Exploring speed–accuracy tradeoff in reaching movements: a neurocomputational model


The tradeoff between speed and accuracy of human movements has been exploited from many different perspectives, such as experimental psychology, workspace design, human–machine interface. This tradeoff is formalized by Fitts’ law, which states a linear relationship between the duration and the difficulty of the movement. The bigger is the required accuracy in reaching a target or farther is the target, the slower has to be the movement. A variety of computational models of neuromusculoskeletal systems have been proposed to pinpoint the neurobiological mechanisms that are involved in human movement. We introduce a neurocomputational model of spinal cord to unveil how the tradeoff between speed and accuracy elicits from the interaction between neural and musculoskeletal systems. Model simulations showed that the speed–accuracy tradeoff is not an intrinsic property of the neuromuscular system, but it is a behavioral trait that emerges from the strategy adopted by the central nervous system for executing faster movements. In particular, results suggest that the velocity of a previous learned movement is regulated by the monosynaptic connection between cortical cells and alpha motoneurons.

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This study was partially funded by the “Bando PRIN2015-Progetto HAND” under Grant H96J16000820001 from the Italian Ministero dell’Istruzione, dell’ Università e della Ricerca.

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Parziale, A., Senatore, R. & Marcelli, A. Exploring speed–accuracy tradeoff in reaching movements: a neurocomputational model. Neural Comput & Applic 32, 13377–13403 (2020). https://doi.org/10.1007/s00521-019-04690-z

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  • Human movement
  • Speed–accuracy tradeoff
  • Fitts’ law
  • Neurocomputational model