Dual-process decomposition in human sensorimotor adaptation
Abstract
Multiple distinct learning processes are known to contribute to sensorimotor adaptation in humans. It is challenging to identify and characterize these multiple processes, however, because only their summed contribution can typically be observed. A general strategy for decomposing adaptation into its constituent components is to exploit their differential susceptibility to specific experimental manipulations. Several such approaches have recently emerged which, taken together, suggest that two fundamental systems operate together to achieve the adapted state: one system learns slowly, is implicit, is temporally stable over short breaks, is expressible at low reaction times, and its properties do not change based on experience. The second learns rapidly, is explicit, requires a long preparation time to be expressed, and exhibits long-term memory for prior learning.
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The distinct algorithms operating in adaptation experiments include error-based learning, reinforcement learning, and cognitive strategies.
“The distinct algorithms operating in adaptation experiments include error-based learning, reinforcement learning, and cognitive strategies (Huberdeau et al., 2015).”
From Neuroscience Needs Behavior: Correcting a Reductionist Bias (2017) · cites this paper as Huberdeau et al., 2015
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- Authors
- Huberdeau, D. M., Krakauer, J. W., & Haith, A. M.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Krakauer, John W
- Haith, Adrian M
- Venue
- Current Opinion in Neurobiology
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 33
- Pages
- 71-77
- ISSN
- 0959-4388 (ISSN-L)
- OpenAlex
- W2099070313
- Cited by
- 161
- References
- 65
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 14 · 2023: 4 · 2022: 15 · 2021: 9 · 2020: 14 · 2019: 29 · 2018: 18 · 2017: 12 · 2016: 18 · 2015: 4
- FWCI
- 1.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Current Opinion in Neurobiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- NSF (1358756)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Keywords
- sensorimotor adaptation, dual-process theory, implicit learning, explicit learning, motor learning, learning memory, reaction time
- MeSH terms
- Adaptation, Physiological, Awareness, Humans, Learning, Movement, Psychomotor Performance, Mental Recall
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