Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

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 publication

DOI

10.1016/j.neuron.2014.01.020

Type

Journal article

Journal

Neuron

Publication Date

19/03/2014

Volume

81

Pages

1429 - 1441

Keywords

Adaptation, Psychological, Bias, Choice Behavior, Decision Making, Humans, Neuroimaging, Photic Stimulation, Visual Perception