Use this URL to cite or link to this record in EThOS:
Title: The role of planning in motor learning
Author: Sheahan, Hannah Rachel
ISNI:       0000 0004 7968 6243
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2019
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Humans can learn a remarkable diversity of motor skills. While these skills are sometimes long lasting, they may also be subject to interference. For example, people can learn to reach in the presence of a dynamic (force-field) perturbation generated by a robotic interface. However, when two force fields that act in opposing directions are presented alternately, there is substantial interference, preventing learning of either. Here we examine the role of motor planning in motor memory formation and interference. We challenge a predominant view of motor learning, which suggests that multiple perturbations can only be learned when each is associated (closely in time) with a different physical (or perceived) state of the body. Instead, we show that two opposing perturbations which interfere when experienced over the same movement, can be learned if each is associated with a different neural state (i.e. motor plan). That is, distinct motor memories can be formed by planning each movement through the perturbation as part of a different, wider motor sequence, even if not executed. Exploring the implications of this result, we subsequently show that like planning, motor imagery of different future movements can change the neural state to affect the separation of motor memories. These results lead us to propose that situations which generate different neural responses in motor-related regions will naturally act as different contexts for learning. Interestingly however, we show that the same principle does not appear to underlie motor memory decay. Finally, having established the importance of planning in motor adaptation, we attempt to predict how motor plans should be divided and recombined when task sets become more complex. We simulate normative control policies under the hypothesis that motor chunking may arise from the need to efficiently represent motor commands, and test the implications for concurrent field learning. Together, these results highlight that the actions that humans plan are critical to the representation of motor skills that are learned. This suggests a key role for motor planning in the broad control repertoire humans develop.
Supervisor: Wolpert, Daniel Sponsor: Rutherford Foundation
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: motor ; learning ; planning ; psychophysics ; motor control ; neuroscience ; memory