How expectation influences perception

ScienceDaily | 7/15/2019 | Staff
j.moomin (Posted by) Level 3
The process of combining prior knowledge with uncertain evidence is known as Bayesian integration and is believed to impact widely 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.

Researchers - Animals - Timing - Task - Time

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.

MIT postdoc Hansem Sohn, former postdoc Devika Narain, and graduate student Nicolas Meirhaeghe are the lead authors of the study, which appears in the July 15 issue of Neuron.

Statisticians - Centuries - Integration - Strategy - Information

Statisticians have known for centuries that Bayesian integration is the optimal strategy for handling uncertain information. When we are uncertain about something, we automatically rely on our prior experiences to optimize behavior.

"If you can't quite tell what something is, but from your prior experience you have some expectation of what it ought to be, then you will use that...
(Excerpt) Read more at: ScienceDaily
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