Bayesian integration is the process of combining prior knowledge with uncertain evidence. Statisticians have shown that Bayesian integration is the most optimal strategy for handling a certain environment with uncertain information.  Whenever we are uncertain about something the human brain automatically relies on the most suitable prior experience that it believes can successfully help tackle the oncoming situation. It is also proved that Bayesian integration can vastly impact our actions, thoughts and even our perspectives. MIT neuroscientists have discovered unique brain signals that encode the prior believe and have found that the brain makes use of these signals to make decisions when confronted with uncertainty. The researchers also made use of a computer model which further underlines the mechanism which is currently impossible to experiment with regards to the brain. They, however, were able to show the neural representations and unwrapping of extremely biased behavior which validate the critical knowledge of Bayesian integration of prior data.

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