Our brain represents our environment using probabilities

While processing ambiguities in our environment, the brain uses very detailed probabilistic inference models to determine whether we are safe or in danger. This is what emerges from the latest study carried out by Philipp Schustek, Alexandre Hyafil and Rubén Moreno-Bote, researchers at the Center for Brain and Cognition at Pompeu University in Barcelona (Spain).

Posted in NatureCommunications, the study provides insight into how humans perceive their environment and make decisions. According to the researchers, information gathered from our immediate environment is not enough to determine whether we are in a safe or unsafe environment, which is why our brain uses an elaborate probabilistic inference model to reach a conclusion.

Reasoning by deduction

The researchers found that the human brain has a sophisticated form of representation of uncertainty at several hierarchical levels, which also takes into account the context of what it perceives.

According to Rubén Moreno-Bote, coordinator of the theoretical and cognitive neuroscience research group at Pompeu University, “notions of probability, although intuitive, are very difficult to quantify and use rigorously. For example, my statistics students often fail to solve some of the problems I pose in class. In our study, we find that a complex mathematical problem involving the use of the most sophisticated rules of probability can be solved intuitively if presented simply and in a natural context.”

Football fans at the airport

The researchers brought together a group of subjects, and asked them to project themselves into an airport. They had to predict the probability that the next plane carrying passengers would contain more or fewer people of a certain type, by observing the passengers of the previous planes.

Rubén Moreno-Bote explains his approach. “Participants were asked to count, for example, Barca supporters and Madrid supporters arriving at the airport and then predict the likelihood of more supporters arriving on the next flight. In general, this task structure creates hierarchical dependencies between the hidden variables to be solved (by inferring the context from previous observations) and getting the message across (by deducing the current state by combining the current observations with the inferred context). ”

The results showed that the subjects, from their preliminary observations, constructed a probabilistic representation of the situation, which helped the researchers to understand how these participants develop mental images of their environment and how they attribute and perceive the context uncertainty.

The researchers discovered that the human brain was capable of a probabilistic mathematical representation of the environment, which surely affected the perception of our environment and our decision-making.