Not Noisy, Just Wrong: The Role of Suboptimal Inference in Behavioral Variability

Jeffrey M. Beck, Wei Ji Ma, Xaq Pitkow, Peter E. Latham, Alexandre Pouget

Research output: Contribution to journalReview articlepeer-review

Abstract

Behavior varies from trial to trial even when the stimulus is maintained as constant as possible. In many models, this variability is attributed to noise in the brain. Here, we propose that there is another major source of variability: suboptimal inference. Importantly, we argue that in most tasks of interest, and particularly complex ones, suboptimal inference is likely to be the dominant component of behavioral variability. This perspective explains a variety of intriguing observations, including why variability appears to be larger on the sensory than on the motor side, and why our sensors are sometimes surprisingly unreliable. Behavioral variability has often been attributed to noise in the brain. In this Perspective, Pouget and colleagues propose that there is another major source of variability, suboptimal inference, which is the dominant component of behavioral variability in complex tasks.

Original languageEnglish (US)
Pages (from-to)30-39
Number of pages10
JournalNeuron
Volume74
Issue number1
DOIs
StatePublished - Apr 12 2012

ASJC Scopus subject areas

  • Neuroscience(all)

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