Incorporating motor preparation time transforms micro-offline gains into micro-offline losses

During explicit sequence learning (ESL), micro-offline gains (MOGS) occur during brief rest periods. MOGS are calculated as the difference in sequence speed between the first correct sequence of one trial and the last sequence of the preceding trial. To date, all studies evaluating MOGS have calculated sequence speed from the execution time that occurs between keypresses, but this approach ignores potential contributions from motor preparation which occur prior to the first keypress. Given that ESL relies on both pre-movement motor planning and subsequent motor execution, we hypothesized that ignoring motor preparation time neglects a critical component of skill acquisition, potentially misrepresenting the true magnitude of MOGS. To test this, we calculated MOGS with and without preparation time in thirty adults who performed an ESL task. The dataset used for this analysis was obtained as part of a larger study to evaluate the effects of pre-trial temporal predictability on ESL performance and learning by controlling the predictability of trial onset. Our results show that including preparation time flipped MOGS from positive to negative and significantly increased the positive correlation between early learning and a gold-standard ESL metric: the number of correct sequences performed. Our results suggest that preparation time should be incorporated into MOGS calculations and that excluding it overestimates micro-offline learning.

Authors

Institutions

Publication Details

Journal
Journal of Neurophysiology
Published
2026-07-16
DOI
https://doi.org/10.1152/jn.00181.2026
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Incorporating motor preparation time transforms micro-offline gains into micro-offline losses

Sara J. Hussain, Michael Freedberg, NI Ahmed, T. Suresh
Journal of Neurophysiology
Motor Control and Adaptation
article

Incorporating motor preparation time transforms micro-offline gains into micro-offline losses

Sara J. Hussain, Michael Freedberg, NI Ahmed, T. Suresh
article en

Abstract

During explicit sequence learning (ESL), micro-offline gains (MOGS) occur during brief rest periods. MOGS are calculated as the difference in sequence speed between the first correct sequence of one trial and the last sequence of the preceding trial. To date, all studies evaluating MOGS have calculated sequence speed from the execution time that occurs between keypresses, but this approach ignores potential contributions from motor preparation which occur prior to the first keypress. Given that ESL relies on both pre-movement motor planning and subsequent motor execution, we hypothesized that ignoring motor preparation time neglects a critical component of skill acquisition, potentially misrepresenting the true magnitude of MOGS. To test this, we calculated MOGS with and without preparation time in thirty adults who performed an ESL task. The dataset used for this analysis was obtained as part of a larger study to evaluate the effects of pre-trial temporal predictability on ESL performance and learning by controlling the predictability of trial onset. Our results show that including preparation time flipped MOGS from positive to negative and significantly increased the positive correlation between early learning and a gold-standard ESL metric: the number of correct sequences performed. Our results suggest that preparation time should be incorporated into MOGS calculations and that excluding it overestimates micro-offline learning.

Journal of Neurophysiology
University of Iowa (US), The University of Texas at Austin (US)
Quality Education
Openalex Percentile: Top 7%
Motor Control and Adaptation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.