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Related Experiment Video

Updated: Aug 26, 2025

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Perceived speed at low luminance: Lights out for the Bayesian observer?

Tom C A Freeman¹, Georgie Powell¹

¹School of Psychology, Cardiff University, Tower Building, 70, Park Place, Cardiff CF10 3AT, United Kingdom.

Vision Research

|October 4, 2022

Summary

Bayesian models explain perception using sensory precision and prior expectations. New findings suggest motion perception is Bayesian, but relies on noisy sensory data that varies with light levels.

Keywords:

Bayesian models Luminance Motion perception Perceived speed

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Published on: May 2, 2019

Area of Science:

Visual perception
Computational neuroscience
Bayesian modeling

Background:

Bayesian models explain perception by weighting sensory evidence with prior expectations based on measurement precision.
In motion perception, a 'slow-motion' prior explains illusions, aligning with precision thresholds.
A challenge arises because moving objects appear faster in darkness, contradicting models where low luminance worsens motion thresholds.

Purpose of the Study:

To investigate the role of luminance and sensory precision in motion perception within a Bayesian framework.
To determine if motion processing deviates from Bayesian principles under varying light conditions.
To explore how contrast cues influence perceived speed in low light.

Main Methods:

Experiments measured speed discrimination performance across different luminance levels.
A perceived contrast cue was manipulated to isolate its effect on speed perception.
External noise was added to sensory measurements in a final experiment.

Main Results:

Speed discrimination performance improved in low light due to a salient perceived contrast cue.
When the contrast cue was removed, discrimination became luminance-independent.
Perceived speed still increased in the dark, independent of the contrast cue.
Adding external noise restored Bayesian behavior, worsening discrimination and slowing perceived speed.

Conclusions:

Motion perception appears to operate in a Bayesian manner, contrary to initial challenges posed by low-light conditions.
The accuracy of sensory measurements in motion processing is not independent of stimulus properties like luminance.
Noisy sensory measurements, whose accuracy varies with conditions, underpin Bayesian motion processing.