Does a Cognitive Task Promote Implicit or Explicit Motor Learning?

We developed a sway-referenced system for sitting to highlight the role of vestibular and visual contributions to trunk control. Motor control was investigated by measuring trunk kinematics in the frontal plane while manipulating visual availability and introducing a concurrent cognitive task. We examined motor learning on three timescales (within the same trial, minutes), within the same test session (1 h), and between sessions (1 wk). Posture sway was analyzed through time-based measures [root mean square (RMS) sway and RMS velocity], frequency-based measures (amplitude spectra), and parameterized feedback modeling. We found that posture differed in both magnitude and frequency distribution during sway referencing compared with quiet sitting. Modeling indicated that sway referencing caused greater uncertainty/noise in sensory feedback and motor outputs. Sway referencing was also associated with lower active stiffness and damping model parameters. The influence of vision and a cognitive task was more apparent during sway referencing compared with quiet sitting. Short-term learning was reflected by reduced RMS velocity in quiet sitting immediately following sway referencing. Longer term learning was evident from one week to the next, with a 23% decrease in RMS sway and 9% decrease in RMS velocity. These changes occurred predominantly during cognitive tests at lower frequencies and were associated with lower sensory noise and higher stiffness and integral gains in the model. With the findings taken together, the sitting sway-referenced test elicited neural changes consistent with optimal integration and sensory reweighting, similar to standing, and should be a valuable tool to closely examine sensorimotor control of the trunk. NEW & NOTEWORTHY We developed the first sway-referenced system for sitting to highlight the role of vestibular and visual contributions to trunk control. A parametric feedback model explained sensorimotor control and motor learning in the task with and between two test sessions. The sitting sway-referenced test elicited neural changes consistent with optimal integration and sensory reweighting, similar to standing, and should be a valuable tool to closely examine sensorimotor control of the trunk.

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Critically appraised paper: Implicit motor learning is not superior to explicit motor learning for improving gait speed in chronic stroke [commentary]

Journal of Physiotherapy ◽

10.1016/j.jphys.2021.09.003 ◽

2021 ◽

Author(s):

Lara A Boyd

Keyword(s):

Motor Learning ◽

Gait Speed ◽

Chronic Stroke ◽

Implicit Motor Learning ◽

Implicit Motor ◽

Explicit Motor Learning

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Implicit and explicit motor learning interventions have similar effects on walking speed in people after stroke: a randomized controlled single blind trial

10.1101/19008797 ◽

2019 ◽

Author(s):

Li-Juan Jie ◽

Melanie Kleynen ◽

Kenneth Meijer ◽

Anna Beurskens ◽

Susy Braun

Keyword(s):

Motor Learning ◽

Walking Speed ◽

Chronic Phase ◽

Learning Approaches ◽

Post Intervention ◽

Walking Intervention ◽

Implicit Motor Learning ◽

Implicit Motor ◽

Single Blind ◽

Explicit Motor Learning

ABSTRACTBackgroundTherapists may use (more) implicit or (more) explicit motor learning approaches to facilitate motor skill learning of stroke patients. The use of implicit motor learning approaches has shown promising results in healthy populations.ObjectiveTo assess whether an implicit motor learning walking intervention is more effective compared to an explicit motor learning walking intervention delivered at home with regard to walking speed in people after stroke in the chronic phase of recovery.DesignRandomized controlled single blind trial.SettingHome environment.Patients79 people in the chronic phase after stroke (66.4 ± 11.0 years; 70.1 ± 64.3 months after stroke; walking speed 0.7 ± 0.3 m/s; Berg Balance Scale score 44.5 ± 9.5) were randomly assigned to an implicit (n=39) or explicit (n=41) group.InterventionAnalogy learning was used as the implicit motor learning walking intervention, whereas the explicit motor learning walking intervention consisted of detailed verbal instructions. Both groups received nine training sessions, 30 minutes each, for a period of three weeks.MeasurementsThe primary outcome was walking speed measured by the 10-Meter Walk Test. Outcome measures were assessed at baseline, immediate and 1-month post intervention.ResultsNo statistically or clinically relevant differences between groups were obtained post intervention (between-group difference estimated 0.02 m/s [95% CI −0.04 to 0.08] and at follow-up (between-group difference estimated −0.02 m/s [95% CI −0.09 to 0.05], p=0,563).LimitationsThe treatment effects may have been diluted by “noise” accompanied with research within real life settings, complex tasks and a representative sample.ConclusionsImplicit motor learning was not superior to the explicit motor learning to improve walking speed in people after stroke in the chronic phase of recovery.

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Timing is everything: event-related transcranial direct current stimulation improves motor adaptation

10.1101/2021.11.26.470091 ◽

2021 ◽

Author(s):

Matthew Weightman ◽

John Stuart-Brittain ◽

Alison Hall ◽

Chris Miall ◽

Ned Jenkinson

Keyword(s):

Motor Learning ◽

Short Duration ◽

Direct Current ◽

Transcranial Direct Current Stimulation ◽

Neural Circuits ◽

Cognitive Task ◽

Motor Adaptation ◽

Reaching Movements ◽

Tight Coupling ◽

Direct Current Stimulation

There is a fundamental discord between the foundational theories underpinning motor learning and how we currently apply transcranial direct current stimulation (TDCS). The former is dependent on tight coupling of events; the latter is conducted with very low temporal resolution, typically being applied for 10-20 minutes, prior to or during performance of a particular motor or cognitive task. Here we show that when short duration stimulation epochs (< 3 seconds) are yoked to movement, only the reaching movements repeatedly performed simultaneously with stimulation are selectively enhanced. We propose that mechanisms of Hebbian-like learning are potentiated within neural circuits that are active during movement and concurrently stimulated, thus driving improved adaptation.

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