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The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

Consolidation patterns of human motor memory.

Sarah E Criscimagna-Hemminger¹, Reza Shadmehr

¹Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA. sarah.hemminger@jhu.edu

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|September 26, 2008

Summary

Motor memories are not unlearned but masked by new, fragile memories that stabilize over time. This study explores how new learning competes with and conceals existing motor skills.

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Area of Science:

Neuroscience
Motor Learning
Cognitive Psychology

Background:

The nature of memory unlearning remains debated.
It is unclear if unlearning involves erasing memories or forming competing ones.

Purpose of the Study:

To investigate whether motor memories can be truly unlearned or if they are masked by new learning.
To differentiate between unlearning and memory masking in motor skill acquisition.

Main Methods:

Participants learned to reach with a novel tool (Tool A).
Memory recall was assessed using error-clamp trials to minimize new learning.
Performance was measured after exposure to a second tool (Tool B) to observe effects on Tool A memory.

Main Results:

Exposure to Tool B initially appeared to extinguish Tool A memory, returning performance to baseline.
Spontaneous recovery of Tool A performance was observed shortly after Tool B exposure, indicating masking, not unlearning.
The new memory (Tool B) was initially fragile but stabilized over minutes, while the original memory (Tool A) remained resistant to change.

Conclusions:

Motor memory unlearning does not occur; instead, new learning creates a competing, fragile memory that masks the old one.
This fragile memory transforms into a more stable state over time.
Motor learning involves adaptive processes at multiple timescales, with fast states potentially transforming into slower ones after practice cessation.