Human perception is based on mathematically optimal principles, but the brain implements these principles imperfectly, suggests new research by Elina Stengård and Ronald van den Berg of the University of Uppsala, Sweden. They present their findings in PLOS computational biology.
The human brain uses inaccurate sensory inputs to determine the truths about the surrounding environment. Previous research has suggested that human perception is "Bayesian", which means that the brain explains the uncertainty of sensory observations in a mathematically optimal way. However, some of those studies have been mathematically criticized, and other research suggests that the brain is intrinsically inaccurate at the neural level.
To address these concerns, Van den Berg and Stengård presented 30 volunteers with a series of perception tests. These tests involved identifying if the ellipse shapes that appeared on a screen tilted to the right or to the left from the vertical. Different tests incorporated the sensory uncertainty in different ways, such as varying degrees of elongation of the ellipse shape, distractions in the form of nearby ellipses, and a brief display time of the ellipse on the screen.
The researchers then badyzed their results against a series of different mathematical models. They found that the data is better explained by a model that is Bayesian in its core, but is also subject to imperfections. This model surpbaded both an optimal Bayesian model and all the non-Bayesian models that were tested.
"Our results suggest that human perception is marked in optimal strategies, although the brain's execution of these strategies seems to be imperfect," says Van den Berg. "This new concept provides a theoretical middle ground between the seemingly opposite literatures of optimal models and heuristic models."
Additional research is needed to identify the causes of the apparent imperfections in the decision-making process during the perception tests of the ellipse. Future research could also test whether the imperfect Bayesian model can explain human behavior in other types of perception tests and higher level cognitive decision-making tasks.
Self-consistency influences how we make decisions.
Elina Stengård et al, Bayesian imperfect inference in visual perception, PLOS computational biology (2019). DOI: 10.1371 / journal.pcbi.1006465
The imperfect execution of the brain of mathematically optimal perception (2019, April 18)
retrieved on April 18, 2019
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