for ABP. If the pain reporting nerve cell recognized inputs from its neighbours, it could also respond to neighbouring pain and fire to report sympathetic pain. It could respond to touch and inhibit its own sympathetic pain message. The cell could respond to context.
Nerve cells didn’t receive just a few inputs. They received thousands. So, pain could be sensitive to context. Inherited memories in combinatorial codes could enable the system to recognize and respond to patterns in context. Combinatorial coding could explain the mind as a pattern recognition engine. But science worked on the assumption that the neurons in the brain did not recognize, but did computations. The search for a mathematical formula which could simulate the computations of the mind goes on. But, if you assumed pattern recognition, you just stepped out of the mathematical maze. Unfortunately, the recognition of patterns was too formidable a task for computers. The diagnosis of diseases was a typical pattern recognition problem.
The pattern recognition difficulty
The obstacle was that many shared symptoms were presented by different diseases. Pain, or fever were present for many diseases. Each symptom pointed to several diseases. In the customary search, the first selected disease with the first presented symptom could lack the second symptom. So the back and forth searches followed an exponentially expanding trajectory as the database increased in size. That made the process absurdly long drawn – theoretically, even years, when searching extensive databases. In the light of such an impregnable problem, science did not evaluate pattern recognition as a practical process for the nervous system.
An instant pattern recognition process
There is an Intuitive Algorithm (IA), which follows a logical process to achieve real time pattern recognition. IA was unique. In a feat never achieved by computers before, IA could almost instantly diagnose diseases. IA used elimination to narrow down possibilities to reach the correct answer. In essence, IA did not calculate, but used elimination to recognize patterns. IA acted 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 did this holistically and almost instantly, through simple, logical steps. IA proved that holistic, instant, real time pattern recognition was practical. IA provided a clue to the secret of intuition. The website intuition.co.in and the book explain IA in detail.
Seamless pattern recognition
The mind was a recognition machine, which instantly recognized the context of its ever changing environment. The system triggered feelings when particular classes of events were recognized. The process was achieved by inherited nerve cell memories accumulated across millions of years. The memories enabled the mind to recognize events. Similar inherited memories in nerve cells enabled the mind to trigger feelings, when events were recognized. And further cell memories caused feelings to trigger actions. Actions were sequences of muscle movements. Even drive sequences could be remembered by nerve cells. That was how we were driven. So the circuit closed. Half a second for a 100 billion nerve cells to use context to eliminate irrelevance and deliver motor output. The time between the shadow and the scream. So, from input to output, the mind was a seamless pattern recognition machine.
Intuition and memory
Walter Freeman the famous neurobiologist defined the critical difficulty for science in understanding the mind. “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 step, your next breath, your next moment.” The mind was holistic. It evaluated all its knowledge for the next activity. However large its database, the logic of IA could yield instant pattern recognition. Since that logic was robust and practical, intuition could also be such an instant pattern recognition process. Intuition could then power the mind to instantly recognize an infinite variety of objects and events to trigger motor responses. Each living moment, it could evaluate the context of a dynamic multi-sensory world and its own vast memories. Those memories could be stored in the combinatorial codes of nerve cells. The Nobel Prize should have been awarded not for the discovery of combinatorial coding, but for the discovery of human memory.