Measures of Implicit and Explicit Adaptation Do Not Linearly Add
preprint
OA: closed
CC-BY-4.0
Abstract
Moving effectively is essential for any animal. Thus, many different kinds of brain processes likely contribute to learning and adapting movement. How these contributions are combined is unknown. Nevertheless, the field of motor adaptation has been working under the assumption that measures of explicit and implicit motor adaptation can simply be added in total adaptation. While this has been tested, we show that these tests were insufficient. We put this additivity assumption to the test in various ways, and find that measures of implicit and explicit adaptation are not additive. This means that future studies should measure both implicit and explicit adaptation directly. It also challenges us to disentangle how various motor adaptation processes do combine when producing movements, and may have implications for our understanding of other kinds of learning as well. (data and code: https://osf.io/dh86e )
My notes (saved in your browser only)
Citation neighborhood (sparse)
Too few in-corpus citations on either side for a chart; here are the lists.
Cites (4)
- Implicit Adaptation is Fast, Robust and Independent from Explicit Adaptation 2024
- Motor adaptation does not differ when a perturbation is introduced abruptly or gradually 2022
- Adapting to visuomotor rotations in stepped increments increases implicit motor learning 2022
- Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment 2021
References (34)
- Adapting to visuomotor rotations in stepped increments increases implicit motor learning via crossref
- Implicit Adaptation is Fast, Robust and Independent from Explicit Adaptation via crossref
- Motor adaptation does not differ when a perturbation is introduced abruptly or gradually via crossref
- Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment via crossref
- doi:10.1152/jn.00009.2015 via crossref
- doi:10.1523/eneuro.0308-19.2019 via crossref
- doi:10.1152/jn.00066.2015 via crossref
- doi:10.1007/s00221-022-06352-4 via crossref
- doi:10.1038/415429a via crossref
- doi:10.1038/s41598-020-76940-3 via crossref
- doi:10.1007/s00221-021-06109-5 via crossref
- doi:10.1016/0749-596x(91)90025-f via crossref
- doi:10.1016/j.neubiorev.2021.06.037 via crossref
- doi:10.1111/ejn.14945 via crossref
- doi:10.1523/jneurosci.5317-05.2006 via crossref
- doi:10.1523/jneurosci.5061-14.2015 via crossref
- doi:10.1038/s41593-020-0600-3 via crossref
- doi:10.1371/journal.pone.0220884 via crossref
- doi:10.1007/s00221-018-5282-7 via crossref
- doi:10.1080/00222895.1993.9941642 via crossref
- doi:10.1038/s41598-021-81031-y via crossref
- doi:10.1038/s41598-019-53543-1 via crossref
- doi:10.1152/jn.00451.2018 via crossref
- doi:10.1371/journal.pbio.0040179 via crossref
- doi:10.1016/j.concog.2008.12.001 via crossref
- doi:10.1371/journal.pcbi.1001096 via crossref
- doi:10.1523/jneurosci.3619-13.2014 via crossref
- doi:10.1371/journal.pone.0239032 via crossref
- doi:10.1371/journal.pone.0123321 via crossref
- doi:10.7554/elife.65361 via crossref
- doi:10.1523/eneuro.0312-20.2021 via crossref
- doi:10.1152/jn.00197.2017 via crossref
- doi:10.1152/jn.00002.2011 via crossref
- doi:10.1371/journal.pcbi.1002210 via crossref
Source provenance
- crossref
- last seen: 2026-06-24T06:27:30.769196+00:00
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-4.0