The Calcitron: A Simple Neuron Model That Implements Many Learning Rules via the Calcium Control Hypothesis
Toviah Moldwin,
Li Shay Azran,
Idan Segev
Abstract:Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules for linear neuron models to enable artificial neural networks to accomplish supervised and unsupervised learning tasks. It has not been clear, however, how these theoretically-derived rules relate to biological mechanisms of plasticity that exist in the brain, or how the brain might mechanistically implement different learning rules in different contexts and brain regions. Here, we show that the calcium contr… Show more
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