The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning
Open accessAbstract
A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The assessment and analysis of handedness: The Edinburgh inventory
Oldfield, R. C. (1971) · Neuropsychologia · doi:10.1016/0028-3932(71)90067-4 · Cited by 35,900
James, W. (1913) · Henry Holt and Company eBooks · doi:10.1037/11059-000 · Cited by 25,226
A process dissociation framework: Separating automatic from intentional uses of memory
Jacoby, L. L. (1991) · Journal of Memory and Language · doi:10.1016/0749-596x(91)90025-f · Cited by 3,696
Daw, N. D., Niv, Y., & Dayan, P. (2005) · Nature Neuroscience · doi:10.1038/nn1560 · Cited by 2,533
Gläscher, J., Daw, N., Dayan, P., & O'Doherty, J. P. (2010) · Neuron · doi:10.1016/j.neuron.2010.04.016 · Cited by 1,166
Interacting adaptive processes with different timescales underlie short-term motor learning
Smith, M. A., Ghazizadeh, A., & Shadmehr, R. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040179 · Cited by 1,113 · cited 17×
“We believe that our lack of observed rebound decay may be due to the fact that we used a longer R1 training session relative to Smith et al. (2006) and this extra training could act to buoy adaptation rebound, perhaps due to the directional biases mentioned above.”
BackgroundMethodResultInfluentialAshby, F. G., & Maddox, W. T. (2005) · Annual Review of Psychology · doi:10.1146/annurev.psych.56.091103.070217 · Cited by 938
Learning of Visuomotor Transformations for Vectorial Planning of Reaching Trajectories
Krakauer, J. W., Pine, Z. M., Ghilardi, M.-F., & Ghez, C. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-23-08916.2000 · Cited by 873
Explicit and implicit contributions to learning in a sensorimotor adaptation task
Taylor, J. A., Krakauer, J. W., & Ivry, R. B. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.3619-13.2014 · Cited by 768
Self-citationGalea, J. M., Vazquez, A., Pasricha, N., Orban de Xivry, J.-J., & Celnik, P. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq246 · Cited by 760
Cited by
Taking aim at the cognitive side of learning in sensorimotor adaptation tasks
McDougle, S. D., Ivry, R. B., & Taylor, J. A. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.05.002 · Cited by 236
Self-citationButcher, P. A., Ivry, R. B., Kuo, S.-H., Rydz, D., Krakauer, J. W., & Taylor, J. A. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00451.2017 · Cited by 119
Self-citationBechara, A., Berridge, K. C., Bickel, W. K., Morón, J. A., Williams, S. B., & Stein, J. S. (2019) · Psychological Science in the Public Interest · doi:10.1177/1529100619860513 · Cited by 82
Massaly, N., Morón, J. A., & Al-Hasani, R. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00480 · Cited by 59
Motor actions across psychiatric disorders: a research domain criteria (RDoC) perspective
Osborne, K. J., Walther, S., & Mittal, V. A. (2024) · Clinical Psychology Review · doi:10.1016/j.cpr.2024.102511 · Cited by 9
Metadata
- Authors
- McDougle, S. D., Bond, K. M., & Taylor, J. A.
- Venue
- Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2015-07-01
- Volume
- 35
- Issue
- 26
- Pages
- 9568-9579
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W1602511075
- Cited by
- 370
- References
- 36
- FWCI
- 13.83
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning. https://app.cochat.ai/papers/10.1523/jneurosci.5061-14.2015
- The paper
- McDougle, S. D., Bond, K. M., & Taylor, J. A. (2015). Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning. Journal of Neuroscience. https://doi.org/10.1523/jneurosci.5061-14.2015
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
