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Items: 1 to 20 of 83

1.

Controlling variability.

Sanger TD.

J Mot Behav. 2010 Nov;42(6):401-7. doi: 10.1080/00222895.2010.526496.

PMID:
21184358
2.

An optimal feedback control framework for grasping objects with position uncertainty.

Christopoulos VN, Schrater PR.

Neural Comput. 2011 Oct;23(10):2511-36. doi: 10.1162/NECO_a_00180. Epub 2011 Jul 6.

PMID:
21732861
3.

Why professional athletes need a prolonged period of warm-up and other peculiarities of human motor learning.

Ajemian R, D'Ausilio A, Moorman H, Bizzi E.

J Mot Behav. 2010 Nov;42(6):381-8. doi: 10.1080/00222895.2010.528262. Erratum in: J Mot Behav. 2011 Jan;43(1):85.

PMID:
21184356
4.

Probabilistic mechanisms in sensorimotor control.

K├Ârding KP, Wolpert DM.

Novartis Found Symp. 2006;270:191-8; discussion 198-202, 232-7. Review.

PMID:
16649715
5.

Evidence for model-based action planning in a sequential finger movement task.

Fermin A, Yoshida T, Ito M, Yoshimoto J, Doya K.

J Mot Behav. 2010 Nov;42(6):371-9. doi: 10.1080/00222895.2010.526467.

PMID:
21184355
6.

Computational principles of sensorimotor control that minimize uncertainty and variability.

Bays PM, Wolpert DM.

J Physiol. 2007 Jan 15;578(Pt 2):387-96. Epub 2006 Sep 28. Review.

7.

Computational motor control: feedback and accuracy.

Guigon E, Baraduc P, Desmurget M.

Eur J Neurosci. 2008 Feb;27(4):1003-16. doi: 10.1111/j.1460-9568.2008.06028.x. Epub 2008 Feb 13.

PMID:
18279368
8.

Error correction, sensory prediction, and adaptation in motor control.

Shadmehr R, Smith MA, Krakauer JW.

Annu Rev Neurosci. 2010;33:89-108. doi: 10.1146/annurev-neuro-060909-153135. Review.

PMID:
20367317
9.

Task-Independent Cognitive State Transition Detection From Cortical Neurons During 3-D Reach-to-Grasp Movements.

Kang X, Sarma SV, Santaniello S, Schieber M, Thakor NV.

IEEE Trans Neural Syst Rehabil Eng. 2015 Jul;23(4):676-82. doi: 10.1109/TNSRE.2015.2396495. Epub 2015 Jan 27.

PMID:
25643410
10.

Optimality, stochasticity, and variability in motor behavior.

Guigon E, Baraduc P, Desmurget M.

J Comput Neurosci. 2008 Feb;24(1):57-68. doi: 10.1007/s10827-007-0041-y. Epub 2007 May 22.

11.

Editors' introduction to the issue: theoretical ideas in motor neuroscience and their capacity for falsification.

Ajemian R, Sternad D.

J Mot Behav. 2010 Nov;42(6):331-2. doi: 10.1080/00222895.2010.536108. No abstract available.

PMID:
21184349
12.

Optimal weighting of costs and probabilities in a risky motor decision-making task requires experience.

Neyedli HF, Welsh TN.

J Exp Psychol Hum Percept Perform. 2013 Jun;39(3):638-45. doi: 10.1037/a0030518. Epub 2012 Nov 19.

PMID:
23163791
13.

Combining priors and noisy visual cues in a rapid pointing task.

Tassinari H, Hudson TE, Landy MS.

J Neurosci. 2006 Oct 4;26(40):10154-63.

14.

Motor control is decision-making.

Wolpert DM, Landy MS.

Curr Opin Neurobiol. 2012 Dec;22(6):996-1003. doi: 10.1016/j.conb.2012.05.003. Epub 2012 May 29. Review.

15.

Brain-computer interface research comes of age: traditional assumptions meet emerging realities.

Wolpaw JR.

J Mot Behav. 2010 Nov;42(6):351-3. doi: 10.1080/00222895.2010.526471.

PMID:
21184352
16.

Cerebral-cortical networking and activation increase as a function of cognitive-motor task difficulty.

Rietschel JC, Miller MW, Gentili RJ, Goodman RN, McDonald CG, Hatfield BD.

Biol Psychol. 2012 May;90(2):127-33. doi: 10.1016/j.biopsycho.2012.02.022. Epub 2012 Mar 3.

PMID:
22410264
17.

Movement variability resulting from different noise sources: a simulation study.

Shi Y, Buneo CA.

Hum Mov Sci. 2012 Aug;31(4):772-90. doi: 10.1016/j.humov.2011.07.003. Epub 2012 Jul 13.

PMID:
22795761
18.
19.

The tuning of human motor response to risk in a dynamic environment task.

Dunning A, Ghoreyshi A, Bertucco M, Sanger TD.

PLoS One. 2015 Apr 22;10(4):e0125461. doi: 10.1371/journal.pone.0125461. eCollection 2015.

20.

Modularity for sensorimotor control: evidence and a new prediction.

d'Avella A, Pai DK.

J Mot Behav. 2010 Nov;42(6):361-9. doi: 10.1080/00222895.2010.526453.

PMID:
21184354

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