Mirror neurons, the representation of word meaning, and the foot of the third left frontal convolution

Brain & Language 112 (2010) 77–84

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Mirror neurons, the representation of word meaning, and the foot of the third left frontal convolution Greig de Zubicaray a,*, Natasha Postle b, Katie McMahon a, Matthew Meredith a, Roderick Ashton b a b

Functional MRI Laboratory, Centre for Magnetic Resonance, University of Queensland, Brisbane, Qld. 4072, Australia School of Psychology, University of Queensland, Brisbane, Qld., Australia

a r t i c l e

i n f o

Article history: Accepted 29 September 2008 Available online 1 November 2008 Keywords: Broca’s area Language comprehension Mirror neurons Action observation Imitation Semantics Phonology

a b s t r a c t Previous neuroimaging research has attempted to demonstrate a preferential involvement of the human mirror neuron system (MNS) in the comprehension of effector-related action word (verb) meanings. These studies have assumed that Broca’s area (or Brodmann’s area 44) is the homologue of a monkey premotor area (F5) containing mouth and hand mirror neurons, and that action word meanings are shared with the mirror system due to a proposed link between speech and gestural communication. In an fMRI experiment, we investigated whether Broca’s area shows mirror activity solely for effectors implicated in the MNS. Next, we examined the responses of empirically determined mirror areas during a language perception task comprising effector-specific action words, unrelated words and nonwords. We found overlapping activity for observation and execution of actions with all effectors studied, i.e., including the foot, despite there being no evidence of foot mirror neurons in the monkey or human brain. These ‘‘mirror” areas showed equivalent responses for action words, unrelated words and nonwords, with all of these stimuli showing increased responses relative to visual character strings. Our results support alternative explanations attributing mirror activity in Broca’s area to covert verbalisation or hierarchical linearisation, and provide no evidence that the MNS makes a preferential contribution to comprehending action word meanings. Ó 2008 Elsevier Inc. All rights reserved.

1. Introduction At the foot of the third left frontal convolution of the human cerebral cortex is a region whose role in language remains controversial almost a century and a half after it was first proposed. This region, called Broca’s area after the French neurologist who first proposed a role for it in articulate speech, is now referred to more generally in terms of its cytoarchitecture as Brodmann’s area 44 (BA44; sometimes referred to as encompassing areas 44 and 45; Hagoort, 2005). Theoretical perspectives of Broca’s area have changed considerably in recent years, informed by the results of neuroimaging studies indicating BA44 is active when subjects observe actions performed by both the mouth and hand (e.g., Baumgaertner, Buccino, Lange, McNamara, & Binkofski, 2007; Binkofski et al., 2000; Buccino, Binkofski, & Riggio, 2004a; Buccino et al., 2004b; Iacoboni et al., 1999; Molnar-Szakacs, Iacoboni, Koski, & Mazziotta, 2005; Nishitani & Hari, 2002; for reviews, see Binkofski & Buccino, 2006; Iacoboni, 2005; Nishitani, Schurmann, Amunts, & Hari, 2005; Rizzolatti & Craighero, 2004). The neuroimaging investigations of the visuomotor properties of human BA44 were prompted by comparative neuroanatomy studies revealing * Corresponding author. Fax: +61 7 3365 3833. E-mail address: [email protected] (G. de Zubicaray). 0093-934X/$ - see front matter Ó 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.bandl.2008.09.011

it to have apparently similar cytoarchitectonic characteristics to premotor area F5 in the macaque monkey (Nelissen, Luppino, Vanduffel, Rizzolatti, & Orban, 2005; but see Petrides, 2005; for a critique of this evidence, see Toni, de Lange, Noordzij, & Hagoort, 2008). As area F5 contains a class of visuomotor neurons (called mirror neurons) that respond congruently when goal-directed mouth or hand actions are both observed and executed, some authors have proposed that it (and its putative human homologue BA44) might transform visual information into knowledge coded at an abstract level, i.e., it might be involved in understanding the action meaning (Nishitani et al., 2005; Rizzolatti & Craighero, 2004). A corollary to this theory is that the mirror neuron system (MNS) in Broca’s area might represent a mechanism linking speech and gestural communication (Arbib, 2005; Gallese & Lakoff, 2005; Gentilucci & Corballis, 2006; Nishitani et al., 2005; Rizzolatti & Arbib, 1998). At least two alternative explanations have been proposed for the activity elicited in BA44 when actions are observed. The first is referred to as the ‘‘verbalization hypothesis” (see Buccino et al., 2001; Grèzes & Decety, 2001; Iacoboni, 2005; Iacoboni & Dapretto, 2006). This explanation acknowledges a role for Broca’s area in speech production and proposes that the activity reflects an internal verbalization of the observed actions; similar to the activity detected during verbally instructed motor preparation

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Fig. 1. Left: Fig. 3a from Buccino et al. (2001; p. 402) depicting left hemisphere cortical activity elicited by observing foot actions such as those mimicking ball-kicking or brake-pushing. Reproduced with permission of the publisher Wiley-Blackwell. Right: A similar rendering depicting the cytoarchitectonic maximum probability map (MPM) of Broca’s area from Eickhoff et al. (2006).

(see Heyes, 2001). The second explanation attributes the activity to delayed motor execution (Makuuchi, 2005). According to Makuuchi (2005), visuomotor transformations, and therefore imitation, are not required by most observe-then-execute tasks as subjects continuously observe and then perform the same movement (e.g., Iacoboni et al., 1999). That is, subjects might use the information repeated in the observation task as a cue when to respond rather than as a specification of what movement to perform. According to this account, subjects could simply perform the requisite movements using the motor program they had learned on the first observation (see also Turella, Pierno, Tubaldi, & Castiello, 2008). The role of Broca’s area in these tasks would then be essentially one of sequencing rather than imitation (Makuuchi, 2005). Prior to Rizzolatti and Arbib’s (1998) conjecture concerning the linguistic relevance of the MNS, sequencing (or the hierarchical linearisation of information) was considered Broca’s area’s primary contribution to language (e.g., Greenfield, 1992; Wilkins & Wakefield, 1995). If the verbalisation or sequencing hypotheses are correct, Broca’s area should show activity during action observation irrespective of the effector being viewed. However, if the activity is due to a mirror mechanism, then only those effectors implicated in the MNS (mouth, hand) should show activity; there being no evidence to date of mirror neurons related to foot actions in monkeys or humans (see Binkofski & Buccino, 2004; Nishitani et al., 2005). As Iacoboni (2005) states succinctly: ‘‘This also means that in an imaging experiment on, say, imitating foot movements, one should not expect to observe activation of BA44, if this activation reflects the motor aspect of BA44, and not its linguistic one.” (p. 89) The study by Buccino et al. (2001) is often cited as evidence supporting the latter contention (e.g., Iacoboni, 2005). Indeed, Buccino et al. interpreted their findings as definitive proof that action observation is not due to verbalisation (p. 403). This is perhaps why MNS neuroimaging studies almost invariably investigate only one effector (e.g., the hand; Baumgaertner et al., 2007; see the meta-analysis by Molnar-Szakacs et al., 2005; or the mouth; Buccino et al., 2004b; Nishitani & Hari, 2002). However, when their subjects were observing foot actions such as those mimicking ball-kicking or brake-pushing, Buccino et al. reported: ‘‘There also was an activation of the frontal lobe (rostrally located). . . Because we have no explanation for this activation. . . we will not comment on it further.” (p. 401). This activation was depicted in their Fig. 3a (reproduced here in Fig. 1). The relevant peak coordinates were omitted from their Table 2 that summarised the activation foci for the entire experiment. As can be seen from Fig. 1, the activation is located within the

vicinity of Broca’s area. The reviews of the MNS literature that often summarise Buccino et al.’s results in detail also tend to omit mention of this activation (e.g., Rizzolatti & Craighero, 2004). The reason why Buccino et al. (2001) omitted this result from further consideration might be that it was elicited by the observation of intransitive actions. In the monkey, MNS activity is typically observed for transitive, goal-directed actions (e.g., grasping an object), although not for intransitive actions. Yet there is considerable evidence that humans do show activity while viewing intransitive actions, and this is attributed to a distinct operation of the human MNS (e.g., Press, Bird, Walsh, & Heyes, 2008; for a review, see Rizzolatti & Craighero, 2004). Consequently, Buccino et al.’s (2001) findings cannot be considered a definitive refutation of the verbalisation hypothesis, and the issue of whether BA44 shows foot ‘‘mirror” activity warrants further investigation. If the human MNS is involved in understanding action meanings, then it seems reasonable to assume that Broca’s area should show preferential activity during the comprehension of action word (i.e., verb) meanings, particularly those pertaining to the mouth and hand. Several neuroimaging studies have investigated this issue (e.g., Aziz-Zadeh, Wilson, Rizzolatti, & Iacoboni, 2006b; Baumgaertner et al., 2007; Hauk, Johnsrude, & Pulvermüller, 2004; Rüschemeyer, Brass, & Friederici, 2007; Tettamanti et al., 2005; Vigliocco et al., 2006) with some interpreting activity in Broca’s area as action-specific (e.g., Baumgaertner et al., 2007; Tettamanti et al., 2005). As the designs of these studies differ, it is worth examining them in some detail.1 Of the three recent studies that used single-word reading, two did not report activity in Broca’s area for comparisons involving comprehension of concrete versus abstract action meanings (Rüschemeyer et al., 2007) or action versus sensory meanings (Vigliocco et al., 2006). The third employed a comparison with visual characters, finding activation in Broca’s area for comprehension of both face-related words and action word meanings irrespective of effector (Hauk et al., 2004). Two studies compared comprehension of action words embedded in similar literal/concrete and metaphorical/abstract sentences and found different results (Aziz-Zadeh et al., 2006b; Tettamanti et al., 2005). Tettamanti et al. (2005) reported significant activity in Broca’s area for concrete versus abstract action sentences both pertaining to the mouth and irrespective of effector, while Aziz-Zadeh et al., 2006b found this activity only for a comparison of all action sentence stimuli (literal and metaphorical, irrespective of effector) with a resting baseline. Moreover, the latter authors were unable to replicate Tettamanti et al.’s finding in Broca’s area, as their contrast of literal and metaphorical sen-

1 Some of these studies have also investigated proposals concerning a somatotopic organisation of action word meanings in primary and premotor cortices. These proposals are beyond the scope of the present paper and are addressed in Postle, et al. (2008).

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tences resulted in only one activation peak in the inferior frontal gyrus (pars orbitalis; BA47), and this was an increase in activation for metaphorical sentences (p. 1820). Another issue, as Rüschemeyer et al. (2007) noted, is that the sentences used in these studies entailed different sentential objects with abstract meanings varying according to the verb used (e.g., in the abstract sentence ‘‘He grasped the idea”, the object noun is also abstract). Thus, the activity reported could be attributable to comprehension of the meaning of the action word, object noun or a combination of the two. More recently, Baumgaertner et al. (2007) reported significant activity in Broca’s area for a comparison involving comprehension of German sentences describing goal-directed hand actions and sentences describing inanimate motion. These sentences also entailed different sentential objects according to condition, with the animate sentences all involving tools (e.g., hammer) while the inanimate sentences were a mixture of natural objects and mediums (e.g., volcano, air), man-made objects (e.g., chimney, boat) and two dimensional planes (e.g., circle, line). In addition, according to the linearisation hypothesis (Bornkessel & Schlesewsky, 2006), BA44 is sensitive to a range of principles determining linear (word) order in a language (see also Dominey & Hoen, 2006; Grodzinsky, 2006). A number of neuroimaging studies have indicated activity in BA44 is influenced by syntactic linearisation principles (e.g., subject- versus object-first; Ben-Shachar, Hendler, Kahn, Ben-Bashat, & Grodzinsky, 2003; Ben-Shachar, Palti, & Grodzinsky, 2004; Bornkessel, Zysset, Friederici, von Cramon, & Schlesewsky, 2005; Grewe et al., 2005) and semantic principles such as animacy (animate-before inanimate; e.g., Chen, Caplan, West, & Waters, 2006; Grewe et al., 2006; Kuperberg, Sitnikova, & Lakshmanan, 2008). Unlike English in which the first argument is always the subject, German is a flexible word order language. In German, animacy influences the order in which noun phrases (NPs) are read, either indirectly by assigning grammatical functions or directly by determining positional placement within sentences (see Kempen & Harbusch, 2004; Müller, 1999). Thus, a comparison of German sentences describing animate and inanimate movements might reveal activity differences due to word order/animacy principles, rather than the comprehension of the action word meaning per se. A final methodological issue concerns the demonstration of overlapping activity in the MNS, including that with language comprehension tasks. As Turella et al. (2008) noted in their review, few neuroimaging studies of the MNS have required their subjects to both observe and execute the same movements with the goal of eliciting overlapping activation in the same region. This is a necessary requirement for exploring ‘‘mirror” activity. The neuroimaging studies cited in support of shared language comprehension and MNS activity have tended to employ only action observation tasks with nameable objects (e.g., Aziz-Zadeh et al., 2006b; Baumgaertner et al., 2007; Meister & Iacoboni, 2007), or tasks with verbally instructed movements (Hauk et al., 2004), or omitted action tasks altogether (e.g., Tettamanti et al., 2005). The present experiment employed a design in which subjects performed a language perception task followed by a task requiring them to both observe and execute actions with each of three effectors (foot, mouth, hand), the latter with the goal of eliciting ‘‘mirror” activity. As we wished to explore whether access to action word meanings was dissociable from more general semantic as well as phonological access in Broca’s area, we compared effector-specific action words with each other as well as words unrelated to body parts and nonwords. This design should enable us to test whether (1) Broca’s area shows ‘‘mirror” activity irrespective of the effector involved (the prediction of the verbalization and sequencing hypotheses), or only for effectors implicated in the MNS (i.e., hand, mouth), and (2) whether the ‘‘mirror” regions

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identified within Broca’s area show preferential or selective activity for the comprehension of action word meanings. 2. Methods 2.1. Participants Seventeen healthy, right-handed volunteers participated, all native speakers of English (5 male, mean age 27.5 years). The study was approved by the University of Queensland’s Medical Research Ethics Committee, and all volunteers provided written informed consent prior to participating. 2.2. Materials For the language task, 75 effector-related verbs comprising 25 each specific to the hand (e.g., grasp), foot (e.g., kick) and mouth (e.g., bite) were selected, along with 25 concrete words unrelated to body parts (e.g., rain) and 25 nonwords (e.g., yuft) from the ARC Nonword Database (Rastle, Harrington, & Coltheart, 2002). A series of six hashes (######) were included as a low-level control for visual character recognition. Word and nonword stimuli were matched as appropriate on a range of variables, including length, syllables, CELEX lexical frequency (Baayen, Piepenbrock, & Gulikers, 1995), orthographic and phonological neighbourhood sizes (Davis, 2005), and imageability (Table 1). Although the unrelated words were all concrete nouns, TMS and neuroimaging studies have demonstrated consistently that the activity elicited in BA44 during reading of single words is not modulated by grammatical class per se (e.g., Bedny & Thompson-Schill, 2006; Cappelletti, Fregni, Shapiro, Pascual-Leone, & Caramazza, 2008; Tyler, Randall, & Stamatakis, 2008; Vigliocco et al., 2006). Both the effector-related and unrelated words were derived from a separate pilot study conducted with 10 native or longstanding English-speakers (mean age 24 years, 3 male). The rating procedure used a five point scale (1 = word does not remind me of this body part at all; 5 = word very much reminds me of this body part). This ensured each effectorrelated word was predominantly associated with its appropriate effector and each unrelated word was not associated with any body part. Each word’s imageability was also rated on a five point scale (1 = not imageable at all; 5 = very imageable). For the ‘‘mirror” task, 10 silent movie clips were generated for each effector (hand, foot, mouth), each depicting simple intransitive actions performed repeatedly for 5 s (e.g., fist clenching, toes curling, lips puckering). Only the relevant body part was visible. An additional 10 movies of equal length were generated of frequently encountered natural and man-made stimuli moving as they would in their natural environments (e.g., ceiling fan rotating slowly, water dripping from a tap, second hand moving around a clock). 2.3. Procedure The language task was administered first, followed by the ‘‘mirror” task, in two separate imaging runs. At the end of the imaging session, a memory task was administered that required subjects to describe the movie stimuli to the experimenter, discriminate the 100 target words from 20 other words (five hand, foot, mouth and unrelated) and discriminate the 25 target nonwords from 25 other nonwords. Subjects were not forewarned that they would be tested. The purpose of this task was to verify that participants attended to the different word meanings and processed all words beyond mere visual perception. For the language task, mini-blocks of five items of each stimulus type were presented consecutively (i.e., hand, foot, mouth, and unrelated words, nonwords and hashes) in pseudorandom order and with a different pseudorandom ordering employed for each

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Table 1 Matching data for word and nonword stimuli. Matching variables Category

Letters

Syllables

Frequency*

Orthographic Neighbours

Phonological Neighbours

Imageability

Effector Association

Mouth

4.76 (1.2) 4.56 (1.08) 4.6 (1.12) 4.6 (1.19) 4.6 (1.19)

1.2 (.41) 1.04 (.2) 1.2 (.41) 1.28 (.46) 1.16 (.37)

80.80 (122.82) 98.56 (134.11) 79.08 (155.86) 115.64 (161.84) NA

6.0 (4.42) 6.0 (5.95) 6.0 (4.87) 7.08 (5.19) NA

16.2 (8.845) 15.4 (9.08) 12.76 (8.3) 16.2 (10.42) NA

4.1 (0.58) 4.11 (0.47) 3.94 (0.67) 3.79 (0.38) NA

4.6 (0.35) 4.48 (0.29) 4.6 (0.27) 0.0 (0.0) NA

Hand Foot Unrelated Nonwords

Notes: Data are means with standard deviations in parentheses. NA, not applicable. * CELEX frequency per million.

subject. Items were presented for 3 s. A resting fixation period of 15 s followed. This sequence was repeated 5 times (i.e., [90 + 15 s]  5 = 525 s). Subjects read the words silently and when the fixation cross or hashes were presented, watched the stimuli without mentally reciting any words. For the ‘‘mirror” task, each movie was repeated for 10 s followed by the presentation of a green or red dot (20 mm diameter) for 10 s, and then a blank screen for 5 s. The green dot always followed effector action movies while the control (mechanical motion) movies were always followed by a red dot. Subjects viewed the movies, then replicated the action of the effector viewed (using their right hand/foot or mouth) while the green dot was presented, or remained motionless following the control movie for the duration of the red dot. Movies were presented in pseudorandom order within and across subjects, continuing until all 40 movie clips had been presented. 2.4. fMRI acquisition A 4T Bruker MedSpec system equipped with a transverse electromagnetic (TEM; Vaughan et al., 2002) head coil was used to acquire whole-brain fMRI data (36 slices, in-plane resolution 3.60  3.60 mm, slice thickness of 3 and 0.6 mm gap) with a gradient echo echo-planar imaging (EPI) sequence sensitive to blood oxygen level dependent (BOLD) signal (TE 30 ms). For the language task, 176 brain volumes were acquired using a TR of 3 s. For the ‘‘mirror” task, 405 brain volumes of identical resolution were acquired with a TR of 2.5 s. The TRs were chosen so that all image volumes were acquired with the same delay from stimulus presentation within each task (the ‘‘time-lock” strategy; see Amaro & Barker, 2006). The first 5 volumes from each run were discarded to allow for T1 equilibration. Distortions in the fMRI data generated by magnetic field inhomogeneities at high-field were corrected using a point-spread mapping function (Zaitsev, Hennig, & Speck, 2003). Within the same session, a high-resolution MP-RAGE 3D T1 structural image was acquired (TI 700, TR 1500, TE 3.35 ms and resolution 0.73 mm3). 2.5. Data analysis The fMRI data were analysed with statistical parametric mapping software (SPM5; Wellcome Department of Imaging Neuroscience, Queen Square, London, UK). For each subject, image volumes were realigned (Freire, Roche, & Mangin 2002), and spatially normalised to MNI atlas space using the linear and nonlinear transformations from their coregistered T1 structural image. The resulting images were resampled to 3 mm3 voxels and smoothed with an 8 mm FWHM isotropic Gaussian kernel. Global signal effects were then estimated and removed using a voxel-level linear model (Macey, Macey, Kumar, & Harper, 2004).

Statistical analysis was performed in two stages corresponding to a mixed effects model. For each subject, two sets of fixed effects analyses were conducted. The first involved regressors for the four observation and three execution conditions of the ‘‘mirror” task, while the second comprised regressors for the six types of stimuli in the language task. The BOLD response to single trials was modelled with a canonical hemodynamic response function (HRF) following Mechelli, Henson, Price, and Friston (2003). A 128 s high pass filter was employed to remove low frequency fluctuations, and serial correlations estimated and removed with an AR(1) model. For the ‘‘mirror” task, the main contrasts of interest involved comparing the movement observation and execution conditions with the control observation condition and fixation/baseline, respectively. Linear contrasts of the parameter estimates were then subjected to one-sample t-tests in a second stage model that treated subjects as a random effect. These contrasts were constrained to voxels within a language dominant left hemisphere search volume using combined cytoarchitectonic maximum probability maps (MPMs; Eickhoff, Heim, Zilles, & Amunts, 2006) of BA44 and 45 (Broca’s area). In order to identify cluster-based regions of interest (ROIs) that demonstrated ‘‘mirror” activity (i.e., overlapping activity for observation and execution of actions) for each effector, the contrast of execution > rest was used to inclusively mask the contrast of effector > control observation using a combined height threshold of p < .001 and cluster threshold of > 25 contiguous voxels. In addition, contrasts for each effector were exclusively masked (at p < .05, uncorrected) with contrasts involving the other two effectors (see Tettamanti et al., 2005 for a similar approach). For example, the mouth > control contrast was exclusively masked with both the hand > control and foot > control contrasts in order to avoid overlapping activity. The mean percent BOLD signals for each of the six language task conditions were then extracted from each of the 3 ‘‘mirror” ROIs using Marsbar software (v0.41; http:// marsbar.sourceforge.net). Activations were rendered on an inflated cortical surface using FreeSurfer (Dale, Fischl, & Sereno, 1999; Fischl, Sereno, & Dale, 1999; http://surfer.nmr.mgh.harvard.edu/) and the SPM surfrend toolbox (written by I. Kahn; http:// spmsurfrend.sourceforge.net).

3. Results 3.1. Main effects of action execution and observation These contrasts (effector execution > rest and effector > control observation) revealed significant activity solely in BA44 that showed good concordance for execution and observation conditions for each effector (Table 2).

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3.2. ‘‘Mirror” effects

foot-related, 6.39 (SD = 2.38) of the mouth-related and 6.22 (SD = 1.93) of the non-action (mechanical motion) movies. They correctly recognised 19.72 (SD = 4.00) of the hand-related, 19.83 (SD = 4.44) of the foot-related, 18.94 (SD = 4.68) of the mouth-related, 19.17 (SD = 5.66) of the body-part-unrelated and 14.33 (SD = 4.77) of the nonwords. ANOVAs revealed no difference in the recall of movie stimuli across conditions (p > .05), nor any differences in recognition among the action and unrelated word stimuli conditions (p < .05).

Inclusively masking the main effect for observation with the main effect for action execution for each effector revealed activation consistent with mirror activity in BA44 (Fig. 2, top). However, exclusively masking each effector’s mirror activity with that of the other two effectors failed to reveal any significant activity specific to any effector. As Fig. 2 shows, this was due to the large amount of overlap among the effectors’ ‘‘mirror” clusters. 3.3. Action word meaning comprehension in ‘‘mirror” regions

3.5. Action word meaning comprehension in ‘‘mirror” regions according to memory performance

Given the lack of specific effector ‘‘mirror” clusters, we defined 10 mm spherical ROIs centred on the peak maxima for overlapping observation and execution activity for each effector in order to identify voxels maximally responsive to each effector. For each ROI, data were extracted according to the stimulus type presented in the language task and entered into repeated measures ANOVAs. Within the mouth ROI, there was no effect of stimulus type, F(5) = 1.06, p = .39 (Fig. 2, bottom left). The effect of stimulus type was significant in the hand ROI, F(5) = 5.19, p < .001 (Fig. 2, bottom middle). This result was further investigated with pairwise t-tests across stimulus types that showed significantly increased activity for all word and nonword stimuli compared to hashes. However, hand words did not show significantly greater activity compared to mouth words, t(16) = .53, p = .60, foot words, t(16) = .85, p = .41, unrelated words, t(16) = 1.2, p = .25, or nonwords, t(16) = 1.44, p = .17. The foot ROI showed a similar effect of stimulus type to the hand ROI, F(5) = 4.27, p < .005 (Fig. 2, bottom right). Pairwise t-tests again showed this effect was driven mainly by significantly greater activity for all word and nonword stimuli relative to hashes, with comparisons between foot and hand words, t(16) = .939, p = .36, mouth words, t(16) = 1.2, p = .11, unrelated words, t(16) = .11, p = .91, and nonwords, t(16) = 1.9, p = .08 failing to reach significance. A final analysis compared activity for generic action words with the other stimulus types following Rizzollati and Craighero’s (2004) proposal that there might be a more general representation of action words in this region (see also Tettamanti et al., 2005). First, ‘‘mirror” activity for combined effectors was identified by inclusively masking a contrast of all effector > control observation conditions with the contrast of all effector movements > rest (see Table 2). Next, data from the combined action word stimuli were extracted from this generic ‘‘mirror” cluster (Fig. 3, left) for comparison with the data from the other stimulus types (Fig. 3, right). The effect of stimulus type within this ROI was significant, F(5) = 4.28, p < .01. Pairwise t-tests revealed this was due to all word and nonword stimuli showing greater activity than hashes. However, action words were not significantly different from unrelated words, t(16) = .42, p = .68, or nonwords, t(16) = 1.24, p = .23.

We conducted an additional analysis on the remembered items from the language task using the same ROIs centred on the peak maxima for overlapping observation and execution activity for each effector. These analyses produced substantially the same pattern of results as the analyses conducted with all of the items (see Supplementary material). 4. Discussion Using fMRI, we examined whether observing and executing effector-specific actions elicits overlapping activity in BA44 consistent with the operation of a proposed human mirror neuron system. Next, we determined whether the identified ‘‘mirror” regions showed preferential activity for the comprehension of action word meanings. We found ‘‘mirror” activity for all effectors investigated, including the foot. These ‘‘mirror” regions did not show dissociable activity during a language perception task in which action words, words unrelated to body parts and nonwords were presented. The results therefore provide support for alternative explanations of ‘‘mirror” activity (e.g., Heyes, 2001; Makuuchi, 2005; cf. Buccino et al., 2001; Iacoboni, 2005), and provide no evidence that the putative human MNS makes a preferential or selective contribution to comprehending action word meanings (cf. Arbib, 2005; Gallese & Lakoff, 2005; Gentilucci & Corballis, 2006; Rizzolatti & Arbib, 1998; Rizzolatti & Craighero, 2004). As Turella et al. (2008) noted in their review, relatively few fMRI investigations of the human MNS have employed both execution and observation tasks in order to satisfy the requirement for identifying ‘‘mirror” activity, and the overwhelming majority of those only examined one effector—the hand. The ‘‘mirror” activity we identified for the hand had a peak ( 57, 12, 24) similar to that reported by Molnar-Szakacs et al. (2005) in their meta-analysis ( 56, 10, 20). Our other ‘‘mirror” results for the mouth and foot can be considered the first such fMRI findings for these effectors, as we were unable to find any previous MNS fMRI studies that had investigated these effectors in BA44 (see also Turella et al., 2008). Of interest, the activity we found was not specific to each effector, as the clusters showed considerable overlap (Fig. 2, top), unlike the relatively reliable somatotopic organisation reported for action observation and execution in the motor cortices (e.g., Postle et al., 2008; Schubotz & von Cramon, 2003). One major limitation of the present study and others that have used observe-then-execute tasks (e.g., Iacoboni et al., 1999) is the potential confounding of

3.4. Memory performance Of the 10 action movies, participants correctly recalled approximately 5.28 (SD = 1.78) of the hand-related, 5.33 (SD = 1.57) of the Table 2 Peak maxima for execution and observation of effector actions in BA44. Effector

Execution Coordinates (x, y, z)

Mouth Hand Foot Combined

60, 57, 48, 57,

9, 9, 3, 6,

12 24 6 27

Observation Cluster (voxels)

Z-score

115 74 73 78

5.73 5.0 5.36 3.9

Coordinates (x, y, z) 54, 57, 57, 51,

9, 9 12, 24 6, 21 9, 12

Cluster (voxels)

Z-score

120 55 103 103

4.72 4.62 4.63 4.77

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Fig. 2. Top (from left to right): ‘‘Mirror” activity in BA44 for the mouth (green), hand (red), and foot (blue) rendered on an inflated cortical surface in MNI atlas space. Bottom (from left to right): Bold signal responses in the mouth, hand, and foot mirror ROIs during the language perception task (with effector-related words coloured accordingly).

Fig. 3. From left to right: ‘‘Mirror” activity in BA44 for all effectors combined (yellow) rendered on an inflated cortical surface in MNI atlas space. Bold signal responses in the combined mirror ROI during the language perception task (with action words coloured accordingly).

activity in the two conditions. It is possible that the activity detected in the observation task reflected motor preparation prior to imitating the movement. Inserting a delay interval between observation and execution would likewise be problematic (see Makuuchi, 2005). In addition, we examined ‘‘mirror” activity in the language dominant left hemisphere for obvious reasons, although it should be noted that a recent fMRI study reported bilateral representation of the human MNS, with stronger ipsilateral activation for the observation of actions (Aziz-Zadeh, Koski, Zaidel, Mazziotta, & Iacoboni, 2006a). This result was based upon a comparison with a resting baseline. When Baumgaertner et al. (2007) used non-action movies (i.e., of mechanical motion) for comparison, only left hemisphere activation was detected. The finding of foot ‘‘mirror” activity corroborates and clarifies Buccino et al.’s (2001) finding of left inferior frontal cortex activation for the observation of intransitive foot movements, a finding that they considered inexplicable. As we mentioned in the Introduction to this paper, there is now considerable evidence

that the proposed human MNS is responsive during the observation and execution of intransitive actions, indicating a potential discontinuity with the monkey MNS (Press et al., 2008; see Rizzolatti & Craighero, 2004). This finding cannot be reconciled easily with the operation of foot mirror neurons, as there is no evidence to date of their existence in the monkey or human brain (see Binkofski & Buccino, 2004). A ramification of this result is that ‘‘mirror” activity in BA44 cannot necessarily be attributed to the operation of a mirror system without the provision of further corroborating evidence. This leaves the so-called verbalisation (Buccino et al., 2001; Grèzes & Decety, 2001; Heyes, 2001) or sequencing (Makuuchi, 2005) hypotheses as viable alternative explanations of ‘‘mirror” effects. While not excluding the former of the two explanations, we favour the latter as we will elaborate below. Consistent with previous studies comparing action with nonaction word comprehension using single-word stimuli (e.g., Rüschemeyer et al., 2007; Vigliocco et al., 2006), we did not find

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evidence of preferential or selective engagement of BA44. However, if we were to restrict our findings and only present responses to action words relative to a low-level baseline such as visual character strings, then we might arrive at a positive result in Broca’s area similar to that of previous studies investigating the MNS and language (e.g., Hauk et al., 2004). A broader and more balanced perspective is provided by the comparisons within each effector ROI with the other effector-related words (especially with the foot action words, given the absence of evidence for foot mirror neurons), unrelated words and nonwords. These comparisons show, quite clearly, that the BA44 ‘‘mirror” regions show equivalent responses to all word and nonword stimuli, i.e., there is no selectivity or preferential activation for the comprehension of action word meanings. It could be argued that single-word reading does not necessarily involve automatic semantic access according to some models of reading aloud, and instead relies on a faster orthographic-phonological route (e.g., Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001), although it does in others (e.g., Hillis & Caramazza, 1995; Plaut, McClelland, Seidenberg, & Patterson, 1996). However, previous fMRI studies that used semantic matching paradigms likewise failed to detect activity in Broca’s area for comparisons of action words with non-action words (e.g., Kable, Lease-Spellmeyer, & Chatterjee, 2002; Noppeney, Josephs, Kiebel, Friston, & Price, 2005), although comparisons with a low-level baseline involving character strings from the Wingdings font did result in such activity (e.g., for running and cutting verbs; Kemmerer, Castillo, Talavage, Patterson, & Wiley, 2008), perhaps because the latter condition did not require grapheme–phoneme conversion or lexical access. Nor do design issues appear responsible, as previous studies also used blocks of single-word stimuli (e.g., Vigliocco et al., 2006) with equivalent or fewer items per condition (e.g., 23 action words; Rüschemeyer et al., 2007). Hence, we interpret the available evidence as indicating that the comprehension of single action word meanings does not engage BA44 in a preferential manner. Nevertheless, our null results in terms of preferential representation of action meanings in BA44 might be considered compatible with an MNS-language mechanism on two counts: First, following event structure approaches to verb meaning (e.g., Pustejovsky, 1991), BA44 might only be engaged when accessing aspects of action representation that involve the goals and intentions of agents. If this is the case, then one would not necessarily expect to observe preferential activity in BA44 during reading of single action words (see Kemmerer & Castillo, 2010). This account suggests that sentence comprehension tasks are more likely to entail processing of verb meanings related to event structures. The challenge to this account is to differentiate event meanings from their syntactic behaviours given the evidence concerning Broca’s area’s involvement in syntactic operations (e.g., Bornkessel & Schlesewsky, 2006; Dominey & Hoen, 2006; Grodzinsky, 2006).2 Second, it might be proposed that the comprehension of word meanings per se will elicit activation in the ‘‘mirror” system consistent with a more general role in language, a possibility that Rüschemeyer et al. (2007) entertained. This explanation has the disadvantage of negating previous attempts to demonstrate preferential hand or mouth action word meaning related activity in Broca’s area (e.g., Baumgaertner et al., 2007; Tettamanti et al., 2005). Despite these alternative explanations, there is still the issue that Broca’s area is responsive to many more classes of

2 It is possible that subjects comprehend single action words in the imperative form as an instruction or command (e.g., ‘‘sit!”; see Postle et al., 2008). This reflects the use of the verb in its simplest, unmarked form. If this is the case, then some limited event structure information could be accessed (e.g., the agent being the reader).

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stimuli than just meaningful words. For example, our results indicate that nonwords activate BA44 to a similar extent to meaningful words, consistent with much prior research (for a review, see Snyder, Feigenson, & Thompson-Schill, 2007). Several studies have demonstrated that the activity elicited by nonwords in Broca’s area probably reflects sequencing of phonemes rather than phonological processing per se (e.g., Gelfand & Bookheimer, 2003; Snyder et al., 2007). In addition, it has been shown that Broca’s aphasics have a general difficulty with phoneme assembly that contributes to their impaired reading of verbs with regular past tenses (e.g., Braber, Patterson, Ellis, & Lambon Ralph, 2005). We therefore interpret our results as being consistent with theoretical perspectives that attribute to Broca’s area a role of sequencing or hierarchical linearisation of information across action and linguistic domains (e.g., Bornkessel & Schlesewsky, 2006; Dominey & Hoen, 2006; Fiebach & Schubotz, 2006; Greenfield, 1992; Grodzinsky, 2006; Hagoort, 2005; Koechlin & Jubault, 2006; Makuuchi, 2005; Wilkins & Wakefield, 1995). According to these accounts, Broca’s area shares functionality with the rest of prefrontal cortex that has a primary role in processing hierarchical action representations (e.g., Botvinick, 2008; see Dominey & Hoen, 2006; Fiebach & Schubotz, 2006; Hagoort, 2005; Koechlin & Jubault, 2006). In this respect, our results can be interpreted as supporting the long-held view of an association between language and motor systems (see Fischer & Zwaan, 2008; Willems & Hagoort, 2007). However, they provide no evidence that the putative human MNS makes a preferential or selective contribution to comprehending action word meanings (cf. Arbib, 2005; Gallese & Lakoff, 2005; Gentilucci & Corballis, 2006; Rizzolatti & Arbib, 1998; Rizzolatti & Craighero, 2004). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.bandl.2008.09.011. References Amaro, E., & Barker, G. (2006). Study design in fMRI: Basic principles. Brain and Cognition, 60, 220–232. Arbib, M. A. (2005). From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics. Behavioral and Brain Sciences, 28, 105–167. Aziz-Zadeh, L., Koski, L., Zaidel, E., Mazziotta, J., & Iacoboni, M. (2006a). Lateralization of the human mirror neuron system. Journal of Neuroscience, 26, 2964–2970. Aziz-Zadeh, L., Wilson, S. M., Rizzolatti, G., & Iacoboni, M. (2006b). Congruent embodied representations for visually presented actions and linguistic phrases describing actions. Current Biology, 16, 1818–1823. Baayen, R. H., Piepenbrock, R., & Gulikers, L. (1995). The CELEX lexical database [CDROM]. Philadelphia: Linguistic Data Consortium, University of Pennsylvania. Baumgaertner, A., Buccino, G., Lange, R., McNamara, A., & Binkofski, F. (2007). Polymodal conceptual processing of human biological actions in the left inferior frontal lobe. European Journal of Neuroscience, 25, 881–889. Bedny, M., & Thompson-Schill, S. L. (2006). Neuroanatomically separable effects of imageability and grammatical class during single-word comprehension. Brain and Language, 98, 127–139. Ben-Shachar, M., Hendler, T., Kahn, I., Ben-Bashat, D., & Grodzinsky, Y. (2003). The neural reality of syntactic transformations: Evidence from functional magnetic resonance imaging. Psychological Science, 14, 433–440. Ben-Shachar, M., Palti, D., & Grodzinsky, Y. (2004). Neural correlates of syntactic movement: Converging evidence from two fMRI experiments. NeuroImage, 21, 1320–1336. Binkofski, F., Amunts, K., Stephan, K. M., Posse, S., Schormann, T., Freund, H.-J., et al. (2000). Broca’s region subserves imagery of motion: A combined cytoarchitectonic and fMRI study. Human Brain Mapping, 11, 273–285. Binkofski, F., & Buccino, G. (2004). Motor functions of Broca’s region. Brain and Language, 89, 362–369. Binkofski, F., & Buccino, G. (2006). The role of ventral premotor cortex in action execution and action understanding. Journal of Physiology—Paris, 99, 396–405. Bornkessel, I., & Schlesewsky, M. (2006). The extended argument dependency model: A neurocognitive approach to sentence comprehension across languages. Psychological Review, 113, 787–821.

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