The human brain is the most sophisticated organ in the human body. The things that the brain can do, and how it does them, have even inspired a model of artificial intelligence (AI). Now, a recent study published in the journal Frontiers in Systems Neuroscience shows how human intelligence may be a product of a basic algorithm. This algorithm is found in the Theory of Connectivity, a "relatively simple mathematical logic underlies our complex brain computations," according to researcher and author Joe Tsien, neuroscientist at the Medical College of Georgia at Augusta University, co-director of the Augusta University Brain and Behavior Discovery Institute and Georgia Research Alliance Eminent Scholar in Cognitive and Systems Neurobiology. He first proposed the theory in October 2015.

At its core, Tsien's theory of connectivity describes how our billions of neurons flexibly assemble to not only gather knowledge, but to crystalize concepts and extrapolate from learned ideas to reason about things we have not yet experienced. "Intelligence is really about dealing with uncertainty and infinite possibilities," Tsien said in a press release. The theory is so seemingly banal that it's easy to dismiss as another pompous attempt at solving the brain's neural code -- all theory, no evidence. But in a new paper published in Frontiers in Systems Neuroscience, Tsien and his team took the theory to task in a series of animal experiments and found it at work in seven different brain regions, governing basic behaviors such as feeding, memory and fear. Even more controversially, the theory goes head-to-head with a fundamental teaching in neuroscience: cells that fire together, wire together.

A simple algorithm could explain the inner workings of human intelligence, and it could one day be encoded into artificial intelligence (AI) systems, researchers suggest. It's a mind-bending idea: that all the complex thoughts running through our heads are the product of a set of definable sums. But scientists have identified clear patterns in the brains of mice and hamsters, and if a similar phenomenon could be found in human brains, it could form the basis of such an algorithm for intelligence. "Many people have long speculated that there has to be a basic design principle from which intelligence originates and the brain evolves, like how the double helix of DNA and genetic codes are universal for every organism," says lead researcher Joe Tsien from Augusta University in Georgia. "We present evidence that the brain may operate on an amazingly simple mathematical logic."

It seems algorithms rule the world, now scientists think they have identified the algorithm responsible for human intelligence, if true then it could revolutionise artificial intelligence Little might you realise but as you read this article good chances are your brain is running its "n 2ⁱ-1" algorithm. And who said you couldn't do maths!? Scientists in the USA now believe that our brains have a basic algorithm that enable us to not just recognise a meal, or words on a page, for example, but also the intelligence to ponder their broader implications. "A relatively simple mathematical logic underlies our complex brain computations," said Dr. Joe Tsien, a neuroscientist at the Medical College of Georgia at Augusta University. Tsien is talking about his Theory of Connectivity, a fundamental principle for how our billions of neurons assemble and align not just to acquire knowledge, but to generalise and draw conclusions from it. Scientists pull images from peoples minds using AI and fMRI "Intelligence is really about dealing with uncertainty and infinite possibilities," said Tsien, "it appears to be enabled when a group of similar neurons form a variety of cliques to handle each basic like recognising food, shelter, friends and foes. Groups of cliques then cluster into functional connectivity motifs, or FCMs, to handle every possibility in each of these basics like extrapolating that rice is part of an important food group that might be a good side dish for your meal. The more complex the thought, the more cliques join in."