Abstract

Prior work has identified a common left parietofrontal network for storage of tool-related information for various tasks. How these representations become established within this network on the basis of different modes of exposure is unclear. Here, healthy subjects engaged in physical practice (direct exposure) with familiar and unfamiliar tools. A separate group of subjects engaged in video-based observation (indirect exposure) of the same tools to understand how these learning strategies create representations. To assess neural mechanisms engaged for pantomime after different modes of exposure, a pantomime task was performed for both tools while recording neural activation with high-density EEG. Motor planning–related neural activation was evaluated using beta band (13–22 Hz) event-related desynchronization. Hemispheric dominance was assessed, and activation maps were generated to understand topography of activations. Comparison of conditions (effects of tool familiarity and tool exposure) was performed with standardized low-resolution brain electromagnetic tomography. Novel tool pantomime following direct exposure resulted in greater activations of bilateral parietofrontal regions. Activations following indirect training varied by tool familiarity; pantomime of the familiar tool showed greater activations in left parietofrontal areas, whereas the novel tool showed greater activations at right temporoparieto-occipital areas. These findings have relevance to the mechanisms for understanding motor-related behaviors involved in new tools that we have little or no experience with and can extend into advancing theories of tool use motor learning.

INTRODUCTION

It has been consistently documented that the left parietofrontal areas play a dominant role in planning and executing tool-related movements, which are a subset of skilled movements called praxis (Bohlhalter et al., 2009; Fridman et al., 2006; Johnson-Frey, Newman-Norlund, & Grafton, 2005; Wheaton, Nolte, Bohlhalter, Fridman, & Hallett, 2005; Wheaton, Shibasaki, & Hallett, 2005; Wheaton, Yakota, & Hallett, 2005; Johnson-Frey, 2003; Haaland, Harrington, & Knight, 2000). Expanding this to include the temporal and occipital cortex, which are involved in tool identification (Beauchamp, Lee, Haxby, & Martin, 2002; Chao, Weisberg, & Martin, 2002; Choi et al., 2001), these areas have been hypothesized to create a “neural tool network” that is responsible for the identification of tools, understanding of tool properties, proper function, and familiarity (Vingerhoets, 2008).

Although the abovementioned findings are relevant to known tools, of interest is the mechanism of how we create representations for new tools. In a recent study, novel tool function was learned over sets of observation of function and practice (Weisberg, van Turennout, & Martin, 2007). Here, researchers found that items with a previously unknown function could obtain tool status after training, as indicated by neural activations at regions of the brain consistent with tool use (e.g., left middle temporal gyrus, intraparietal sulcus, and premotor cortex). Likewise, knowledge for skilled action develops in the left parietal and premotor areas when novel abstract objects are given a functional use (Creem-Regehr, Dilda, Vicchrilli, Federer, & Lee, 2007). This work fits the idea that parietofrontal areas acquire and maintain functional knowledge related to tool use (Buxbaum, Kyle, Tang, & Detre, 2006) and that these representations are recalled to perform a symbolic motor act, such as tool use pantomime (Kroliczak & Frey, 2009; Wheaton, Fridman, Bohlhalter, Vorbach, & Hallett, 2009; Johnson-Frey et al., 2005). As well, the left parietal cortex seems to play a role in “motor cognition” or general knowledge about tool-related action (Creem-Regehr, 2009; Creem & Proffitt, 2001).

By what behavioral methods does one acquire functional tool action knowledge? There are two common ways to gain knowledge of a tool and its appropriate action: direct and indirect. We define this “direct exposure” as originating from physical use of the tool for a desired outcome. In contrast, “indirect exposure” does not involve physical experience of the tool but may simply involve watching its use demonstrated. Although it may be apparent from the abovementioned studies (Creem-Regehr et al., 2007; Weisberg et al., 2007) that a combination of direct and indirect exposure establishes such representations, these two types of exposures may involve distinct neural mechanisms. Successfully imitating an observed, known (or practiced) movement may be achieved through the recall of known perceptual representations (Massen & Prinz, 2009; Menz, McNamara, Klemen, & Binkofski, 2009). However, if the movement is unfamiliar, other neural mechanisms may be required to afford action.

Two neural mechanisms may be involved in forming representations through indirect exposure: mirror neurons (Cattaneo & Rizzolatti, 2009) and a social network model (Wheatley, Milleville, & Martin, 2007). In human studies, a mirror neuron system may code specific goals of observed actions using a largely left parietal and frontal system (Buccino et al., 2001, 2004; Murata et al., 1997; Rizzolatti, Fogassi, & Gallese, 1997; Grafton, Arbib, Fadiga, & Rizzolatti, 1996). Not only observation of the act but hearing sounds related to that act can activate the mirror neuron system (Keysers et al., 2003; Kohler et al., 2002). This system bears similarities to areas involved in the production of tool use gestures, as many regions of the mirror neuron system also contribute to the tool-related action network (Cattaneo & Rizzolatti, 2009).

A social cognition model has been considered for understanding actions of animate agents by utilizing right temporal and prefrontal areas for processing of biological motion that may be performed later (Wheatley et al., 2007; Allison, Puce, & McCarthy, 2000; Ishai, Ungerleider, Martin, & Haxby, 2000). Unlike the mirror neuron system, this network is largely anatomically distinct from the typical tool-related action network. The social network is specifically active in the observation and understanding of goals of animate agents (Wheatley et al., 2007). The animate specificity of this network is thought to engage areas involved in comprehending biologically relevant motion, such as right STS (Wyk, Hudac, Carter, Sobel, & Pelphrey, 2009; Pelphrey & Morris, 2006; Beauchamp et al., 2002; Iacoboni et al., 2001; Allison et al., 2000). In addition to processing the global aspects of biological motion, regions within the social cognition network may be “sensitive to the intentionality and appropriateness of biological motion” (Pelphrey, Morris, & McCarthy, 2004). Further, Pelphry and Morris have suggested that activation of these areas is “… modulated by the context within which the actions of biological entities are observed. Such a contextual influence is consistent with a broader tradition within social psychology emphasizing the powerful influences of situational and contextual factors on behavior and perception” (Pelphrey & Morris, 2006). In part, this network appears relevant for determining the ability of an observer to carry out an observed act. As such, given the unique (novel) context of pantomiming an unfamiliar tool, we suggest similar function of the social cognition network in the current work.

The present work seeks to understand how direct and indirect modes of exposure differentially facilitate the formation of a traditional left parietofrontal tool use representation for an unfamiliar tool. A dichotomy of lateralization of activation and contrasts of exposure styles based on tool familiarity may be informative for understanding what mechanisms may be engaged. In accord with this, mirror activation may evoke largely left hemispheric networks similar to known tool representation networks, whereas a social cognition activity might show right hemispheric activation unlike the tool representation network. A specific focus is to determine whether indirect exposure of a novel tool alone is sufficient to promote the typical left parietofrontal tool-related representation to plan symbolic movement of that tool. We focus on planning, as this shows the clearest pattern of left lateralization of the tool action network (Bohlhalter et al., 2009; Wheaton, Shibasaki, et al., 2005). In this work, we selected two tools with the same overall goal, but one in which subjects have no prior experience. Physical (direct) exposure to tools (familiar and unfamiliar) was allowed in one group, whereas the other group only watched the tools being used in a video (indirect). All subjects were to pantomime using the tool after each exposure. We sought to test the overall effect of exposure of each tool (indirect video vs. direct practice) and the effect of tool within the different exposure types (familiar vs. unfamiliar). This allowed us to evaluate if direct and indirect exposures cause different activations for planning motor related tasks and to determine effects of tool familiarity on motor planning activations. Oscillations in the high alpha band (Mu rhythm; ∼10–12 Hz) are thought to indicate activation of the mirror neuron system. However, our prior work shows dynamics of beta band event-related desynchronization (ERD) related to praxis movement (Wheaton et al., 2009; Wheaton, Shibasaki, et al., 2005). Because beta band (13–22 Hz) activation is well known to reflect motoric processes (Pfurtscheller, Stancak, & Edlinger, 1997) and is thought to reflect activation of the mirror neuron system (Kilner, Marchant, & Frith, 2009; Neuper, Scherer, Wriessnegger, & Pfurtscheller, 2009; Pfurtscheller et al., 2007), we chose to evaluate beta band activation in the current work.

The parietofrontal tool action network shares many anatomical correlates with the network for conceptual “tool knowledge” (Lewis, 2006) as well as the human mirror neuron network (Rizzolatti & Sinigaglia, 2010). However, we sought to control for this by using “direct” exposure, in which subjects gained physical experience in using the new (and old) tools. In this condition, activation specific to the tool action network was expected (e.g., there was no exposure to the video to activate the mirror neuron system). We hypothesized that direct exposure of the unfamiliar tool will engage focused left hemispheric parietofrontal representations of a traditional tool action network (Vingerhoets, 2008) whereas indirect exposure of the unfamiliar tool would not. Furthermore, right hemisphere areas are well known to contribute to tool-related knowledge (Lewis, 2006) and engagement of right hemisphere structures has long been known to accompany the early phases of skill development (Halsband & Lange, 2006). Similarly, learning to use a new tool has been shown to induce gray and white matter changes in temporo-parietal areas in the monkey (Quallo et al., 2009). As such, we reasoned that rapid experience in use of the novel tool may additionally engage right hemisphere tool-related areas. Indirect exposure of the unfamiliar tool was expected to engage broader mirror neuron-related areas that emulate areas for storage of tool use representations (left parietofrontal) specific for action observation learning (Rizzolatti & Sinigaglia, 2010; Cattaneo & Rizzolatti, 2009). For the familiar tool, we hypothesized style of exposure would show no differences between direct and indirect in accessing left parietofrontal tool-specific representations to carry out the motor task. As described above, we further expected the unfamiliar tool would engage right hemispheric parietal areas related to novel tool representation and storage. Our findings are suggestive of the use of both mirror and social networks for pantomime with indirect unfamiliar tool exposure, whereas a mirror neuron system and traditional tool use representations more robustly activates indirect familiar tool exposure. Direct exposure appears to activate areas for tool use representations bilaterally.

METHODS

Thirty right-handed (by self-report) healthy subjects (14 women, 23.7 ± 2.8 years) participated in this study. Before participation, all subjects were consented according to guidelines of the Georgia Institute of Technology Institutional Review Board. Subjects were seated in a chair and fitted with a standard tin 58-channel EEG cap (Electrocap, Eaton, OH) to record neural activity using Synamps 2 (Neuroscan, Charlotte, NC). Data acquisition was performed using a right ear reference at a sampling rate of 1000 Hz and filtered to DC-100 Hz. The left ear was also recorded and used to create (off-line) a linked ear reference. Surface EMG was recorded from anterior and posterior aspects of the deltoid, triceps, and flexor carpi radialis (sampling rate, 1000 Hz; 5–200 Hz on-line filter) of the right arm and was used to determine onset of muscle activation by visual inspection (e.g., where anterior deltoid EMG activation showed a clear departure from baseline leading to a sustained burst of activation).

All subjects were exposed to a familiar tool (traditional twist screwdriver) and an unfamiliar tool (Yankee-style push screwdriver; Figure 1A). The two screwdrivers have similar handles for grasp but differ in the actual motor act required to accomplish the task; twist screwdriver requires forearm rotation and the push screwdriver requires elbow extension. No subjects reported familiarity with the push-style screwdriver. Half (15) of the subjects were exposed to the tools indirectly via two short videos in which an actor was shown using the twist, then push screwdrivers in separate videos to drive a series of screws into a wooden board (Figure 1B). The angle of the video demonstrated clearly the orientation of the actor's body, arm, and screwdriver to the target to allow for clear encoding of the actor's perspective. These subjects never touched or actually saw the push-style or twist screwdrivers.

Figure 1. 

(A) Two screwdrivers used in the present study, twist (left) and push (right). (B) The practice board for direct exposure (left) and video presentations for both tools (right).

Figure 1. 

(A) Two screwdrivers used in the present study, twist (left) and push (right). (B) The practice board for direct exposure (left) and video presentations for both tools (right).

The remaining subjects (15) were exposed directly to each tool through a bout of practice with twist and push screwdrivers separately. Practice was performed on a board of screws partially drilled into a plywood board. Subjects engaged in a seated task of screwing in rows of screws with the screwdriver in their right hand. Subjects were told to only use the screwdriver and to try not to assist the movement with the left hand. The time of exposure was equal for both tools and in both exposure modalities at approximately 4 min.

Exposure and pantomime were performed in alternating blocks of twist and push screwdriver use (i.e., twist exposure–twist pantomime–push exposure–push pantomime). The ordering of twist and push exposure was counterbalanced across subjects. EEG was not recorded during the video or physical exposure because of the vast distinctions of exposure modes. Specifically, movement and auditory artifacts during direct exposure would hinder clear analysis and interpretation of these data.

The experimental session consisted of two 12-min conditions of instructed tool use pantomime. The pantomime tasks were executed in a self-paced manner, with movements generally 10 sec apart. All subjects began the movement from a resting position, seated with the arm on an armrest. Subjects were told to briskly perform the pantomime and return to rest.

Data Analysis

Continuous data were bandpass filtered within the beta frequency range (13–22 Hz) to compute ERD to evaluate activity of neural areas. Data were epoched from −3000 msec to +1500 msec relative to anterior deltoid EMG onset (time 0). The anterior deltoid was the recorded muscle that showed activation first, reliably across subjects and conditions. Signal power changes were normalized by expressing the magnitude of the power as a percentage of increase (positive percentage) or decrease (negative percentage) from a reference interval (−3000 to −2500 msec; Pfurtscheller, 2001). Epochs with artifact were visually identified and removed from analysis. To reduce the effect of intersubject variability in the amplitude of the evoked responses, data for the 15 subjects within each group were resampled to 1000 trials for each condition according to the bootstrap procedure (Efron, 1981).

Two motor planning time bins (−1000 msec through −500 msec and −500 msec through EMG onset) in which to determine activation differences were defined post hoc. To better characterize the electrode-based ERD data, an initial analysis of lateralization was performed. Here, the magnitude of the beta ERD was compared between homologous contralateral electrodes (e.g., left parietal P3 vs. right parietal P4; left occipital O1 vs. right occipital O2) via Bonferroni corrected t tests for all possible electrode pairs. Mesial electrodes (which have no corresponding contralateral pairing) were not assessed. Significance was assessed at p = .05 (pcorr = .002). Results of the significant electrode data (channel pairs with the greatest magnitude of ERD, if significant) were identified.

Further analysis of the chosen motor planning time bins was performed using standardized low-resolution brain electromagnetic tomography (sLORETA; Pascual-Marqui, 2002) to optimally define neuroanatomical generators without a priori localization bias. Motor planning activation differences were determined for 6239 brain matter voxels at a 5-mm spatial resolution in four comparison groups: indirect versus direct exposure of the twist screwdriver, indirect versus direct exposure of the push screwdriver, indirect exposure of the twist versus the push screwdriver, and direct exposure of the twist versus the push screwdriver. Using log-transformed t values, statistical significance was set for all comparisons at voxels corresponding to p = .01.

RESULTS

ERD Analysis

Exemplar ERD traces at left and right premotor and parietal areas are shown in Figure 2 from the direct training–twist screwdriver condition, and tomography plots of ERD activation from all conditions is seen in Figure 3. Overall head plots revealed predominant ERD in posterior areas for most comparisons. Pantomime after indirect exposure generated large ERD over occipital and frontal electrodes for both movement types. Pantomime after direct exposure lead to ERD seen largely over bilateral posterior parietal and frontal electrodes.

Figure 2. 

Group-averaged ERD traces in the direct-twist screwdriver condition observed at left premotor (average of electrodes C3A and C1A) and parietal (average of electrodes C3P, C1P, P3, and P1) and right premotor (average of electrodes C4A and C2A) and parietal (average of electrodes C4P, C2P, P4, and P2) areas. The time range reflects the entire epoch (−3000 msec before EMG onset through 1500 msec after EMG onset), and the vertical bar indicates EMG onset.

Figure 2. 

Group-averaged ERD traces in the direct-twist screwdriver condition observed at left premotor (average of electrodes C3A and C1A) and parietal (average of electrodes C3P, C1P, P3, and P1) and right premotor (average of electrodes C4A and C2A) and parietal (average of electrodes C4P, C2P, P4, and P2) areas. The time range reflects the entire epoch (−3000 msec before EMG onset through 1500 msec after EMG onset), and the vertical bar indicates EMG onset.

Figure 3. 

Activation maps for the beta band activity during planning of tool use tasks. Time indicates latency relevant to movement onset.

Figure 3. 

Activation maps for the beta band activity during planning of tool use tasks. Time indicates latency relevant to movement onset.

To describe overall aspects of the data based on potential lateralization distinctions, homologous left–right electrode analysis was performed on ERD by electrode site for significance (p = .05, corrected). Figure 4 illustrates the results of this analysis. For indirect exposure, overall left laterality was evident but differed regionally based on the type of tool. Indirect exposure of the twist screwdriver showed a left lateralized frontal ERD. Indirect exposure of the push screwdriver showed a left lateralized parieto-occipital ERD in both planning time bins. Direct exposure of the twist screwdriver showed a strong left lateralized parietal ERD with right frontal lateralization. Direct exposure of the push screwdriver revealed strong right hemispheric dominance at temporo-frontal sites but with left parietofrontal distribution for early and late time bins.

Figure 4. 

Lateralization head plot for statistical comparison of left–right homologous electrode pairs for the time bins of interest. Significant (pcorr = .002) differences are colored over the electrode that showed the greatest ERD. For visualization purposes, combinations where the left electrode was greater than the right electrode are colored red. Combinations where the right is greater than left are colored blue.

Figure 4. 

Lateralization head plot for statistical comparison of left–right homologous electrode pairs for the time bins of interest. Significant (pcorr = .002) differences are colored over the electrode that showed the greatest ERD. For visualization purposes, combinations where the left electrode was greater than the right electrode are colored red. Combinations where the right is greater than left are colored blue.

Mode of Exposure

Analysis was undertaken to assess the overall effect of exposure for both tool types. For both types of screwdriver, analysis of motor planning activations showed a consistent pattern suggestive of systematic differences based on the mode of exposure (Figure 5).

Figure 5. 

Significant (p < .01) activation differences for the overall comparison of direct and indirect exposure for both tools. In all panels, greater activation for direct exposure is shown in blue and indirect exposure is in red.

Figure 5. 

Significant (p < .01) activation differences for the overall comparison of direct and indirect exposure for both tools. In all panels, greater activation for direct exposure is shown in blue and indirect exposure is in red.

Indirect Exposure

For both tools, generally, indirect over direct exposure resulted in significant (p < .01) activation of the right lateralized parietal cortex (e.g., superior and inferior parietal lobules, angular gyrus, and precuneus), widespread aspects of anterior frontal cortex bilaterally (e.g., inferior, medial, and superior frontal gyrus) and also included bilateral temporal regions (e.g., insula, fusiform gyrus, and superior, middle, and inferior temporal gyri) for early and late time bins.

Direct Exposure

Similar patterns of activation were also seen for both tools following direct exposure (direct over indirect, p < .01) but were more restricted to left hemisphere parietal (e.g., postcentral gyrus, precuneus, and inferior parietal lobule) in early and late planning and sensorimotor regions (e.g., precentral gyrus) for late planning. Activation differences for direct over indirect were also seen at the right parietal cortex (cingulate and postcentral gyri) and parietotemporal areas in late preparation only.

Comparison of Tool Familiarity

Direct Exposure

We then focused on whether the type of tool (familiar twist screwdriver vs. unfamiliar push screwdriver) was differentially affected by exposure modality (direct vs. indirect). Evaluation of push versus twist screwdriver following direct exposure showed significant activation differences only for the push screwdriver in both early and late motor planning (Figure 6; Tables 1 and 2). In early motor planning (Figure 6; Table 1), greater activation for push (p < .01) was primarily focused at left frontal regions (e.g., precentral gyrus, middle frontal gyrus, and cingulate gyrus), and bilateral parietal regions (e.g., right precuneus and left postcentral gyrus), but also included right temporal regions (e.g., superior temporal gyrus and insula) and right occipital regions (e.g., cuneus). Similar patterns of activation were seen in late motor planning (Figure 6; Table 2). Again, activation differences (p < .01) were seen only for the push over the twist screwdriver, including bilateral sensorimotor areas (e.g., precentral gyrus and paracentral lobule), anterior frontal cortex (e.g., middle, medial, and superior frontal gyri), parietal areas (e.g., bilateral postcentral gyrus and inferior parietal lobule), right lateralized temporal areas (e.g., insula, superior temporal gyrus, and fusiform gyrus), and bilateral occipital regions (e.g., cuneus and lingual gyrus).

Figure 6. 

Significant (p < .01) activation differences for the comparison of twist versus push screwdrivers for each exposure type. In all panels, greater activation for the push screwdriver is shown in blue and for the twist screwdriver in red.

Figure 6. 

Significant (p < .01) activation differences for the comparison of twist versus push screwdrivers for each exposure type. In all panels, greater activation for the push screwdriver is shown in blue and for the twist screwdriver in red.

Table 1. 

Activation Differences Seen in the Comparison of Twist versus the Push Screwdriver in Early Motor Planning following Direct Exposure

Direct Exposure: Push vs. Twist Screwdriver in Early Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Push > Twist 
Frontal lobe Left precentral gyrus −30 −17 47 −9.00 14 
Left middle frontal gyrus −30 −7 46 −7.85 
Left cingulate gyrus −20 −17 42 −6.76 
Occipital lobe Right cuneus 25 −81 32 −7.05 
Parietal lobe Right precuneus 30 −71 36 −9.40 
Left postcentral gyrus −30 −22 47 −7.71 
Temporal lobe Right insula 54 −38 20 −6.65 
Right superior temporal gyrus 64 −33 11 −7.68 
Direct Exposure: Push vs. Twist Screwdriver in Early Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Push > Twist 
Frontal lobe Left precentral gyrus −30 −17 47 −9.00 14 
Left middle frontal gyrus −30 −7 46 −7.85 
Left cingulate gyrus −20 −17 42 −6.76 
Occipital lobe Right cuneus 25 −81 32 −7.05 
Parietal lobe Right precuneus 30 −71 36 −9.40 
Left postcentral gyrus −30 −22 47 −7.71 
Temporal lobe Right insula 54 −38 20 −6.65 
Right superior temporal gyrus 64 −33 11 −7.68 

Coordinates are given in Talairach space. Coordinates given for each region represents the peak voxel. The number of significant (p < .01) voxels in a region is identified as k.

Table 2. 

Activation Differences Seen in the Comparison of Twist versus the Push Screwdriver in Late Motor Planning following Direct Exposure

Direct Exposure: Push vs. Twist Screwdriver in Late Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Push > Twist 
Frontal lobe Left precentral gyrus −25 −12 47 −12.48 37 
Left medial frontal gyrus −15 −12 47 −10.89 37 
Right medial frontal gyrus 51 −7.97 31 
Right precentral gyrus 30 −11 65 −8.41 19 
Left middle frontal gyrus −25 −7 46 −11.74 15 
Right paracentral lobule −12 47 −7.38 
Right superior frontal gyrus 50 −7.33 
Right middle frontal gyrus 25 −12 60 −7.55 
Left superior frontal gyrus −5 50 −7.31 
Left cingulate gyrus −20 −17 42 −12.35 50 
Right cingulate gyrus −3 42 −10.48 49 
Left paracentral lobule −10 −12 47 −9.62 11 
Occipital lobe Right lingual gyrus −83 −4 −8.31 24 
Left lingual gyrus −5 −78 −7.18 
Left cuneus −5 −82 −8.02 
Right cuneus −82 −7.02 
Parietal lobe Left postcentral gyrus −30 −22 43 −11.43 50 
Left inferior parietal lobule −45 −32 43 −9.94 36 
Right postcentral gyrus 20 −27 52 −8.13 10 
Right inferior parietal lobule 54 −33 25 −7.48 
Temporal lobe Right insula 54 −33 20 −7.86 
Right superior temporal gyrus 64 −33 20 −8.12 10 
Right fusiform gyrus 50 −40 −23 −6.90 
Direct Exposure: Push vs. Twist Screwdriver in Late Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Push > Twist 
Frontal lobe Left precentral gyrus −25 −12 47 −12.48 37 
Left medial frontal gyrus −15 −12 47 −10.89 37 
Right medial frontal gyrus 51 −7.97 31 
Right precentral gyrus 30 −11 65 −8.41 19 
Left middle frontal gyrus −25 −7 46 −11.74 15 
Right paracentral lobule −12 47 −7.38 
Right superior frontal gyrus 50 −7.33 
Right middle frontal gyrus 25 −12 60 −7.55 
Left superior frontal gyrus −5 50 −7.31 
Left cingulate gyrus −20 −17 42 −12.35 50 
Right cingulate gyrus −3 42 −10.48 49 
Left paracentral lobule −10 −12 47 −9.62 11 
Occipital lobe Right lingual gyrus −83 −4 −8.31 24 
Left lingual gyrus −5 −78 −7.18 
Left cuneus −5 −82 −8.02 
Right cuneus −82 −7.02 
Parietal lobe Left postcentral gyrus −30 −22 43 −11.43 50 
Left inferior parietal lobule −45 −32 43 −9.94 36 
Right postcentral gyrus 20 −27 52 −8.13 10 
Right inferior parietal lobule 54 −33 25 −7.48 
Temporal lobe Right insula 54 −33 20 −7.86 
Right superior temporal gyrus 64 −33 20 −8.12 10 
Right fusiform gyrus 50 −40 −23 −6.90 

Coordinates are given in Talairach space. Coordinates given for each region represents the peak voxel. The number of significant (p < .01) voxels in a region is identified as k.

Indirect Exposure

Indirect exposure showed a different pattern of activation differences based on tool type (Figure 6; Tables 3 and 4). In early motor planning (Figure 6; Table 3), greater activation (p < .01) for twist over push was seen at left frontal (precentral and medial frontal gyri and anterior cingulate) and parietal areas (postcentral gyrus and inferior parietal lobule). Activation differences (p < .01) for push over twist were seen at right parietal (inferior parietal lobule and supramarginal gyrus) and temporal regions (insula). Similarly, in late motor planning (Figure 6; Table 4), greater activation (p < .01) was seen for the twist over the push screwdriver at left parietal regions (inferior parietal lobule and supramarginal gyrus) and activation of push over twist (p < .01) was predominantly right hemispheric, including parietal (e.g., right inferior and superior parietal lobules and precuneus), temporal (right middle and superior temporal gyri) and occipital regions (right cuneus and bilateral lingual gyrus).

Table 3. 

Activation Differences Seen in the Comparison of Twist versus the Push Screwdriver in Early Motor Planning following Indirect Exposure

Indirect Exposure: Push vs. Twist Screwdriver in Early Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Twist > Push 
Frontal lobe Left precentral gyrus −35 −26 57 10.06 11 
Left medial frontal gyrus −10 39 −6 7.00 
Left anterior cingulate −5 34 8.16 18 
Parietal lobe Left postcentral gyrus −40 −26 57 11.23 30 
Left inferior parietal lobule −50 −27 47 8.53 14 
 
Push > Twist 
Parietal lobe Right inferior parietal lobule 45 −56 44 −7.81 10 
Right supramarginal gyrus 40 −47 35 −7.73 
Temporal lobe Right insula 30 −33 20 −7.74 
Indirect Exposure: Push vs. Twist Screwdriver in Early Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Twist > Push 
Frontal lobe Left precentral gyrus −35 −26 57 10.06 11 
Left medial frontal gyrus −10 39 −6 7.00 
Left anterior cingulate −5 34 8.16 18 
Parietal lobe Left postcentral gyrus −40 −26 57 11.23 30 
Left inferior parietal lobule −50 −27 47 8.53 14 
 
Push > Twist 
Parietal lobe Right inferior parietal lobule 45 −56 44 −7.81 10 
Right supramarginal gyrus 40 −47 35 −7.73 
Temporal lobe Right insula 30 −33 20 −7.74 

Coordinates are given in Talairach space. Coordinates given for each region represents the peak voxel. The number of significant (p < .01) voxels in a region is identified as k.

Table 4. 

Activation Differences Seen in the Comparison of Twist versus the Push Screwdriver in Late Motor Planning following Indirect Exposure

Indirect Exposure: Push vs. Twist Screwdriver in Late Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Twist > Push 
Parietal lobe Left inferior parietal lobule −35 −37 39 8.88 
Left supramarginal gyrus −40 −42 34 8.14 
 
Push > Twist 
Occipital lobe Right lingual gyrus −87 −9.77 11 
Left lingual gyrus −3 −87 −9.23 
Right cuneus 25 −91 28 −7.97 
Parietal lobe Right inferior parietal lobule 50 −61 40 −10.69 25 
Right angular gyrus 50 −62 31 −10.56 11 
Right precuneus 40 −66 36 −7.78 
Right supramarginal gyrus 54 −62 31 −10.41 
Right superior parietal lobule 40 −56 49 −8.01 
Temporal lobe Right superior temporal gyrus 45 −57 30 −10.48 
Right middle temporal gyrus 50 −62 26 −7.51 
Indirect Exposure: Push vs. Twist Screwdriver in Late Motor Planning
Lobe
Region
X(TAL)
Y(TAL)
Z(TAL)
Z
k
Twist > Push 
Parietal lobe Left inferior parietal lobule −35 −37 39 8.88 
Left supramarginal gyrus −40 −42 34 8.14 
 
Push > Twist 
Occipital lobe Right lingual gyrus −87 −9.77 11 
Left lingual gyrus −3 −87 −9.23 
Right cuneus 25 −91 28 −7.97 
Parietal lobe Right inferior parietal lobule 50 −61 40 −10.69 25 
Right angular gyrus 50 −62 31 −10.56 11 
Right precuneus 40 −66 36 −7.78 
Right supramarginal gyrus 54 −62 31 −10.41 
Right superior parietal lobule 40 −56 49 −8.01 
Temporal lobe Right superior temporal gyrus 45 −57 30 −10.48 
Right middle temporal gyrus 50 −62 26 −7.51 

Coordinates are given in Talairach space. Coordinates given for each region represents the peak voxel. The number of significant (p < .01) voxels in a region is identified as k.

To ensure that no practice or adaptation effects confound the data, we compared activations at motor (e.g., C3) and parietal (e.g., P3) electrodes. Activation, for each subject, was averaged over the time bins used for sLORETA analysis and compared between the first and second half of the experiment using a two-tailed t test. This was done for both the push and twist screwdrivers in direct and indirect exposure modes. Statistically significant differences were not seen at any electrode in either exposure mode or with either tool (actual p values ranged from 0.2 to 0.6). Thus, we are confident that adaptation effects were not seen in our data.

DISCUSSION

This study sought to understand possible neural systems used in planning tool use pantomime motor tasks based on the type of tool exposure (direct and indirect) and tool familiarity. Using EEG allowed us to assess this in subjects performing tool pantomime in a naturalistic setting; with similar hand-body orientation during pantomime with that of the direct and indirect exposure sessions. Generally, we observed distinct neural activations following direct and indirect exposure to familiar and unfamiliar tools. As expected, prominent activations were seen at regions within the canonical tool network during pantomime after direct tool exposure. However, indirect tool exposure resulted in a pattern of activations that varied by the tool (familiar vs. unfamiliar). Here, we propose involvement of two well known networks, the mirror neuron network and social cognition network, for reproducing observed familiar and unfamiliar tool-related movements, respectively.

The mechanisms for recalling established tool representations for performing skilled, tool-related movements have been well documented (Bohlhalter et al., 2009; Fridman et al., 2006; Johnson-Frey et al., 2005; Wheaton, Nolte, et al., 2005; Wheaton, Shibasaki, et al., 2005; Wheaton, Yakota, et al., 2005; Johnson-Frey, 2003; Haaland et al., 2000). However, the process through which we develop tool representations is less clear. Previous research into the acquisition of tool-related knowledge has primarily focused on direct training, where knowledge of tool use is gained through physical experience (Creem-Regehr et al., 2007; Weisberg et al., 2007). It is possible that the creation and storage of tool representations may occur through action observation alone (indirect exposure). It is well known that a mirror neuron system exists in the monkey, where viewing a motor act often activates regions involved in actual performance (Rizzolatti, Fogassi, & Gallese, 2001). Likewise, a social cognition model reflecting actions of animate agents may be engaged by utilizing right hemisphere areas for processing of biological motion that are more distinct from traditional tool representation areas (Wheatley et al., 2007; Allison et al., 2000; Ishai et al., 2000).

Direct versus Indirect Exposure Styles

A goal of this work was to assess general differences in exposure of tools, where we can compare indirect (observation) means of tool understanding with direct (physical) exposure. A clear differential based on exposure styles can be seen (Figure 5). Here, indirect exposure elicited greater activations at bilateral temporo-parietal and widespread bilateral inferior and middle frontal regions. Alternatively, direct exposure (physical practice) showed primary activations of the traditional tool use and sensorimotor network underlying pantomime of tool use. Although evaluation of subject performance was not the central question of the current work, it could be a potential limitation that we did not collect kinematic or behavioral data of subject performance in this study. However, we are confident that subjects were creating appropriate, complex tool use action plans by virtue of the instruction (e.g., “Show me how you would use the push/twist screwdriver”) which preceded each condition. Further, the plan phase of pantomime actions engages neural mechanisms similar actual tool use (Johnson-Frey et al., 2005). As well, experimenter observations of subject performance within the recording sessions suggest that subjects were correctly performing pantomime of push and twist screwdriver use.

Perhaps a typical tool-related action network is recalled following direct exposure, symbolic of having actually touched and used each tool, which created a tool representation for the push-style screwdriver that previously did not exist. It can be seen that direct exposure (compared with indirect) of the push screwdriver caused increased ERD at the left parietal lobe (localized to inferior and superior parietal lobule in sLORETA). Studies of the formation of novel tool representations after physical exposure support this finding (Creem-Regehr et al., 2007; Weisberg et al., 2007). It may be that recent usage of the tool engages more active and robust motor and kinesthetic memory for the task that is recalled during the pantomime task. A proposed mechanism has been suggested in evaluation of real versus pantomime motor acts (Senkfor, 2008), which suggests that the fine details of real movements are critical to successful accomplishment, whereas pantomime is based on (but distinct from) the real usage task. It is important to consider that we were concerned with motor planning of pantomime actions, which serves to “… convey information, while actual use has to obey the mechanical demands of the task” (Hermsdorfer, Hentze, & Goldenberg, 2006). In the planning phase of pantomime versus actual tool use, neural activations are nearly indistinguishable (Hermsdorfer, Terlinden, Muhlau, Goldenberg, & Wohlschlager, 2007), suggesting that similar tool use representations are necessary for both. Studies have also shown activation of posterior parietal, sensorimotor and premotor cortex for encoding and maintaining a kinesthetic working memory for learned shape tracing with a stylus (Fiehler, Burke, Engel, Bien, & Rosler, 2008). Here, the tool (stylus) movement for different tracings was encoded and stored in these areas based on holding the tool and kinesthetic feedback that was determined by the shape traced. Similarly, hand–object interactive movement information seems to be stored in the anterior intraparietal area (Naito & Ehrsson, 2006).

We propose that in our study, direct exposure heavily engages a motor memory system for kinesthetic recall of the tool that is in turn utilized in planning pantomime after physical exposure. If this requires kinesthetic working memory acquired directly from actual tool use, it is not likely that indirect exposure would show this activation as kinesthetic working memory of the actual tool is not encoded. However, we cannot firmly determine this effect, as we did not evaluate movement kinematics or skill differences between the two exposure styles. One may expect that there is a performance difference between pantomime after direct versus indirect exposure. Also, pantomime after direct exposure may be more similar to actual use than pantomime after indirect exposure. If increased motor system engagement after direct (over indirect) exposure is a common phenomenon, further evaluation of tool action encoding may be worthwhile (as in Fiehler et al., 2008).

Tool Familiarity

When each exposure modality was separately evaluated based on tool familiarity, we observed discrete regional differences based on the type of tool. Engagement of the different systems is dependent on modality of exposure (direct vs. indirect training) and personal history of tool use (familiar vs. unfamiliar tool).

Following direct exposure, no significant activation differences were seen for the familiar over the unfamiliar screwdriver; instead, greater activation for the unfamiliar push-style screwdriver was found at bilateral sensorimotor and parietal regions. This suggests an encoding of the previously unfamiliar push screwdriver into the canonical tool-related neural architecture, which was not required of the familiar twist screwdriver. Similar regions have recently been reported to show cortical changes following development of new motoric skills related to novel tools (Quallo et al., 2009). Activation differences were also seen at right insula and temporal areas. Although not normally considered for tool-related motor function, regions of the right temporal cortex have been shown to respond to processing of infrequently used tools (Vingerhoets, 2008), and right hemisphere networks show greater coherent activation in the early phases of skill acquisition which diminishes with proficiency (Deeny, Haufler, Saffer, & Hatfield, 2009). We suggest the right lateralized temporal activation seen in the current study may support similar processes for pantomime of the unfamiliar tool.

Unlike activation of the canonical tool network following direct exposure, we observed a second pattern of activation differences following indirect exposure of the familiar versus unfamiliar tools. Because of this, we suggest alternative theories which account for these activations. Left sensorimotor and parietal activation was seen for pantomime of the familiar screwdriver and primarily right temporal, parietal and occipital areas for the unfamiliar screwdriver. The left hemisphere is well known to be the predominant site of activation in pantomiming tool use (Hermsdorfer et al., 2007; Wheaton, Yakota, et al., 2005; Johnson-Frey, 2004), where parietofrontal networks are engaged in the recall of tool-related motor representations (for a review, see Johnson-Frey, 2004). As such, activations for pantomime of the familiar twist screwdriver in parietal and frontal areas observed in the current work were expected and could simply have been activation of the representation of the familiar tool. Although we cannot fully identify this activation as a function of the mirror neuron system, we suggest involvement of the mirror system as an alternative explanation (detailed below).

Although left parietal laterality is seen in the indirect push pantomime condition (Figure 4 and discussed below), additional neural activations are evident based on contrasting this indirect exposure based on tool history. Pantomime of the unfamiliar tool after indirect exposure showed predominant activations differences in right occipital, parietal and temporal areas compared with the familiar tool (Figure 6). Our results generally do not fully support the idea that an unfamiliar tool, when given exposure through indirect mechanisms, completely becomes a part of the left hemisphere tool action network for physically known tools. This result suggests a further encoding of the unfamiliar tool outside the typical tool use network. Recall of knowledge for a tool where the user is relatively unskilled may rely on added encoding of the task for action recall in right hemisphere. The mechanisms of this right hemispheric activation have relevance to models of how we encode seen action. As will be discussed below, we suggest the social cognition theory incorporates each of these factors, providing an explanation for the observed activations in pantomime of the unfamiliar tool following indirect exposure.

Mirror Neurons and Social Cognition after Indirect Exposure

Importantly, we are not suggesting activation of the mirror neuron system or social cognition network in pantomime following direct exposure, but rather that these theories work well to account for activations seen following indirect exposure. Pantomime of the unfamiliar tool following indirect exposure predominately activated bilateral occipital and parietofrontal areas, yet pantomime of the unfamiliar tool following indirect exposure activated predominately right temporo-parieto-occipital structures. This suggests complementary roles of the mirror neuron system and social cognition system for the production of unfamiliar tool-related pantomimes (Van Overwalle & Baetens, 2009). It is also important to note that there was no significant difference in frontal cortex activation for indirect exposure to familiar versus unfamiliar tools. Frontal cortex activation is often attributed to the mirror neuron system, and is commonly seen in imitation-based motor tasks (Margulis, Mlsna, Uppunda, Parrish, & Wong, 2009; Haslinger et al., 2005) and in clinical studies of imitation deficits (Goldenberg, Hermsdorfer, Glindemann, Rorden, & Karnath, 2007; Goldenberg & Karnath, 2006). A recent meta-analysis of the literature has shown that the mirror system is related to activation at the anterior intraparietal sulcus and premotor cortex, whereas the complementary social cognition (mentalizing) system is related to activations of TPJ, cuneus, and pFC (Van Overwalle & Baetens, 2009). The mirror system seems to be engaged specifically in understanding the movement of seen body parts, whereas the social cognition system is related, more generally, to understanding the behavioral intent of others. A factor that may relate to differences between the two is a preexisting motor template for the observed action (Van Overwalle & Baetens, 2009). If a template for the observed movement exists (i.e., a stored action representation of a familiar tool), activation of the mirror neuron system may emerge. If no template exists, further analysis of observed behavior through the social cognition network may be needed.

Additional meta-analysis demonstrated that the social cognition network (specifically areas of the TPJ) is, among other functions, engaged in visual comprehension of goal directed movement, understanding action goals, and in understanding agency and perspective (Van Overwalle & Baetens, 2009). Activation of the social cognition network is seen in action reproduction (for a review, see Wheatley et al., 2007), where right temporo-parietal areas are especially responsive to the perception of biological motion (Wyk et al., 2009; Pelphrey & Morris, 2006; Beauchamp et al., 2002; Iacoboni et al., 2001; Allison et al., 2000). On the basis of the characterizations of these two systems, there is clear potential for overlap between the mirror and social cognition ideas under certain conditions. In our study, we tested two movements that require rather distinct arm actions to conduct them (forearm rotation vs. elbow extension) but which yield the same intended outcome (driving in a screw). As subjects were “recreating” visuospatial elements of the environment following video-based exposure, pantomime of each tool should have elicited similar activations of the “social cognition” areas, yet this was not the case. As such, we offer this as a possible mechanism through which such a tool-based visuospatial task might be encoded.

Indirect exposure to the unfamiliar screwdriver may necessitate engagement of neural areas to understand and comprehend the behavioral goal of using the tool without physical experience (social cognition). At the same time, the outcome of the task equivalently (for both screwdrivers) matches a known template (mirror neuron system), thus resulting in no distinction of the strong frontal activation (Figure 5) when comparing indirect exposure of familiar versus unfamiliar tools (Figure 6). In other words, engagement of the frontal mirror neuron system is equivalent for both tools after indirect exposure, perhaps related to task–outcome encoding. Studies have shown that the frontal cortex is active for identifying actions associated with tools consistent with planning-related tool pantomime activity (Johnson-Frey et al., 2005). This frontal (particularly the inferior frontal gyrus) activity is likely a strong candidate in storing tool action memories (Goldenberg et al., 2007; Peigneux et al., 2004; Hamzei et al., 2003) which should be established for both tools after indirect exposure. However, actual performance may engage a separate system to encode aspects when the observer has no prior physical experience.

Should right hemisphere structures have been only engaged in reconstruction of the environment seen through video exposure, we would have expected to see equal activations for both tools (e.g., twist and push screwdrivers were seen used in the same space in the video). The social cognition theory offers a unique solution to the activations seen in the current work, namely greater right hemisphere activity for the novel tool (push screwdriver) over the familiar tool (twist screwdriver). In this case, we suggest that the unique context applied to a familiar movement was the factor that engaged the right hemisphere social cognition network. This conceptualization suggests a potential for studies investigating new motor tasks and behavioral goals on the social cognition and mirror neuron systems. An example may be to evaluate learning multiple functions of a single tool to test for action-related versus outcome-related encoding of the new functions using a mirroring versus social cognition model. As well, the engagement of different perspectives of video learning (allocentric, egocentric, and other angled perspectives) may alter this process (Shmuelof & Zohary, 2008; Lamm, Batson, & Decety, 2007) and require advanced processing for the transformation of seen action into real action (Handy, Grafton, Shroff, Ketay, & Gazzaniga, 2003). Furthermore, the systematic evaluation of tool-learning related to these processes is also warranted (Serrien, Ivry, & Swinnen, 2006). Behavioral correlates of learning were not studied in the present work, as we did not evaluate customary learning-based motor control. Future investigations will focus on evaluating learning-based improvements in motor performance, which represent skill acquisition.

Right Hemisphere and Imitation

An alternative view is that the right hemisphere activation seen after indirect training of the unfamiliar tool is likened to activity in the right intraparietal sulcus related to visuospatial components of a gesture that is about to be reproduced (Hermsdorfer et al., 2001). This idea was elaborated further by demonstrating that the right parietal areas are substrates for imitation that identify visuospatial and not motoric features of an upcoming movement (Chaminade, Meltzoff, & Decety, 2005). In our study, this should correlate to both tools in the indirect exposure conditions. Our results show this right hemispheric effect only for the novel push-style screwdriver (Figure 6) suggesting that the type of tool being pantomimed may matter. It is possible that the visuospatial encoding of the movement seen in the studies mentioned above is mediated by the mechanisms of mirroring and social cognition. This remains to be seen in further, more specific studies that might engage broader sets of familiar and unfamiliar tool use and communicative gestures, and nonsymbolic movements.

Laterality

The within condition laterality analysis largely supported the expected effects on based on the tool and exposure type. Overall, most activations seen were strongly left lateralized. Indirect exposure seemed to generate this left lateralized activation at different areas based on tool type. Twist pantomime generated strong left frontal (but not parietal) laterality, perhaps similar to findings of left frontal laterality of recognition systems related to tool pantomime recognition compared with meaningless gestures (Villarreal et al., 2008). The left parietal laterality for indirect exposure to the push screwdriver remains to be explored. As this left lateralized activation was not greater than indirect twist (Figure 6) it suggests a relative weakness of this activity.

Exceptions to the left laterality were seen in the direct exposure conditions, as right frontal dominance after direct exposure of the twist screwdriver was seen. Upon observing the activation mapping of these data, it is readily seen that there is a far right frontal ERD effect in this condition (Figure 3) that may affect the laterality seen here. Right temporo-parietal-frontal electrodes demonstrate strong right laterality for direct exposure of the push screwdriver. This is clearly represented in the activation maps and perhaps suggests an aspect of novelty in pantomime of the new tool (i.e., a pantomime that has never before been performed by the subject). Such right laterality is not unfounded, as prior studies point to right lateralization for tools that are not frequently used (Vingerhoets, 2008).

Conclusion

Activation and laterality analyses suggest some engagement of left hemisphere areas in pantomime to tools based on novelty of tool and how one is exposed to the tool. However, further analysis showed key activation dependencies on tool familiarity and exposure types. To account for these activation differences, we suggest involvement of the canonical tool network for pantomime following direct exposure to a tool, and of the potential involvement of mirror neuron and social cognition networks following indirect exposure to familiar and unfamiliar tools, respectively. Direct exposure better engages the traditional tool use network perhaps through motor template establishment and kinesthetic feedback required to perform the pantomime as though one is actually engaged in tool use. However, neither motor templates nor kinesthetic feedback are available following indirect exposure. In this case, the mirror neuron system may become active to reproduce an observed familiar tool-related movement (e.g., motor, sensory and contextual elements are previously established). Alternatively, it may also involve simple recall of the existing action representation for the tool. To reproduce an observed unfamiliar tool-related movement, the social cognition network engages to derive an understanding of the motor, sensory and contextual elements related to actual use of the tool rather than a precise action representation. These results point to neural mechanisms of tool learning that may be helpful in establishing neural activity for new tool functions. Although applicable to normal learning of tool use in adulthood, this finding impels more investigation into neural mechanisms of tool learning during development and how exposure style may affect tool-related tasks after neural injury.

Acknowledgments

We thank the Atlanta Center for Behavioral Neuroscience BRAIN program, which receives funding from the National Institute of General Medical Sciences (R01GM085391-02), and the National Science Foundation (IBN-9876754).

Reprint requests should be sent to Lewis A. Wheaton, Cognitive Motor Control Laboratory, School of Applied Physiology, Georgia Institute of Technology, 281 Ferst Dr., Atlanta, GA 30332-0356, or via e-mail: Lewis.wheaton@ap.gatech.edu.

REFERENCES

Allison
,
T.
,
Puce
,
A.
, &
McCarthy
,
G.
(
2000
).
Social perception from visual cues: Role of the STS region.
Trends in Cognitive Sciences
,
4
,
267
278
.
Beauchamp
,
M. S.
,
Lee
,
K. E.
,
Haxby
,
J. V.
, &
Martin
,
A.
(
2002
).
Parallel visual motion processing streams for manipulable objects and human movements.
Neuron
,
34
,
149
159
.
Bohlhalter
,
S.
,
Hattori
,
N.
,
Wheaton
,
L.
,
Fridman
,
E.
,
Shamim
,
E. A.
,
Garraux
,
G.
,
et al
(
2009
).
Gesture subtype-dependent left lateralization of praxis planning: An event-related fMRI study.
Cerebral Cortex
,
19
,
1256
1262
.
Buccino
,
G.
,
Binkofski
,
F.
,
Fink
,
G. R.
,
Fadiga
,
L.
,
Fogassi
,
L.
,
Gallese
,
V.
,
et al
(
2001
).
Action observation activates premotor and parietal areas in a somatotopic manner: An fMRI study.
European Journal of Neuroscience
,
13
,
400
404
.
Buccino
,
G.
,
Vogt
,
S.
,
Ritzl
,
A.
,
Fink
,
G. R.
,
Zilles
,
K.
,
Freund
,
H. J.
,
et al
(
2004
).
Neural circuits underlying imitation learning of hand actions: An event-related fMRI study.
Neuron
,
42
,
323
334
.
Buxbaum
,
L. J.
,
Kyle
,
K. M.
,
Tang
,
K.
, &
Detre
,
J. A.
(
2006
).
Neural substrates of knowledge of hand postures for object grasping and functional object use: Evidence from fMRI.
Brain Research
,
1117
,
175
185
.
Cattaneo
,
L.
, &
Rizzolatti
,
G.
(
2009
).
The mirror neuron system.
Archives of Neurology
,
66
,
557
560
.
Chaminade
,
T.
,
Meltzoff
,
A. N.
, &
Decety
,
J.
(
2005
).
An fMRI study of imitation: Action representation and body schema.
Neuropsychologia
,
43
,
115
127
.
Chao
,
L. L.
,
Weisberg
,
J.
, &
Martin
,
A.
(
2002
).
Experience-dependent modulation of category-related cortical activity.
Cerebral Cortex
,
12
,
545
551
.
Choi
,
S. H.
,
Na
,
D. L.
,
Kang
,
E.
,
Lee
,
K. M.
,
Lee
,
S. W.
, &
Na
,
D. G.
(
2001
).
Functional magnetic resonance imaging during pantomiming tool use gestures.
Experimental Brain Research
,
139
,
311
317
.
Creem
,
S. H.
, &
Proffitt
,
D. R.
(
2001
).
Grasping objects by their handles: A necessary interaction between cognition and action.
Journal of Experimental Psychology: Human Perception and Performance
,
27
,
218
228
.
Creem-Regehr
,
S. H.
(
2009
).
Sensory-motor and cognitive functions of the human posterior parietal cortex involved in manual actions.
Neurobiology of Learning and Memory
,
91
,
166
171
.
Creem-Regehr
,
S. H.
,
Dilda
,
V.
,
Vicchrilli
,
A. E.
,
Federer
,
F.
, &
Lee
,
J. N.
(
2007
).
The influence of complex action knowledge on representations of novel graspable objects: Evidence from functional magnetic resonance imaging.
Journal of the International Neuropsychological Society
,
13
,
1009
1020
.
Deeny
,
S. P.
,
Haufler
,
A. J.
,
Saffer
,
M.
, &
Hatfield
,
B. D.
(
2009
).
Electroencephalographic coherence during visuomotor performance: A comparison of cortico-cortical communication in experts and novices.
Journal of Motor Behavior
,
41
,
106
116
.
Efron
,
B.
(
1981
).
Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods.
Biometrika
,
68
,
589
599
.
Fiehler
,
K.
,
Burke
,
M.
,
Engel
,
A.
,
Bien
,
S.
, &
Rosler
,
F.
(
2008
).
Kinesthetic working memory and action control within the dorsal stream.
Cerebral Cortex
,
18
,
243
253
.
Fridman
,
E. A.
,
Immisch
,
I.
,
Hanakawa
,
T.
,
Bohlhalter
,
S.
,
Waldvogel
,
D.
,
Kansaku
,
K.
,
et al
(
2006
).
The role of the dorsal stream for gesture production.
Neuroimage
,
29
,
417
428
.
Goldenberg
,
G.
,
Hermsdorfer
,
J.
,
Glindemann
,
R.
,
Rorden
,
C.
, &
Karnath
,
H. O.
(
2007
).
Pantomime of tool use depends on integrity of left inferior frontal cortex.
Cerebral Cortex
,
17
,
2769
2776
.
Goldenberg
,
G.
, &
Karnath
,
H. O.
(
2006
).
The neural basis of imitation is body part specific.
Journal of Neuroscience
,
26
,
6282
6287
.
Grafton
,
S. T.
,
Arbib
,
M. A.
,
Fadiga
,
L.
, &
Rizzolatti
,
G.
(
1996
).
Localization of grasp representations in humans by positron emission tomography. 2. Observation compared with imagination.
Experimental Brain Research
,
112
,
103
111
.
Haaland
,
K. Y.
,
Harrington
,
D. L.
, &
Knight
,
R. T.
(
2000
).
Neural representations of skilled movement.
Brain
,
123
,
2306
2313
.
Halsband
,
U.
, &
Lange
,
R. K.
(
2006
).
Motor learning in man: A review of functional and clinical studies.
Journal of Physiology (Paris)
,
99
,
414
424
.
Hamzei
,
F.
,
Rijntjes
,
M.
,
Dettmers
,
C.
,
Glauche
,
V.
,
Weiller
,
C.
, &
Buchel
,
C.
(
2003
).
The human action recognition system and its relationship to Broca's area: An fMRI study.
Neuroimage
,
19
,
637
644
.
Handy
,
T. C.
,
Grafton
,
S. T.
,
Shroff
,
N. M.
,
Ketay
,
S.
, &
Gazzaniga
,
M. S.
(
2003
).
Graspable objects grab attention when the potential for action is recognized.
Nature Neuroscience
,
6
,
421
427
.
Haslinger
,
B.
,
Erhard
,
P.
,
Altenmuller
,
E.
,
Schroeder
,
U.
,
Boecker
,
H.
, &
Ceballos-Baumann
,
A. O.
(
2005
).
Transmodal sensorimotor networks during action observation in professional pianists.
Journal of Cognitive Neuroscience
,
17
,
282
293
.
Hermsdorfer
,
J.
,
Goldenberg
,
G.
,
Wachsmuth
,
C.
,
Conrad
,
B.
,
Ceballos-Baumann
,
A. O.
,
Bartenstein
,
P.
,
et al
(
2001
).
Cortical correlates of gesture processing: Clues to the cerebral mechanisms underlying apraxia during the imitation of meaningless gestures.
Neuroimage
,
14
,
149
161
.
Hermsdorfer
,
J.
,
Hentze
,
S.
, &
Goldenberg
,
G.
(
2006
).
Spatial and kinematic features of apraxic movement depend on the mode of execution.
Neuropsychologia
,
44
,
1642
1652
.
Hermsdorfer
,
J.
,
Terlinden
,
G.
,
Muhlau
,
M.
,
Goldenberg
,
G.
, &
Wohlschlager
,
A. M.
(
2007
).
Neural representations of pantomimed and actual tool use: Evidence from an event-related fMRI study.
Neuroimage
,
36
(Suppl. 2),
T109
T118
.
Iacoboni
,
M.
,
Koski
,
L. M.
,
Brass
,
M.
,
Bekkering
,
H.
,
Woods
,
R. P.
,
Dubeau
,
M. C.
,
et al
(
2001
).
Reafferent copies of imitated actions in the right superior temporal cortex.
Proceedings of the National Academy of Sciences, U.S.A.
,
98
,
13995
13999
.
Ishai
,
A.
,
Ungerleider
,
L. G.
,
Martin
,
A.
, &
Haxby
,
J. V.
(
2000
).
The representation of objects in the human occipital and temporal cortex.
Journal of Cognitive Neuroscience
,
12
(Suppl. 2),
35
51
.
Johnson-Frey
,
S. H.
(
2003
).
What's so special about human tool use?
Neuron
,
39
,
201
204
.
Johnson-Frey
,
S. H.
(
2004
).
The neural bases of complex tool use in humans.
Trends in Cognitive Sciences
,
8
,
71
78
.
Johnson-Frey
,
S. H.
,
Newman-Norlund
,
R.
, &
Grafton
,
S. T.
(
2005
).
A distributed left hemisphere network active during planning of everyday tool use skills.
Cerebral Cortex
,
15
,
681
695
.
Keysers
,
C.
,
Kohler
,
E.
,
Umilta
,
M. A.
,
Nanetti
,
L.
,
Fogassi
,
L.
, &
Gallese
,
V.
(
2003
).
Audiovisual mirror neurons and action recognition.
Experimental Brain Research
,
153
,
628
636
.
Kilner
,
J. M.
,
Marchant
,
J. L.
, &
Frith
,
C. D.
(
2009
).
Relationship between activity in human primary motor cortex during action observation and the mirror neuron system.
PLoS One
,
4
,
e4925
.
Kohler
,
E.
,
Keysers
,
C.
,
Umilta
,
M. A.
,
Fogassi
,
L.
,
Gallese
,
V.
, &
Rizzolatti
,
G.
(
2002
).
Hearing sounds, understanding actions: Action representation in mirror neurons.
Science
,
297
,
846
848
.
Kroliczak
,
G.
, &
Frey
,
S. H.
(
2009
).
A common network in the left cerebral hemisphere represents planning of tool use pantomimes and familiar intransitive gestures at the hand-independent level.
Cerebral Cortex
,
19
,
2396
2410
.
Lamm
,
C.
,
Batson
,
C. D.
, &
Decety
,
J.
(
2007
).
The neural substrate of human empathy: Effects of perspective-taking and cognitive appraisal.
Journal of Cognitive Neuroscience
,
19
,
42
58
.
Lewis
,
J. W.
(
2006
).
Cortical networks related to human use of tools.
Neuroscientist
,
12
,
211
231
.
Margulis
,
E. H.
,
Mlsna
,
L. M.
,
Uppunda
,
A. K.
,
Parrish
,
T. B.
, &
Wong
,
P. C.
(
2009
).
Selective neurophysiologic responses to music in instrumentalists with different listening biographies.
Human Brain Mapping
,
30
,
267
275
.
Massen
,
C.
, &
Prinz
,
W.
(
2009
).
Movements, actions and tool use actions: An ideomotor approach to imitation.
Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences
,
364
,
2349
2358
.
Menz
,
M. M.
,
McNamara
,
A.
,
Klemen
,
J.
, &
Binkofski
,
F.
(
2009
).
Dissociating networks of imitation.
Human Brain Mapping
,
30
,
3339
3350
.
Murata
,
A.
,
Fadiga
,
L.
,
Fogassi
,
L.
,
Gallese
,
V.
,
Raos
,
V.
, &
Rizzolatti
,
G.
(
1997
).
Object representation in the ventral premotor cortex (area F5) of the monkey.
Journal of Neurophysiology
,
78
,
2226
2230
.
Naito
,
E.
, &
Ehrsson
,
H. H.
(
2006
).
Somatic sensation of hand-object interactive movement is associated with activity in the left inferior parietal cortex.
Journal of Neuroscience
,
26
,
3783
3790
.
Neuper
,
C.
,
Scherer
,
R.
,
Wriessnegger
,
S.
, &
Pfurtscheller
,
G.
(
2009
).
Motor imagery and action observation: Modulation of sensorimotor brain rhythms during mental control of a brain-computer interface.
Clinical Neurophysiology
,
120
,
239
247
.
Pascual-Marqui
,
R. D.
(
2002
).
Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details.
Methods & Findings in Experimental & Clinical Pharmacology
,
24(Suppl. D)
,
5
12
.
Peigneux
,
P.
,
Van der Linden
,
M.
,
Garraux
,
G.
,
Laureys
,
S.
,
Degueldre
,
C.
,
Aerts
,
J.
,
et al
(
2004
).
Imaging a cognitive model of apraxia: The neural substrate of gesture-specific cognitive processes.
Human Brain Mapping
,
21
,
119
142
.
Pelphrey
,
K. A.
, &
Morris
,
J. P.
(
2006
).
Brain mechanisms for interpreting the actions of others from biological-motion cues.
Current Directions in Psychological Science
,
15
,
136
140
.
Pelphrey
,
K. A.
,
Morris
,
J. P.
, &
McCarthy
,
G.
(
2004
).
Grasping the intentions of others: The perceived intentionality of an action influences activity in the superior temporal sulcus during social perception.
Journal of Cognitive Neuroscience
,
16
,
1706
1716
.
Pfurtscheller
,
G.
(
2001
).
Functional brain imaging based on ERD/ERS.
Vision Research
,
41
,
1257
1260
.
Pfurtscheller
,
G.
,
Scherer
,
R.
,
Leeb
,
R.
,
Keinrath
,
C.
,
Neuper
,
C.
,
Lee
,
F.
,
et al
(
2007
).
Viewing moving objects in virtual reality can change the dynamics of sensorimotor EEG rhythms.
Presence
,
16
,
111
118
.
Pfurtscheller
,
G.
,
Stancak
,
A.
, Jr., &
Edlinger
,
G.
(
1997
).
On the existence of different types of central beta rhythms below 30 Hz.
Electroencephalography and Clinical Neurophysiology
,
102
,
316
325
.
Quallo
,
M. M.
,
Price
,
C. J.
,
Ueno
,
K.
,
Asamizuya
,
T.
,
Cheng
,
K.
,
Lemon
,
R. N.
,
et al
(
2009
).
Gray and white matter changes associated with tool use learning in macaque monkeys.
Proceedings of the National Academy of Sciences, U.S.A.
,
106
,
18379
18384
.
Rizzolatti
,
G.
,
Fogassi
,
L.
, &
Gallese
,
V.
(
1997
).
Parietal cortex: From sight to action.
Current Opinion in Neurobiology
,
7
,
562
567
.
Rizzolatti
,
G.
,
Fogassi
,
L.
, &
Gallese
,
V.
(
2001
).
Neurophysiological mechanisms underlying the understanding and imitation of action.
Nature Reviews Neuroscience
,
2
,
661
670
.
Rizzolatti
,
G.
, &
Sinigaglia
,
C.
(
2010
).
The functional role of the parieto-frontal mirror circuit: Interpretations and misinterpretations.
Nature Reviews Neuroscience
,
11
,
264
274
.
Senkfor
,
A. J.
(
2008
).
Memory for pantomimed actions versus actions with real objects.
Cortex
,
44
,
820
833
.
Serrien
,
D. J.
,
Ivry
,
R. B.
, &
Swinnen
,
S. P.
(
2006
).
Dynamics of hemispheric specialization and integration in the context of motor control.
Nature Reviews Neuroscience
,
7
,
160
166
.
Shmuelof
,
L.
, &
Zohary
,
E.
(
2008
).
Mirror-image representation of action in the anterior parietal cortex.
Nature Neuroscience
,
11
,
1267
1269
.
Van Overwalle
,
F.
, &
Baetens
,
K.
(
2009
).
Understanding others' actions and goals by mirror and mentalizing systems: A meta-analysis.
Neuroimage
,
48
,
564
584
.
Villarreal
,
M.
,
Fridman
,
E. A.
,
Amengual
,
A.
,
Falasco
,
G.
,
Gerscovich
,
E. R.
,
Ulloa
,
E. R.
,
et al
(
2008
).
The neural substrate of gesture recognition.
Neuropsychologia
,
46
,
2371
2382
.
Vingerhoets
,
G.
(
2008
).
Knowing about tools: Neural correlates of tool familiarity and experience.
Neuroimage
,
40
,
1380
1391
.
Weisberg
,
J.
,
van Turennout
,
M.
, &
Martin
,
A.
(
2007
).
A neural system for learning about object function.
Cerebral Cortex
,
17
,
513
521
.
Wheatley
,
T.
,
Milleville
,
S. C.
, &
Martin
,
A.
(
2007
).
Understanding animate agents: Distinct roles for the social network and mirror system.
Psychological Science
,
18
,
469
474
.
Wheaton
,
L.
,
Fridman
,
E.
,
Bohlhalter
,
S.
,
Vorbach
,
S.
, &
Hallett
,
M.
(
2009
).
Left parietal activation related to planning, executing and suppressing praxis hand movements.
Clinical Neurophysiology
,
120
,
980
986
.
Wheaton
,
L. A.
,
Nolte
,
G.
,
Bohlhalter
,
S.
,
Fridman
,
E.
, &
Hallett
,
M.
(
2005
).
Synchronization of parietal and premotor areas during preparation and execution of praxis hand movements.
Clinical Neurophysiology
,
116
,
1382
1390
.
Wheaton
,
L. A.
,
Shibasaki
,
H.
, &
Hallett
,
M.
(
2005
).
Temporal activation pattern of parietal and premotor areas related to praxis movements.
Clinical Neurophysiology
,
116
,
1201
1212
.
Wheaton
,
L. A.
,
Yakota
,
S.
, &
Hallett
,
M.
(
2005
).
Posterior parietal negativity preceding self-paced praxis movements.
Experimental Brain Research
,
163
,
535
539
.
Wyk
,
B. C.
,
Hudac
,
C. M.
,
Carter
,
E. J.
,
Sobel
,
D. M.
, &
Pelphrey
,
K. A.
(
2009
).
Action understanding in the superior temporal sulcus region.
Psychological Science
,
20
,
771
777
.