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Generalization of the resource-rationality principle to neural control of goal-directed movements

Published online by Cambridge University Press:  11 March 2020

Natalia Dounskaia  and
Yury P. Shimansky
Natalia Dounskaia
Affiliation:
College of Health Solutions, Arizona State University, Phoenix, AZ85004. natalia.dounskaia@asu.eduyury.shimansky@asu.eduhttps://chs.asu.edu/natalia-dounskaia
Yury P. Shimansky
Affiliation:
College of Health Solutions, Arizona State University, Phoenix, AZ85004. natalia.dounskaia@asu.eduyury.shimansky@asu.eduhttps://chs.asu.edu/natalia-dounskaia
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Abstract

We review evidence that the resource-rationality principle generalizes to human movement control. Optimization of the use of limited neurocomputational resources is described by the inclusion of the “neurocomputational cost” of sensory information processing and decision making in the optimality criterion of movement control. A resulting tendency to decrease this cost can account for various phenomena observed during goal-directed movements.

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Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 43 , 2020 , e10
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Copyright
Copyright © Cambridge University Press 2020

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References

Bruton, M. & O'Dwyer, N. (2018) Synergies in coordination: A comprehensive overview of neural, computational, and behavioral approaches. Journal of Neurophysiology 120:2761–74.CrossRefGoogle ScholarPubMed
Dounskaia, N. (2005) The internal model and the leading joint hypothesis: Implications for control of multi-joint movements. Experimental Brain Research 166:1–16.CrossRefGoogle ScholarPubMed
Dounskaia, N. (2010) Control of human limb movements: The leading joint hypothesis and its practical applications. Exercise and Sport Sciences Reviews 4:201–08.CrossRefGoogle Scholar
Dounskaia, N. & Shimansky, Y. (2016) Strategy of arm movement control is determined by minimization of neural effort for joint coordination. Experimental Brain Research 234:1335–50.CrossRefGoogle ScholarPubMed
Fitts, P. M. (1954) The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47:381–91.CrossRefGoogle Scholar
Giszter, S. F. (2015) Motor primitives − New data and future questions. Current Opinion Neurobiology 33:156–65.CrossRefGoogle ScholarPubMed
Scholz, J. P. & Schoner, G. (1999) The uncontrolled manifold concept: Identifying control variables for a functional task. Experimental Brain Research 126:289–306.CrossRefGoogle ScholarPubMed
Shimansky, Y. P. & Rand, M. K. (2013) Two-phase strategy of controlling motor coordination determined by task performance optimality. Biological Cybernetics 107:107–29.CrossRefGoogle ScholarPubMed
Swinnen, S. P. (2002) Intermanual coordination: From behavioural principles to neural-network interactions. Nature Reviews Neuroscience 3:348–59.CrossRefGoogle ScholarPubMed