The brain is a complex processing unit that contains more than 200 billion neurons that emit thousands of electrical signals per second. This specificity is that the human brain is one of the most sophisticated organs of the human body. The capacity of the brain, i.e. the things it can do and how it performs have led researchers to be inspired to create an artificial intelligence model.
A recent study published in the Frontiers in Systems Neuroscience journal shows that human intelligence would be the product of an underlying algorithm. The paper suggests that despite the complexity of the human brain, a simple algorithm could help replicate our thinking.
According to Joe Tsien, a neuroscientist at the Medical College Of Georgia in the State University of Augusta, the algorithm found in the Connectivity Theory (Theory of Connectivity) is based on a relatively simple mathematical logic behind the complexity the computations in the human brain. Basically, it is a theory based on the acquisition of knowledge and our ability to generalize and draw conclusions, and billions of neurons perform this function. The brain would only follow a simple but amazing mathematical logic.
The theory describes how a group of similar neurons form a complex cliques or groups to handle basic ideas or information. These groups gather into FCM (functional connectivity patterns), which are responsible for handling all the possible combinations of ideas. More thoughts are complex, and it will take cliques to manipulate.
To test this hypothesis, Tsien and his team monitored and documented how the algorithm works in seven different regions of the brain, each specialized in a specific type of tasks and basics feelings like food and fear of mice and hamsters. The algorithm shows how many clicks are required for FCM.
The researchers gave the animals several combinations of four different types of food (biscuits, pellets, rice, and milk). By using electrodes placed on specific parts of the brain, they were able to capture the response of neurons. The researchers were able to identify every fifteen different combinations of neurons or cliques who responded to the assortment of combinations of food on offer and as predicted by theory. They also found that these neural cliques are pre-recorded in the brain since they appear immediately after the presentation of food choices.
If intelligence in the human brain in all its complexity can be summarized to a particular algorithm, imagine what it would mean for the Advancement of Artificial Intelligence. It will be possible to build models of AI based on models inspired by the human brain.
What do you think?