Savings in locomotor adaptation explained by changes in learning parameters following initial adaptation

被引:39
|
作者
Mawase, Firas [1 ]
Shmuelof, Lior [2 ]
Bar-Haim, Simona [3 ]
Karniel, Amir [1 ]
机构
[1] Ben Gurion Univ Negev, Dept Biomed Engn, IL-84105 Beer Sheva, Israel
[2] Ben Gurion Univ Negev, Dept Brain & Cognit Sci, IL-84105 Beer Sheva, Israel
[3] Ben Gurion Univ Negev, Dept Phys Therapy, IL-84105 Beer Sheva, Israel
基金
以色列科学基金会;
关键词
computational motor control; locomotor adaptation; motor learning; split-belt; SHORT-TERM; MOTOR ADAPTATION; MODEL; MEMORY; CONSOLIDATION; COORDINATION; CEREBELLUM; TREADMILL; DYNAMICS; ERRORS;
D O I
10.1152/jn.00734.2013
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Faster relearning of an external perturbation, savings, offers a behavioral linkage between motor learning and memory. To explain savings effects in reaching adaptation experiments, recent models suggested the existence of multiple learning components, each shows different learning and forgetting properties that may change following initial learning. Nevertheless, the existence of these components in rhythmic movements with other effectors, such as during locomotor adaptation, has not yet been studied. Here, we study savings in locomotor adaptation in two experiments; in the first, subjects adapted to speed perturbations during walking on a split-belt treadmill, briefly adapted to a counter-perturbation and then readapted. In a second experiment, subjects readapted after a prolonged period of washout of initial adaptation. In both experiments we find clear evidence for increased learning rates (savings) during readaptation. We show that the basic error-based multiple timescales linear state space model is not sufficient to explain savings during locomotor adaptation. Instead, we show that locomotor adaptation leads to changes in learning parameters, so that learning rates are faster during readaptation. Interestingly, we find an intersubject correlation between the slow learning component in initial adaptation and the fast learning component in the readaptation phase, suggesting an underlying mechanism for savings. Together, these findings suggest that savings in locomotion and in reaching may share common computational and neuronal mechanisms; both are driven by the slow learning component and are likely to depend on cortical plasticity.
引用
收藏
页码:1444 / 1454
页数:11
相关论文
共 50 条
  • [21] Online reinforcement learning of controller parameters adaptation law
    Alhazmi, Khalid
    Sarathy, S. Mani
    2023 AMERICAN CONTROL CONFERENCE, ACC, 2023, : 2975 - 2980
  • [22] Adaptation of parameters of BP algorithm using learning automata
    Beigy, H
    Meybodi, MR
    SIXTH BRAZILIAN SYMPOSIUM ON NEURAL NETWORKS, VOL 1, PROCEEDINGS, 2000, : 24 - 31
  • [23] Comparison of learning strategies for adaptation of fuzzy controller parameters
    Eklund, P
    Zhou, J
    FUZZY SETS AND SYSTEMS, 1999, 106 (03) : 321 - 333
  • [24] Comparison of learning strategies for adaptation of fuzzy controller parameters
    Department of Computing Science, Umeå University, 90187 Umeå, Sweden
    Fuzzy Sets Syst, 3 (321-333):
  • [25] Seeing Is Believing: Effects of Visual Contextual Cues on Learning and Transfer of Locomotor Adaptation
    Torres-Oviedo, Gelsy
    Bastian, Amy J.
    JOURNAL OF NEUROSCIENCE, 2010, 30 (50): : 17015 - 17022
  • [26] Gait speed influences aftereffect size following locomotor adaptation, but only in certain environments
    Hamzey, Rami J.
    Kirk, Eileen M.
    Vasudevan, Erin V. L.
    EXPERIMENTAL BRAIN RESEARCH, 2016, 234 (06) : 1479 - 1490
  • [27] Gait speed influences aftereffect size following locomotor adaptation, but only in certain environments
    Rami J. Hamzey
    Eileen M. Kirk
    Erin V. L. Vasudevan
    Experimental Brain Research, 2016, 234 : 1479 - 1490
  • [28] Self-adaptation of XCS learning parameters based on Learning theory
    Horiuchi, Motoki
    Nakata, Masaya
    GECCO'20: PROCEEDINGS OF THE 2020 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2020, : 342 - 349
  • [29] STRUCTURAL ADAPTATION IN INITIAL COLLECTING TUBULE FOLLOWING REDUCTION IN RENAL MASS
    ZALUPS, RK
    STANTON, BA
    WADE, JB
    GIEBISCH, G
    KIDNEY INTERNATIONAL, 1985, 27 (04) : 636 - 642
  • [30] Robust Design for Product Adaptation Considering Changes in Configurations and Parameters
    Deabae, Reza
    Xue, Deyi
    JOURNAL OF MECHANICAL DESIGN, 2025, 147 (02)