Expectations about precision bias metacognition and awareness.

Area of Science:

• Cognitive Neuroscience
• Computational Psychiatry
• Psychology

Background:

• Bayesian models propose the brain estimates sensory signal reliability (precision) for perception and confidence.
• Accurate precision estimation is challenging for biological systems.
• Expectations about sensory precision may guide metacognition and awareness.

Purpose of the Study:

• To investigate if expectations about sensory precision influence metacognition and subjective awareness.
• To test the role of predictive learning in inferring sensory precision.

Main Methods:

• Participants performed perceptual decisions on visual motion stimuli.
• Confidence and subjective visibility ratings were collected.
• Probabilistic expectations about signal strength were acquired.
• Computational modeling using a predictive learning framework was employed.

Main Results:

• Expectations about precision altered metacognition and awareness.
• Higher confidence and vividness were reported when stronger signals were expected.
• Objective perceptual performance remained unchanged.
• A predictive learning model explained the observed effects.

Conclusions:

• Expectations about sensory precision significantly influence metacognition and subjective awareness.
• The brain utilizes prior knowledge about precision, not just incoming evidence.
• This supports the role of predictive processing in shaping sensory experience and trust.