A model of audio-visual motion integration during active self-movement.

Area of Science:

• Neuroscience
• Sensory Perception
• Human Movement Science

Background:

• Optimal audio-visual integration is well-established in stationary individuals.
• Self-movement, including head and eye motion, complicates sensory integration due to differing coordinate frames.
• Understanding how the brain integrates audio-visual information during active movement is crucial.

Purpose of the Study:

• To investigate the impact of self-generated head rotations on audio-visual motion perception.
• To test the hypothesis that audio and visual motion cues are transformed into a common body-centered frame before integration.
• To determine if shared noise from head movement signals affects perceptual precision.

Main Methods:

• A psychophysical audio-visual integration task was employed.
• Participants judged audio, visual, or audio-visual targets during self-generated yaw head rotations.
• Models predicting audio-visual performance based on coordinate transformation and shared noise were evaluated.

Main Results:

• Audio-visual performance was accurately predicted by models incorporating coordinate transformation.
• Models not relying on coordinate transformation failed to explain the observed performance.
• Perceptual precision was better explained by models accounting for shared noise related to head movement signals.

Conclusions:

• Motion perception during self-movement involves integrating partially correlated body-centered signals.
• Coordinate transformation of sensory cues into a common frame is essential for audio-visual integration during active motion.
• Shared neural noise associated with self-movement signals influences the precision of integrated perception.