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      Temporal dynamics of cerebellar and motor cortex physiological processes during motor skill learning

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      1 , 2 , a , 2 , 3 , 4
      Scientific Reports
      Nature Publishing Group

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          Abstract

          Learning motor tasks involves distinct physiological processes in the cerebellum (CB) and primary motor cortex (M1). Previous studies have shown that motor learning results in at least two important neurophysiological changes: modulation of cerebellar output mediated in-part by long-term depression of parallel fiber-Purkinje cell synapse and induction of long-term plasticity (LTP) in M1, leading to transient occlusion of additional LTP-like plasticity. However, little is known about the temporal dynamics of these two physiological mechanisms during motor skill learning. Here we use non-invasive brain stimulation to explore CB and M1 mechanisms during early and late motor skill learning in humans. We predicted that early skill acquisition would be proportional to cerebellar excitability (CBI) changes, whereas later stages of learning will result in M1 LTP-like plasticity modifications. We found that early, and not late into skill training, CBI changed. Whereas, occlusion of LTP-like plasticity over M1 occurred only during late, but not early training. These findings indicate a distinct temporal dissociation in the physiological role of the CB and M1 when learning a novel skill. Understanding the role and temporal dynamics of different brain regions during motor learning is critical to device optimal interventions to augment learning.

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          Most cited references54

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          Functional MRI evidence for adult motor cortex plasticity during motor skill learning.

          Performance of complex motor tasks, such as rapid sequences of finger movements, can be improved in terms of speed and accuracy over several weeks by daily practice sessions. This improvement does not generalize to a matched sequence of identical component movements, nor to the contralateral hand. Here we report a study of the neural changes underlying this learning using functional magnetic resonance imaging (MRI) of local blood oxygenation level-dependent (BOLD) signals evoked in primary motor cortex (M1). Before training, a comparable extent of M1 was activated by both sequences. However, two ordering effects were observed: repeating a sequence within a brief time window initially resulted in a smaller area of activation (habituation), but later in larger area of activation (enhancement), suggesting a switch in M1 processing mode within the first session (fast learning). By week 4 of training, concurrent with asymptotic performance, the extent of cortex activated by the practised sequence enlarged compared with the unpractised sequence, irrespective of order (slow learning). These changes persisted for several months. The results suggest a slowly evolving, long-term, experience-dependent reorganization of the adult M1, which may underlie the acquisition and retention of the motor skill.
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            Inter-individual variability in response to non-invasive brain stimulation paradigms.

            Non-invasive Brain Stimulation (NIBS) paradigms are unique in their ability to safely modulate cortical plasticity for experimental or therapeutic applications. However, increasingly, there is concern regarding inter-individual variability in the efficacy and reliability of these paradigms. Inter-individual variability in response to NIBS paradigms would be better explained if a multimodal distribution was assumed. In three different sessions for each subject (n = 56), we studied the Paired Associative Stimulation (PAS25), Anodal transcranial DC stimulation (AtDCS) and intermittent theta burst stimulation (iTBS) protocols. We applied cluster analysis to detect distinct patterns of response between individuals. Furthermore, we tested whether baseline TMS measures (such as short intracortical inhibition (SICI), resting motor threshold (RMT)) or factors such as time of day could predict each individual's response pattern. All three paradigms show similar efficacy over the first hour post stimulation--there is no significant effect on excitatory or inhibitory circuits for the whole sample, and AtDCS fares no better than iTBS or PAS25. Cluster analysis reveals a bimodal response pattern--but only 39%, 45% and 43% of subjects responded as expected to PAS25, AtDCS, and iTBS respectively. Pre-stimulation SICI accounted for 10% of the variability in response to PAS25, but no other baseline measures were predictive of response. Finally, we report implications for sample size calculation and the remarkable effect of sample enrichment. The implications of the high rate of 'dose-failure' for experimental and therapeutic applications of NIBS lead us to conclude that addressing inter-individual variability is a key area of concern for the field. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Learning-induced LTP in neocortex.

              The hypothesis that learning occurs through long-term potentiation (LTP)- and long-term depression (LTD)-like mechanisms is widely held but unproven. This hypothesis makes three assumptions: Synapses are modifiable, they modify with learning, and they strengthen through an LTP-like mechanism. We previously established the ability for synaptic modification and a synaptic strengthening with motor skill learning in horizontal connections of the rat motor cortex (MI). Here we investigated whether learning strengthened these connections through LTP. We demonstrated that synapses in the trained MI were near the ceiling of their modification range, compared with the untrained MI, but the range of synaptic modification was not affected by learning. In the trained MI, LTP was markedly reduced and LTD was enhanced. These results are consistent with the use of LTP to strengthen synapses during learning.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                16 January 2017
                2017
                : 7
                : 40715
                Affiliations
                [1 ]Department of Biomedical Engineering, Johns Hopkins School of Medicine , 720 Rutland Avenue Baltimore, MD 21205, USA
                [2 ]Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine , 600 North Wolfe Street Baltimore, MD 21287, USA
                [3 ]Department of Neuroscience, Johns Hopkins School of Medicine , 725 North Wolfe Street Baltimore, MD 21205, USA
                [4 ]Department of Neurology, Johns Hopkins School of Medicine , 600 North Wolfe Street Baltimore, MD 21287, USA.
                Author notes
                Article
                srep40715
                10.1038/srep40715
                5238434
                28091578
                1094f208-0449-4e78-a869-47501f497a06
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 18 July 2016
                : 08 December 2016
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