The primary aim of the present study was to evaluate changes in the action simulation circuit that track with participants’ objective and subjective experience with movements. The first level of findings addressed the question of what brain areas are active when dancers observed and simulated another dancer’s complex whole-body movements, regardless of physical experience or perceived expertise with the movements. We reported activations within a large complement of cortical and subcortical neural regions. Importantly, we found activity within the 5 regions of the purported simulation circuit, including SMAr, PMv, IPL, STS, and M1. We also found a main effect of simulation of rehearsed movement compared to non-rehearsed movement, with more pronounced activity in STS, PMv, IPS, and SMAr.
Next, we distinguished between the influences of time (weeks) spent rehearsing the movements and participants’ self-assessed ratings of movement embodiment. We did not find a linear effect of weeks spent rehearsing on activity within the simulation circuit. This could be because we began scanning the dancers 1 week after they started learning the movement and thus lacked power in the analysis or because the effects of rehearsal may not be linear. Future studies should be able to establish more precise effects of learning time for complex actions by including a pre-training scan and scanning at closer intervals, such as every 24 h, instead of every 7 days, as in the present study. However, we did find an interaction between motor experience and judged ability in three regions. One was the left parahippocampal cortex, which is known to be involved in various elements of spatial and multimodal associative learning (see Squire et al., 2004
, for a review). However, we will limit our discussion to the predicted areas within the simulation circuit since we had no a priori predictions about the hippocampal activity. The other two regions fell within the predicted simulation circuit. Specifically, activity in left IPL and PMv was positively correlated with participants’ self-rated sense of action competency, but only for the rehearsed movements.
While it is true that we did not formally evaluate dancers’ competency with performing the movements they observed, we can surmise that sense of competency matches actual embodiment of the newly acquired motor skill. This is a reasonable inference because most trained athletes and dancers have an accurate ability to judge relevant performance in self and others, and post hoc verbal reporting of performance by highly trained performers has been validated by the expert performance literature (Ericsson and Lehmann, 1996
; Ericsson and Simon, 1993
). Our findings demonstrate the sensitivity of the IPL and PMV regions within the simulation circuit to physical embodiment, not just to movement that is familiar through weeks of practice or visual experience. In the following discussion, we will examine both the relationship between action embodiment and activity within IPL and PMv/pars opercularis and how these findings inform and extend upon prior research.
Activation was found in left IPL and PMv when participants observed movements that they had practiced weekly and judged they could perform well, compared to observing movement that they never practiced and judged their performance ability as poor. These two regions make up the human mirror system as defined by Rizzolatti and Craighero (2004)
. Neuroimaging research conducted with human subjects supports the notion that a functional relationship exists between inferior parietal and premotor areas, including PMv (Binkofski et al., 2000
; Creem-Regehr and Lee, 2005
; Wise et al., 1997
More specifically, the IPL is activated when humans observe, prepare, or simulate actions, and this activation is specific for movement of the limbs, but not the eyes (Deiber et al., 1991
; Krams et al., 1998
). This area has been shown to be involved with mediating motor attention processes (Rushworth et al., 2001
) and is strongly implicated as the primary area of cortex responsible for the visuomotor transformations necessary for imitation or reproduction of observed movement (Grezes et al., 1998
; Zentgraf et al., 2005
). Evidence from work with non-human primates further informs our knowledge of the role of IPL in action understanding (Fogassi et al., 2005
; Gallese et al., 2002
). Fogassi and colleagues recorded responses from individual neurons within the convexity of IPL and demonstrated that, not only do many of these neurons show mirror neuron properties for observed and executed actions, but they also code for the specific goals or intentions of motor acts (Fogassi et al., 2005
). Here, we have shown that activity in human IPL is greatest when participants simulate actions with which they have physical experience and judge that they can perform. Thus, mirror activity in IPL is related to the degree to which an action is embodied.
Our finding of PMv/pars opercularis activation under these same conditions is in accord with the pattern of results reported from a number of other neuroimaging works on action observation or imagined action (e.g., Buccino et al., 2004
; Calvo-Merino et al., 2005
; Decety, 1996
; Grezes and Decety, 2001
). Although the PMv activation seen in the present study is less robust than the IPL activation, it nonetheless has valuable implications. Animal data indicate that the non-human primate homologue of PMv, area F5, is primarily composed of sensorimotor neurons that code for specific action goals, such as reaching or grasping (Rizzolatti and Fadiga, 1998
). Work conducted with humans shows that PMv is more involved in covert action stages, such as action observation and imagination, than in actual action execution (Schubotz and von Cramon, 2004
). In humans, the main motor area present in caudal inferior frontal gyrus (IFG) is BA 44/pars opercularis, directly adjacent to premotor cortex (BA6). Schubotz and von Cramon (2004)
suggest that this caudal motor area of IFG might be responsible for performing higher-level organization of actions, while the adjacent section of inferior premotor cortex (inferior BA 6) is involved with the organization of simpler, lower-level action representations. Such an explanation is in accord with our finding of activity mainly within BA 44/pars opercularis while simulating complex dance sequences.
While it is true that the BA44 is also involved in language processing, it is unlikely that activation in this area in the present study is being driven by an increased ability to verbalize observed and imagined movements. First, we do not see activation of other middle temporal areas involved with semantic categorization (Vandenberghe et al., 1996
). In addition, several studies have demonstrated clear activation of this area in action tasks where speech was not involved, suggesting that BA44/PMv can have an action component independent of language processing (Carey et al., 1997
; Decety et al., 1997
; Iacoboni et al., 1999
; Nishitani and Hari, 2000
; Rizzolatti et al., 1996a
; Schubotz and von Cramon, 2004
). As discussed earlier, we specifically chose to study the learning of modern dance movements that are not associated with standardized verbal labels. While it is possible that participants could have assigned arbitrary labels to the movements, this would almost certainly have been done at an implicit level as post hoc interviews revealed that dancers did not rely on specific verbal labels or descriptions while simulating (or learning) movement.
There are several aspects of the present study that are best understood by comparison to other relevant studies in the field. First, we consider a recent study that investigated how acquired motor skills influence the perception of another individual’s actions in ballet dancers, capoeira dancers, and inexpert control subjects (Calvo-Merino et al., 2005
). All participants passively viewed ballet and capoeira dance clips while being scanned. The authors reported activity within the action resonance circuit, including the 5 sites in the simulation circuit, when the participants observed the movement style they had expertise in performing. This indicates that brain regions involved in action resonance processes are sensitive to movement familiarity. Our results replicate these findings in a within-subjects design with a single class of movements, all of the same style and differing only in motor experience. We showed that, when the same participants observe movement they had rehearsed, areas within the action resonance circuit show greater activity than when observing never-rehearsed movements. We extend Calvo-Merino et al.’s findings further through use of externally guided movement simulation, instead of passive movement observation, to begin to address the issue of movement embodiment. Thus, areas involved in action observation and imagination are sensitive to prior physical experience.
An additional issue broached by the Calvo-Merino et al. study that we have addressed is the role of verbal familiarity. Confounds of verbal familiarity cannot be ruled out with certainty in the Calvo-Merino et al. study as both dance styles investigated have well-established movement lexicons associated with the component movements. The present study has extended this work by investigating the neural processes subserving action simulation in an active context, guided by visual input, with less of a chance of engagement of language processes. Within this framework, we have established that time spent practicing the movements and visual and physical familiarity with the movements is not enough to drive core areas of the simulation circuit. Instead, it is one’s own ability to actually generate the movement that has the greatest influence on further increasing activity within action understanding areas.
Another study that informs the findings of the present study was conducted by Creem-Regehr and Lee on the degree to which tools or graspable non-tool objects stimulate the action simulation circuit (Creem-Regehr and Lee, 2005
). In this fMRI study, participants viewed 3D images of tools or other graspable, non-tool objects and were asked to simply view the items or to view and imagine grasping them. Data revealed that, when participants imagined grasping either type of object, a consistent pattern of premotor (including PMv) and posterior parietal activity was present, with stronger activations in the left hemisphere. This pattern of activity was far more robust and encompassed more parietal and premotor areas when participants were imagining grasping the tools they were viewing compared to grasping the non-tool objects. The grasping simulation was in response to a visually presented object and the task relied upon the object’s features to create the simulation. A question that arises from this approach is whether participants were actually simulating the movement or simply recalling overlearned functional knowledge of familiar objects, as has been shown to occur when participants view tools compared to non-tool objects (e.g., Chao et al., 1999
; Chao and Martin, 2000
). The issue of nameability is present in their study as well since tools have readily accessed names that non-tool shapes do not necessarily have. This difference might be partially responsible for some of the differences in IFG activation between the tool and non-tool conditions in this study. The present study extends this work by looking at how unnamed perceptual motor processes change with learning when simulation is not just externally triggered but is externally guided as well.
A third study to consider is the seminal work by Buccino and colleagues on imitation learning in the context of learning to play chords on the guitar (Buccino et al., 2004
). In this imaging study, musically naive participants completed multiple sessions of four experimental conditions. In the imitate condition, participants observed an experienced guitar-playing model play a chord then imitated the same chord after a pause. In the non-imitative condition, participants observed the same thing, but this time performed a different, non-chord-related hand action after the pause. In the observe condition, participants simply watched the model play a chord, and, in the execute condition, participants performed a chord of their choice without visual guidance from a model. These authors found that IPL and PMv became active as participants observed a model play the chords that they had to imitate after the pause and suggest that the relay of sensorimotor information between these two mirror neuron-rich areas is an essential component of imitation learning. This result is in accord with our findings that these same areas are activated when participants observe and imagine performing actions that they have physically embodied and are able to perform.
The present study establishes a role of physical embodiment in action simulation. We replicated past findings that reveal a general mechanism for action resonance and action simulation that encompasses parietal, premotor, and subcortical areas. This general mechanism has been shown by prior work to be sensitive to different features including familiarity, conceptual knowledge, and physical plausibility. Within this network, IPL and PMv/pars opercularis are demonstrated to be the two distinct regions that are sensitive to perceived physical competency. This finding is in accord with the theory that motor vocabularies are stored within these two brain regions, an idea that is supported by studies with apraxic patients (Buxbaum et al., 2003
; Fukutake, 2003
) and animal studies (Rizzolatti and Craighero, 2004
; Rizzolatti et al., 1996a
). This implies a close relationship between the substrates of action and physical embodiment.