Our brains contain a basic algorithm that allows us not only to recognize cats in any images on the Internet, but also triggers the intelligence that makes us who we are: intelligent beings, humans.
“At the heart of our complex brain computations is relatively simple mathematical logic,” says Dr. Joe Tsien, a neuroscientist at the Georgia College of Medicine at Augusta University. He talks about his "fusion theory", the fundamental principle of the assembly and relationship of our billions of neurons.
“Intelligence is a lot about working with uncertainty and endless possibilities,” says Tsien. It is born when a group of similar neurons forms a variety of groups that process basic things: recognize food, shelter, friends and enemies. These groups then coalesce into Functional Connectivity Motives (FMPs) to handle every possibility of these fundamentals, such as concluding that rice is part of an important food group that would be a Thanksgiving side dish. The more complex the thought, the more neurons get knocked together (or "clique," as the scientist calls it).
This means, for example, that we not only recognize the office chair, but also the office in which we saw the chair, and we know that we were sitting in this chair in this office.
“You know this is an office, whether in your home or in the White House,” says Tsien, noting that the ability to conceptualize knowledge is one of the many things that distinguishes us from computers.
Tsien first published his theory in October 2015 in the journal Trends in Neuroscience. Now he and his colleagues have documented this algorithm in seven different areas of the brain associated with these basics like food and fear in mice and hamsters. Their rationale was published in the journal Frontiers in Systems Neuroscience.
“For this principle to be universal, it must work in many neural circuits, so we selected seven different regions of the brain and suddenly saw this principle at work in all of these areas,” he says.
The human brain, it seems, could not work without the most complex organization - it is badly needed by 86 billion neurons, despite the fact that each neuron can have tens of thousands of synapses, and between all these neurons there are trillions of interactions. And on top of all these countless connections is the reality of an infinite number of things that each of us, presumably, can comprehend and study.
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Neuroscientists and computer experts have long wondered how the brain is able not only to hold specific information like a computer, but also - unlike even the most modern technologies - to classify and summarize information into abstract knowledge and concepts.
“Many people have long assumed that there should be a basic design principle from which intelligence flows and the brain develops, like the DNA double helix and genetic code that all organisms have,” says Tsien. "We came to the conclusion that the brain can work from surprisingly simple mathematical logic."
At the heart of Tjien's compound theory is the n = 2i-1 algorithm, which determines the number of groups (or "cliques" as the scientist calls them) needed for a PMF, and which allows scientists to predict the number of groups needed to recognize food options, for example framework of theory testing.
N is the number of neural groups connected in all possible ways; 2 - means that neurons in this group are receiving or not receiving input; i is the information they receive; -1 is the math part, allowing you to consider all the possibilities.
To test the theory, they placed electrodes in an area of the brain to "listen" to the neurons' responses or their action potential and to study the unique waveforms generated by these actions. They gave the animals different combinations of four different foods, like common rodent cookies, sugar balls, rice and milk, and as predicted by the connection theory, the scientists were able to identify all 15 different groups of neurons that respond to the potential variety of food combinations.
Neural clicks seem to appear already connected during brain development because they showed up immediately when food choices were made. This fundamental mathematical rule remained almost unchanged even when the NMDA prescription for learning and memory was turned off after the brain grew up.
Scientists have also found that size matters because although the human and animal brains have six-layered cortex - the outer layer of the brain that plays a key role in higher brain functions like learning and memory - the extra longitudinal length of the human brain provides more room for clicks and PMF. says Tsien. Although the overall girth of the elephant's brain is definitely larger than that of the human brain, most of its neurons are located in the cerebellum, which is much smaller than the cerebral cortex. The cerebellum is more actively involved in muscle coordination, which can explain the agility of a huge mammal with its gigantic size.
ILYA KHEL