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      The Value of the Follow-Through Derives from Motor Learning Depending on Future Actions

      brief-report
      1 , , 2 , 3 , 2 , 3 , ∗∗
      Current Biology
      Cell Press

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          Summary

          In ball sports, we are taught to follow through, despite the inability of events after contact or release to influence the outcome [ 1, 2]. Here we show that the specific motor memory active at any given moment critically depends on the movement that will be made in the near future. We demonstrate that associating a different follow-through movement with two motor skills that normally interfere [ 3–7] allows them to be learned simultaneously, suggesting that distinct future actions activate separate motor memories. This implies that when learning a skill, a variable follow-through would activate multiple motor memories across practice, whereas a consistent follow-through would activate a single motor memory, resulting in faster learning. We confirm this prediction and show that such follow-through effects influence adaptation over time periods associated with real-world skill learning. Overall, our results indicate that movements made in the immediate future influence the current active motor memory. This suggests that there is a critical time period both before [ 8] and after the current movement that determines motor memory activation and controls learning.

          Highlights

          • Future movements determine which motor memory is currently active and modifiable

          • Skills that otherwise interfere can be learned if each has a unique follow-through

          • A single skill is learned faster if its follow-through is consistent

          • Selection of motor memories depends on both lead-in and follow-through movements

          Abstract

          For a motor skill to be learned, its motor memory must be stored, protected from interference, and reactivated for modification during practice. Howard et al. demonstrate that future movement determines which motor memory is currently active and that a consistent follow-through constrains skill acquisition to a single memory, thereby speeding up learning.

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          Most cited references34

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          Neural population dynamics during reaching

          Most theories of motor cortex have assumed that neural activity represents movement parameters. This view derives from an analogous approach to primary visual cortex, where neural activity represents patterns of light. Yet it is unclear how well that analogy holds. Single-neuron responses in motor cortex appear strikingly complex, and there is marked disagreement regarding which movement parameters are represented. A better analogy might be with other motor systems, where a common principle is rhythmic neural activity. We found that motor cortex responses during reaching contain a brief but strong oscillatory component, something quite unexpected for a non-periodic behavior. Oscillation amplitude and phase followed naturally from the preparatory state, suggesting a mechanistic role for preparatory neural activity. These results demonstrate unexpected yet surprisingly simple structure in the population response. That underlying structure explains many of the confusing features of individual-neuron responses.
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            Neural correlates of reaching decisions in dorsal premotor cortex: specification of multiple direction choices and final selection of action.

            We show that while a primate chooses between two reaching actions, its motor system first represents both options and later reflects selection between them. When two potential targets appeared, many (43%) task-related, directionally tuned cells in dorsal premotor cortex (PMd) discharged if one of the targets was near their preferred direction. At the population level, this generated two simultaneous sustained directional signals corresponding to the current reach options. After a subsequent nonspatial cue identified the correct target, the corresponding directional signal increased, and the signal for the rejected target was suppressed. The PMd population reliably predicted the monkey's response choice, including errors. This supports a planning model in which multiple reach options are initially specified and then gradually eliminated in a competition for overt execution, as more information accumulates.
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              Consolidation in human motor memory.

              Learning a motor skill sets in motion neural processes that continue to evolve after practice has ended, a phenomenon known as consolidation. Here we present psychophysical evidence for this, and show that consolidation of a motor skill was disrupted when a second motor task was learned immediately after the first. There was no disruption if four hours elapsed between learning the two motor skills, with consolidation occurring gradually over this period. Previous studies in humans and other primates have found this time-dependent disruption of consolidation only in explicit memory tasks, which rely on brain structures in the medial temporal lobe. Our results indicate that motor memories, which do not depend on the medial temporal lobe, can be transformed by a similar process of consolidation. By extending the phenomenon of consolidation to motor memory, our results indicate that distinct neural systems share similar characteristics when encoding and storing new information.
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                Author and article information

                Contributors
                Journal
                Curr Biol
                Curr. Biol
                Current Biology
                Cell Press
                0960-9822
                1879-0445
                02 February 2015
                02 February 2015
                : 25
                : 3
                : 397-401
                Affiliations
                [1 ]Centre for Robotics and Neural Systems, University of Plymouth, Portland Square, Plymouth PL4 8AA UK
                [2 ]Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK
                Author notes
                []Corresponding author ian.howard@ 123456plymouth.ac.uk
                [∗∗ ]Corresponding author dwf25@ 123456cam.ac.uk
                [3]

                Co-senior author

                Article
                S0960-9822(14)01640-6
                10.1016/j.cub.2014.12.037
                4320013
                25578907
                858e369d-beb2-415d-af5c-d737e95451e9
                © 2015 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 8 September 2014
                : 28 October 2014
                : 15 December 2014
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                Life sciences
                Life sciences

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