Non-Associative Learning Representation in the Nervous System of the Nematode Caenorhabditis elegans

Ramin M. Hasani, Magdalena Fuchs, Victoria Beneder, Radu Grosu

Feb 15, 2017 (modified: Mar 20, 2017) ICLR 2017 workshop submission readers: everyone
  • Abstract: Caenorhabditis elegans (C. elegans) illustrated remarkable behavioral plasticities including complex non-associative and associative learning representations. Understanding the principles of such mechanisms presumably leads to constructive inspirations for the design of efficient learning algorithms. In the present study, we postulate a novel approach on modeling single neurons and synapses to study the mechanisms underlying learning in the C. elegans nervous system. In this regard, we construct a precise mathematical model of sensory neurons where we include multi-scale details from genes, ion channels and ion pumps, together with a dynamic model of synapses comprised of neurotransmitters and receptors kinetics. We recapitulate mechanosensory habituation mechanism, a non-associative learning process, in which elements of the neural network tune their parameters as a result of repeated input stimuli. Accordingly, we quantitatively demonstrate the roots of such plasticity in the neuronal and synaptic-level representations. Our findings can potentially give rise to the development of new bio-inspired learning algorithms.
  • TL;DR: The paper investigates the principles underlaying learning in the brain of the worm, C. elegans.
  • Keywords: Theory
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