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Journal of Computational Neuroscience - Editor's Highlight: A model for the transfer of control from the brain to the spinal cord through synaptic learning

In this paper, the authors present a novel approach to understanding the organization of spinal circuitry. Rather than taking the viewpoint that the circuitry is hardwired, they consider models in which spinal synaptic organization is learned from descending control signals.  Their model leads to the emergence of reflex groups in accord with known neurophysiology, and proposes hypothetical learning mechanisms that can be probed in future experiments.

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