Adaptive gain control during human perceptual choice

Samuel Cheadle, Valentin Wyart, Konstantinos Tsetsos, Nicholas Myers, Vincent de Gardelle, Santiago Herce Castañón, Christopher Summerfield

Research output: Contribution to journalArticle (Academic Journal)peer-review

108 Citations (Scopus)


Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, with more consistent or expected samples wielding the greatest influence over choice. This bias was also visible in the encoding of decision information in pupillometric signals and in cortical responses measured with functional neuroimaging. These data can be accounted for with a serial sampling model in which the gain of information processing adapts rapidly to reflect the average of the available evidence.

Original languageEnglish
Pages (from-to)1429-1441
Number of pages13
Issue number6
Publication statusPublished - 19 Mar 2014

Bibliographical note

Copyright © 2014 Elsevier Inc. All rights reserved.


  • Adaptation, Psychological/physiology
  • Bias
  • Choice Behavior/physiology
  • Decision Making/physiology
  • Humans
  • Neuroimaging/methods
  • Photic Stimulation/methods
  • Visual Perception/physiology


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