Abstract

Studies of speech motor control suggest that articulatory and phonemic goals are defined in multidimensional motor, somatosensory, and auditory spaces. To test whether motor simulation might rely on sensory–motor coding common with those for motor execution, we used a repetition suppression (RS) paradigm while measuring neural activity with sparse sampling fMRI during repeated overt and covert orofacial and speech actions. RS refers to the phenomenon that repeated stimuli or motor acts lead to decreased activity in specific neural populations and are associated with enhanced adaptive learning related to the repeated stimulus attributes. Common suppressed neural responses were observed in motor and posterior parietal regions in the achievement of both repeated overt and covert orofacial and speech actions, including the left premotor cortex and inferior frontal gyrus, the superior parietal cortex and adjacent intraprietal sulcus, and the left IC and the SMA. Interestingly, reduced activity of the auditory cortex was observed during overt but not covert speech production, a finding likely reflecting a motor rather an auditory imagery strategy by the participants. By providing evidence for adaptive changes in premotor and associative somatosensory brain areas, the observed RS suggests online state coding of both orofacial and speech actions in somatosensory and motor spaces with and without motor behavior and sensory feedback.

INTRODUCTION

On the basis of the concepts of efference copy and internal models (e.g., Kawato, 1999; Wolpert, Ghahramani, & Jordan, 1995; Kawato, Furukawa, & Suzuki, 1987; Francis & Wonham, 1976; von Holst & Mittelstaedt, 1950), influential models of speech production propose that articulatory and phonemic perceptuo-motor goals that define successful speech motor acts are gradually learned by the CNS during language acquisition and stored in the form of an internal forward model. Once mature, the internal forward model can simulate the perceptual consequences of planned motor commands by internal motor-to-sensory simulation and efference copies. These internal motor-to-sensory predictions, generated before the actual motor execution and sensory feedback, can assist in online sensory–motor state estimation of the intended perceptuo-motor goals and trigger corrective motor adjustments in case of discrepancy with actual sensory feedback (e.g., Tian & Poeppel, 2010, 2012, 2013; Guenther & Vladusich, 2012; Hickok, 2012; Perkell, 2012; Hickok, Houde, & Rong, 2011; Houde & Nagarajan, 2011; Price, Crinion, & MacSweeney, 2011; Guenther, 2006). For instance, in the Directions Into Velocities of Articulators model (Guenther & Vladusich, 2012; Guenther, 2006), efference copies from planned speech motor commands are sent from the left ventral premotor cortex to both auditory and somatosensory state maps (thought to be located in the primary and associative auditory and somatosensory cortices) for sensory–motor state estimation and, if necessary, corrective motor commands.

In line with these models, a large number of behavioral studies employing manipulations of auditory and/or somatosensory feedback during speech production demonstrate articulatory adjustments that partly counteract the effect of perturbed feedback. These studies provide indirect evidence for sensory predictive and corrective feedback loops during speech production and suggest that phonemic goals are defined in multidimensional motor, auditory, and somatosensory spaces (e.g., Lametti, Nasir, & Ostry, 2012; Cai, Ghosh, Guenther, & Perkell, 2011; Feng, Gracco, & Max, 2011; Rochet-Capellan & Ostry, 2011; Shiller, Sato, Gracco, & Baum, 2009; Nasir & Ostry, 2006; Purcell & Munhall, 2006; Tremblay, Shiller, & Ostry, 2003; Jones & Munhall, 2000; Houde & Jordan, 1998; Gracco & Abbs, 1985). Recent brain imaging studies also support online sensory feedback control mechanisms. Reduced responses of the auditory cortex have been repeatedly reported during self-produced overt speech, compared with utterances recorded and replayed to the participants (e.g., Christoffels, van de Ven, Waldorp, Formisano, & Schiller, 2011; Christoffels, Formisano, & Schiller, 2007; Heinks-Maldonado, Nagarajan, & Houde, 2006; Ford & Mathalon, 2004; Houde, Nagarajan, Sekihara, & Merzenich, 2002; Numminen & Curio, 1999). Conversely, increased activity during overt speech production has been observed in auditory and somatosensory cortices with altered sensory feedback (e.g., Christoffels et al., 2007, 2011; Golfinopoulos et al., 2011; Tourville, Reilly, & Guenther, 2008). The modulation of sensory activity in speech production is thought to be driven by efference copies that assist in online sensory feedback control and sensory–motor state estimation, by tuning sensory phonemic targets to normal sensory feedback or, conversely, by increasing sensitivity to perturbed feedback.

Remarkably, auditory activity and reduced neural responses compared with speech perception have been shown to also occur during covert speech production (e.g., Tian & Poeppel, 2010, 2013; Numminen & Curio, 1999). Because imagery process depends on internal sensory–motor simulation (for reviews, see Jeannerod, 1994, 2001), these results further suggest the existence of internally generated motor-to-auditory predictions even in the absence of overt motor behavior and sensory feedback.

In keeping with these later findings, this fMRI study aimed at investigating whether overt and imagined repeated orofacial and speech actions might both induce auditory–motor and somatosensory–motor control mechanisms, with and without motor behavior and sensory feedback. To this aim, we used an adaptation paradigm in which orofacial or speech actions were repeatedly produced either overtly or covertly. fMRI adaptation is based on the phenomenon that repeated motor acts or stimulus presentation can lead to a reduction in the BOLD signal in specific brain areas that are sensitive to the performed actions or observed stimuli (the so-called repetition suppression effect or RS; see Grill-Spector, Henson, & Martin, 2006; Grill-Spector & Malach, 2001). RS is a highly complex phenomenon that depends on multiple experimental factors such as the number of repetitions, stimuli, and tasks and may occur at multiple temporal scales. Although a number of potential neural/synaptic mechanisms and theoretical models have been proposed to explain RS (for reviews, see Friston, 2012; Gotts, Chow, & Martin, 2012; Henson, 2012; Grill-Spector et al., 2006), all are associated with neural selectivity, increased processing, and information encoding efficiencies in relation to the repeated motor acts or stimulus attributes. Interestingly, recent fMRI adaptation studies on action goal coding of transitive and intransitive manual behaviors (Hamilton & Grafton, 2006, 2009; Kilner, Neal, Weiskopf, Friston, & Frith, 2009; Lingnau, Gesierich, & Caramazza, 2009; Majdandžić, Bekkering, van Schies, & Toni, 2009; Chong, Cunnington, Williams, Kanwisher, & Mattingley, 2008; Dinstein, Hasson, Rubin, & Heeger, 2007) all demonstrated that repeated manual actions with similar goals cause RS in premotor and posterior parietal cortices. Given the role of these regions in visual–somatosensory–motor control, these results appear compatible with the hypothesis that RS reflects a combination of attention and sensorimotor control mechanisms (Friston, 2005, 2011, 2012; Larsson & Smith, 2012).

On the basis of the abovementioned internal models of orofacial and speech motor control, the working hypothesis of this study was that possible RS in premotor, associative auditory, and somatosensory cortices during repeated overt and/or covert orofacial or speech actions might indirectly represent stronger motor-to-sensory control mechanisms in the first compared with the second repetition of the same action. Our experimental design was based on a previous fMRI adaptation study in which participants repeatedly and overtly produced silent lip, tongue, or laryngeal movements, devoid of any auditory but somatosensory feedbacks and revealing specific RS in premotor and posterior parietal cortices (Grabski, Lamalle, & Sato, 2012). To further extend these results, we here used a 3 × 2 × 2 factorial design involving three different orofacial actions, produced either overtly or covertly, in trains of two consecutive trials. To determine possible RS differences in auditory and somatosensory regions in relation to speech and nonspeech actions and to auditory–motor and somatosensory–motor control mechanisms, the three types of actions consisted of either a silent orofacial movement (nonspeech action thought to involve somatosensory–motor control mechanisms), an audible orofacial movement (nonspeech action thought to involve both auditory–motor and somatosensory–motor control mechanisms), or a syllable production (speech action thought to involve both auditory–motor and somatosensory–motor control mechanisms).

METHODS

Participants

Fourteen healthy adults, native French speakers, participated in the study after giving their informed consent. All were right handed according to standard handedness inventory (Oldfield, 1971); had normal or corrected-to-normal vision; and reported no history of motor, speaking, or hearing disorders. Participants were screened for neurological, psychiatric, and other possible medical problems and contraindications to MRI. The protocol was approved by the Grenoble University ethics committee and was carried out in accordance with the ethical standards of the 1964 Declaration of Helsinki. Two participants were removed from the study because of excessive head movements or technical problems during MRI acquisition.

Experimental Procedure

Three production tasks were performed overtly in a first functional run and then covertly in a subsequent functional run. The motor tasks consisted of a silent orofacial movement (a lip protrusion in half of the trials and a tongue retraction in the other half, with both movements performed without phonation), an audible orofacial movement (a kiss in half of the trials and a tongue click in the other half), or a syllable production (/pa/ in half of the trials, /ta/ in the other half). Each run lasted 17 min with the 3 × 2 motor tasks performed in a pseudorandom sequence. For all motor tasks, participants were instructed to initiate and end each movement from a resting state position, with the mouth closed. Crucially, each identical motor task (e.g., a kiss) was performed in sets of two consecutive trials to investigate RS. In addition, a resting condition, without any movement, served as baseline.

In each trial, a 1000-msec lexico-visual instruction informed the participants about the motor condition or the resting baseline (i.e., “lips,” “tongue,” “kiss,” “click,” “pa,” “ta,” “pause”) and indicated the onset of the movement to be produced. Participants were instructed to initiate each motor task as soon as they perceived the visual instruction and to maintain the movement until the visual cue disappeared. Apart from articulatory movements in the overt condition, participants were instructed not to move during the whole experimental session to avoid head-movement artifacts. For covert actions, the only indication given to the participants was to mentally produce each action without any movement (motor imagery). Importantly, they received no indication regarding possible auditory, visual, and/or somatosensory sensations (sensory imagery).

All motor tasks were briefly practiced overtly and covertly before entering into the scanner. In addition, overt actions were performed in the first functional scan to further help producing covert actions in the second functional scan. No participant reported any difficulty performing the tasks. Through the experiment, audible actions were monitored online to ensure their adequate execution in the overt mode as well as their fully silent execution in the covert mode.

Data Acquisition

Magnetic resonance images were acquired with a 3-T whole-body MR scanner (Philips Achieva TX, Best, The Netherlands). Participants were laid in the scanner with head movements minimized with a standard birdcage 32-channel head coil and foam cushions. Visual instructions were presented using Presentation software (Neurobehavioral Systems, Albany, CA) and displayed on a screen situated behind the scanner via a mirror placed above the participant's eyes. Participant's audible productions were monitored using an MRI-compatible microphone. Functional images were obtained in two consecutive functional runs using a T2*-weighted, EPI sequence with whole-brain coverage (repetition time [TR] = 8 sec, acquisition time = 3 sec, echo time = 30 msec, flip angle = 90°). Each functional scan was composed of 53 axial slices parallel to the anteroposterior commissural plane acquired in noninterleaved order (72 × 72 matrix, field of view = 216 mm, 3 × 3 mm2 in-plane resolution with a slice thickness of 3 mm without gap). A high-resolution T1-weighted whole-brain structural image was acquired for each participant after the last functional run (sagittal volume of 256 × 224 × 176 mm3 with a 1-mm isotropic resolution, inversion time = 900 msec, two segments, segment repetition time = 2500 msec, segment duration = 1795 msec, TR/echo time = 16/5 in msec with 35% partial echo, flip angle = 30°).

To avoid movement artifacts and to reduce acoustic noise, a sparse sampling acquisition was used (e.g., Gracco, Tremblay, & Pike, 2005; Barch et al., 1999; Birn, Bandettini, Cox, & Shaker, 1999; Hall et al., 1999). This acquisition technique is based on neurophysiological properties of the slowly rising hemodynamic response, which is estimated to occur with a 4- to 6-sec delay in case of orofacial and speech movements (e.g., Grabski et al., 2013; Grabski, Lamalle, & Sato, 2012; Grabski, Lamalle, Vilain, et al., 2012). In this study, functional scanning therefore occurred only during a fraction of the TR, alternating with silent interscanning periods, where participants produced the required motor task. The time interval between the visual instruction onset and the midpoint of the following functional scan acquisition was 5 sec. In each functional run, the motor tasks were performed in two consecutive trials in a pseudorandom sequence. This RS structure allows measuring changes in BOLD signal for repeated compared with novel performed actions. Altogether, 252 functional scans were therefore acquired (2 runs × [(3 conditions × 2 repetitions) + (1 resting baseline)] × 18 trials). In addition, three “dummy” scans at the beginning of each run were added to allow for equilibration of the MRI signal and were removed from the analyses.

Data Analyses

Data were analyzed using the SPM8 software package (Wellcome Department of Imaging Neuroscience, Institute of Neurology, London, UK) running on Matlab (Mathworks, Natick, MA). Brain activated regions were labeled using the SPM Anatomy toolbox (Eickhoff et al., 2005) and, if a brain region was not assigned or not specified in the SPM Anatomy toolbox, using the Talairach Daemon software (Lancaster et al., 2000). For visualization, activation maps were superimposed on a standard brain template using the MRICRON software (www.sph.sc.edu/comd/rorden/mricron/).

Data Preprocessing

The first three volumes (dummy scans) were discarded. For each participant, the functional series were first realigned by estimating the six movement parameters of a rigid-body transformation to control for head movements between scans. After segmentation of the T1 structural image (using the unified segmentation model; Ashburner & Friston, 2005) and coregistration to the mean functional image, all functional images were spatially normalized into standard stereotaxic space of the Montreal Neurological Institute (MNI) using segmentation parameters of the T1 structural image. All functional images were then smoothed using an 8-mm FWHM Gaussian kernel to improve the signal-to-noise ratio and to compensate for the anatomical variability among individual brains.

Individual and Group Analyses

Neural activations related to the motor tasks were analyzed using the general linear model (Friston et al., 1995), including 12 regressors of interest (2 production modes × 3 tasks × 2 repetitions × 24 trials) with the silent trials forming an implicit baseline. Because of a low number of trials (i.e., 12), the two movements related to each motor task were included in a single regressor (e.g., lip protrusion and tongue retraction for silent orofacial action). The six realignment parameters were also included as covariates of no interest. The BOLD response for each event was modeled using a single-bin finite impulse response basis function spanning the time of acquisition (3 sec). Before estimation, a high-pass filtering with a cutoff period of 128 sec was applied. Beta weights associated with the modeled finite-impulse-response responses were then computed to fit the observed BOLD signal time course in each voxel for each condition. Individual statistical maps were calculated for each repetition of each task in both covert and overt conditions with the related baseline and subsequently used for group statistics.

To draw population-based inferences (Friston, Holmes, Price, Buchel, & Worsley, 1999), a second-level random effect group analysis was carried out. The present experiment is based on a 3 × 2 × 2 factorial design. Accordingly, a repeated-measures ANOVA was performed, with the task (three levels: silent orofacial movement, audible orofacial movement, and syllable production), the production mode (two levels: overt mode and covert mode), and the repetition (two levels: RS1 and RS2) as within-subject factors and the participants treated as a random factor. All reported main effects (bidirectional F contrasts), interactions (bidirectional F contrasts), and conjunctions (unidirectional t contrasts) were calculated with a significance level set at p < .0001 uncorrected at the voxel level with a cluster extent of at least 30 voxels. For all main effects and interactions, the contrast estimates related to the 3 × 2 × 2 conditions are reported for each significantly activated brain region in the related tables.

RESULTS

Given the 3 × 2 × 2 factorial design, the repeated-measures ANOVA allowed us to test activity changes for each experimental factor independently of the others: namely, possible activity changes between the silent orofacial, audible orofacial, and speech actions (main effect of the Task), between the overt and covert modes (main effect of the Production mode), and between the first and second productions of a same action (main effect of RS). All interactions between the experimental factors were also computed to determine whether possible activity changes between the tasks differ in the overt and covert modes (Task × Production mode interaction) and in the first and second productions (Task × RS interaction), whether possible activity changes between the overt and covert modes differ in the first and second productions (Production mode × RS interaction), and whether possible activity changes between the tasks differ according to both the production mode and the first and second productions of a same action (Task × Production mode × RS interaction).

For clarity, we subdivided our results in two parts. The first part is related to the main effects of the task and the production mode as well as their interaction. These results mainly confirmed the basic design and correct data analyses regarding previous brain imaging studies on overt and covert orofacial and speech motor control. Of more interest, the second part is related to the main effect of RS and the interactions with the other factors. It allowed us to determine possible RS from the first to second productions as well as possible RS changes between the tasks and the production modes: that is, are there similar or different RS in motor and sensory cortices in the three tasks and/or in the overt and covert modes?

Effects of the Task, the Production Mode, and Their Interaction

Main Effect of Task and Conjunction

Independent of the production modes and RS, and as provided by a conjunction analysis (see Figure 1, top), orofacial and speech actions activated a set of largely overlapping brain areas, including the sensory–motor and premotor cortices, the SMA, the inferior parietal cortex and adjacent parietal operculum, the IC, the BG, and the cerebellum. These results appear fully consistent with previous brain imaging studies on orofacial and speech motor control, with the abovementioned brain areas classically assigned to motor preparation, execution, and regulation loops (e.g., Grabski et al., 2013; Grabski, Lamalle, & Sato, 2012; Grabski, Lamalle, Vilain, et al., 2012; Brown, Ngan, & Liotti, 2008; Dhanjal, Handunnetthi, Patel, & Wise, 2008; Ghosh, Tourville, & Guenther, 2008; Bohland & Guenther, 2006; Guenther, 2006; Özdemir, Norton, & Schlaug, 2006; Sörös et al., 2006; Riecker et al., 2000, 2005; Wise et al., 2001; Wise, Greene, Büchel, & Scott, 1999; Murphy et al., 1997). Notably, these results support a core orofacial motor network observed in two previous fMRI studies on overt orofacial supralaryngeal and laryngeal movements, using a similar sparse sampling experimental paradigm with and without motor adaptation (Grabski, Lamalle, & Sato, 2012; Grabski, Lamalle, Vilain, et al., 2012).

Figure 1. 

Effect of the motor task. (Top) Brain regions showing overlapping activity between the three motor tasks compared with the baseline (conjunction, unidirectional t contrast). (Center/Bottom) Brain regions showing significant change in activity between the motor tasks (main effect, bidirectional F contrast) and related contrast estimates (p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 1 for details).

Figure 1. 

Effect of the motor task. (Top) Brain regions showing overlapping activity between the three motor tasks compared with the baseline (conjunction, unidirectional t contrast). (Center/Bottom) Brain regions showing significant change in activity between the motor tasks (main effect, bidirectional F contrast) and related contrast estimates (p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 1 for details).

Despite strong overlapping activity between the three motor tasks in these cortical and subcortical brain areas, the main effect of the motor task and contrast estimates (see Figure 1, bottom) demonstrated that silent and audible orofacial actions induced stronger activity than speech actions in the primary sensorimotor cortex, the ventral part of the left premotor cortex, the dorsal part of the right premotor cortex, and the inferior parietal cortex. This result likely reflects lower motor demands in case of well-learned speech actions compared with less automated orofacial actions (e.g., tongue retraction). Conversely, in line with its functional role in auditory speech perception and in monitoring one's own speech (e.g., Wise et al., 2001), neural activity was only observed during syllable production in the left STS, extending to the adjacent superior and middle temporal gyri (Table 1).

Table 1. 

Brain Regions Showing Significant Change in Activity between the Three Motor Tasks

RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (797 Voxels) 
Primary sensorimotor cortex −56 −24 44 40.54 0.19 0.19 0.15 0.15 0.06 0.01 0.05 0.04 0.03 0.03 0.00 0.00 
Inferior parietal cortex 40 −58 −22 38 39.14 0.20 0.19 0.17 0.17 0.09 0.04 0.07 0.04 0.06 0.05 0.01 0.00 
 
Cluster 2 (529 Voxels) 
Primary sensorimotor cortex 58 −16 34 32.18 0.19 0.23 0.16 0.17 0.08 0.05 0.02 0.02 0.01 0.01 −0.04 −0.02 
Inferior parietal cortex 40 62 −16 22 20.74 0.17 0.20 0.20 0.22 0.13 0.09 0.04 0.04 0.02 0.02 −0.04 −0.01 
 
Cluster 3 (167 Voxels) 
Middle temporal gyrus 21 −60 −16 −6 26.14 −0.02 −0.03 0.00 −0.01 0.09 0.05 −0.03 −0.02 −0.03 −0.03 −0.03 −0.01 
Superior temporal gyrus 22 −62 −22 23.32 0.00 0.00 0.03 0.02 0.11 0.08 −0.01 0.00 −0.02 −0.01 −0.01 −0.01 
 
Cluster 4 (42 Voxels) 
Premotor cortex 36 −10 56 22.01 0.09 0.09 0.06 0.06 0.03 0.00 0.01 0.03 0.00 0.02 0.00 0.01 
 
Cluster 5 (41 Voxels) 
Premotor cortex −56 34 20.21 0.25 0.26 0.23 0.24 0.18 0.15 0.09 0.08 0.09 0.07 0.04 0.05 
RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (797 Voxels) 
Primary sensorimotor cortex −56 −24 44 40.54 0.19 0.19 0.15 0.15 0.06 0.01 0.05 0.04 0.03 0.03 0.00 0.00 
Inferior parietal cortex 40 −58 −22 38 39.14 0.20 0.19 0.17 0.17 0.09 0.04 0.07 0.04 0.06 0.05 0.01 0.00 
 
Cluster 2 (529 Voxels) 
Primary sensorimotor cortex 58 −16 34 32.18 0.19 0.23 0.16 0.17 0.08 0.05 0.02 0.02 0.01 0.01 −0.04 −0.02 
Inferior parietal cortex 40 62 −16 22 20.74 0.17 0.20 0.20 0.22 0.13 0.09 0.04 0.04 0.02 0.02 −0.04 −0.01 
 
Cluster 3 (167 Voxels) 
Middle temporal gyrus 21 −60 −16 −6 26.14 −0.02 −0.03 0.00 −0.01 0.09 0.05 −0.03 −0.02 −0.03 −0.03 −0.03 −0.01 
Superior temporal gyrus 22 −62 −22 23.32 0.00 0.00 0.03 0.02 0.11 0.08 −0.01 0.00 −0.02 −0.01 −0.01 −0.01 
 
Cluster 4 (42 Voxels) 
Premotor cortex 36 −10 56 22.01 0.09 0.09 0.06 0.06 0.03 0.00 0.01 0.03 0.00 0.02 0.00 0.01 
 
Cluster 5 (41 Voxels) 
Premotor cortex −56 34 20.21 0.25 0.26 0.23 0.24 0.18 0.15 0.09 0.08 0.09 0.07 0.04 0.05 

Maximum activation peak summary of brain regions showing significant change in activity between the three motor tasks and contrast estimates in all conditions (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels). SO = silent orofacial movement; AO = audible orofacial movement; SY = syllable production.

Main Effect of Production Mode and Conjunction

Independent of the tasks and RS, overlapping activity between the overt and covert modes was observed in the ventral and dorsal parts of the left premotor cortex, the posterior part of the left inferior frontal gyrus (pars opercularis), the dorsal part of the right premotor cortex, the left IC, and the SMA (conjunction analysis; see Figure 2, top). These results confirm, and extend to orofacial actions, that mental simulation and actual execution of an action both involve motor preparation and coordination processes (e.g., Hetu et al., 2013; Jeannerod, 1994, 2001).

Figure 2. 

Effect of the production mode. (Top) Brain regions showing overlapping activity between the two production modes (conjunction, unidirectional t contrast). (Center/Bottom) Brain regions showing significant change in activity between the production modes (main effect, bidirectional F contrast) and related contrast estimates (p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 2 for details).

Figure 2. 

Effect of the production mode. (Top) Brain regions showing overlapping activity between the two production modes (conjunction, unidirectional t contrast). (Center/Bottom) Brain regions showing significant change in activity between the production modes (main effect, bidirectional F contrast) and related contrast estimates (p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 2 for details).

Complementing these findings, the main effect of the production mode (see Figure 2, bottom) showed stronger activity during overt compared with covert actions in the primary sensorimotor cortex, the ventral part of the right premotor cortex, the inferior parietal cortex and adjacent parietal operculum, the SMA and middle cingulate gyrus, the transverse temporal gyrus and posterior part of the right superior temporal gyrus, the calcarine gyrus, and the cerebellum. These results replicate previous fMRI studies showing that overt speech, despite similarities with covert speech, produced greater BOLD response in brain areas involved in motor preparation, coordination, and execution as well as in auditory monitoring (e.g., Shuster & Lemieux, 2005; Barch et al., 1999; Yetkin et al., 1995; Table 2).

Table 2. 

Brain Regions Showing Significant Change in Activity between the Two Production Modes

RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (5548 Voxels) 
Primary sensorimotor cortex −50 −12 30 352.26 0.30 0.30 0.33 0.32 0.29 0.25 0.01 0.01 0.02 −0.01 −0.04 −0.01 
Transverse temporal gyrus 41 −52 −24 10 88.02 0.12 0.12 0.20 0.19 0.28 0.22 −0.02 −0.03 −0.07 −0.07 −0.10 −0.06 
Transverse temporal gyrus 42 −38 −32 16 87.49 0.09 0.09 0.17 0.15 0.18 0.14 −0.03 −0.01 −0.05 −0.05 −0.07 −0.03 
Parietal operculum 40/43 −50 −14 81.09 0.11 0.11 0.16 0.16 0.23 0.17 −0.01 0.00 −0.02 −0.02 −0.05 −0.02 
Inferior parietal cortex 40 −58 −36 16 55.80 0.11 0.10 0.16 0.15 0.19 0.17 0.00 0.02 0.00 −0.01 −0.03 0.00 
 
Cluster 2 (4467 Voxels) 
Primary sensorimotor cortex 50 −8 32 305.86 0.33 0.34 0.37 0.37 0.34 0.30 0.00 0.00 0.01 −0.01 −0.05 −0.02 
Parietal operculum 40/43 64 −8 20 132.04 0.15 0.18 0.20 0.22 0.17 0.14 0.00 0.01 0.00 0.00 −0.04 −0.01 
Transverse temporal gyrus 41 50 −16 87.27 0.10 0.15 0.19 0.20 0.25 0.17 0.01 0.00 −0.01 −0.01 −0.05 −0.03 
Inferior parietal cortex 40 52 −30 22 75.15 0.14 0.16 0.15 0.16 0.15 0.14 0.00 0.01 −0.02 −0.02 −0.04 −0.02 
Premotor cortex 46 −8 56 34.95 0.14 0.16 0.17 0.17 0.14 0.11 0.02 0.03 0.01 0.00 −0.01 0.01 
Superior temporal gyrus 22 48 −28 −2 29.67 0.04 0.01 0.08 0.06 0.14 0.09 0.00 −0.02 −0.01 −0.01 −0.01 −0.01 
 
Cluster 3 (123 Voxels) 
SMA L/R −6 48 57.91 0.15 0.16 0.17 0.15 0.19 0.11 −0.01 −0.01 0.01 −0.03 −0.03 −0.01 
Middle cingulate cortex L/R 32 −4 −6 40 52.84 0.05 0.05 0.10 0.05 0.16 0.07 −0.04 −0.07 −0.02 −0.05 −0.04 −0.04 
 
Cluster 4 (84 Voxels) 
Calcarine gyrus 18 14 −66 12 34.49 0.08 0.05 0.10 0.07 0.13 0.08 −0.03 −0.02 −0.01 −0.06 −0.01 −0.01 
 
Cluster 5 (70 Voxels) 
Cerebellum (lobule VI)  −16 −66 −20 40.97 0.16 0.17 0.12 0.18 0.15 0.11 0.02 0.01 0.01 −0.01 0.00 0.00 
 
Cluster 6 (48 Voxels) 
Calcarine gyrus 17 −8 −74 12 32.74 0.09 0.06 0.11 0.08 0.15 0.08 −0.02 −0.02 −0.01 −0.04 0.00 −0.02 
 
Cluster 7 (31 Voxels) 
Cerebellum (lobule VI)  12 −68 −14 31.99 0.12 0.10 0.12 0.15 0.18 0.13 0.01 0.00 0.00 0.01 0.01 0.01 
RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (5548 Voxels) 
Primary sensorimotor cortex −50 −12 30 352.26 0.30 0.30 0.33 0.32 0.29 0.25 0.01 0.01 0.02 −0.01 −0.04 −0.01 
Transverse temporal gyrus 41 −52 −24 10 88.02 0.12 0.12 0.20 0.19 0.28 0.22 −0.02 −0.03 −0.07 −0.07 −0.10 −0.06 
Transverse temporal gyrus 42 −38 −32 16 87.49 0.09 0.09 0.17 0.15 0.18 0.14 −0.03 −0.01 −0.05 −0.05 −0.07 −0.03 
Parietal operculum 40/43 −50 −14 81.09 0.11 0.11 0.16 0.16 0.23 0.17 −0.01 0.00 −0.02 −0.02 −0.05 −0.02 
Inferior parietal cortex 40 −58 −36 16 55.80 0.11 0.10 0.16 0.15 0.19 0.17 0.00 0.02 0.00 −0.01 −0.03 0.00 
 
Cluster 2 (4467 Voxels) 
Primary sensorimotor cortex 50 −8 32 305.86 0.33 0.34 0.37 0.37 0.34 0.30 0.00 0.00 0.01 −0.01 −0.05 −0.02 
Parietal operculum 40/43 64 −8 20 132.04 0.15 0.18 0.20 0.22 0.17 0.14 0.00 0.01 0.00 0.00 −0.04 −0.01 
Transverse temporal gyrus 41 50 −16 87.27 0.10 0.15 0.19 0.20 0.25 0.17 0.01 0.00 −0.01 −0.01 −0.05 −0.03 
Inferior parietal cortex 40 52 −30 22 75.15 0.14 0.16 0.15 0.16 0.15 0.14 0.00 0.01 −0.02 −0.02 −0.04 −0.02 
Premotor cortex 46 −8 56 34.95 0.14 0.16 0.17 0.17 0.14 0.11 0.02 0.03 0.01 0.00 −0.01 0.01 
Superior temporal gyrus 22 48 −28 −2 29.67 0.04 0.01 0.08 0.06 0.14 0.09 0.00 −0.02 −0.01 −0.01 −0.01 −0.01 
 
Cluster 3 (123 Voxels) 
SMA L/R −6 48 57.91 0.15 0.16 0.17 0.15 0.19 0.11 −0.01 −0.01 0.01 −0.03 −0.03 −0.01 
Middle cingulate cortex L/R 32 −4 −6 40 52.84 0.05 0.05 0.10 0.05 0.16 0.07 −0.04 −0.07 −0.02 −0.05 −0.04 −0.04 
 
Cluster 4 (84 Voxels) 
Calcarine gyrus 18 14 −66 12 34.49 0.08 0.05 0.10 0.07 0.13 0.08 −0.03 −0.02 −0.01 −0.06 −0.01 −0.01 
 
Cluster 5 (70 Voxels) 
Cerebellum (lobule VI)  −16 −66 −20 40.97 0.16 0.17 0.12 0.18 0.15 0.11 0.02 0.01 0.01 −0.01 0.00 0.00 
 
Cluster 6 (48 Voxels) 
Calcarine gyrus 17 −8 −74 12 32.74 0.09 0.06 0.11 0.08 0.15 0.08 −0.02 −0.02 −0.01 −0.04 0.00 −0.02 
 
Cluster 7 (31 Voxels) 
Cerebellum (lobule VI)  12 −68 −14 31.99 0.12 0.10 0.12 0.15 0.18 0.13 0.01 0.00 0.00 0.01 0.01 0.01 

Maximum activation peak summary of brain regions showing significant change in activity between the two production modes and contrast estimates in all conditions (bidirectional F contrast; p < .0001 uncorrected at the voxel level).

Interaction between the Task and the Production Mode

Brain regions showing significant change in activity between the tasks and the production modes were localized in the transverse, superior, and middle temporal gyri (Task × Production mode interaction; see Figure 3 and Table 3). The contrast estimates showed that although in the overt mode all these regions showed a growing gradient of activity from the silent to the audible orofacial actions and to the audible orofacial to the speech actions, no activity was observed in the covert mode. This contrasts with previous studies on auditory verbal imagery, with clear auditory activity linked to auditory self-monitoring (e.g., Sato et al., 2004; Shergill et al., 2001). In our view, this likely reflects a motor rather than an auditory imagery strategy in this study, with participants instructed to mentally produce each action without indication regarding possible auditory, visual, and/or somatosensory sensations.

Figure 3. 

Interaction between the task and the production mode. Brain regions showing significant change in activity between the tasks and the production modes and related contrast estimates (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 3 for details). SO = silent orofacial movement; AO = audible orofacial movement; SY = syllable production.

Figure 3. 

Interaction between the task and the production mode. Brain regions showing significant change in activity between the tasks and the production modes and related contrast estimates (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 3 for details). SO = silent orofacial movement; AO = audible orofacial movement; SY = syllable production.

Table 3. 

Brain Regions Showing Significant Change in Activity between the Tasks and the Production Modes

RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (980 Voxels) 
Transverse temporal gyrus 41 −56 −20 46.99 0.06 0.05 0.13 0.13 0.24 0.18 0.00 0.01 −0.04 −0.03 −0.06 −0.04 
Superior temporal gyrus 22 −62 −28 35.81 0.02 0.02 0.06 0.06 0.13 0.10 −0.01 −0.01 −0.03 −0.02 −0.03 −0.02 
Middle temporal gyrus 21 −58 −8 −4 28.82 −0.02 −0.02 0.01 0.00 0.10 0.06 −0.02 0.00 −0.02 −0.02 −0.04 −0.01 
Transverse temporal gyrus 42 −36 −28 20.89 0.05 0.05 0.12 0.09 0.14 0.11 −0.01 0.00 −0.03 −0.03 −0.04 −0.02 
 
Cluster 2 (590 Voxels) 
Superior temporal gyrus 22 62 −18 41.35 −0.01 0.00 0.04 0.05 0.12 0.08 0.00 0.00 −0.02 −0.01 −0.04 −0.01 
Middle temporal gyrus 21 64 −14 −2 37.29 −0.02 0.02 0.03 0.04 0.10 0.07 −0.01 0.01 −0.02 −0.01 −0.03 −0.02 
RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (980 Voxels) 
Transverse temporal gyrus 41 −56 −20 46.99 0.06 0.05 0.13 0.13 0.24 0.18 0.00 0.01 −0.04 −0.03 −0.06 −0.04 
Superior temporal gyrus 22 −62 −28 35.81 0.02 0.02 0.06 0.06 0.13 0.10 −0.01 −0.01 −0.03 −0.02 −0.03 −0.02 
Middle temporal gyrus 21 −58 −8 −4 28.82 −0.02 −0.02 0.01 0.00 0.10 0.06 −0.02 0.00 −0.02 −0.02 −0.04 −0.01 
Transverse temporal gyrus 42 −36 −28 20.89 0.05 0.05 0.12 0.09 0.14 0.11 −0.01 0.00 −0.03 −0.03 −0.04 −0.02 
 
Cluster 2 (590 Voxels) 
Superior temporal gyrus 22 62 −18 41.35 −0.01 0.00 0.04 0.05 0.12 0.08 0.00 0.00 −0.02 −0.01 −0.04 −0.01 
Middle temporal gyrus 21 64 −14 −2 37.29 −0.02 0.02 0.03 0.04 0.10 0.07 −0.01 0.01 −0.02 −0.01 −0.03 −0.02 

Maximum activation peak summary of brain regions showing significant change in activity between the tasks and the production modes and contrast estimates in all conditions (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels).

Effect of RS and Related Interactions

Main Effect of RS

Independent of the tasks and the production modes, repeated motor acts led to decreased activity in the left premotor cortex, the superior parietal cortex and adjacent intraparietal sulcus, the left inferior frontal gyrus (pars triangularis) and adjacent pFC, the left IC, the SMA, the middle and posterior cingulate cortices, and the left fusiform gyrus (main effect; see Figure 4 and Table 4). Importantly, the contrast estimates showed RS for all six overt and covert motor tasks in all these regions (see Table 4).

Figure 4. 

Effect of the repetition. Brain region showing significant change in activity between the two repetitions and related contrast estimates (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 4 for details).

Figure 4. 

Effect of the repetition. Brain region showing significant change in activity between the two repetitions and related contrast estimates (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels; see Table 4 for details).

Table 4. 

Brain Regions Showing Significant Change in Activity between the Two Repetitions

RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (4087 Voxels) 
SMA L/R −6 12 50 94.39 0.11 0.01 0.09 0.03 0.07 −0.02 0.09 0.02 0.08 0.02 0.05 0.01 
Posterior cingulate cortex L/R 23 −2 −28 26 80.27 0.07 −0.01 0.09 −0.01 0.08 −0.02 0.01 −0.07 0.03 −0.09 0.00 −0.05 
pFC −40 10 30 75.50 0.04 −0.04 0.05 −0.03 0.05 −0.04 −0.01 −0.04 0.01 −0.05 −0.01 −0.04 
Middle cingulate cortex L/R 32 22 30 74.54 0.08 0.03 0.12 0.06 0.12 0.03 0.04 −0.02 0.04 −0.02 0.01 −0.03 
Premotor cortex −22 58 51.70 0.10 0.06 0.09 0.02 0.08 −0.01 0.05 0.01 0.04 0.00 0.01 0.01 
Inferior frontal gyrus 45 −46 30 24 44.74 0.09 0.02 0.08 0.03 0.04 −0.01 0.03 0.00 0.05 0.00 0.01 −0.02 
 
Cluster 2 (1374 Voxels) 
Superior parietal cortex −24 −68 50 61.48 0.09 0.00 0.07 −0.03 0.08 −0.04 0.00 −0.05 0.00 −0.08 0.02 −0.02 
Superior parietal cortex 12 −70 34 40.80 0.06 −0.02 0.10 −0.01 0.12 0.03 −0.01 −0.05 0.01 −0.08 −0.01 −0.04 
 
Cluster 3 (343 Voxels) 
Fusiform gyrus 37 −44 −54 −14 63.27 0.02 −0.02 0.01 −0.03 0.02 −0.04 −0.01 −0.03 0.02 −0.02 0.00 −0.03 
 
Cluster 4 (164 Voxels) 
IC 13 −30 22 45.42 0.07 0.01 0.06 0.01 0.05 0.01 0.06 0.02 0.06 0.01 0.02 0.00 
RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (4087 Voxels) 
SMA L/R −6 12 50 94.39 0.11 0.01 0.09 0.03 0.07 −0.02 0.09 0.02 0.08 0.02 0.05 0.01 
Posterior cingulate cortex L/R 23 −2 −28 26 80.27 0.07 −0.01 0.09 −0.01 0.08 −0.02 0.01 −0.07 0.03 −0.09 0.00 −0.05 
pFC −40 10 30 75.50 0.04 −0.04 0.05 −0.03 0.05 −0.04 −0.01 −0.04 0.01 −0.05 −0.01 −0.04 
Middle cingulate cortex L/R 32 22 30 74.54 0.08 0.03 0.12 0.06 0.12 0.03 0.04 −0.02 0.04 −0.02 0.01 −0.03 
Premotor cortex −22 58 51.70 0.10 0.06 0.09 0.02 0.08 −0.01 0.05 0.01 0.04 0.00 0.01 0.01 
Inferior frontal gyrus 45 −46 30 24 44.74 0.09 0.02 0.08 0.03 0.04 −0.01 0.03 0.00 0.05 0.00 0.01 −0.02 
 
Cluster 2 (1374 Voxels) 
Superior parietal cortex −24 −68 50 61.48 0.09 0.00 0.07 −0.03 0.08 −0.04 0.00 −0.05 0.00 −0.08 0.02 −0.02 
Superior parietal cortex 12 −70 34 40.80 0.06 −0.02 0.10 −0.01 0.12 0.03 −0.01 −0.05 0.01 −0.08 −0.01 −0.04 
 
Cluster 3 (343 Voxels) 
Fusiform gyrus 37 −44 −54 −14 63.27 0.02 −0.02 0.01 −0.03 0.02 −0.04 −0.01 −0.03 0.02 −0.02 0.00 −0.03 
 
Cluster 4 (164 Voxels) 
IC 13 −30 22 45.42 0.07 0.01 0.06 0.01 0.05 0.01 0.06 0.02 0.06 0.01 0.02 0.00 

Maximum activation peak summary of brain regions showing significant change in activity between the two repetitions and contrast estimates in all conditions (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels).

Additional analyses also confirm RS in the left premotor cortex, posterior parietal cortex, and fusiform gyrus in both the overt and covert modes, with the contrast estimates showing RS for all motor tasks (see Figure 5). Finally, we also computed RS individually for all six overt and covert actions. RS in the ventral premotor cortex was observed for all actions except for the covert silent orofacial and speech actions, whereas RS in the posterior parietal cortex was only observed for the overt audible orofacial and speech actions as well as for the covert audible orofacial actions. It is, however, worthwhile noting that the contrast estimates related to the main effect of RS and to the additional analyses of overt and covert RS (see above) showed a reduced activity from the first to second trials for all six actions in the ventral premotor and posterior parietal cortices. Furthermore, no significant differences were observed in these two brain regions when computing the interaction between RS and the other factors (see below). Failure to achieve significant RS in the premotor and posterior parietal cortices for all overt and covert actions is therefore likely to be the result of a lack of statistical power because of a limited sample size.

Figure 5. 

Single effects of the repetition. Brain region showing significant change in activity between the two repetitions in the overt and covert modes irrespectively of the three motor tasks (bidirectional F contrasts) or in relation to either the silent orofacial actions, the audible orofacial actions, or the syllable production (unidirectional t contrasts). All contrasts at p < .0001 uncorrected at the voxel level with a cluster extent threshold of 30 voxels.

Figure 5. 

Single effects of the repetition. Brain region showing significant change in activity between the two repetitions in the overt and covert modes irrespectively of the three motor tasks (bidirectional F contrasts) or in relation to either the silent orofacial actions, the audible orofacial actions, or the syllable production (unidirectional t contrasts). All contrasts at p < .0001 uncorrected at the voxel level with a cluster extent threshold of 30 voxels.

Interaction between the Task and RS

No significant change in activity between the task and RS was observed.

Interaction between the Production Mode and RS

Significant change in activity between the production modes and RS was only observed in the dorsal part of the right premotor cortex and adjacent primary motor cortex (interaction; p < .0001 uncorrected at the voxel level; single cluster of 107 voxels; maximal peak in MNI coordinates: x = 10, y = −24, z = 52). The contrast estimates showed that, although no activity was observed in the covert mode in these regions, RS was observed for all motor tasks during overt production, albeit stronger for speech actions.

Interaction between the Task, the Production Mode, and RS

Significant change in activity between the motor tasks, the production modes, and RS was observed in the right transverse and superior temporal gyri, extending to the parietal operculum and IC; the middle cingulate cortex; and the right calcarine gyrus (interaction; see Figure 6, top, and Table 5). The contrast estimates showed that this interaction was mainly because of RS for speech actions and to repetition enhancement for silent orofacial actions in the overt mode. Additional analyses further confirmed these significant changes in activity between the tasks and the repetitions in the overt mode, whereas, in the covert mode, no significant differences were observed (see Figure 6, bottom).

Figure 6. 

Interaction between the task, the production mode, and RS. (Top) Brain regions showing significant change in activity between the tasks, the production modes, and the repetitions (bidirectional F contrast) as well as related contrast estimates. (Bottom) Brain region showing significant change in activity between the tasks and the repetitions in the overt mode (bidirectional F contrast). In the covert mode, no significant differences were observed. All contrasts at p < .0001 uncorrected at the voxel level, with cluster extent threshold of 30 voxels (see Table 5 for details).

Figure 6. 

Interaction between the task, the production mode, and RS. (Top) Brain regions showing significant change in activity between the tasks, the production modes, and the repetitions (bidirectional F contrast) as well as related contrast estimates. (Bottom) Brain region showing significant change in activity between the tasks and the repetitions in the overt mode (bidirectional F contrast). In the covert mode, no significant differences were observed. All contrasts at p < .0001 uncorrected at the voxel level, with cluster extent threshold of 30 voxels (see Table 5 for details).

Table 5. 

Brain Regions Showing Significant Change in Activity between the Tasks, the Production Modes, and the Repetitions

RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (235 Voxels) 
Parietal operculum 40/43 38 −12 14 14.18 0.07 0.13 0.13 0.13 0.14 0.08 0.00 0.00 0.01 0.01 −0.03 0.00 
Transverse temporal gyrus 41 56 −10 14.10 0.00 0.03 0.04 0.06 0.11 0.06 0.01 0.00 0.00 0.00 −0.03 0.00 
Insula 13 42 −12 10 13.35 0.08 0.14 0.14 0.14 0.15 0.09 0.02 0.01 0.01 0.01 −0.04 0.00 
Superior temporal gyrus 22 54 −14 −2 10.86 −0.01 0.01 0.02 0.03 0.08 0.04 0.01 −0.01 −0.01 −0.00 −0.02 0.00 
 
Cluster 2 (42 Voxels) 
Middle cingulate cortex L/R 32 −10 40 13.35 0.05 0.06 0.06 0.04 0.08 0.03 0.01 −0.01 0.01 −0.01 −0.02 −0.01 
 
Cluster 3 (33 Voxels) 
Calcarine gyrus 17 20 −82 10 12.14 0.00 0.00 0.01 0.01 0.05 0.01 −0.02 0.00 0.00 0.04 0.00 0.00 
RegionsHBAMNI CoordinatesFContrast Estimates
Overt ModeCovert Mode
xyzSO-1SO-2AO-1AO-2SY-1SY-2SO-1SO-2AO-1AO-2SY-1SY-2
Cluster 1 (235 Voxels) 
Parietal operculum 40/43 38 −12 14 14.18 0.07 0.13 0.13 0.13 0.14 0.08 0.00 0.00 0.01 0.01 −0.03 0.00 
Transverse temporal gyrus 41 56 −10 14.10 0.00 0.03 0.04 0.06 0.11 0.06 0.01 0.00 0.00 0.00 −0.03 0.00 
Insula 13 42 −12 10 13.35 0.08 0.14 0.14 0.14 0.15 0.09 0.02 0.01 0.01 0.01 −0.04 0.00 
Superior temporal gyrus 22 54 −14 −2 10.86 −0.01 0.01 0.02 0.03 0.08 0.04 0.01 −0.01 −0.01 −0.00 −0.02 0.00 
 
Cluster 2 (42 Voxels) 
Middle cingulate cortex L/R 32 −10 40 13.35 0.05 0.06 0.06 0.04 0.08 0.03 0.01 −0.01 0.01 −0.01 −0.02 −0.01 
 
Cluster 3 (33 Voxels) 
Calcarine gyrus 17 20 −82 10 12.14 0.00 0.00 0.01 0.01 0.05 0.01 −0.02 0.00 0.00 0.04 0.00 0.00 

Maximum activation peak summary of brain regions showing significant change in activity between the tasks, the production modes, and the repetitions as well as contrast estimates in all conditions (bidirectional F contrast; p < .0001 uncorrected at the voxel level, cluster extent threshold of 30 voxels).

DISCUSSION

The goal of this fMRI adaptation study was to investigate whether auditory and somatosensory adaptive learning both occur during overt and imagined orofacial and speech actions. Irrespective of RS, orofacial and speech actions activated a set of largely overlapping, common brain areas forming a core neural network classically involved in orofacial motor control. Within this network, mental simulation and actual execution of actions both involved motor preparation and coordination of neural processes. Crucially, common suppressed neural responses were observed in motor and somatosensory regions in the achievement of repeated overt and covert orofacial and speech actions. Reduced activity of the auditory cortex was, however, only observed during overt but not covert speech production, a finding likely reflecting a motor rather than an auditory imagery strategy by the participants. The observed RS provides evidence for somatosensory–motor adaptive learning and suggests online state coding of orofacial and speech actions in somatosensory and motor spaces with and without motor behavior and sensory feedback.

Before we discuss these results, it is important to consider some methodological issues that could impact on their interpretation. First, perceptual RS is known to reflect a combination of stimulus selectivity and attention-dependent expectation (e.g., Larsson & Smith, 2012; Summerfield et al., 2006) and, as such, to vary as a function of the frequency of repeated and nonrepeated stimuli and as whether the task is directed toward the repeated stimuli. Notably, perceptual RS can be caused by a reduced BOLD response to repeated stimuli (adaptation effect) or, conversely, by a stronger response to nonrepeated, new stimuli (expectation effect). Regarding our experimental design involving self-produced overt or covert actions, it has first to be noted that it appears difficult to drive attention away from the motor act. In addition, with two successive trials of the same actions, with the same intertrial interval, produced in a global random order first in the overt mode and then in a covert mode, it is here impossible to disentangle the respective contribution of selectivity and expectation in the observed RS. However, in line with our working hypothesis and RS specifically observed in the premotor and posterior parietal cortices, it can be noted that both adaptation and expectation effects have been previously and partly attributed to predictive mechanisms. Second, RS is also known to occur as a function of the adaption duration, the number of repeated trials, and to occur at multiple temporal scales, from millisecond to minutes and even days (Grill-Spector et al., 2006). Obviously, the observed RS is therefore restricted to the specific experimental parameters used in this study (notably two repetitions of the same action with an 8-sec interval). A third methodological imitation of this study is that overt and covert actions were separately produced in two successive functional scans. Randomizing the overt and covert productions would have strengthened our results by avoiding possible effects because of the order of presentation. Although we ensured from time to time that participants correctly produced audible orofacial and speech actions in the overt mode, it was impossible to control what participants really did in the covert mode. The fact that the covert actions were produced in the second functional scan was therefore designed to help participants to correctly produce these covert actions. Finally, because of no EMG measures, we cannot rule out that covert actions resulted in any orofacial muscular activation, although we ensured from time to time that no auditory vocal responses occurred. From this question, it has, however, to be noted that the main effect of the production mode clearly demonstrated stronger sensorimotor activity in the overt mode and that overlapping activity between the overt and covert modes was mainly observed in the premotor cortex but not in the primary motor, auditory, and somatosensory cortices.

Despite the abovementioned limitations, repeated motor acts led to decreased activity in specific sensory–motor brain regions, namely the left premotor cortex, the superior parietal cortex and adjacent intraparietal sulcus, the left IC, the SMA, the middle and posterior cingulate cortices, the left inferior frontal gyrus (pars triangularis) and adjacent pFC, and the left fusiform gyrus. RS observed in this widely distributed set of brain areas might reflect distinct processes, including attention decrease and more efficient motor processing as well as sensory–motor control and action goal coding. From that view, reduced activity in the left fusiform gyrus and the left pars triangularis of the inferior frontal gyrus has been previously observed in fMRI adaptation studies (Grabski, Lamalle, & Sato, 2012; Hamilton & Grafton, 2009) and has been attributed to reduced visuo-attentional and lexical processing of orthographic instructions. RS observed in the SMA and in the left IC is likely because of more efficient motor processing in the second trial, in relation to the classical role of these regions in motor initiation and coordination during orofacial and speech actions (e.g., Grabski et al., 2013; Grabski, Lamalle, & Sato, 2012; Grabski, Lamalle, Vilain, et al., 2012). In addition, activity decrease in the cingulate cortex might rely on both attention and motor processing because of its function in motor attention and movement selection and its connections with frontal and parietal cortices (Grafton, Fagg, & Arbib, 1998).

Importantly, RS in premotor and posterior parietal cortices has been repeatedly observed in fMRI adaptation studies on transitive and intransitive manual and orofacial actions (Grabski, Lamalle, & Sato, 2012; Hamilton & Grafton, 2009; Lingnau et al., 2009; Majdandžić et al., 2009; Dinstein et al., 2007). On the basis of a hierarchical organization of action into distinct levels of control that represent increasingly abstract aspects of the performed behavior (for a recent review, see Grafton & Hamilton, 2007), these studies argue for a role of these premotor and posterior parietal regions in predictive sensory–motor control and action goal coding. As previously mentioned, RS is associated with increased processing and information encoding efficiencies in relation to the repeated stimulus attributes (Friston, 2012; Gotts et al., 2012; Henson, 2012; Grill-Spector et al., 2006) and might also reflect sensory–motor adaptive learning and internal predictive coding schemes for online state estimation (Friston, 2012). From this hypothesis, repeated manual or orofacial actions in these fMRI adaptation studies might have caused gradual sensory–motor adaptive learning in posterior parietal and premotor areas, with enhanced internal prediction to action goal reflected in BOLD suppression. Apart from RS and adaptation paradigms, evidence for action goal coding in frontoparietal areas also comes from the pioneering work of Liepmann (1908) on patients with ideomotor apraxia, with lesions located in the left posterior parietal and premotor cortices, and on single-unit neurophysiological recordings of visually guided manual motor acts in nonhuman primates (e.g., Bonini et al., 2010, 2011). It is worthwhile noting that RS in parietal regions was here confined to the superior parietal cortex and adjacent intraparietal sulcus. These sensory–motor regions are known to use and integrate visual and proprioceptive feedback to guide eye, limb, and head movements to the intended spatial target. It has also been shown that these regions are equally active in hand reaching with or without visual feedback, a result suggesting that sensory processing in these regions is primarily proprioceptive (Filimon, Nelson, Huang, & Sereno, 2009). Regarding orofacial movements, strong activity within these regions was also observed during spatial processing of precise tongue movements (i.e., tongue reaching to the left or right, upper or lower, incisor, canine, or molar tooth; Watanabe et al., 2004). Apart from the superior parietal cortex, no RS was observed in the inferior parietal cortex and adjacent anterior intraparietal sulcus, two regions previously shown to be sensitive to motor adaptation and thought to also be involved in action goal coding (Grabski, Lamalle, & Sato, 2012; Hamilton & Grafton, 2006, 2009; Kilner et al., 2009; Lingnau et al., 2009; Majdandžić et al., 2009; Chong et al., 2008; Dinstein et al., 2007). Notably, RS was observed in both premotor, inferior parietal, and superior parietal cortices in a previous study on lip, jaw, and tongue repeated actions, using a similar sparse sampling experimental paradigm but with six consecutive occurrences of each action performed in distinct trials to precisely explore the timing of adaptation effect (Grabski, Lamalle, & Sato, 2012). Three different time courses of adaptation across the six repetitions were tested, corresponding to a linear decrease, an exponential decrease, and a categorical decrease (from the first trial vs. the others) of the BOLD response (for a discussion on RS analyses, see Noppeney & Penny, 2006). Although activity in the premotor and superior parietal cortices mainly decreased from the first to second trials, RS observed in the inferior parietal cortex and adjacent intraparietal sulcus appeared to be more linear through the six trials. Although we do not have a clear explanation for these distinct RS profiles, the one-shot repetition paradigm used in this study could explain the absence of RS in these two brain areas from the first to second trials.

As previously discussed, whereas action goal coding and forward sensory–motor control processes have been primarily studied in the context of upper limb movements, recent models of speech production also postulate that speech motor control is based on a running internal estimate of the dynamic state of orofacial effectors (based on position and velocity estimates) and its effect on sensory outputs in relation to the intended phonemic goal (e.g., Tian & Poeppel, 2010, 2012, 2013; Guenther & Vladusich, 2012; Hickok, 2012; Perkell, 2012; Hickok et al., 2011; Houde & Nagarajan, 2011; Price et al., 2011; Guenther, 2006). In these models, it is assumed that an internal forward model of the vocal tract, which captures the relationships between speech motor commands and their sensory consequences, is gradually learned by the CNS during language acquisition. Once mature and based on an estimate of the dynamic state of the actual vocal tract, the internal forward model can provide accurate predictions of sensory outputs of planned motor commands and, in relation to actual sensory feedback, can make ongoing adjustments to the articulatory trajectory being generated.

By providing evidence for neural adaptive changes through repeated overt speech actions in the premotor cortex, the superior parietal cortex, and the transverse and superior temporal gyri, our results appear in line with these models and an internal state estimate of orofacial speech effectors in somatosensory–motor spaces in relation to the intended phonemic action goal. We will here discuss aspects of the observed RS in light of these models. First, these adaptive changes occurred during the overt production of overlearned syllables with clear auditory feedback, whereas sensory–motor state estimation has been proposed to be strongly recruited in case of complex articulatory speech sequences and/or altered auditory feedback (Guenther & Vladusich, 2012). This result appears in line with previous electroencephalographic and magnetoencephalographic studies and confirms that motor-to-sensory predictions are also performed for “simple” speech stimuli (e.g., Heinks-Maldonado et al., 2006; Ford & Mathalon, 2004; Houde et al., 2002; Numminen & Curio, 1999). Second, because RS during repeated overt silent and audible orofacial actions were observed in the same parieto-frontal regions as for syllables, our results also suggest similar motor-to-somatosensory state estimation processes for nonspeech orofacial actions. On the other hand, RS observed for overt actions was stronger for syllables in the right premotor and adjacent primary motor cortices and was restricted to speech actions in the auditory cortex. In our view, these results might partly come from well-learned motor and auditory representations and their interactions for syllables. This hypothesis is partly supported by the stronger activity observed for orofacial actions compared with speech actions in motor areas, possibly reflecting higher sustained motor demands for less automated orofacial actions. Third, somatosensory–motor adaptive changes were also observed in the same premotor and posterior parietal regions for imagined actions. This finding suggests that somatosensory state estimation processes for speech and nonspeech orofacial actions occur even in the absence of overt motor behavior and sensory feedback. This fits well with the view that mental simulation and actual execution of an action share similar motor preparation and coordination processes and that motor imagery depends on internal sensory–motor simulation (for reviews, see Jeannerod, 1994, 2001). This result also suggests that efference copies are automatically sent to the sensory systems even when corrective motor adjustments related to the intended proprioceptive targets are not needed (Tian & Poeppel, 2010, 2012, 2013). Importantly, no RS and auditory activity were observed in the covert mode, even for audible orofacial and speech actions. As previously mentioned, this finding likely reflects a motor rather than an auditory imagery strategy here used by the participants. From that view, a recent magnetoencephalographic study demonstrate early RS in the auditory cortex in an auditory imagery task (with participants instructed to imagine hearing a cued syllable), whereas early repetition enhancement was found during a motor imagery task (with participants instructed to imagine saying a syllable without any movements; Tian & Poeppel, 2013). Hence, although auditory activity and reduced neural responses compared with speech perception have been shown to occur during covert speech production (e.g., Tian & Poeppel, 2010, 2013; Numminen & Curio, 1999), participants might have rather relied on internal motor and somatosensory processes in this study. The observed RS in premotor, somatosensory, and auditory regions during overt speech production, but only in premotor and somatosensory regions during covert speech production, also indirectly suggests the existence of distinct internal simulation processes for somatosensory and auditory state monitoring. From that view, a systematic priority for auditory feedback processing (Feng et al., 2011) or a speaker-dependent reliance on either somatosensory or auditory feedback (Lametti et al., 2012) was observed during speech production when somatosensory and auditory feedback were altered alone or in combination. Whether motor, auditory, and somatosensory speech signals are integrated in the human brain remains to be further explored.

Acknowledgments

This study was supported by research grants from the Centre National de la Recherche Scientifique (CNRS) and the Agence Nationale de la Recherche (ANR SPIM—Imitation in speech: from sensorimotor integration to the dynamics of conversational interaction). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. We thank Pascal Perrier for helpful discussions.

Reprint requests should be sent to Marc Sato, Laboratoire Parole & Langage, UMR 7309 CNRS & Aix-Marseille Université, 5 avenue Pasteur, 13100 Aix-en-Provence, France, or via e-mail: marc.sato@lpl-aix.fr.

REFERENCES

REFERENCES
Ashburner
,
J. T.
, &
Friston
,
K. J.
(
2005
).
Unified segmentation.
Neuroimage
,
26
,
839
851
.
Barch
,
D. M.
,
Sabb
,
F. W.
,
Carter
,
C. S.
,
Braver
,
T. S.
,
Noll
,
D. C.
, &
Cohen
,
J. D.
(
1999
).
Overt verbal responding during fMRI scanning: Empirical investigations of problems and potential solutions.
Neuroimage
,
10
,
642
657
.
Birn
,
R. M.
,
Bandettini
,
P. A.
,
Cox
,
R. W.
, &
Shaker
,
R.
(
1999
).
Event-related fMRI of tasks involving brief motion.
Human Brain Mapping
,
7
,
106
114
.
Bohland
,
J. W.
, &
Guenther
,
F. H.
(
2006
).
An fMRI investigation of syllable sequence production.
Neuroimage
,
32
,
821
841
.
Bonini
,
L.
,
Rozzi
,
S.
,
Serventi
,
F. U.
,
Simone
,
L.
,
Ferrari
,
P. F.
, &
Fogassi
,
L.
(
2010
).
Ventral premotor and inferior parietal cortices make distinct contribution to action organization and intention understanding.
Cerebral Cortex
,
20
,
1372
1385
.
Bonini
,
L.
,
Serventi
,
F. U.
,
Simone
,
L.
,
Rozzi
,
S.
,
Ferrari
,
P. F.
, &
Fogassi
,
L.
(
2011
).
Grasping neurons of monkey parietal and premotor cortices encode action goals at distinct levels of abstraction during complex action sequences.
Journal of Neuroscience
,
31
,
5876
5887
.
Brown
,
S.
,
Ngan
,
E.
, &
Liotti
,
M.
(
2008
).
A larynx area in the human motor cortex.
Cerebral Cortex
,
18
,
837
845
.
Cai
,
S.
,
Ghosh
,
S. S.
,
Guenther
,
F. H.
, &
Perkell
,
J. S.
(
2011
).
Focal manipulations of formant trajectories reveal a role of auditory feedback in the online control of both within-syllable and between-syllable speech timing.
Journal of Neuroscience
,
31
,
16483
16490
.
Chong
,
T. T.
,
Cunnington
,
R.
,
Williams
,
M. A.
,
Kanwisher
,
N.
, &
Mattingley
,
J. B.
(
2008
).
fMRI adaptation reveals mirror neurons in human inferior parietal cortex.
Current Biology
,
18
,
1576
1580
.
Christoffels
,
I. K.
,
Formisano
,
E.
, &
Schiller
,
N. O.
(
2007
).
Neural correlates of verbal feedback processing: An fMRI study employing overt speech.
Human Brain Mapping
,
28
,
868
879
.
Christoffels
,
I. K.
,
van de Ven
,
V.
,
Waldorp
,
L. J.
,
Formisano
,
E.
, &
Schiller
,
N. O.
(
2011
).
The sensory consequences of speaking: Parametric neural cancellation during speech in auditory cortex.
PLoS One
,
6
,
e18307
.
Dhanjal
,
N. S.
,
Handunnetthi
,
L.
,
Patel
,
M. C.
, &
Wise
,
R. J.
(
2008
).
Perceptual systems controlling speech production.
Journal of Neuroscience
,
28
,
9969
9975
.
Dinstein
,
I.
,
Hasson
,
U.
,
Rubin
,
N.
, &
Heeger
,
D. J.
(
2007
).
Brain areas selective for both observed and executed movements.
Journal of Neurophysiology
,
98
,
1415
1427
.
Eickhoff
,
S. B.
,
Stephan
,
K. E.
,
Mohlberg
,
H.
,
Grefkes
,
C.
,
Fink
,
G. R.
,
Amunts
,
K.
,
et al
(
2005
).
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data.
Neuroimage
,
25
,
1325
1335
.
Feng
,
Y.
,
Gracco
,
V. L.
, &
Max
,
L.
(
2011
).
Integration of auditory and somatosensory error signals in the neural control of speech movements.
Journal of Neurophysiology
,
106
,
667
679
.
Filimon
,
F.
,
Nelson
,
J. D.
,
Huang
,
R. S.
, &
Sereno
,
M. I.
(
2009
).
Multiple parietal reach regions in humans: Cortical representations for visual and proprioceptive feedback during on-line reaching.
The Journal of Neuroscience
,
29
,
2961
2971
.
Ford
,
J. M.
, &
Mathalon
,
D. H.
(
2004
).
Electrophysiological evidence of corollary discharge dysfunction in schizophrenia during talking and thinking.
Journal of Psychiatric Research
,
38
,
37
46
.
Francis
,
B. A.
, &
Wonham
,
W. M.
(
1976
).
The internal model principle of control theory.
Automatica
,
12
,
457
651
.
Friston
,
K.
(
2005
).
A theory of cortical responses.
Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences
,
360
,
815
836
.
Friston
,
K.
(
2011
).
What is optimal about motor control?
Neuron
,
72
,
488
498
.
Friston
,
K.
(
2012
).
Predictive coding, precision and synchrony.
Cognitive Neuroscience
,
3
,
238
239
.
Friston
,
K. J.
,
Holmes
,
A. P.
,
Poline
,
J. B.
,
Grasby
,
P. J.
,
Williams
,
S. C.
,
Frackowiak
,
R. S.
,
et al
(
1995
).
Analysis of fMRI time-series revisited.
Neuroimage
,
2
,
45
53
.
Friston
,
K. J.
,
Holmes
,
A. P.
,
Price
,
C. J.
,
Buchel
,
C.
, &
Worsley
,
K. J.
(
1999
).
Multisubject fMRI studies and conjunction analyses.
Neuroimage
,
10
,
385
396
.
Ghosh
,
S. S.
,
Tourville
,
J. A.
, &
Guenther
,
F. H.
(
2008
).
A neuroimaging study of premotor lateralization and cerebellar involvement in the production of phonemes and syllables.
Journal of Speech Language and Hearing Research
,
51
,
1183
1202
.
Golfinopoulos
,
E.
,
Tourville
,
J. A.
,
Bohland
,
J. W.
,
Ghosh
,
S. S.
,
Nieto-Castanon
,
A.
, &
Guenther
,
F. H.
(
2011
).
fMRI investigation of unexpected somatosensory feedback perturbation during speech.
Neuroimage
,
55
,
1324
1338
.
Gotts
,
S. J.
,
Chow
,
C. C.
, &
Martin
,
A.
(
2012
).
Repetition priming and repetition suppression: A case for enhanced efficiency through neural synchronization.
Cognitive Neuroscience
,
3
,
227
259
.
Grabski
,
K.
,
Lamalle
,
L.
, &
Sato
,
M.
(
2012
).
Somatosensory–motor adaptation of orofacial actions in posterior parietal and ventral premotor cortices.
Plos One
,
7
,
e49117
.
Grabski
,
K.
,
Lamalle
,
L.
,
Vilain
,
C.
,
Schwartz
,
J. L.
,
Vallée
,
N.
,
Troprès
,
I.
,
et al
(
2012
).
Functional MRI assessment of orofacial articulators: Neural correlates of lip, jaw, larynx and tongue movements.
Human Brain Mapping
,
33
,
2306
2321
.
Grabski
,
K.
,
Schwartz
,
J. L.
,
Lamalle
,
L.
,
Vilain
,
C.
,
Vallée
,
N.
,
Baciu
,
M.
,
et al
(
2013
).
Shared and distinct neural correlates of vowel perception and production.
Journal of Neurolinguistics
,
26
,
384
408
.
Gracco
,
V. L.
, &
Abbs
,
J. H.
(
1985
).
Dynamic control of the perioral system during speech: Kinematic analyses of autogenic and nonautogenic sensorimotor processes.
Journal of Neurophysiology
,
54
,
418
432
.
Gracco
,
V. L.
,
Tremblay
,
P.
, &
Pike
,
G. B.
(
2005
).
Imaging speech production using fMRI.
Neuroimage
,
26
,
294
301
.
Grafton
,
S. T.
,
Fagg
,
A. H.
, &
Arbib
,
M. A.
(
1998
).
Dorsal premotor cortex and conditional movement selection: A PET functional mapping study.
Journal of Neurophysiology
,
79
,
1092
1097
.
Grafton
,
S. T.
, &
Hamilton
,
A. F.
(
2007
).
Evidence for a distributed hierarchy of action representation in the brain.
Human Movement Science
,
26
,
590
616
.
Grill-Spector
,
K.
,
Henson
,
R.
, &
Martin
,
A.
(
2006
).
Repetition and the brain: Neural models of stimulus-specific effects.
Trends in Cognitive Science
,
10
,
14
23
.
Grill-Spector
,
K.
, &
Malach
,
R.
(
2001
).
fMR-adaptation: A tool for studying the functional properties of human cortical neurons.
Acta Psychologica (Amsterdam)
,
107
,
293
321
.
Guenther
,
F. H.
(
2006
).
Cortical interactions underlying the production of speech sounds.
Journal of Communication Disorders
,
39
,
350
365
.
Guenther
,
F. H.
, &
Vladusich
,
T.
(
2012
).
A neural theory of speech acquisition and production.
Journal of Neurolinguistics
,
25
,
408
422
.
Hall
,
D. A.
,
Haggard
,
M. P.
,
Akeroyd
,
M. A.
,
Palmer
,
A. R.
,
Summerfield
,
A. Q.
,
Elliott
,
M. R.
,
et al
(
1999
).
Sparse temporal sampling in auditory fMRI.
Human Brain Mapping
,
7
,
213
223
.
Hamilton
,
A. F.
, &
Grafton
,
S. T.
(
2009
).
Repetition suppression for performed hand gestures revealed by fMRI.
Human Brain Mapping
,
30
,
2898
2906
.
Hamilton
,
F. C.
, &
Grafton
,
S. T.
(
2006
).
Goal representation in human anterior intraparietal sulcus.
The Journal of Neuroscience
,
26
,
1133
1137
.
Heinks-Maldonado
,
T. H.
,
Nagarajan
,
S. S.
, &
Houde
,
J. F.
(
2006
).
Magnetoencephalographic evidence for a precise forward model in speech production.
NeuroReport
,
17
,
1375
1379
.
Henson
,
R. N.
(
2012
).
Repetition accelerates neural dynamics: In defense of facilitation models.
Cognitive Neuroscience
,
3
,
240
241
.
Hetu
,
S.
,
Gregoire
,
M.
,
Saimpont
,
A.
,
Coll
,
M. P.
,
Eugene
,
F.
,
Michon
,
P. E.
,
et al
(
2013
).
The neural network of motor imagery: An ALE meta-analysis.
Neuroscience & Biobehavioral Reviews
,
37
,
930
949
.
Hickok
,
G.
(
2012
).
Computational neuroanatomy of speech production.
Nature Reviews Neuroscience
,
13
,
135
145
.
Hickok
,
G.
,
Houde
,
J.
, &
Rong
,
F.
(
2011
).
Sensorimotor integration in speech processing: Computational basis and neural organization.
Neuron
,
69
,
407
422
.
Houde
,
J. F.
, &
Jordan
,
M. I.
(
1998
).
Sensorimotor adaptation in speech production.
Science
,
279
,
1213
1216
.
Houde
,
J. F.
, &
Nagarajan
,
S. S.
(
2011
).
Speech production as state feedback control.
Frontiers in Human Neuroscience
,
5
,
82
.
Houde
,
J. F.
,
Nagarajan
,
S. S.
,
Sekihara
,
K.
, &
Merzenich
,
M. M.
(
2002
).
Modulation of the auditory cortex during speech: An MEG study.
Journal of Cognitive Neuroscience
,
14
,
1125
1138
.
Jeannerod
,
M.
(
1994
).
The representing brain. Neural correlates of motor intention and imagery.
Behavioral and Brain Sciences
,
17
,
187
245
.
Jeannerod
,
M.
(
2001
).
Neural simulation of action: A unifying mechanism for motor cognition.
Neuroimage
,
14
,
S103
S109
.
Jones
,
J. A.
, &
Munhall
,
K. G.
(
2000
).
Perceptual calibration of F0 production: Evidence from feedback perturbation.
Journal of the Acoustical Society of America
,
108
,
1246
1251
.
Kawato
,
M.
(
1999
).
Internal models for motor control and trajectory planning.
Current Opinion in Neurobiology
,
9
,
718
727
.
Kawato
,
M.
,
Furukawa
,
K.
, &
Suzuki
,
R.
(
1987
).
A hierarchical neural network model for the control and learning of voluntary movements.
Biological Cybernetics
,
56
,
1
17
.
Kilner
,
J. M.
,
Neal
,
A.
,
Weiskopf
,
N.
,
Friston
,
K. J.
, &
Frith
,
C. D.
(
2009
).
Evidence of mirror neurons in human inferior frontal gyrus.
The Journal of Neuroscience
,
29
,
10153
10159
.
Lametti
,
D. R.
,
Nasir
,
S. M.
, &
Ostry
,
D. J.
(
2012
).
Sensory preference in speech production revealed by simultaneous alteration of auditory and somatosensory feedback.
The Journal of Neuroscience
,
32
,
9351
9358
.
Lancaster
,
J. L.
,
Woldorff
,
M. G.
,
Parsons
,
L. M.
,
Liotti
,
M.
,
Freitas
,
C. S.
,
Rainey
,
L.
,
et al
(
2000
).
Automated Talairach atlas labels for functional brain mapping.
Human Brain Mapping
,
10
,
120
131
.
Larsson
,
J.
, &
Smith
,
A. T.
(
2012
).
fMRI repetition suppression: Neuronal adaptation or stimulus expectation?
Cerebral Cortex
,
22
,
567
576
.
Liepmann
,
H.
(
1908
).
Apraxie.
In
J. S.
Brown
(Ed.),
Agnosia and apraxia: Selected papers of Liepmann, Lange and Potzl
.
Hillsdale, NJ
:
Lawrence Erlbaum Associates
.
Lingnau
,
A.
,
Gesierich
,
B.
, &
Caramazza
,
A.
(
2009
).
Asymmetric fMRI adaptation reveals no evidence for mirror neurons in humans.
Proceedings of the National Academy of Sciences, U.S.A.
,
106
,
9925
9930
.
Majdandžić
,
J.
,
Bekkering
,
H.
,
van Schies
,
H. T.
, &
Toni
,
I.
(
2009
).
Movement-specific repetition suppression in ventral and dorsal premotor cortex during action observation.
Cerebral Cortex
,
19
,
2736
2745
.
Murphy
,
K.
,
Corfield
,
D. R.
,
Guz
,
A.
,
Fink
,
G. R.
,
Wise
,
R. J.
,
Harrison
,
J.
,
et al
(
1997
).
Cerebral areas associated with motor control of speech in humans.
Journal of Applied Physiology
,
83
,
1438
1447
.
Nasir
,
S. M.
, &
Ostry
,
D. J.
(
2006
).
Somatosensory precision in speech production.
Current Biology
,
16
,
1918
1923
.
Noppeney
,
U.
, &
Penny
,
W.
(
2006
).
Two approaches to repetition suppression.
Human Brain Mapping
,
27
,
411
416
.
Numminen
,
J.
, &
Curio
,
G.
(
1999
).
Differential effects of overt, covert and replayed speech on vowel-evoked responses of the human auditory cortex.
Neuroscience Letters
,
272
,
29
32
.
Oldfield
,
R. C.
(
1971
).
The assessment and analysis of handedness: The Edinburgh inventory.
Neuropsychologia
,
9
,
97
114
.
Özdemir
,
E.
,
Norton
,
A.
, &
Schlaug
,
G.
(
2006
).
Shared and distinct neural correlates of singing and speaking.
Neuroimage
,
33
,
628
635
.
Perkell
,
J. S.
(
2012
).
Movement goals and feedback and feedforward control mechanisms in speech production.
Journal of Neurolinguistics
,
25
,
382
407
.
Price
,
C. J.
,
Crinion
,
J. T.
, &
MacSweeney
,
M.
(
2011
).
A generative model of speech production in Broca's and Wernicke's areas.
Frontiers in Psychology
,
2
,
237
.
Purcell
,
D. W.
, &
Munhall
,
K. G.
(
2006
).
Compensation following real-time manipulation of formants in isolated vowels.
Journal of the Acoustical Society of America
,
119
,
2288
2297
.
Riecker
,
A.
,
Ackermann
,
H.
,
Wildgruber
,
D.
,
Meyer
,
J.
,
Dogil
,
G.
,
Haider
,
H.
,
et al
(
2000
).
Articulatory/phonetic sequencing at the level of the anterior perisylvian cortex: A functional magnetic resonance imaging (fMRI) study.
Brain and Language
,
75
,
259
276
.
Riecker
,
A.
,
Mathiak
,
K.
,
Wildgruber
,
D.
,
Erb
,
M.
,
Hertrich
,
I.
,
Grodd
,
W.
,
et al
(
2005
).
fMRI reveals two distinct cerebral networks subserving speech motor control.
Neurology
,
64
,
700
706
.
Rochet-Capellan
,
A.
, &
Ostry
,
D. J.
(
2011
).
Simultaneous acquisition of multiple auditory–motor transformations in speech.
Journal of Neuroscience
,
31
,
2657
2662
.
Sato
,
M.
,
Baciu
,
M.
,
Lœvenbruck
,
H.
,
Schwartz
,
J. L.
,
Cathiard
,
M. A.
,
Segebarth
,
C.
,
et al
(
2004
).
Multistable representation of speech forms: An fMRI study of verbal transformations.
Neuroimage
,
23
,
1143
1151
.
Shergill
,
S. S.
,
Bullmore
,
E. T.
,
Brammer
,
M. J.
,
Williams
,
S. C.
,
Murray
,
R. M.
, &
McGuire
,
P. K.
(
2001
).
A functional study of auditory imagery.
Psychological Medicine
,
31
,
241
253
.
Shiller
,
D. M.
,
Sato
,
M.
,
Gracco
,
V. L.
, &
Baum
,
S.
(
2009
).
Perceptual recalibration of speech sounds following speech motor learning.
Journal of the Acoustical Society of America
,
125
,
1103
1113
.
Shuster
,
L. I.
, &
Lemieux
,
S. K.
(
2005
).
An fMRI investigation of covertly and overtly produced mono- and multisyllabic words.
Brain and Language
,
93
,
20
31
.
Sörös
,
P.
,
Sokoloff
,
L. G.
,
Bose
,
A.
,
McIntosh
,
A. R.
,
Graham
,
S. J.
, &
Stuss
,
D. T.
(
2006
).
Clustered functional MRI of overt speech production.
Neuroimage
,
32
,
376
387
.
Summerfield
,
C.
,
Egner
,
T.
,
Greene
,
M.
,
Koechlin
,
E.
,
Mangels
,
J.
, &
Hirsch
,
J.
(
2006
).
Predictive codes for forthcoming perception in the frontal cortex.
Science
,
314
,
1311
1314
.
Tian
,
X.
, &
Poeppel
,
D.
(
2010
).
Mental imagery of speech and movement implicates the dynamics of internal forward models.
Frontiers in Psychology
,
1
,
166
.
Tian
,
X.
, &
Poeppel
,
D.
(
2012
).
Mental imagery of speech processing: Linking motor and sensory systems through internal simulation.
Frontiers in Human Neuroscience
,
6
,
314
.
Tian
,
X.
, &
Poeppel
,
D.
(
2013
).
The effect of imagination on stimulation: The functional specificity of efference copies in speech processing.
Journal of Cognitive Neuroscience
,
25
,
1020
1036
.
Tourville
,
J. A.
,
Reilly
,
K. J.
, &
Guenther
,
F. H.
(
2008
).
Neural mechanisms underlying auditory feedback control of speech.
Neuroimage
,
39
,
1429
1443
.
Tremblay
,
S.
,
Shiller
,
D. M.
, &
Ostry
,
D. J.
(
2003
).
Somatosensory basis of speech production.
Nature
,
423
,
866
869
.
von Holst
,
E.
, &
Mittelstaedt
,
H.
(
1950
).
Das Reafferenzprinzip. Wechselwirkungen zwischen Zentralnervensystem und Peripherie.
Naturwissenchaften
,
37
,
464
476
.
Watanabe
,
J.
,
Sugiura
,
M.
,
Miura
,
N.
,
Watanabe
,
Y.
,
Maeda
,
Y.
,
Matsue
,
Y.
,
et al
(
2004
).
The human parietal cortex is involved in spatial processing of tongue movement: An fMRI study.
Neuroimage
,
21
,
1289
1299
.
Wise
,
R. J.
,
Greene
,
J.
,
Büchel
,
C.
, &
Scott
,
S. K.
(
1999
).
Brain regions involved in articulation.
Lancet
,
353
,
1057
1061
.
Wise
,
R. J.
,
Scott
,
S. K.
,
Blank
,
S. C.
,
Mummery
,
C. J.
,
Murphy
,
K.
, &
Warburton
,
E. A.
(
2001
).
Separate neural subsystems within “Wernicke's area.”
Brain
,
124
,
83
95
.
Wolpert
,
D. M.
,
Ghahramani
,
Z.
, &
Jordan
,
M. I.
(
1995
).
An internal model for sensorimotor integration.
Science
,
269
,
1880
1882
.
Yetkin
,
F. Z.
,
Hammeke
,
T. A.
,
Swanson
,
S. J.
,
Morris
,
G. L.
,
Mueller
,
W. M.
,
McAuliffe
,
T. L.
,
et al
(
1995
).
A comparison of functional MR activation patterns during silent and audible language tasks.
American Journal of Neuroradiology
,
16
,
1087
1092
.