Movement execution is the end-product of multiple intricate neural processes including action selection and planning. Although the neural dynamics involved in such internal processes are generally investigated during the build-up to movement execution, the study of motor imagery provides an alternative window on the large-scale cortical dynamics mediating formation of motor plans. Indeed, motor imagery is associated with oscillatory power modulations widely distributed in sensorimotor cortical networks (Pfurtscheller and Neuper, 1997). However, the functional role of such oscillations and the putative inter-regional coupling within and across multiple frequency bands are still unresolved issues.
The study by de Lange et al. (2008) addresses these timely questions by using whole-head magnetoencephalography (MEG) to investigate oscillatory brain dynamics in subjects performing a motor imagery task. The participants were required to judge the handedness of drawings of a left hand or a right hand presented at various angles. Such a task elicits internal simulations of rotating one's own hands. With frequency domain analysis and MEG source estimation, the authors evaluate modulations of various rhythmic components induced by the hand motor imagery task demands. While task-related suppressions in oscillatory power were found in the alpha (8–12 Hz) and beta (16–24 Hz) bands over occipito-parietal and precentral areas, significant increases in gamma-range (50–80 Hz) power were revealed over occipitoparietal cortex. Interestingly, when compared to right-hand motor imagery, left hand imagery was associated with stronger suppressions in contralateral motor areas. A further significant novelty of the study is the usage of cross-frequency amplitude correlation to specifically investigate oscillatory interactions between posterior parietal and frontal regions during formation of a motor plan. The authors therefore provide evidence for a significant long-range anti-correlation between parietal gamma power and frontal beta power at specific periods during mental simulation of action.
Viewed in the broader context of the previous work, the findings are of particular significance. Firstly, because the findings provide novel insights into the local and long-range oscillatory dynamics within the parieto-frontal network during motor imagery, and secondly, because of the important questions raised by the findings for future research. Acknowledging the fact that behavior arises from the integrative action of large-scale brain networks (Varela et al., 2001), earlier electrophysiological studies have assessed long-range interactions between distant structures of the human brain during different experimental paradigms by using various measures of coupling (e.g., Hummel and Gerloff, 2006; Jerbi et al., 2007; Lachaux et al., 1999; Schoffelen and Gross, 2009; Sehatpour et al., 2008; von Stein et al., 2000). These studies suggest that coupling between distinct neural structures at certain frequencies might provide an efficient mechanism for inter-regional communication in the brain (Fries, 2005). A growing body of research in recent years extends this view by pointing to cross-frequency coupling as a further putative mechanism mediating complex hierarchies of integrated neural ensembles at various scales (Jensen and Colgin, 2007). The study by de Lange et al. (2008) provides evidence for cross-frequency inter-areal amplitude coupling adding to a list of reported inter-frequency relations such as cross-frequency phase synchrony (Palva et al., 2005) or nested oscillations. The latter findings are observed as a locking between amplitude fluctuation of faster oscillations and the phase of slower oscillations, and have been observed during active tasks as well as in spontaneous brain activity (Bruns and Eckhorn, 2004; Canolty et al., 2006; Lakatos et al., 2008; Monto et al., 2008; Mormann et al., 2005; Osipova et al., 2008; Schack et al., 2002). Finally, in order to better understand the functional role of these mechanisms, future studies will have to monitor the putative relationship between interaction measures and behavioral performance. Investigating the alteration of cross-frequency coupling in pathology will also enhance the shift from descriptions of correlations to causal inference.
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