One Simple Algorithm Could Explain Human Intelligence
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.”
Last year, Tsien published a paper describing his “Theory of Connectivity”, in which he put forward the idea that groups of neurons, called neural cliques, come together in pre-wired ways to process thought and knowledge.
Essentially, it’s a framework for arranging the brain’s billions of neurons.
Tsien says these cliques then assemble to form functional connectivity motifs (FCMs), which could represent all the potential variations in human thought.
The harder we need to think, the hypothesis goes, the more cliques are required to make up that FCM.
For his latest study, Tsien put his Theory of Connectivity and FCMs to the test, using electrodes implanted at specific points in the brains of mice and hamsters to monitor neuron activity.
Sure enough, his team was able to predict the neural cliques that formed in response to certain scenarios, such as the arrival of food or the presence of a threat. Depending on the scenario, the animals’ neurons arranged themselves in very predictable groups.
In one test, four different foods were placed in front of a group of mice, and the researchers watched as the neurons grouped together instantly. They were even able to identify different clique formations depending on what combinations of foods were presented.
“For it to be a universal principle, it needs to be operating in many neural circuits, so we selected seven different brain regions and, surprisingly, we indeed saw this principle operating in all these regions,” explains Tsien.
These cliques appeared almost immediately as the food appeared, which suggests that they’re somehow ‘pre-wired’ during brain development.
At the centre of Tsien’s hypothesis is the formula n=2ⁱ-1, where ‘n’ is the number of connected neural cliques, ‘2’ indicates whether the neurons are receiving an input or not, ‘i’ is the information being received, and ‘-1’ is accounting for multiple possibilities.
Tsien says this formula is enough to predict FCM grouping.
“This equation gives you a way to wire the brain cells in such a way to turn seemingly infinite possibilities into organised knowledge,” he said.
Of course, these experiments have so far only been conducted on hamsters and mice, so until we can replicate the findings in humans, we won’t have a complete set of rules that explains all our human thoughts.
But the algorithm does demonstrate how neuron groupings can follow certain patterns, and gives scientists a new direction in the study of intelligence.
“Tsien proposes an interesting idea that proposes a simple organisational principle of the brain, and that is supported by intriguing and suggestive evidence,” says neuroscientist Thomas Südhof from Stanford University, who wasn’t involved in the research.
“This idea is very much worth testing further.”
The study has been published in Frontiers in Systems Neuroscience.
DAVID NIELD, ScienceAlert