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Related Experiment Video

Updated: May 1, 2026

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Adaptive gain control during human perceptual choice.

Samuel Cheadle¹, Valentin Wyart², Konstantinos Tsetsos¹

¹Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK.

|March 25, 2014

Summary

This summary is machine-generated.

Neural systems show adaptive gain control in decision-making. Information processing gain adapts to recent evidence, influencing choices and neural signals during serial integration.

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Area of Science:

Neuroscience
Cognitive Science
Computational Modeling

Background:

Adaptive gain control is crucial for sensory processing.
Its role in decision-making models is understudied.
Understanding neural adaptation in decision tasks is key.

Purpose of the Study:

To investigate adaptive gain control in serial information integration for decision-making.
To explore how neural systems adjust processing based on evidence history.
To link behavioral biases to neural and physiological signals.

Main Methods:

Human observers performed a visual decision task involving serial sampling.
Behavioral choices were analyzed for biases related to evidence consistency.
Pupillometry and functional neuroimaging (fMRI) recorded neural and physiological responses.
A serial sampling model with adaptive gain was used for data interpretation.

Main Results:

Sample influence on choice depended on consistency with prior evidence.
More consistent samples had a greater impact on decisions.
Pupillometric and neuroimaging signals reflected this adaptive gain control.
The observed effects were well-explained by the adaptive serial sampling model.

Conclusions:

Evidence supports adaptive gain control during serial decision-making.
Neural gain rapidly adjusts to the average of available evidence.
This mechanism influences both behavior and neural processing in decision tasks.