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Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons.

Hazem Toutounji1, Frank Pasemann1

  • 1Department of Neurocybernetics, Institute of Cognitive Science, University of Osnabrück Osnabrück, Germany.

Frontiers in Neurorobotics
|June 7, 2014
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Summary

This study introduces self-regulating neurons with homeostatic properties and short-term memory for artificial agents. These neural networks enable stable behaviors and rapid state switching, crucial for robotic control.

Keywords:
autonomous agenthomeostasishysteresisoscillationself-regulationsensorimotor loopshort-term plasticitysynaptic plasticity

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Area of Science:

  • Computational Neuroscience
  • Robotics
  • Artificial Intelligence

Background:

  • Living systems rely on recurrent neural networks and neuronal plasticity for behavior and memory.
  • Artificial agents struggle with complex body-environment interactions and supporting multiple stable behaviors.
  • Short-term memory is essential for agents to switch behaviors rapidly, mirroring biological short-term synaptic plasticity.

Purpose of the Study:

  • To derive synaptic dynamics in recurrent neural networks for artificial agents.
  • To enable agents to support multiple stable behaviors and switch between them dynamically.
  • To implement short-term memory through neuronal self-regulation and homeostatic properties.

Main Methods:

  • Derivation of synaptic dynamics in recurrent neural networks.
  • Modeling neurons as self-regulating units with homeostatic properties and oscillatory capabilities.
  • Utilizing engineered or evolved network structures for neural behavior control.

Main Results:

  • Developed self-regulating neurons exhibiting stable states and short-term memory.
  • Demonstrated the capacity for rapid state switching in response to input history.
  • Successfully applied the neural systems to control hexapod locomotion and robot obstacle avoidance.

Conclusions:

  • The derived synaptic dynamics provide a foundation for artificial agents with adaptive and dynamic behavioral control.
  • Self-regulating neurons with homeostatic properties are effective for implementing short-term memory in neurocontrollers.
  • This approach advances the development of autonomous mobile agents capable of complex interactions.