Internal models in active self-motion estimation: role of inertial sensory cues
1Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
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Summary
Participants can build an internal model to predict steering dynamics, using past steering gain predictability to inform self-motion estimation. This model aids in predicting inertial sensory consequences during driving and self-motion.
Area of Science:
- Neuroscience
- Human Motor Control
- Perception
Background:
- Self-motion perception relies on sensory input and motor output predictions.
- In driving, steering commands can predict inertial motion cues if an internal model of steering dynamics exists.
Purpose of the Study:
- To investigate if humans can build an internal model of steering dynamics.
- To determine if steering behavior adapts to the predictability of steering-to-motion gain.
Main Methods:
- A closed-loop steering experiment was conducted on a motion platform in darkness.
- Steering-to-motion gain varied unpredictably (white noise), moderately (random walk), or predictably (constant gain) across trials.
- Participants steered to align with a memorized target, and their reliance on previous gain versus inertial feedback was assessed.
Main Results:
- Participants utilized previous trial gain more when it followed a random walk compared to unpredictable variations.
- Fast corrective responses to gain jumps occurred regardless of predictability, indicating reliance on inertial feedback.
- Findings support the internal model hypothesis over simple path integration.
Conclusions:
- The brain constructs internal models of steering dynamics to predict sensory consequences.
- These internal models are crucial for accurate self-motion estimation, particularly in dynamic environments like driving.
- The study highlights the interplay between predictive processing and sensory feedback in motor control.