Mapping Information Flow in Sensorimotor Networks
Author Information
Author(s): Lungarella Max, Sporns Olaf
Primary Institution: Department of Mechano-Informatics, The University of Tokyo, Tokyo, Japan
Hypothesis
Statistical regularities in sensory inputs and optimal coding in natural environments can be induced by the combined action of sensory and motor systems and by body morphology.
Conclusion
The study reveals that sensorimotor interaction and body morphology significantly influence information structure and flow in sensory inputs and neural control architectures.
Supporting Evidence
- Sensorimotor interaction induces statistical regularities in sensory inputs.
- Information flow is affected by learning and changes in body morphology.
- Robots were used to model embodied organisms and study information processing.
Takeaway
This study shows that how our bodies move and interact with the world affects how our brains process information, just like robots do when they sense and react to their environment.
Methodology
The study analyzed sensory and motor data from real and simulated robots to investigate the effects of sensorimotor coupling and body morphology on information flow.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website