Functional stages in the formation of human long-term motor memory. J. Neurosci., 17:409-19

Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, Maryland 21205-2195, USA.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 02/1997; 17(1):409-19.
Source: PubMed


Previous research has demonstrated that the primate CNS has the ability to learn and store multiple and conflicting visuo-motor maps. Here we studied the ability of human subjects to learn to make reaching movements while interacting with one of two conflicting mechanical environments as produced by a robotic manipulandum. We demonstrate that two motor maps may be learned and retained, but only if the training sessions in the tasks are separated by an interval of approximately 5 hr. If the interval is shorter, learning of the second map begins with an internal model appropriate for the first task and performance in the second task is significantly impaired. Analysis of the after-effects suggests that with a short temporal distance, learning of the second task leads to an unlearning of the internal model for the first. With the longer temporal distance, learning of the second task starts with an unbiased internal model, and performance approaches that of naives. Furthermore, the memory of the consolidated skill lasts for at least 5 months after training. These results argue for a distinct change in the state of resistance of motor memory (to disruption) within a few hours after acquisition. We suggest that motor practice results in memories that have at least two functional components: soon after completion of practice, one component fades while another is strengthened. A further experiment suggests that the hypothetical first stage is not merely a gateway to long-term memory, but also temporary storage for items of information, whether new or old, for use in the near-term. Our results raise the possibility that there are distinct neuronal mechanisms for representation of the two functional stages of motor memory.

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    • "In situations in which we repeatedly encounter the same motor task, the brain generates sensorimotor predictions about the likely outcome of the event and accordingly adapts our motor plans (Shadmehr and Brashers-Krug 1997; Wolpert et al. 2011). This is an error-based motor learning process that quickly allows modification of motor strategies to maintain motor control in the face of an external perturbation (Bastian 2008). "
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    ABSTRACT: Observing the motor actions of another person could facilitate compensatory motor behaviour in the passive observer. Here, we explored whether action observation alone can induce automatic locomotor adaptation in humans. To explore this possibility we used the "broken-escalator" paradigm. Conventionally this involves stepping upon a stationary sled after having previously experienced it actually moving (MOVING trials). This history of motion produces a locomotor aftereffect when subsequently stepping on to a stationary sled. We found that viewing an actor perform the MOVING trials was sufficient to generate a locomotor aftereffect in the observer, the size of which was significantly correlated with the size of the movement (postural sway) observed. Crucially, the effect is specific to watching the task being performed, as no motor adaptation occurs after simply viewing the sled move in isolation. These findings demonstrate that locomotor adaptation in humans can be driven purely by action observation, with the brain adapting motor plans in response to the size of the observed individual's motion. This mechanism may be mediated by a mirror neuron system that automatically adapts behaviour to minimise movement errors and improve motor skills through social cues, though further neurophysiological studies are required to support this theory. These data suggest that merely observing the gait of another person in a challenging environment is sufficient to generate appropriate postural countermeasures, implying the existence of an automatic mechanism for adapting locomotor behaviour. Copyright © 2015, Journal of Neurophysiology.
    Journal of Neurophysiology 07/2015; 114(3):jn.00446.2015. DOI:10.1152/jn.00446.2015 · 2.89 Impact Factor
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    • "There have been important advancements in our understanding of the time-course (phases) and constraints on the acquisition of volitional, task oriented, motor skills in adults (Born, 2010; Stickgold and Walker, 2005; Robertson et al., 2005; Doyon and Ungerleider, 2003; Karni et al., 1998; Karni, 1996) but whether these characterize the acquisition of balance skills as well is not known. The learning of task-related movement routines and specifically the generation of long-term procedural memory for the performance of task oriented movement sequences can be characterized by several distinct phases which have been delineated in a number of laboratory tasks (e.g., Meital et al., 2013; Korman et al., 2007; Robertson, 2005; Stickgold and Walker, 2005; Sosnik et al., 2004; Maquet et al., 2003; Doyon and Ungerleider, 2003; Korman et al., 2003; Hikosaka et al., 1999; Karni et al., 1998; Shadmehr and Brashers-Krug, 1997). Rapid gains in performance occur early on in training ( " fast learning " , novelty effect) but after a certain number of within-session task iterations, performance levels off if task conditions during the training session are unchanged (e.g., Adi-Japha et al., 2008; Korman et al., 2003; Hauptmann and Karni, 2002; Karni and Sagi, 1993). "
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    ABSTRACT: Does the learning of a balance and stability skill exhibit time-course phases and transfer limitations characteristic of the acquisition and consolidation of voluntary movement sequences? Here we followed the performance of young adults trained in maintaining balance while standing on a moving platform synchronized with a virtual reality road travel scene. The training protocol included 8 3-minutes long iterations of the road scene. Center of Pressure (CoP) displacements were analyzed for each task iteration within the training session, as well as during tests at 24h, 4 weeks and 12 weeks post-training to test for consolidation phase ("offline") gains and assess retention. In addition, CoP displacements in reaction to external perturbations were assessed before and after the training session and in the 3 subsequent post-training assessments (stability tests). There were significant reductions in CoP displacements as experience accumulated within session, with performance stabilizing by the end of the session. However, CoP displacements were further reduced at 24h post-training (delayed "offline" gains) and these gains were robustly retained. There was no transfer of the practice-related gains to performance in the stability tests. The time-course of learning the balance maintenance task, as well as the limitation on generalizing the gains to untrained conditions, are in line with the results of studies of manual movement skill learning. The current results support the conjecture that a similar repertoire of basic neuronal mechanisms of plasticity may underlay skill (procedural, "how to" knowledge) acquisition and skill memory consolidation in voluntary and balance maintenance tasks. Copyright © 2015. Published by Elsevier B.V.
    Brain research 03/2015; 1609(1). DOI:10.1016/j.brainres.2015.03.020 · 2.84 Impact Factor
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    • "Furthermore, a model employing two coordinate representations has been proposed, where a weighted sum of reference frames can be shaped by the context of the environment (Berniker and Kording 2008). These internal models can also have interference or combinatory effect during adaptation (Ghahramani and Wolpert 1997; Shadmehr and Brashers-Krug 1997; Blakemore et al. 1998; Wolpert and Kawato 1998; Flanagan et al. 1999; Haruno et al. 1999; Shadmehr and Holcomb 1999). We suspect that separate networks encode the inverse dynamics of the environment, based on both extrinsic versus intrinsic coordinates. "
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    ABSTRACT: Several studies have suggested that the motor system takes advantage of a coordinate system when learning a novel sensorimotor environment. Such investigations, however, have not distinguished between initial preferences of a coordinate system versus possible changes due to learning. Here, we present experimental methods that specifically entertain the possibility of multiple coordinate systems during generalization. Subjects trained with their right arm on a viscous force field. We evaluated their performances for both arms in an untrained workspace before and after training using three fields, each representing extrapolation with a candidate coordinate system. Surprisingly, our results showed evidence of improvement (pre to post) in all fields for both limbs. These findings are consistent with the hypothesis of multiple, simultaneous coordinate systems involved in generalization. We also investigated how feedback might affect the results and found in several cases that performance was better for visual displays that were aligned with the limb (in first person) versus non-aligned.
    Experimental Brain Research 09/2014; 233(1). DOI:10.1007/s00221-014-4034-6 · 2.04 Impact Factor
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