Transfer learning is the capacity for learning in one context to influence behavior in another.  Though it has been studied across many domains, a mechanistic understanding of the dynamics governing the adaptability of learned representations remains elusive. Coleoid cephalopods, including the octopus, present a unique system capable of complex behaviors that are produced by a distributed nervous system in which sensory, motor, and memory circuits are more readily disentangled.  The octopus has a particularly sophisticated peripheral nervous system that exhibits highly efficient transfer learning across its arms, even in the context of arm damage and regeneration. An understanding of an alternative, highly successful, biological solution to transfer learning has far-reaching implications, and may inform novel strategies for engineering better adaptability in artificial or rehabilitation systems.  As a Grass Fellow, I will combine behavioral and computational approaches to establish the octopus arm as a model of sensorimotor learning and transfer.