The role of the left putamen in multilingual language production

Brain & Language 125 (2013) 307–315

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The role of the left putamen in multilingual language production Jubin Abutalebi a,b,⇑, Pasquale Anthony Della Rosa a, Anna Kaarina Castro Gonzaga a, Roland Keim a, Albert Costa c, Daniela Perani a a

Centre for Cognitive Neuroscience, Vita Salute San Raffaele University, Milan, Italy Division of Speech & Hearing Sciences, University of Hong Kong, Hong Kong c University Pompeu Fabra & Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain b

a r t i c l e

i n f o

Article history: Available online 24 April 2012 Keywords: Bilingual Left putamen Articulation VBM fMRI Language Multilingualism

a b s t r a c t Subcortical structures are a key component of bilingual language processing. For instance, there is now evidence that the head of the left caudate is involved in controlling languages in bilingual individuals. On the other hand, the left putamen is hypothesized to be involved in articulatory processes but little is known on its engagement in bilingual language processing. Here, our hypothesis was that the left putamen of multilinguals is engaged when producing words in the less proficient language. We investigated this issue with event-related functional Magnetic Resonance (er-fMRI) in a group of multilinguals (n = 14) and in monolinguals (n = 14) during a picture-naming task. Further, we hypothesized increased grey matter density in the left putamen as an effect of experience since multilinguals constantly face a major articulatory load (i.e., speaking multiple languages) during life. To test these hypotheses we measured structural differences between multilinguals and monolinguals using voxel-based morphometry (VBM). Our results indicate that multilinguals have increased activation in the left putamen for a non-native language, but only if they are not highly proficient in that language. In addition, we found increased grey matter density in the left putamen of multilinguals compared to monolinguals. These findings highlight that the multilingual brain handles a complex articulatory repertoire (i.e., dealing with multiple languages) by inducing structural plasticity in the left putamen. Ó 2012 Elsevier Inc. All rights reserved.

1. Introduction The neural circuitry underlying language production has received considerable attention within the past two decades (see for review, Abutalebi, 2008; Indefrey, 2006; Perani & Abutalebi, 2005). Functional neuroimaging studies have at first shown a number of consistent cortical activations associated with language production, and later, they revealed the associated subcortical activations. Crucially, concerning language acquisition, neuroimaging studies have clearly shown that those brain areas responsible for L1 are also involved in the acquisition of an L2 (Abutalebi, 2008; Abutalebi & Green, 2007). Functional neuroimaging studies, however, have also reported that there may be differences in the pattern of brain activity for L1 and L2, especially in the case when an individual is less proficient in an L2 (Perani & Abutalebi, 2005). Being less proficient in a language may correspond to a more extended brain representation at the neural level (i.e., in terms of the cluster extension of brain activity). These proficiency-dependent neural differences disappear once a speaker has gained suffi⇑ Corresponding author. Address: Faculty of Psychology, Vita Salute San Raffaele University, Via Olgettina 58, 20132 Milan, Italy. Fax: +39 02 26434892. E-mail address: [email protected] (J. Abutalebi). 0093-934X/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.bandl.2012.03.009

cient L2 proficiency (Green, 2003; Perani & Abutalebi, 2005). Similar results were also reported for studies investigating grammatical processing in late L2 learners that run contrary to what has been suggested on the notion of critical periods (Abutalebi, 2008). As summarized by Indefrey (2006), and Abutalebi and Green (2007), a constant finding is that at the initial stages of L2 acquisition there is additional brain activity in the left prefrontal cortex in language production. Indeed, two major neural differences in L1 and L2 processing are mostly observed: on the one hand, increased L2-related brain activity in and around the areas also mediating L1 such as Broca’s area, and on the other, the specific engagement of additional brain structures outside the left language networks such as those related to cognitive control (i.e., left prefrontal cortex, ACC, left caudate). In the first case, as proposed by Indefrey (2006), low proficiency L2 speakers could compensate for lower efficiency by driving these regions more strongly and the greater activity observed for L2 production may reflect the increased number of neurons necessary to perform a difficult task such as speaking an L2. In the second case, the specific engagement of control structures may underline that unlike L1, L2 is not processed in an automatic manner but rather in a ‘‘controlled manner’’ (Abutalebi & Green, 2007). Another interesting and nearly constant finding, as it specifically relates to the role of subcortical structures in language

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processing, is the engagement of the left caudate nucleus. As aforementioned, the caudate nucleus, apart from its functions in motor control, has been related also to cognitive control. Many recent imaging studies focusing on bilingualism have reported caudate activity for tasks where some control may be necessary such as switching between languages (Abutalebi et al., 2007, 2008; Crinion et al., 2006; Garbin et al., 2011; Wang, Kuhl, Chen, & Dong, 2009; Wang, Xue, Chen, Xue, & Dong, 2007). As to the location of the caudate activity, specifically during production tasks, switching into the weaker language was paralleled to left caudate activity (Abutalebi & Green, 2008; Abutalebi et al., 2008; Crinion et al., 2006) while bilateral caudate activity was observed during language switching in a comprehension task (Abutalebi et al., 2007). An additional subcortical structure that was involved in bilingual language processing was the left putamen (Klein, Zatorre, Milner, Meyer, & Evans, 1994). Tettamanti et al. (2005) have shown in a 11C raclopride PET study a correlation between the dopamine release in the left putamen and the reaction times of detecting phonological errors, whereas the caudate was correlated to accuracy. However, with regard to bilingualism, the left putamen has not received the same attention as the left caudate nucleus, and hence, it has been relatively neglected by neuroscientists working in this field. This is surprising since the first imaging study carried out in this field (Klein et al., 1994) clearly showed that neural differences between languages were found within the left putamen. This subcortical structure has always been included in the fronto-striatal circuit for motor control function and only recent evidence has claimed its role for articulation. Indeed, in monolinguals, it is known that dysarthria may arise following lesions to the putamen (Alexander, Naeser, & Palumbo, 1987; Wise, Greene, Büchel, & Scott, 1999). Further, functional neuroimaging has shown that it is the posterior part of the left putamen that is involved in articulation (Wise et al., 1999). However, perhaps the most striking deficit associated with putaminal lesions is the so-called Foreign Accent Syndrome (FAS) (Gurd, Bessel, Bladon, & Bamford, 1988). FAS is a rare disorder which affects speech patterns in such a way as to make the individual appear to be speaking with a foreign accent in their own native tongue (or any other language) (Kurowski, Blumstein, & Alexander, 1996). The first recorded case of this disorder appears in 1919, as a Czech patient of Pick (1919). Interestingly, a recent functional striatal mapping study on 11 patients with low-grade gliomas of the dominant striatum (Robles, Gatignol, Capelle, Mitchelle, & Duffau, 2005) represents possibly the clearest evidence for putaminal involvement in language functions, specifically phonological processing and articulation. The 11 patients all underwent striatal mapping with the use of direct electrical stimulation of the brain prior to the resection of gliomas involving the dominant striatum. During the stimulation, patients were kept awake and asked to perform tasks involving language and motor skills. The direct stimulation of the putamen and the head of the caudate nucleus had the effect of inhibiting articulatory responses though no motor effects were observed. To better characterize the role of the left putamen in bilingual language processing, we have reviewed in Table 1 the functional neuroimaging literature for those investigations that report left putaminal activity during language production and phonological tasks (see Table 1 and table legend for inclusion criteria). Inspection of Table 1 reveals that left putaminal activity is mostly encountered during L2 processing as compared to L1, and especially when L2 has been learned later in life and processed with a low-medium degree of proficiency (see table legend for details). However, some studies found L2-related, left putaminal activations also in high proficiency, early-acquisition bilinguals (Abutalebi et al., 2007; Chan et al., 2008; Frenck Mestre, Anton, Roth, Vaid, & Viallet, 2005; Meschyan & Hernandez, 2006; Wartenburger et al., 2003).

Hence, it is evident that the role of the left putamen in bilingual and multilingual language processing needs further clarification, although a more prominent role for L2 processing may not be excluded. Our present study was designed to better investigate this issue. The main purpose of the present combined fMRI and VBM work was twofold. First, we expected left putaminal structural changes, such as increased grey matter density, in multilinguals as compared to monolinguals since multilinguals constantly face throughout life a major articulatory load (i.e., speaking multiple languages). Indeed, multilinguals utilize a wider articulatory repertoire of sounds (i.e., consider a multilingual subject that has to deal with sounds from languages such as Italian, German, and English). The articulatory load in this specific case is certainly higher than that of a monolingual (who usually deals with the 30 phonemes or so of his or her single language). Hence, it is reasonable to expect neuroplasticity effects in those brain structures underlying articulation. To this aim, we measured structural differences using voxel-base morphometry (VBM). Previous research has identified changes in plasticity as a function of specific experience in the posterior hippocampus of London taxi drivers (Maguire et al., 2000), and in Heschl’s gyri (Schneider et al., 2002), and superior temporal and dorsolateral prefrontal regions (Bermudez, Lerch, Evans, & Zatorre, 2009) of musicians. In bilinguals, Mechelli et al. (2004) showed in a within-population analysis that bilinguals with early L2 acquisition and high L2 proficiency have increased grey matter (GM) density in the left inferior parietal lobule as compared to low L2 proficiency bilinguals. As aforementioned, our expectation is that multilingualism might induce increases in grey-matter density in regions associated with language articulation, and specifically the left putamen. Second, this study was also aimed at specifying in multilinguals when exactly the putamen is more engaged. For this purpose, multilingual subjects carried out a naming task during er-fMRI scanning in L1, L2 and L3. In our group, L2 represented the high proficiency (native-like) second language whereas L3 was a lowmedium proficiency language. If the left putaminal engagement is only necessary for a language with low proficiency, then we would expect its engagement only for L3. As a control condition, a monolingual group performed a picture naming task in their only language. Finally, we also compare our findings to previous studies focusing on bilingual language processing in order to better characterize the role of the left putamen.

2. Materials and methods 2.1. Subjects Fourteen healthy, right-handed multilinguals and 14 healthy age-matched Italian right-handed monolinguals were recruited for the purposes of this study after screening for any neurological or psychiatric illnesses (all females, age range 18–30 years, mean 23.5 years, standard deviation 4.5 years). All subjects (multilinguals and monolinguals) were psychology students or had recently obtained a bachelor degree in psychology. Since the percentage of males among enrolled students in Psychology Faculties is in average below 5%, we decided to include only females for the sake of homogeneity. The multilinguals came from South Tyrol, a region in Italy in which L1 is German. However Italian (L2) is also acquired early in life (i.e., kindergarten age) and widely used throughout life. The third language (L3), i.e., English, was formally learned at school. Language proficiency was assessed by formal testing with the translation tasks employed in our previous studies (Abutalebi et al., 2007; Perani et al., 1998). In detail, multilinguals had to translate four different word lists, each containing 30 words. The four word lists contained words to be translated 1) from L1 to

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Table 1 Overview on the available functional neuroimaging literature with a special emphasis of the involvement of the putamen in bilingual language processing. In detail, the table lists those neuroimaging studies that report putaminal activity for bilinguals during tasks such as naming, reading, translating, repeating, lexical decision, judgements and identification of words, phonemes and letters. We have also included a very few studies focusing on monolinguals instead (Xue & Poldrack, 2007; Xue et al., 2006). In these studies, monolingual participants were trained in foreign character identification exhibiting also left putaminal activation. However, clear passive tasks such as comprehension tasks were excluded from our review. Also, all studies that did not report putaminal activity were not included in the table. With these criteria in place, a total of 18 studies were reviewed. Our special emphasis was to investigate whether there are specific circumstances that entail left putaminal activity such as different degrees of language proficiency or different ages of L2 acquisition. The table shows that of the 18 studies reviewed 15 report left putaminal activity only for L2 and not for L1. Among the 3 studies that do not report L2 related left putaminal activity, one reported right putaminal activity for both L1 and L2 (Pillai et al., 2003) in a group of low proficiency late bilinguals; one reported right putaminal activity only for L2 in high proficiency late bilinguals (Abutalebi et al., 2008), and one reported left putaminal activity for both L1 and L2 in a group of high proficiency early bilinguals (Frenck Mestre, Anton, Roth, Vaid, & Viallet, 2005). As to question whether language proficiency may be a determinant for left putaminal activity, of the 15 studies that reported left putaminal activity for L2 only, eight studies used low-medium proficiency bilinguals while the other seven studies used high proficiency bilinguals. Moreover, all subjects of the eight studies using low proficiency bilinguals were also late bilinguals (Callan et al., 2003; Dodel et al., 2005; Golestani et al., 2006; Liu et al., 2010; Nosarti, Mechelli, Green, & Price, 2010; Price, Green, & von Studnitz, 1999; Xue & Poldrack, 2007; Xue et al., 2006). On the other hand, of the seven studies using high proficiency bilinguals, three studies used early bilinguals (Wartenburger et al., 2003; Meschyan & Hernandez, 2006; Chan et al., 2003) while the other four studies used late bilinguals (Klein et al., 1994, 1995; Klein, Watkins, Zatorre, & Milner, 2006; Price et al., 1999). Authors

Task and methods

Subjects

Task and language of putaminal activation

Klein et al. (1994) Klein et al. (1995)

PET: word repetition in L1 and L2 PET: rhyme generation, synonym generation, and translation

12 high prof. bilinguals 12 high prof., late acquisition bilinguals

Price et al. (1999)

PET: word translation and reading in L1 and L2

6 high prof., late acquisition bilinguals

Callan et al. (2003)

fMRI: follow-up study after 1 month L2 phonemes training fMRI: semantic and phonological decision tasks fMRI: semantic and grammatical judgment task

9 low prof., late acquisition

L putamen activity during repetition in L2 L putamen activity during L2 to L1 translation, repetition, and synonym generation in L2 Bilateral putaminal activity during translation Increased bilateral putaminal for the L2 phonetic contrast R putaminal activation in L1 and L2 L putamen activation for grammatical judgements in L2

Pillai et al. (2003) Wartenburger et al. (2003) Callan, Jones, Callan, and AkahaneYamada (2004) Dodel et al. (2005) Frenck Mestre et al. (2005) Klein et al. (2006)

Golestani et al. (2006) Meschyan and Hernandez (2006) Xue et al. (2006) Abutalebi et al. (2008) Xue and Poldrack (2007) Chan et al. (2008) Liu et al. (2010) Nosarti et al. (2010)

fMRI: identification of phonemes for native and L2 speakers

8 low prof, late acquisition 11 high prof, early acquisition 12 high prof., late acquisition 9 low prof., late acquisition 22 medium prof., late acquisition

fMRI + functional connectivity: sentence production in L1 and L2 fMRI: reading of L1 and L2 words and sentence production PET: word and non-word repetition

10 medium to low prof., late acquisition

fMRI: covert reading or overt production of sentences fMRI: single word reading in L1 and L2

12 mixed proficiency, late acquisition bilinguals 12 high prof., early acquisition

fMRI: L2 character identification after visual form, phonological, and semantic training fMRI: picture naming in monolingual and bilingual contexts fMRI: foreign character comparisons

12 monolinguals

fMRI: lexical decision task for L1 and L2 nouns, verbs and non-words fMRI: picture naming

11 high prof., early acquisition

fMRI: reading task with switching between L1 and L2 regular words, irregular words, and nonwords

30 medium prof., late acquisition

12 high prof. bilinguals (6 early + 6 late acquisition) 10 high prof., late acquisition

12 high prof., late acquisition 11 monolinguals

24 medium prof., late acquisition

Possible bilateral putaminal activations for L2 phoneme perception L putamen more ‘strongly linked’ during L2 sentence generation L putamen activations during word reading in L1 and L2 for early acquisition bilinguals L putamen activation during L2 word repetition, but not during non-word repetition L putaminal activation during L2 overt sentence production L putaminal activation during single word reading in L2 L putaminal activation is reported after semantic training Right putaminal activation found during L2 naming L putaminal activation increase after character identification training L putaminal activation during L2 verb but not noun identification or L1 identification Bilateral putamen activations for L2 vs. L1 contrast L putaminal activation observed during the reading task (not specified for which language)

Abbreviations: AoA: Age of Aquisition, ER-fMRI: Event-Related Functional magnetic Resonance Imaging, ERP: Event-Related Potentials, fMRI: Functional Magnetic Resonance Imaging, L: left, L1: Native language, L2: Second language, PET: Positron Emission Tomography, Prof.; language proficiency, R: right.

L2; 2) from L2 to L1; 3) from L1 to L3; and 4) from L3 to L1. On the list of words from L1 into L2, subject translations were 81.1%, correct, and from L2 to L1, they were 74.2% correct. Translation from L1 into L3 was achieved with a 64.8% accuracy, and from L3 into L1 with a 69.2% accuracy. Hence, our results revealed that the scores for L3 (English) highlight a medium level of proficiency. This is congruent with the fact that English was acquired after the age of 10 years, while German and Italian (L1 and L2, respectively) were acquired, one as the mother tongue (German), and the other between kindergarten and elementary school, thus making them both high proficiency languages. Moreover, on a self-report questionnaire, all multilingual subjects stated that German (L1) was their dominant language in terms of proficiency. The monolinguals were from mainland Italy. All subjects had a comparable level of education (multilinguals 15.8 mean years and

monolinguals 14.8 mean years of education, respectively) and socio-economic background. All subjects were screened for neurological, psychiatric and speech or language disorders. All participants reported normal vision. The study was approved by the Local Ethics Committee. Informed consent was required and obtained from all participants. 2.2. Stimuli, design, and experimental procedures 2.2.1. Multilinguals A simple picture naming task was presented to the multilingual participants. This consisted of two conditions within which presented pictures were of three colors. The color of the image indicated the language to use for naming. In the first condition (L1–L2 context) green pictures were employed for naming in

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German and blue pictures for naming in Italian. In the second condition (L1–L3 context) the picture to be named was either green (naming in German) or red (naming in English, i.e., L3). All responses were to be given overtly. For all three languages, 32 different pictures were selected from the Snodgrass and Vanderwart set (Snodgrass & Vanderwart, 1980). All pictures, 8.5  8.5 cm, were presented in both conditions. Each picture was repeated three times for each language across both conditions, totalling 96 stimuli in each of the two contexts. Four pre-randomized lists were created defining the order in which the stimuli appeared. With the criterion in place, the experimental design consisted of 2 runs for the first condition (L1–L2 context) and two runs for the second condition (L1–L3 context). For all trials, each picture was made visible on the screen for 2 s, separated from the following picture by an ISI (Inter-Stimulus Interval) of 1880, 3550, or 4950 ms for the purposes of optimizing statistical power (Dale, 1999). All stimuli were checked for naming frequency in each language, based on the norms for each of the three languages (Burnard et al., 2000; Genzel & Scheffter, 1995; Laudanna, Thornton, Brown, Burani, & Marconi, 1995). A one-way ANOVA between the languages showed that there was no significant difference for frequency (p = 0.765 ns). However, English words (L3; mean number of syllables = 1.44) were generally shorter than those from L1 (mean number of syllables = 1.78) and L2 (mean number of syllables = 2.36) A one-way ANOVA between the languages reported a significant difference for numbers of syllables (p = 0.000). However, the fact that L3 words were the shortest should have no major impact upon the experiment since L3 was the least proficient language of the subjects. Finally, no cognate words were used in the experiment. The experimental runs were randomized across contexts and subjects so that specific context biases could be avoided. It is important to underline that in the experimental paradigm employed in our study, the trials could be switch trials (if a picture to be named was preceded by one named in a different language) and by non-switch trials (if a picture to be named was preceded by the one named in the same language). In total there were 48 switch trials (for each language) and 48 non-switch trials (for each language) across two experimental conditions. For the purpose of the present study, all switch trials were discarded for the analysis. However, in order to clearly disentangle the pattern of brain activity related to naming from that related to language switching, we report online in the Supplemental material the pattern of activity related to when subjects switched from L1 into L3 at the same threshold used for all other contrasts (see below). This was performed to rule out the effects of the switch trials upon the non-switch trials used in the present experiment (see online for Supplemental material). 2.2.2. Monolinguals Italian monolingual participants were required to complete a similar naming task with the same set of 32 pictures selected from the Snodgrass and Vanderwart (1980). In this task, however, the color coding used red for producing a noun related to the picture and green for producing a verb related to the picture. As above in the multilingual paradigm (see above), all switch trials (for example, a noun to be produced occurring after a verb to be produced) were excluded from analysis. Furthermore, only nouns were used for analysis in order to match the naming tasks of the multilingual group. Stimuli were also randomized and pictures separated by a maximum interval between first and second appearance as above in the multilingual paradigm. 2.3. Procedures At the foot of the magnet bore, a translucent screen was placed to which stimuli were delivered via a projector connected to a laptop outside the magnet room. Presentation 0.10 (Neurobehavioral

Systems, Albany, CA, USA) was used for the presentation of stimuli. A mirror system inside the magnet room allowed the participants to view the translucent screen from inside the magnet, accomplished with the use of a mirror attached to the top of the head coil. Prior to entering the scanner, all participants undertook a training session on a different set of pictures in order to familiarize with the task and thus optimize performance during the experimental runs. In addition, participants were also trained to minimize head, jaw and tongue movement while naming in order to reduce the amount of movement artifacts. During scanning, the responses of the participants were delivered through a plastic tube from inside the scanner to a small microphone connected to a computer, outside the scanner room. The computer recorded responses. 2.4. Image acquisition An fMRI-event-related technique was used (3T Intera Philips body scanner, Philips Medical Systems, Best, NL, eight channelssense head coil, sense reduction factor = 2, TE = 30 ms, TR = 2400 ms, FOV = 240  240, matrix size = 128  128, 30 contiguous axial slices per volume, 210 volumes for each run, slice thickness = 4 mm). Ten dummy scans preceded each run, all of which were then discarded prior to data analysis to optimize EPI image signal. A high resolution structural MRI was obtained for all subjects during scanning (MPRAGE, 150 slice T1-weighted image, TR = 8.03 ms, TE = 4.1 ms; flip angle = 8°, TA = 4.8 min, resolution = 1 mm  1 mm  1 mm) in the axial plane. SPM5 (Welcome Department of Cognitive Neurology, London, UK), running on Matlab 6.5 (Mathworks, Natick, MA) was used for pre-processing and statistical analysis. 2.5. fMRI study 2.5.1. Image processing All data were processed and analyzed using SPM5 (Statistical parametric Mapping; Welcome Department of Cognitive Neurology, London, UK). Prior to the analysis proper, a series of pre-processing steps were completed. Slice-timing correction was employed to amend for the different times of the slices. All functional volumes were realigned to the first one in the time series to correct for between-scan motion. The third step of the pre-processing was to segment the original MRI images into grey matter and white matter in native space. Segmentation was then achieved through the application of Bayesian priors (probability maps) which estimate the different tissue distributions according to encoded knowledge of these in normal subjects. The segmented images were then spatially normalized to grey matter and white matter MNI templates from which optimized normalization parameters were obtained. These were then applied to all the functional scans and the aligned anatomical scan. Finally an 8-mm full-width, half maximum (FWHM) Gaussian kernel was used to smooth the images in order to make the data more normally distributed, thus increasing statistical analysis validity. 2.5.2. Statistical analysis For each subject, the general linear model was applied at each voxel across the whole brain. All stimulus onsets were modeled as event encoded condition-specific ‘stick-functions’. These stimulus functions were convolved with a canonical hemodynamic response function, with no dispersion or temporal derivatives. Movement parameter estimates, as produced by the realignment procedure, were applied as confound regressors to this first-level single-subject design matrices. Effects are thus assessed through the use of the General Linear model. The coordinates derived from the statistical analysis were converted from the MNI template to

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Talairach and Tournoux stereotaxic space. Three simple main effects were tested for the multilinguals and one for the monolinguals. These were: naming in L1 (non-switch trials in L1); naming in L2 (non-switch trials in L2); naming in L3 (non-switch trials in L3); and noun production in monolinguals (non-switch trials). All simple main effects were then submitted to a second level of analysis which involved testing for random effects in order to generalize effects found for the participant groups to the general population. Statistical parametric maps for the simple main effects were thresholded at p < 0.001 uncorrected at the voxel level and a cluster extent of k = 10 as a contiguity threshold in order to have a more stringent criterion for highlighting significant differences and reduce the probability of false positive results. Furthermore, in order to test whether putaminal activity is related to language proficiency, we carried out direct comparisons between L2 and L3 and vice- versa. The direct comparisons were thresholded at p < 0.001 uncorrected at the voxel level with a cluster extent of k = 10. 2.6. VBM study 2.6.1. Image processing The MRI high resolution structural scans were processed using Statistical Parametric Mapping 5 (SPM5) software (The Wellcome Department of Imaging Neuroscience, London, UK) with Matlab 7.1.0 (The Math Works, Natick, MA, USA). The images were analyzed using the optimized VBM methods, as previously described in detail by Ashburner and Friston (2000) and Good et al. (2001). We used the VBM tools written by C. Gaser (http://dbm.neuro.uni-jena.de/vbm), an extension of the SPM5 algorithms. Each participant’s original image was spatially normalized and segmented into GM, white matter, and cerebrospinal fluid (CSF), and eventually resliced with 1.0  1.0  1.0 mm voxels. In brief, SPM5 uses priors with a Bayes rule to combine the likelihood for belonging to a tissue class and the prior probability derived from prior probability maps. We instead used an experimental approach that involves the use of no prior and avoids the dependency on tissue priors. This method is implemented in the VBM5 toolbox written by C. Gaser (http://dbm.neuro.uni-jena.de/vbm) and increases classification accuracy of the different tissues and segmented images show clearer delineation. This entire process yielded ‘modulated’ and normalized GM images. All images were smoothed with a Gaussian kernel of 4 mm full width at half maximum. In this study, we analyzed only modulated data smoothed by 4mms as we had a specific hypothesis concerning the areas in which we could find differences and as for modulated images the degree of smoothing may be decreased by 70–50% as images are already partially smoothed during the modulation process. The ‘traditional’ VBM analysis compares the proportion of grey matter in each voxel, and does not account for the change in voxel size. The ‘optimized’ VBM analysis includes an algorithm that modulates each voxel with Jacobian determinants derived from the spatial normalization, thus allowing a comparison of the absolute volume of each voxel (Good et al., 2001). Thus, modulated images were used for the group comparison of GM volume differences (GMV) between multilinguals and monolinguals, to detect changes in the absolute amount of grey matter within a region (Ashburner & Friston, 2000). 2.6.2. Statistical analysis At first we calculated the total intracranial volume (TIV) by adding together grey matter volume (GMV), white matter volume (WMV), and CSF volume. Secondly, differences between multilinguals and monolinguals were assessed by using a two sample t test with only TIV as a covariate as both groups were matched for age and gender. A GM mask was further created and thresholded at a

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value of 0.75 (pixels with computed GM fraction values >75% were selected) and then used as explicit mask during the statistical analysis in order to exclude voxels with a low probability value of belonging to grey matter and with a low intersubject anatomic overlay after normalization. The threshold was set to p < 0.005 (uncorrected) and we also applied non-stationary cluster extent correction which is intended to correct for the cluster size due to local varying smoothness of the data (Hayasaka, Luan-Phan, Liberzon, Worsley, & Nichols, 2004). The cluster extent correction threshold was set to k > 40 voxels. Given our specific interest in the putamen and based on a priori knowledge (Dodel et al., 2005; Golestani et al., 2006; Klein, Milner, Zatorre, Meyer, & Evans, 1995; Klein et al., 1994), a small volume correction was then performed to study the subtle differences between multilinguals and monolinguals in this structure. The corrected significance threshold for this sub-volume of interest was set to p < 0.01, corrected for false discovery rate (FDR). 2.7. Second level ROI analysis in multilinguals (VBM and fMRI) To better interpret the significant fMRI and VBM findings and to test the association between regional grey matter volume in the putamen and brain activity during naming in each of three languages (L1–L3) within the multilingual group, supplementary analyses were also executed outside of SPM5 to explore whether BOLD values for naming in a specific language correlated with extracted putaminal grey matter volume (GMV). For these analyses, first we used the Wake Forest University (WFU) Pick Atlas (Maldjian, Laurienti, Kraft, & Burdette, 2003) to define a region of interest (ROI) consisting of the left putamen. Second, we extracted the mean BOLD signal time series in each contrast (naming in L1, naming in L2, naming in L3 contrast parameters) from the left putamen for each individual using MarsBar (Brett, Anton, Valabregue, & Poline, 2002). Specifically, a time series was extracted from the mean BOLD signal of all voxels within the mask defining the left putamen. This procedure resulted in one average time-course value for each naming condition for each putamen. Third, non-smoothed and modulated partial grey matter volumes in litres were extracted from the left putamen ROI in each subject with the Easy Volume toolbox (http://www.sbirc.ed.ac.uk/ cyril/cp_download.html). For the aim of this analysis, we performed correlation and simple regression analysis in SPSS software (v15, SPSS Inc., Chicago, Illinois). 3. Results 3.1. Behavioural results The means for percentages of errors for naming in the three languages for the multilingual group were respectively 1.04% (SD = 1.03%) for L1, 4.86% (SD = 2.62%) for L2 and 27.08% (SD = 3.65%) for L3. The mean error percentage of the monolingual group was 5.21% (SD = 1.38%). Paired sample T-tests were carried out for confronting accuracy measures between the three languages in the multilingual group as a further measurement of language proficiency. The differences in terms of percentage of errors between L1 and L2 naming (p = 0.05), L1 and L3 naming (p = 0.002), L2 and L3 naming (p = 0.003) were all significant. Technical constraints precluded the recording of voice onset times. 3.2. fMRI results 3.2.1. Multilinguals Naming in L1 entailed significant activations in the occipital associative areas bilaterally, in the premotor cortex bilaterally, in

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the left inferior frontal gyrus (BA 44/45), the left middle frontal gyrus (BA46), and the left inferior temporal gyrus and fusiform gyrus (BA 19/37). Small foci were also evident in the left anterior cingulate cortex (BA 24/32) (see Fig. 1 and Table 2). Noteworthy, naming in L2 produced patterns of activation almost identical to those found in L1. However, activations in the left frontal operculum (pars opercolaris) and in the anterior cingulate cortex (ACC) were slightly larger than that found in the L1 naming condition (see Fig. 1 and Table 2) . Naming in L3 produced activations that were the same as those found for L1 and L2 naming. However, the prefrontal activations were more extended (BA 44/45/46). Again, the pattern of brain activity in the anterior cingulate cortex and in the frontal operculum (pars opercolaris) was more extended than those observed for naming in L2. However, differently from naming in L1 and L2 conditions, naming in L3 was associated also to extensive left putaminal activation (see Fig. 1). This latter finding was also confirmed by the direct comparisons between L2 and L3. Only the direct comparison L3 vs. L2 revealed putaminal activity (see Fig. 2). 3.2.2. Monolinguals The Monolingual naming condition produced activations similar to those found for the multilingual naming in L1 (Fig. 1 and Table 2). These included bilaterally activity in occipital associative areas and the premotor cortex. Activations were also seen in the left inferior frontal gyrus (BA 44/45), left middle frontal gyrus (BA 46), left inferior temporal gyrus and fusiform gyrus (BA 19/37). 3.3. VBM results After small volume corrections, only a difference at the level of the left putamen was evident in the comparison with multilinguals

vs. monolinguals (coordinates: x = 27, y = 13, z = 3, k = 124 voxels) remained significant (Fig. 1), in the sense that multilinguals have increased grey matter density in the left putamen. The cluster probability of belonging to the left putamen was confirmed with Anatomy Toolbox (Eickoff et al., 2005). 3.4. Second level ROI correlation analysis in multilinguals (VBM and fMRI) The correlational analysis between brain activity (i.e., naming as measured with fRMI) and grey mater density revealed that naming in L1 (r = 0.471; p = 0.169) or naming in L2 (r = 0.525; p = 0.119) were not significantly related to grey matter volume in the left putamen. However, naming in L3 was positively correlated to GMV (r = 0.740; p = 0.014) and predicted in a significant manner grey matter volume in the left putamen (t = 3.108). 4. Discussion The present study was aimed at investigating the differences in fMRI activation and grey matter volume in multilinguals, and specifically addressing the role of the left putamen in multilingual language production. For this purpose, we carried out a comparative VBM and er-fMRI study in multilinguals and monolinguals. Our results highlight that multilinguals have increased activation in the left putamen for L3 only, the language mastered with the least proficiency. As to this functional role of the left putamen, we suggest that it is specifically engaged when multilinguals use a language that is not mastered in a native-like fashion. We observed increased activation of left subcortical structures together with the anterior cingulate cortex for L3 production. This may represent the neural marker of language control which was already reported

Fig. 1. The 2nd level T-maps are overlaid and rendered on the mean structural image of the study sample (28 subjects) with MRIcron [http://www.sph.sc.edu/comd/rorden/ mricron/]. In (A) brain activity patterns for picture naming in multilinguals are reported and superimposed on the brain template. The blue color indicates naming in L1, green indicates naming in L2 and red indicates naming in L3 (color mixtures indicate that brain regions were engaged by more than one language. In (B), the neural network associated to picture naming for monolinguals. Finally, in (C), the VBM analysis showing increased GM values found in the left putamen for multilinguals as compared to monolinguals.

J. Abutalebi et al. / Brain & Language 125 (2013) 307–315 Table 2 Stereotactical coordinates related to picture naming in multilinguals, respectively for L1, L2 and L3 (a, b, c) and monolinguals (d). Area (a) L1 naming in multilinguals L inferior frontal gyrus L pre-SMA L pre-central gyrus L post-central gyrus L superior temporal gyrus L precuneus L thalamus R pre-central gyrus R middle temporal gyrus R superior occipital gyrus R putamen (b) L2 naming in multilinguals L SMA L inferior frontal gyrus L anterior cingulate cortex L superior temporal gyrus

L post-central gyrus L superior occipital gyrus L thalamus R anterior cingulate cortex L pre-central gyrus R post-central gyrus R middle temporal gyrus R inferior occipital gyrus (c) L3 naming in multilinguals L inferior frontal gyrus

L L L L

anterior cingulate cortex middle frontal gyrus precentral gyrus superior temporal gyrus

L precuneus L superior occipital gyrus L inferior occipital gyrus L putamen L thalamus R pre-SMA R precentral gyrus R superior temporal gyrus R superior/middle temporal gyrus (d) Naming in monolinguals L inferior frontal gyrus L L L L

precentral gyrus SMA pre-SMA superior temporal gyrus

L medial temporal gyrus L precuneus L superior occipital gyrus L middle occipital gyrus L inferior occipital/fusiform gyrus R anterior cingulate cortex R pre-central gyrus R post-central gyrus R medial occipital gyrus

Coordinates

Zvalue

Brodmann’s area

48, 6, 0 40, 30, 16 4, 2, 56 44, 14, 32 20, 28, 60

5.31 3.55 3.97 4.85 4.38

44/45

58, 6, 4 24, 68, 44 8, 20, 4 62, 0, 16 54, 12, 12 32, 76, 24 30, 86, 0 26, 10, 4

5.07 4.57 4.43 5.17 4.32 3.85 5.15 4.01

22 7

4, 4, 56 44, 24, 24 2, 20, 44 60, 4, 4 48, 6, 8 50, 6, 4 22, 28, 56 24, 68, 24

4.25 4.52 3.63 5.21 5.06 4.98 4.14 4.57

6 44/45 24 22 22 22 2 19

32, 20, 4 6, 20, 36 62, 0, 16 50, 10, 32 22, 28, 60 50, 30, 4 36, 78, 0

4.07 3.49 5.02 4.9 4.47 3.85 5.13

32 6 4 4 21 18

32, 24, 4 50, 6, 12 50, 36, 12 44, 2, 32 6, 14, 40 52, 24, 28 44, 2, 32 52, 18, 4 34, 12, 4 24, 64, 44 28, 78, 28 34, 84, 4 24, 6, 0 12, 20, 8 6, 12, 52 64, 0, 24 34, 24, 4 50, 24, 0

4.73 5.1 4.1 4.34 4.73 4.13 4.34 3.78 4.54 3.89 3.44 5.06 3.77 3.99 5.13 3.72 4.13 4.72

45 44 46 44 32 9 4/6 22 22 7 19 18

46, 8, 32 56, 10, 8 52, 6, 28 2, 2, 64 2, 10, 52 56, 18, 8 44, 36, 16 20, 2, 24 24, 64, 40 28, 74, 28 30, 92, 4 26, 90, 8 2, 16, 44 58, 6, 44 64, 4, 16 20, 28, 60 38, 84, 4

3.61 3.83 5.42 4.78 4.36 4.92 3.41 3.94 4.32 3.74 5.14 5.08 4.14 5.51 5.19 4.24 5.53

44 44 6 6 6 42 22 28 19 19 19 18/37 32 4 6/4 2 18/19

6 4/6 2

6 21 19 18

6 4/6 22 22/21

when multilinguals have to produce in L2 or L3 (see for review, Abutalebi & Green, 2007). However, among subcortical structures,

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the role of language control is generally ascribed to the left head of the caudate (Abutalebi & Green, 2007), while the left putamen was reported mostly to be involved in phonological processing (Tettamanti et al., 2005) and articulation (Nota & Honda, 2004). In addition to our functional findings, we found increased grey matter density in the left putamen of multilinguals as compared to monolinguals. Our hypothesis for the increased grey matter density in the left putamen relies on the effect of experience, i.e., in the sense of dealing and mastering an increased articulatory repertoire (as compared to monolinguals). We will discuss these findings in detail and, then compare our findings with those of the literature reviewed above. It is well known that subcortical structures may have a role in language processing (Cappa & Abutalebi, 1999; Crosson, 1985). For instance, an entire subgroup of aphasia has been linked to subcortical lesions, specifically to lesions involving the thalamus, the basal ganglia in general, or periventricular white matter tracts (Boissezon et al., 2005). Nevertheless, it should also be specified that subcortical structures do not have per se a role in language representation but rather contribute to language processing with auxiliary functions such as control and attentive functions (Abutalebi & Green, 2007). In the case of bilingualism, it is now well established that the left caudate has a prominent role in monitoring and controlling languages. For instance, lesions to the left caudate may disrupt this language control system and the bilingual speaker may involuntarily start to mix and switch the two languages (Abutalebi, Della Rosa, Tettamanti, Green, & Cappa, 2009; Abutalebi, Miozzo, & Cappa, 2000; Mariën, Abutalebi, Engelborghs, & De Deyn, 2005). The crucial role of the left caudate in language control was further confirmed by studies employing language switching paradigms in bilinguals (Abutalebi & Green, 2008; Abutalebi et al., 2007; Crinion et al., 2006). However, as aforementioned, less effort has been dedicated to unraveling the role of the left putamen in bilingual language processing. It should be first stressed that the role of the left putamen may be potentially different from the role of the left caudate. While many studies have now shown that the caudate is involved in language control (see for review, Abutalebi & Green, 2008), the left putamen is usually associated with L2 articulation (Frenck Mestre et al., 2005; Klein et al., 1994). Our supplemental analysis performed on the switching trials confirm this hypothesis. The rationale for the supplemental analysis was to rule out that the switching trials may have had any influence upon the non-switch trials used for the current experiment. Indeed, as expected, switching from L1 into L3 engaged large clusters of activity in the caudate nuclei (see online for the supplemental figure reporting switch trials) but no activity in the putamen. Consider also that the switch direction (i.e., from L1 into L3) is usually the most potent one for eliciting the language control network since a dominant language (such as L1 in our experiment) has to be inhibited in order to select words in a weak language (i.e., L3 in our experiment) (see Abutalebi & Green, 2007). On the other hand, as shown in Fig. 2, naming in L3 as compared to L2, entails brain activity in the left putamen and a relatively small foci of activity in the caudates (if compared to the large cluster of activity found during the switching trials as reported online in the supplemental figure). This finding may be interpreted as, first, a major articulatory load for producing words in L3 (i.e., left putaminal activity), and second, the engagement of language control resources for producing words in a weak language (i.e., caudate activity). Indeed, it is well known that a simple naming task may be sufficient to engage the language control network when bilinguals or multilinguals have to produce words in the non-dominant language (Abutalebi & Green, 2007). Taken together, our hypothesis is that the left putaminal activation is correlated to language production in a non-native language that is mastered with less proficiency. This is in line with the

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Fig. 2. Direct comparisons between L2 and L3 in multilinguals. In (A) L2 vs. L3 and in (B) L3 vs. L2. Only the latter contrast was associated to left putaminal activity.

conclusions of Frenck Mestre et al. (2005) wherein putaminal activity was hypothesized to be proficiency-specific. In the present study we provide, in the same group of subjects, the evidence that the engagement of the left putamen may be proficiency-related. Our subjects had a high proficiency L2 and a medium proficiency L3, hence, providing an ideal testing ground. Only the medium proficiency language (i.e., L3) was associated with left putaminal activity but not the high proficiency L2. This latter finding was evident already at the level of the simple main effects and was further confirmed by the direct comparisons between L3 and L2 (see Fig. 2). Further, a correlation analysis between the GM volume of the left putamen and the functional data revealed that only naming in L3 was significantly correlated to the GM increase in the left putamen. However, we do not rule out that our functional differences may be also age-of-acquisition related since only L3 was acquired around the age of puberty while L2 was acquired at kindergarten. Inspection of Table 1 shows that in those studies that report putaminal activity, it is usually present in late acquisition bilinguals except in two studies where it was found in early bilinguals (Frenck Mestre et al., 2005; Chan et al., 2008). As to our structural findings, it is noteworthy that we found a GM increase in the multilingual group. These findings may further characterize the functional role of the left putamen in multilingual and bilingual language processing. Our proposal is that the left putamen is involved, in general, in articulation and phonology processes and that these specific functions are more prominent when it comes to processing non-native language phonology and articulation. A further indication of this specific function may be derived when observing the connections of the left putamen. Dodel et al. (2005) reported in a functional connectivity analysis that the left putamen is more strongly linked to the left inferior frontal gyrus (pars opercolaris) during L2 but not L1 sentence generation in low to moderate proficiency bilinguals. The pars opercolaris is crucially involved, among other functions, in phonology. It is interesting to observe that recent studies report a parallelism between left putaminal activity and left pars opercolaris activity for L2 production but not for L1 (Golestani et al., 2006; Liu, Hu, Guo, & Peng, 2010; Xue, Chen, Jin, & Dong, 2006). It is, therefore, striking that in our study we have observed a gradual increase for the languages of the left pars opercolaris activity. Left pars opercolaris activity was more extended for L2 than L1, and was even more extended for L3 (and for the latter language paralleled by left putaminal activity) (see Fig. 1). Thus, we suggest that processing several languages may specifically entail the intervention of brain areas related to phonology and articulation in general, especially in the case of a language that is not mastered in a native like fashion, such as the L3 in our study. An alternative interpretation of our findings may be that the putaminal activity reflects the fact that the motor planning and articulation of words in the participants’ L3 may be less automatic than those of their L1 and L2. In other words, speaking in L3 would entail more controlled processing than speaking in

L1 or L2. Following this interpretation, the role of the left putamen would be to control articulation for a less proficient language. In conclusion, we suggest that the role of the left putamen is crucial in supporting the major articulatory load and motor planning of speech in multilingual speakers. This subcortical brain structure is thus susceptible to structural brain changes induced by bi- and multilingualism. Its GM densities are increased as compared to monolinguals as reported in the present study, underlining the fact that a multilingual speaker has an increased phonological and articulatory repertoire. Dealing with an increased articulatory repertoire is a prerequisite for successfully speaking of a non-native language. The multilingual brain handles this situation by structural plasticity in the left putamen. Acknowledgments This study was partially supported by the Sparkassenstiftung, Brixen, Italy to J.A. and R.K; and by grants from the Spanish government (PSI2008-01191, Consolider Ingenio 2010 CSD2007-00012) and the Catalan government (Consolidado SGR 2009-1521) to A.C. The authors are also grateful to three anonymous reviewers and to Mr. Sumeer Chadha for their helpful comments on an earlier version of the manuscript. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.bandl.2012.03. 009. References Abutalebi, J. (2008). Neural processing of second language representation and control. Acta Psychologica, 128, 466–478. Abutalebi, J., Annoni, J. M., Zimine, I., Pegna, A. J., Seghier, M. L., Lee-Jahnke, H., et al. (2008). Language control and lexical competition in bilinguals: An event-related fMRI study. Cerebral Cortex, 18, 1496–1505. Abutalebi, J., Brambati, S. M., Annoni, J. M., Moro, A., Cappa, S. F., & Perani, D. (2007). The neural cost of the auditory perception of language switches. An eventrelated functional magnetic resonance imaging study in bilinguals. The Journal of Neuroscience, 27, 13762–13769. Abutalebi, J., Della Rosa, P. A., Tettamanti, M., Green, D. W., & Cappa, S. F. (2009). Bilingual aphasia and language control: A follow-up fMRI and intrinsic connectivity study. Brain & Language, 109, 141–156. Abutalebi, J., & Green, D. (2007). Bilingual language production: The neurocognition of language representation and control. Journal of Neurolinguistics, 20, 242–275. Abutalebi, J., & Green, D. (2008). Control mechanisms in bilingual language production: Neural evidence from language switching studies. Language and Cognitive Processes, 23, 557–582. Abutalebi, J., Keim, R., Brambati, S. M., Tettamanti, M., Cappa, S. F., De Bleser, R., et al. (2007). Late acquisition of literacy in a native language. Human Brain Mapping, 28, 19–33. Abutalebi, J., Miozzo, A., & Cappa, S. F. (2000). Do subcortical structures control ‘language selection’ in polyglots? Evidence from pathological language mixing. Neurocase, 6, 51–56.

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