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. 2014 Sep 25:8:754.
doi: 10.3389/fnhum.2014.00754. eCollection 2014.

Entrainment and motor emulation approaches to joint action: Alternatives or complementary approaches?

Lincoln J Colling  1 , Kellie Williamson  2
Affiliations

Entrainment and motor emulation approaches to joint action: Alternatives or complementary approaches?

Lincoln J Colling et al. Front Hum Neurosci. .

Abstract

Joint actions, such as music and dance, rely crucially on the ability of two, or more, agents to align their actions with great temporal precision. Within the literature that seeks to explain how this action alignment is possible, two broad approaches have appeared. The first, what we term the entrainment approach, has sought to explain these alignment phenomena in terms of the behavioral dynamics of the system of two agents. The second, what we term the emulator approach, has sought to explain these alignment phenomena in terms of mechanisms, such as forward and inverse models, that are implemented in the brain. They have often been pitched as alternative explanations of the same phenomena; however, we argue that this view is mistaken, because, as we show, these two approaches are engaged in distinct, and not mutually exclusive, explanatory tasks. While the entrainment approach seeks to uncover the general laws that govern behavior the emulator approach seeks to uncover mechanisms. We argue that is possible to do both and that the entrainment approach must pay greater attention to the mechanisms that support the behavioral dynamics of interest. In short, the entrainment approach must be transformed into a neuroentrainment approach by adopting a mechanistic view of explanation and by seeking mechanisms that are implemented in the brain.

Keywords: entrainment; joint action; mechanistic explanation; motor emulation; perception–action.

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Figures

Figure 1
Figure 1
(A) Relative phase as a function of time for various initial phase relationships. High values of k represent slow cycling speeds and low values of k represent fast cycling speeds. (B) Stable patterns of coordination (attractors) as a function of decreasing values of k (increasing cycling speeds).
Figure 2
Figure 2
(A) A schematic of open loop control. (B) A schematic of closed-loop control. (C) A schematic of pseudo-closed-loop control.
Figure 3
Figure 3
A schematic of the cerebellum peforming matrix multiplication.
Figure 4
Figure 4
(A) The mannequin stimuli, (B) movement patterns, and (C) results from Colling et al. (2014).
See this image and copyright information in PMC

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