The dynamics of memory as a consequence of optimal adaptation to a changing body
Open accessAbstract
There are many causes for variation in the responses of the motor apparatus to neural commands. Fast-timescale disturbances occur when muscles fatigue. Slow-timescale disturbances occur when muscles are damaged or when limb dynamics change as a result of development. To maintain performance, motor commands need to adapt. Computing the best adaptation in response to any performance error results in a credit assignment problem: which timescale is responsible for this disturbance? Here we show that a Bayesian solution to this problem accounts for numerous behaviors of animals during both short- and long-term training. Our analysis focused on characteristics of the oculomotor system during learning, including the effects of time passage. However, we suggest that learning and memory in other paradigms, such as reach adaptation, adaptation of visual neurons and retrieval of declarative memories, largely follow similar rules.
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Recent work confirms and extends the assessment that humans act as rational Bayesian estimators, in perception and in action, across a wide variety of domains.
“Recent work con fi rms and extends this assessment, suggesting that humans act as rational Bayesian estimators, in perception and in action, across a wide variety of domains (Berniker & Körding 2008; Körding et al. 2007; Yu 2007).”
From Whatever next? Predictive brains, situated agents, and the future of cognitive science (2013) · cites this paper as Körding et al. 2007
The Results show that a Bayesian model accounts for animal motor-adaptation behavior and report similar effects in visual-neuron adaptation. The Discussion mentions human saccade adaptation, but does not establish that humans act as rational Bayesian estimators across a wide variety of perceptual and action domains. (LLM, conf=0.85)
Experimental — accuracy not yet measuredSSM variants that include multiple timescales of learning explain savings over short timescales but fail to predict savings following a prolonged period of washout.
“Although SSM variants that include multiple timescales of learning (Kording et al., 2007; Smith et al., 2006) are able to explain savings over short timescales, this approach fails to predict the fact that savings still occurs following a prolonged period of washout of initial learning (Krakauer et al., 2005; Zarahn et al., 2008).”
From Rethinking motor learning and savings in adaptation paradigms: model-free memory for successful actions combines with internal models (2011) · cites this paper as Kording et al., 2007
A recent motor learning model has been conceptualized in terms of the existence of fast and slow error-based processes.
“A recent motor learning model has been conceptualized in terms of the existence of fast and slow error-based processes (Kording et al., 2007; Smith et al., 2006).”
From Rethinking motor learning and savings in adaptation paradigms: model-free memory for successful actions combines with internal models (2011) · cites this paper as Kording et al., 2007
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- Authors
- Kording, K. P., Tenenbaum, J. B., & Shadmehr, R.
- Affiliations
- Shirley Ryan AbilityLab (US)
- Massachusetts Institute of Technology (US)
- Johns Hopkins University (US)
- Corresponding author
- Kording, Konrad P
- Venue
- Nature Neuroscience
- Published
- 2007-05-13
- Volume
- 10
- Issue
- 6
- Pages
- 779-786
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC2551734
- OpenAlex
- W2170585417
- Cited by
- 393
- References
- 43
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 11 · 2023: 13 · 2022: 15 · 2021: 23 · 2020: 32 · 2019: 29 · 2018: 22 · 2017: 21 · 2016: 18 · 2015: 30 · 2014: 26 · 2013: 22 · 2012: 23
- FWCI
- 10.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of General Medical Sciences (T32GM007057)
- National Institute of Neurological Disorders and Stroke (R01NS057814)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- motor learning, motor memory, motor adaptation, muscle fatigue, limb dynamics, oculomotor system, passage of time
- MeSH terms
- Adaptation, Physiological, Animals, Bayes Theorem, Humans, Learning, Memory, Models, Neurological, Neurons, Afferent, Photic Stimulation, Saccades, Time Factors, Contrast Sensitivity, Nonlinear Dynamics
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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.
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