Micro-offline gains are inconsistent with a dominant contribution of latent motor slowing, supporting consolidation as their driver¶

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? Across Experiments 3 and 4, micro-offline learning accounted for the totality of early learning even when practice duration was substantially reduced or unpredictable, inconsistent with latent motor slowing as the driver. → Marlene Bönstrup 2020

Evidence¶

Marlene Bönstrup 2020¶

Marlene Bönstrup, Iñaki Iturrate, Martin N. Hebart, Nitzan Censor and Leonardo G. Cohen. (2020). Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data. npj Science of Learning. https://doi.org/10.1038/s41539-020-0066-9

q3 · i? · causal · r2

Convergent behavioral tests across Experiments 3 (reduced practice duration) and 4 (unpredictable practice termination): micro-offline gains persisted unchanged under both manipulations, which would not be expected if they reflected dissipation of latent motor slowing.

"Together, the results of Experiments 3 and 4 are inconsistent with a dominant contribution of latent motor slowing to micro-of fline gains and thus support consolidation as driving micro- offline gains."

Discussion¶

Related Claims¶

• Halving practice-period duration from 10 s to 5 s leaves micro-offline gains unchanged, arguing against recovery from motor fatigue — related
• Performance improvements during early motor skill learning occur predominantly during short rest periods (micro-offline gains), replicated in a large crowdsourced sample and in a laboratory study — related
• Random termination of practice periods does not reduce micro-offline gains, ruling out preemptive motor slowing — a narrower finding that bears on this claim