Novel plasticity rule can explain the development of sensorimotor intelligence.
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no system-specific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking, which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution.
Information Theory of Cognitive Systems, Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany;
Ralf
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Der
Information Theory of Cognitive Systems, Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany; Computer Vision and Machine Learning, Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria georg.martius@ist.ac.at.
Georg
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Martius
D001519:Behavior / Q000502:physiology*; D003198:Computer Simulation; D003405:Creativity; D005106:Exploratory Behavior; D006801:Humans; D008959:Models, Neurological; D009042:Motivation; D009424:Nervous System Physiological Phenomena / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology*; D012371:Robotics / Q000379:methods*
development; neural plasticity; robotics; self-organization; sensorimotor intelligence