Elsevier

NeuroImage

Volume 41, Issue 4, 15 July 2008, Pages 1471-1483
NeuroImage

Functional neuroanatomical networks associated with expertise in motor imagery

https://doi.org/10.1016/j.neuroimage.2008.03.042Get rights and content

Abstract

Although numerous behavioural studies provide evidence that there exist wide differences within individual motor imagery (MI) abilities, little is known with regards to the functional neuroanatomical networks that dissociate someone with good versus poor MI capacities. For the first time, we thus compared, through functional magnetic resonance imaging (fMRI), the pattern of cerebral activations in 13 skilled and 15 unskilled imagers during both physical execution and MI of a sequence of finger movements. Differences in MI abilities were assessed using well-established questionnaire and chronometric measures, as well as a new index based upon the subject's peripheral responses from the autonomic nervous system. As expected, both good and poor imagers activated the inferior and superior parietal lobules, as well as motor-related regions including the lateral and medial premotor cortex, the cerebellum and putamen. Inter-group comparisons revealed that good imagers activated more the parietal and ventrolateral premotor regions, which are known to play a critical role in the generation of mental images. By contrast, poor imagers recruited the cerebellum, orbito-frontal and posterior cingulate cortices. Consistent with findings from the motor sequence learning literature and Doyon and Ungerleider's model of motor learning [Doyon, J., Ungerleider, L.G., 2002. Functional anatomy of motor skill learning. In: Squire, L.R., Schacter, D.L. (Eds.), Neuropsychology of memory, Guilford Press, pp. 225–238], our results demonstrate that compared to skilled imagers, poor imagers not only need to recruit the cortico-striatal system, but to compensate with the cortico-cerebellar system during MI of sequential movements.

Introduction

Motor imagery (MI) is a dynamic state during which a subject simulates an action mentally without any body movement (Jeannerod, 1994), and is subdivided into different modalities including visual and kinesthetic imagery. Visual imagery requires self-visualization of the movement from a first- or third-person perspective, while kinesthetic imagery requires one to “feel the movement”. There is now ample evidence that MI and motor performance share the same neural networks (Decety et al., 1994, Gerardin et al., 2000). Lafleur et al. (2002) have also demonstrated that the cerebral plasticity that occurs following physical practice is reflected during MI. This relationship is called “functional equivalence” (Holmes and Collins, 2001), even though the neural substrates mediating these different types of MI and those activated during motor performance of the same action are not totally overlapping (Ruby and Decety, 2001, Sirigu and Duhamel, 2001, Binkofski et al., 2000, Solodkin et al., 2004).

Previous work has demonstrated that mental practice with MI can improve the performance and learning of a variety of motor tasks (for reviews, see Feltz and Landers, 1983, Guillot and Collet, 2008). The benefits of MI have been found, however, to differ depending upon the stages of the acquisition process and the subject's level of expertise (Hardy and Callow, 1999, Guillot et al., 2004). Other subject-dependent variables like the ability to create and manipulate accurate and vivid mental images have also been shown to influence the degree of improvement that can be seen following MI (Munroe et al., 2000). Indeed, the individual capacity to elicit efficient mental images is not universal, hence highlighting the importance to utilize appropriate psychological, behavioral and neurophysiological means to evaluate the subject's capacity in forming accurate motor images (Guillot and Collet, 2005b, Lotze and Halsband, 2006). To do so, researchers have used mental chronometry tests, which measure the ease/difficulty that subjects may encounter in preserving the temporal characteristics of the motor performance (for review, see Guillot and Collet, 2005a, Malouin et al., 2008). Many psychological questionnaires have also been validated to evaluate the individual MI abilities (e.g. Hall and Martin, 1997, Malouin et al., 2007). As responses to those questionnaires remain subjective, however, the use of physiological recordings that correlate with mental representations of actions has recently been proposed. In particular, activity of the autonomic nervous system has been shown to match MI in real time and to evaluate both MI accuracy and individual ability to form mental images (Roure et al., 1999, Guillot and Collet, 2005b).

Despite accumulated evidence that the benefits of MI are dependent upon the individual imagery abilities, there is still no data, however, with respect to the pattern of brain activations in subjects with good and poor MI abilities. Until now, the only neuroimaging study that indirectly touched upon (but did not address directly) this issue comes from Lotze et al. (2003) who compared professional musicians and beginners during both MI and motor performance of a violin concerto. Although the professionals reported using MI more often than the amateur violinists, this study focused more on identifying the brain structures related to the effects of the subject's expertise level in music than on their capacity to produce efficient MI. Furthermore, their participants were not subjected to rigorous MI testing procedures, as the MI abilities were only evaluated through a subjective and an a posteriori questionnaire. Thus, still to date, no study has looked at the cerebral networks associated with differences of expertise in MI.

In the present study, we aimed for the first time to identify the neural substrates mediating MI in good and poor imagers who were selected using a rigorous and quantitatively validated testing procedure including psychological tests, as well as behavioral and physiological measures. Based on the existing literature, it was expected that the neural substrates mediating MI would differ with respect to the accuracy and vividness of the mental images, even if good and poor imagers are showing a similar level of performance on tasks carried out physically. We thus hypothesized that, compared to poor imagers, greater activations in motor-related regions as well as in both the inferior and superior parietal areas would be observed during MI in subjects with good to excellent MI abilities. We also expected that fewer cerebral areas would be activated in good imagers, while a more distributed pattern of activity would be observed in the group of poor imagers. Finally, earlier neuroimaging studies have provided evidence that the cortico-striatal and the cortico-cerebellar anatomical systems contribute differently in motor learning, although they share functional interactions (e.g., Doyon and Ungerleider, 2002, Doyon et al., 2003, Doyon and Benali, 2005). Accordingly, we predicted that these two anatomical systems would contribute differently during MI of sequential movements in skilled and poor imagers.

Section snippets

Methods

In order to investigate the neural substrates mediating MI in good and poor imagers, we first tried to distinguish between subjects who were able to reach a high level of performance from those who were having trouble in using MI. As suggested by Guillot and Collet (2005b) and Lotze and Halsband (2006), a series of psychological, behavioral and neurophysiological tests were thus combined prior to the fMRI study to evaluate MI ability within a large sample of subjects. The fMRI experiment was

MIQ-R

When comparing the two groups selected for the fMRI experiment (n = 28), the MIQ-R scores were significantly different (t = 5.6, p < 0.001), mean MIQ-R scores being 45.7 (2.7) in the good imagers and 38.6 (5.2) in the poor imager groups. The minimal and maximal scores were 42 and 50 in good imagers and 27 and 46 in poor imagers, respectively. Interestingly, there was no significant difference between men and women scores (t = 0.7, p > 0.05, NS).

Mental chronometry

The average time difference between the physical and the

Discussion

This study aimed to investigate whether the neural substrate mediating MI might differ among participants showing high or poor MI ability, i.e. with respect to the accuracy and the vividness of the mental images. To check the compliance of the subjects with instructions and to ensure that they performed MI as they were instructed to, the participants were requested to describe the nature of the mental images they formed after the MI session and to score their effort using a 4-point rating

Acknowledgments

This work was supported by a grant from the Multidisciplinary approach to promote and evaluate locomotion after spinal cord lesions and stroke, and from the Canadian Institutes of Health Research through the Regenerative Medicine and Nanomedicine Initiative program, to Serge Rossignol, Julien Doyon, Francine Malouin and Carol Richards. This work was also supported by a grant from the Foundation Simone and Cino Del Duca to Aymeric Guillot. Finally, we would like to express our gratitude to Vo An

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