Motor learning through the combination of primitives.

By Ferdinando A. Mussa-Ivaldi, Emilio Bizzi. 2000

375 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cognitive Neuroscience, Social Psychology

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Citations in the corpus

Archetypical motion: Supervised game behavior learning with Archetypal Analysis (2013, methodology): “vide the set of behaviors (or repertoires) that biological bodies can perform [15].”
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives (2010, background): “takes place through a combination of motor primitives [37].”
Learning Action Representations for Reinforcement Learning (2019, background): “Such abstractions of behavior that form the building blocks for motor control are often called motor primitives [Lemay and Grill, 2004, Mussa-Ivaldi and Bizzi, 2000].”
Parabolic movement primitives and cortical states: merging optimality with geometric invariance (2009, background): “The existence of motor primitives was demonstrated at the level of forces generated by muscles operating on the limbs (Bizzi et al. 1991; Giszter et al. 1993; Nichols 1994; Kargo and Giszter 2000; Mussa-Ivaldi and Bizzi 2000; Mussa-Ivaldi and Solla 2004), at the level of muscle synergies (Tresch et ”
Generalization in vision and motor control (2004, background): “Box 1 suggests a strong analogy between vision and motor control in the time-dependent case: the basic strategy is to combine locally tuned units with time-dependent propertie”
Coding and use of tactile signals from the fingertips in object manipulation tasks (2009, background): “There is indeed evidence that elementary action phases can be organized in various areas of the CNS, from spinal cord networks to frontoparietal cortical network”
Motor primitives in vertebrates and invertebrates. (2005, background): “Focusing here on motor control, ample evidence from both higher and lower levels of vertebrate and invertebrate motor systems suggests that voluntary actions are composed of simpler elements that are bonded to each other either simultaneously or serially in time [1,2,3 ,4,5].”
Neural primitives for motion control (2004, methodology): “Field approximation has been directly applied to the generation of a desired trajectory in generalized coordinates [35], [36].”
Emergence of Functional Hierarchy in a Multiple Timescale Neural Network Model: A Humanoid Robot Experiment (2008, neutral): “[6,7]).”