For decades, research has shown that our perception of the world
is influenced by our expectations. These expectations also called "prior
beliefs," help us make sense of what we are perceiving in the present,
based on similar past experiences.
Consider,
for instance, how a shadow on a patient's X-ray image, easily missed by a less
experienced intern jumps out at a seasoned physician. The physician's prior
experience helps her arrive at the most probable interpretation of a weak
signal.
The
process of combining prior knowledge with uncertain evidence is known as
Bayesian integration and is believed to widely impact our perceptions,
thoughts, and actions. Now, MIT neuroscientists have discovered distinctive
brain signals that encode these prior beliefs. They have also found how the
brain uses these signals to make judicious decisions in the face of
uncertainty.
"How
these beliefs come to influence brain activity and bias our perceptions was the question we wanted to answer," says Mehrdad Jazayeri, the Robert A.
Swanson Career Development Professor of Life Sciences, a member of MIT's
McGovern Institute for Brain Research, and the senior author of the study.
The
researchers trained animals to perform a timing task in which they had to
reproduce different time intervals. Performing this task is challenging because
our sense of time is imperfect and can go too fast or too slow. However, when
intervals are consistently within a fixed range, the best strategy is to bias
responses toward the middle of the range. This is exactly what animals did.
Moreover, recording from neurons in the frontal cortex revealed a simple mechanism for Bayesian integration: Prior experience warped the representation
of time in the brain so that patterns of neural activity associated with
different intervals were biased toward those that were within the expected
range.
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