Involuntary switching into the native language induced by electrocortical stimulation of the superior temporal gyrus: a multimodal mapping study.

Neuropsychologia 62 (2014) 87–100

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Involuntary switching into the native language induced by electrocortical stimulation of the superior temporal gyrus: A multimodal mapping study Barbara Tomasino a,n, Dario Marin a,1, Cinzia Canderan a, Marta Maieron b, Riccardo Budai d, Franco Fabbro a,e, Miran Skrap c a

IRCCS “E. Medea”, Polo Regionale del Friuli Venezia Giulia, via della Bontà, 7, San Vito al Tagliamento, PN 33078, Italy Fisica Medica A.O.S. Maria della Misericordia, Udine, Italy Unità Operativa di Neurochirurgia, A.O.S. Maria della Misericordia, Udine, Italy d Unità Operativa di Neurologia, Neurofisiopatologia, A.O.S. Maria della Misericordia, Udine, Italy e Dipartimento di Scienze Umane, Università di Udine, Italy b c

art ic l e i nf o

a b s t r a c t

Article history: Received 27 September 2013 Received in revised form 11 July 2014 Accepted 12 July 2014 Available online 21 July 2014

We describe involuntary language switching from L2 to L1 evoked by electro-stimulation in the superior temporal gyrus in a 30-year-old right-handed Serbian (L1) speaker who was also a late Italian learner (L2). The patient underwent awake brain surgery. Stimulation of other portions of the exposed cortex did not cause language switching as did not stimulation of the left inferior frontal gyrus, where we evoked a speech arrest. Stimulation effects on language switching were selective, namely, interfered with counting behaviour but not with object naming. The coordinates of the positive site were combined with functional and fibre tracking (DTI) data. Results showed that the language switching site belonged to a significant fMRI cluster in the left superior temporal gyrus/supramarginal gyrus found activated for both L1 and L2, and for both the patient and controls, and did not overlap with the inferior frontooccipital fasciculus (IFOF), the inferior longitudinal fasciculus (ILF) and the superior longitudinal fasciculus (SLF). This area, also known as Stp, has a role in phonological processing. Language switching phenomenon we observed can be partly explained by transient dysfunction of the feed-forward control mechanism hypothesized by the DIVA (Directions Into Velocities of Articulators) model (Golfinopoulos, E., Tourville, J. A., & Guenther, F. H. (2010). The integration of largescale neural network modeling and functional brain imaging in speech motor control. NeuroImage, 52, 862–874). & 2014 Elsevier Ltd. All rights reserved.

Keywords: L2 learner Language switching Superior temporal gyrus Multimodal mapping fMRI Awake surgery

1. Introduction During language switching, language A is inhibited in favour of language B (Abutalebi, 2008). Despite the neural basis of switching is relevant for the study of bilingualism (Luk, Green, Abutalebi, & Grady, 2012), a few neuropsychological studies have described language switching phenomena. Unfortunately, these studies do not provide functional imaging (fMRI) and diffusion tensor imaging (DTI) information. It has been shown that language switching can be evoked through electrocortical stimulation during awake brain surgery.

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Corresponding author. Tel.: þ 39 0434 842.711; fax: þ39 0434 842.797. E-mail address: [email protected] (B. Tomasino). 1 Co-first author.

http://dx.doi.org/10.1016/j.neuropsychologia.2014.07.011 0028-3932/& 2014 Elsevier Ltd. All rights reserved.

The existence of a language switching mechanism has been postulated following the observations made by Penfield and Roberts (1959) in their electro-cortical stimulation mapping studies and it has been described as an automatic mechanism that turns off one language when the other language is on. Another study has described language switching (French to Chinese) following electro-cortical stimulation of the pars opercularis of the left inferior frontal gyrus and three other sites in the temporal–parietal area while the patient was counting (Kho et al., 2007). This study also reported a language switching (Dutch to English) phenomenon in another patient while he was performing WADA sentence reading, object naming and memory recall tasks. In another study, language switching was described during electro-cortical stimulation of the posterior part of the left superior temporal sulcus and the superior longitudinal fasciculus (Moritz-Gasser & Duffau, 2009b). The patient, a French–English

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B. Tomasino et al. / Neuropsychologia 62 (2014) 87–100

bilingual with a glioma in the left posterior temporal lobe, involuntarily switched from French to English during an object naming task following stimulation of the posterior part of the superior temporal sulcus. The patient correctly named the items in French but suddenly switched to English. At the end of stimulation he resumed naming in French. The phenomenon was replicated during subcortical stimulation of the superior longitudinal fasciculus (SLF). In another study, the authors observed two effects of direct electrical stimulation in a bilingual Chinese–English patient (Wang, Wang, Jiang, Wang, & Wu, 2012). Stimulation of the head of the left caudate nucleus interfered with both switching between L1 and L2 during an object naming task and a colour–shape naming task, another task tapping executive functions. In addition, upon stimulation of the middle frontal gyrus, the superior frontal gyrus, the middle frontal gyrus, and the cingulate gyrus, the authors found involuntary language switching only in the L1 to L2 direction. In these areas, the interference was selective for language switching and did not affect the control colour–shape switching task. These data suggest that these areas are associated with language switching while cognitive control in general is unaffected. By contrast, cognitive control was affected by stimulation of the head of the caudate nucleus (Wang et al., 2012). Neuropsychological studies have shown that brain lesions can cause both language mixing (i.e. intermingling of languages within a single utterance) (Fabbro, Skrap, & Aglioti, 2000), and language switching (i.e. alternation of languages between self-contained speech segments). Importantly, results indicate that there is not a single brain area responsible for switching. Some neuropsychological studies indicated the supramarginal gyrus as a correlate of language switching (Herrmann & Bosch, 2001; Kauders, 1983; Potzl, 1983), others showed that a lesion involving this area did not cause switching phenomena (Gloning & Gloning, 1893; Minkowski, 2013). Other studies suggested that language mixing occurs following a lesion in the head of the caudate nucleus (Abutalebi, Miozzo, & Cappa, 2000), and that pathological switching can occur following a lesion of the left anterior cingulate gyrus and of the white matter underlying the left frontal lobe (Fabbro et al., 2000). Another study documented both language switching and language mixing in a patient with a lesion in the left thalamus and hypoperfusion of the left fronto-parietal and temporal areas as detected by SPECT (Marien, Abutalebi, Engelborghs, & De Deyn, 2005). Language switching can be disrupted or can also be evoked through transcranial magnetic stimulation (TMS). Holtzheimer, Fawaz, Wilson, and Avery (2005) used transcranial magnetic repetitive stimulation (rTMS) of the DLPFC to treat drug-resistant major depressive disorders and reported involuntary language switching in two bilingual patients: an English–German bilingual using English as first language who reported that he thought in German following the stimulation session, and an English–Spanish bilingual who reported that he thought in Spanish following the stimulation session and the will to speak in Spanish instead of English. In another stimulation study (Nardone et al., 2011), the authors reported that TMS to the left dorsolateral prefrontal cortex (DLPFC) was successful in decreasing the tendency to switch between languages in a patient with a left frontal stroke who was presenting pathological switching. These studies indicate that language switching can be evoked or, alternatively, can be damaged by stimulation of the fronto-temporo-parietal areas and the subcortical areas. Functional imaging (fMRI) studies investigating language switching in bilingualism reported somewhat inconsistent results. The left supramarginal gyrus has been found to be selectively activated during language switching (Hernandez, Dapretto, Mazziotta, & Bookheimer, 2001; Price, Green, & von, 1999). Price et al. (1999) studied a group of German–English proficient bilinguals while they were either translating or reading visually

presented words in L1, L2 or alternating L1/L2 and found that language switching increased activation in Broca's area and in the supramarginal gyrus. Hernandez et al. (2001) found that activation in the dorsolateral prefrontal cortex (DLPFC) during picture naming was related to switching between two language conditions (relative to a single language condition). In another study, mixed vs. single language condition during an object naming task activated the DLPFC in Spanish–English bilinguals (Hernandez, Martinez, & Kohnert, 2000). In another study (Hernandez, 2009) switching between languages during a picture naming task did not only elicit activation of the DLPFC but also of the superior parietal lobule. Crinion et al. (2006) found that activation of the left caudate was modulated by changes in the language for German– English and for Japanese–English bilinguals. Other fMRI studies of language switching found activation in the superior temporal sulcus, in the superior and inferior parietal lobules, in the Supplementary Motor Area (SMA), in the DLPFC, in the Inferior Frontal Gyrus (IFG), in the precentral gyrus, in the right anterior cingulate (Abutalebi et al., 2008; Khateb et al., 2007; Price et al., 1999; Rodriguez-Fornells, Rotte, Heinze, Nösselt, & Münte, 2002; Wang, Xue, Chen, Xue, & Dong, 2007; Wang, Kuhl, Chen, & Dong, 2009), see Hervais-Adelman, Moser-Mercer, and Golestani (2011) for a systematic review. Taken together, these studies indicate that language switching elicits activation in very different areas. This inconsistency could also be related to the type of task used, e.g. in Moritz-Gasser and Duffau (2009b) switching occurred during an object naming task, in Kho et al. (2007) during counting, while Fabbro et al. (2000) reported switching of sentences. Some authors argued that the DLPFC, the left IFG, and the left parietal lobule are the areas most frequently found activated (Hervais-Adelman et al., 2011). Others (Abutalebi & Green, 2007) proposed a subcortical– cortical circuit for language switching which includes the left DLPFC (which is part of the fronto-parietal attention network), the ACC (involved in cognitive control), the caudate nucleus (involved in cognitive control), the supramarginal gyrus (part of the frontoparietal attention network). Consistently with psycholinguistic models (Costa, Santesteban, & Ivanova, 2006; Costa, Hernandez, Costa-Faidella, & Sebastian-Galles, 2009; Garbin et al., 2010; Paradis, 1993, 1996, the areas involved in executive and cognitive control and inhibition are activated by language switching (Wang et al., 2007). Besides a role of the fronto-subcortical network (the control network) in language switching, some activations are more related to a language network (Hervais-Adelman et al., 2011), as evidenced by a quantitative ALE meta-analysis of imaging studies involving language switching (Luk et al., 2012). The network of areas found in the meta-analysis included the left IFG, the left middle temporal gyrus, the left middle frontal gyrus, the right precentral gyrus, the right superior temporal gyrus, the pre-SMA and the caudate nuclei bilaterally (Luk et al., 2012). Interestingly, in a review article (Simmonds, Wise, & Leech, 2011b), the authors argued that all the above-mentioned studies concentrated on the cognitive control system mechanisms implicated in language switching, neglecting a role for auditory–motor– sensory control during articulation in a second language, which ensures that a sequence of movements is performed approximating as closely as possible the speech of the second language (Simmonds et al., 2011b). They argued that speaking in a second language increases demands on articulation with a proper accent, with the goal of approximating as closely as possible the speech of native speakers, to a greater extent than when articulating in the first language. They also (Simmonds et al., 2011b) stressed the role of the auditory and somatosensory cortices, which integrate auditory memories of the target sounds and of the postarticulatory auditory and somatosensory feedbacks necessary to monitor the articulation of the utterance (Golfinopoulos et al., 2010; Hickok, Houde, & Rong, 2011).


In the present multi-modal mapping study we investigated the functional neuroanatomy of a 30-year-old Serbian speaker and a late Italian learner, who developed a transitory switch from Italian (L2) to Serbian (L1) during electro-cortical stimulation of the left posterior superior temporal gyrus. Stimulation effects on language switching selectively interfered with counting behaviour but not with object naming. We retrospectively used structural and functional brain imaging data routinely acquired for pre-surgery investigations, and combined them with intraoperative stimulation mapping as well as neuropsychological testing. The positive site in the superior posterior temporal gyrus, where we detected language switching, does not belong to the cognitive control (executive) system. Recent psycholinguistic models have suggested that the bilingual language control system is not entirely subsidiary to the general executive control system (Calabria, Hernandez, Branzi, & Costa, 2012). Therefore, our data are integrated and discussed within a different perspective, with reference to the current neurolinguistic models of speech production (Golfinopoulos et al., 2010; Hickok et al., 2011). The DIVA model has previously been applied to a case of foreign accent syndrome (Tomasino et al., 2013). In the present study we focused on the role of an auditory-sensorimotor feedback control mechanism, which could have been perturbed by the stimulation of the left posterior superior temporal gyrus. This area is an essential node of the feedback control mechanism, which compares the sensory expectations of a speech motor program and the incoming sensory feedback produced by the articulation of that sound, detects errors and corrects the current speech output. It is held that while the movements necessary to articulation of native speech are automatic, those in a late learned language are not (Simmonds, Wise, Dhanjal, & Leech, 2011a) and that altered feedback processing in the second language can cause an increased activity in auditory areas. According to this, it can be expected that stimulation of the superior posterior temporal gyrus can interfere with the auditory and somatosensory feedback for L2, which is more effortful, and left intact the feedback system for L1, which is well learned and automatic, so that the patient switched to L1 to continue carrying out the counting task.

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pre- and post-surgery) carried out in both L1 and L2 no single language switching episode occurred. In 2013 a re-growth of the glioma was evidenced. Conventional T2-weighted MR imaging revealed a hyperintense lesion harbouring the inferior temporal lobe, measuring approximately 40.4 mm3. She was admitted to hospital one month before the study. The neurological examination before surgery did not reveal the presence of focal or global neurological deficits. The patient's fMRI and DTI maps were compared with a group of 18 control monolingual native Italian speakers (12F, 6M; mean age 47.7 7 7.6 years old; age range 35–61; handedness: mean 93.98 7 9.8; range 66.66–100; education: mean 13 years). All participants had normal or corrected-to-normal vision and reported no history of neurological illness (except for the patient), psychiatric disease, or drug abuse. All gave their informed consent to participate in the study. The study was approved by the local Ethics Committee. 2.2. Neuropsychological testing The patient's performance on the Raven's Coloured Progressive Matrices (score: 33/36, cut-off 18, (Basso, Capitani, & Laiacona, 1987)) and the Mini Mental State Examination (MMSE) was normal (score 29/30, cut-off 25, (Magni et al., 1996)). Her verbal short-term memory span (WAIS Digit Span Forward) was 6/9 (cut-off 3, (Orsini et al., 1987)) and her backward span was 4 (cut-off 4, (Orsini, 2003)). The patient showed no ideomotor (72/72, (De Renzi, Motti, & Nichelli, 1980)) nor oral (20/20) apraxia. No signs of dysarthria were found, as assessed by the Italian version of the test by Robertson et al. (1982) (Fussi & Cantagallo, 1999). 2.2.1. Italian language assessment She scored 33/36 (cut-off 29) on verbal comprehension (Token test, (De Renzi & Faglioni, 1978)). Phonological, lexical-semantic and syntactic abilities were examined using the BADA (Battery for the analysis of language disorders, (Miceli, Laudanna, Burani, & Capasso, 1994)). Phonemic discrimination was in the normal range (100% correct). The patient was 60% correct at oral picture naming of nouns (87% of correct answers for high-frequency nouns and 33% of correct answers for low-frequency nouns) and 67% at oral naming of actions (79% of correct answer for high-frequency actions and 57% of correct answers for low-frequency actions). Word (96%) and pseudoword (97%) reading was normal. She was 100% correct at word and pseudoword repetition. Her performance on the Pyramids and Palm Tree Test (Gamboz, Coluccia, Iavarone, & Brandimonte, 2009) (i.e. a semantic memory test that measures the ability to access detailed semantic information necessary for the identification of analogies) was in the normal range (50/52). 2.2.2. Serbian language assessment The patient's performance on the BADA naming task (nouns and actions) in Serbian was 100% accurate. During auditory verbal discrimination and syntactic comprehension tasks (taken from the Bilingual Aphasia Test (BAT) in Serbian (Paradis & Milojkvic, 1993)) her performance was normal (100%). She was 100% correct at both repetition and lexical decision (for words and pseudowords) and reading2.

2. Material and methods 2.3. Post-surgical evaluations 2.1. Participants The patient, female, 30-year-old, 100% right-handed (Oldfield, 1971), is a native Serbian (L1) speaker and a late Italian learner (L2). She has an educational level of 17 years and works as an architect. When she was 25, she was hospitalized due to partial seizures. The MRI revealed a left temporo-basal WHO Grade II glioma (see Fig. 1). Surgery was performed under general anaesthesia. She had no post-surgical neurological or cognitive deficits. Six months after surgery the patient graduated at University. In 2011, she moved to Italy and began to learn Italian by enroling in classes for foreigners. She spoke Italian everyday with her Italian husband, as he does not speak Serbian, as well as with friends and people in everyday life. Her levels of Serbian and Italian exposure were assessed by means of a detailed questionnaire. The patient reported that her Italian proficiency was good. In a typical day she was more exposed to L2 (talking with her husband, with friends, reading newspaper, watching television, etc.) than L1. During a clinical assessment we inferred a good language comprehension (of L2). According to the extensive Bilingual Language History Questionnaire of Fernandez et al., patient A is highly proficient in both L1 and L2 (see Supplementary Table 1 for details) (Fernandez, 2003). Furthermore, as the focus of the present study was language switching, we also report some measures of frequency/proficiency of language switching. The patient reported that she never mixes L1 and L2 and never switches between L1 and L2 in everyday conversations as all her friends, relatives and people she spends time with speak only L1 or L2 and not both. To date in this study L1 and L2 are very different. Indeed when the patient was asked to rate on a scale (0–10) the frequency of language switching between L1 and L2 she rated 0. Similarly, her relatives rated 0 the frequency of the patient's language switching between L1 and L2. Lastly, during the language testing (both

The post-surgery cognitive/language assessment performed 1 week after surgery evidenced that the pre- and post-operative evaluations were very similar. The patient's performance on the Raven's Coloured Progressive Matrices was 34/36. She had no ideomotor apraxia (71/72), and no signs of either dysarthria or oral apraxia (20/20) were found. The patient had a digit span (forward) of 5 (backward of 3). 2.3.1. Italian language assessment The patient scored 29/36 on the verbal comprehension task (Token test, (De Renzi & Faglioni, 1978)). Her phonemic discrimination was normal (60/60) and she was 57% correct at oral naming of nouns (73% for high-frequency nouns and 40% for low-frequency nouns) and 61% at oral naming of actions (64% for high-frequency actions and 57% for low-frequency actions). She was 100% correct at repetition

2 We acknowledge that it would have been methodologically more sound to test both languages with the BAT, and that this can be a limitation of our study. Testing was carried out with the BADA in Italian and partially with the BAT and subtest of the BADA for Serbian, because of pre-surgical testing time constraints, and because of the non-feasibility of the naming from the BAT in fMRI and operatory room as it includes the presentation of real objects and it does not include an action naming task, nor normality cut-offs. The same subtest from BAT she performed for L1 in the postoperative testing was presented at follow up (7 months) for both L1 and L2. Her performance was within the normal range (BAT auditory verbal discrimination: L1 100% and L2 100%; syntactic comprehension: L1 100% and L2 97.7%; repetition and lexical decision (both words and pseudowords: L1: 100% and L2: 100%); reading: L1 100% and L2: 100%).

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Fig. 1. T1- and T2-weighted MR images of the patient's lesion as shown by axial slices.

(both words and pseudowords), 93% at words and 95% at pseudowords reading. Her performance on the Pyramids and Palm Tree Test was normal (50/52).

2.3.2. Serbian language assessment The patient was 96% correct at oral naming of nouns and 93% at oral naming of actions. Her performance on the BAT auditory verbal discrimination and syntactic comprehension tasks was normal (100%). She was 100% correct at repetition and lexical decision (both words and pseudowords) and at reading (words).

2.4. fMRI and DTI study 2.4.1. Paradigms and tasks We retrospectively used structural and functional brain imaging data routinely acquired during pre-surgery investigations in order to combine them with intraoperative stimulation mapping. Language mapping: Language tasks included counting, tapping automatic speech, silent object naming and verb generation which were used also intraoperatively during DES. In the counting task, each block (N ¼4, 15 s each) showed the instruction “Count” with the teeth together (i.e. with no jaw movements). In the baseline conditions (N ¼6), a fixation cross (15 s) was presented between blocks and the patient and the control were asked to relax muscles and stop counting. In the silent object naming task, each block (N ¼4, 15 s each) included 7 trials (2430 ms each). Stimuli were taken from the Snodgrass and Vanderwart's set of pictures (Snodgrass & Vanderwart, 1980), mean word length 6.8 7 2.2, length in syllable 2.8 7 0.89; frequency, 1.4 7 1.6. In accordance with Snodgrass & Yuditsky

(1996), log natural transformation ln (1 þraw frequency count) was applied to normalize the frequency measure for use in correlational analyses, see Szekely et al. (2005). The instruction was: “Silently name the picture as accurately and as quickly as possible”. In the baseline condition (N ¼ 6), a fixation cross (15 s) was presented between blocks. In the silent verb generation task the same stimuli and the same paradigm were presented as used in the silent object naming task. The instruction was: “Silently generate a verb associated to the picture as accurately and as quickly as possible”. The Presentations software (Version 9.9, Neurobehavioral Systems Inc., CA, USA) was used for stimuli presentation and their synchronization with the MR scanner. Participants viewed the stimuli via a VisuaStim Goggles system (Resonance Technology). Prior to the acquisitions participants practiced the tasks outside the scanner. 2.4.2. fMRI and DTI data acquisition Magnetic resonance imaging was performed 6–10 days prior to craniotomy. Anatomical, functional and DTI images were acquired using the MR sequences previously described (Tomasino et al., 2013) on a Philips Achieva 3-T (Best, Netherlands) whole-body scanner and a SENSE-Head-8 channel head coil. 2.4.3. fMRI data processing All calculations were performed on UNIX workstations (Ubuntu 8.04 LTS, i386, http://www.ubuntu.com/) using MATLAB r2007b (The Mathworks Inc., Natick, MA/USA) and SPM5 (Statistical Parametric Mapping software, SPM; Wellcome Department of Imaging Neuroscience, London, UK http://www.fil.ion.ucl.ac.uk/spm). Dummy images were discarded prior to further image processing. Pre-processing

B. Tomasino et al. / Neuropsychologia 62 (2014) 87–100 included spatial realignment of the images to the reference volume of the timeseries, segmentation producing the parameter file used for normalization of EPI data to a standard EPI template of the Montreal Neurological Institute template provided by SPM5, re-sampling to a voxel size of 2 2 2 mm3, and spatial smoothing with a 6-mm FWHM Gaussian kernel to meet the statistical requirements of the General Linear Model and to compensate for residual macro-anatomical variations across subjects. To delineate language networks related to counting, naming, and verb generation tasks, we modelled the alternating epochs by a simple boxcar reference vector. A general linear model for blocked designs was applied to each voxel of the functional data by modelling the activation and the baseline conditions for each subject and their temporal derivatives by means of reference waveforms which correspond to boxcar functions convolved with a hemodynamic response function (; Friston, Frith, Turner, & Frackowiak, 1995a; Friston et al., 1995b). Furthermore, we included 6 additional regressors that modelled the head movement parameters obtained from the realignment procedure. Accordingly, a design matrix, which comprised contrast modelling alternating intervals of “activation” and “baseline” (no movement), was defined. At the single subject level, specific effects were assessed by applying appropriate linear contrasts to the parameter estimates of the baseline and experimental conditions resulting in t-statistics for each voxel. Low-frequency signal drifts were filtered using a cut-off period of 128 s. These t-statistics were then transformed into Z-statistics constituting statistical parametric maps (SPM{Z}) of differences between the experimental conditions and between the experimental conditions and the baseline. SPM{Z} statistics were interpreted in light of the theory of probabilistic behaviour of Gaussian random fields (Friston et al., 1995a, 1995b). For the second-level random effects analyses on the healthy control group, contrast images obtained from individual participants were entered into a one-sample t-test to create a SPM{T}, indicative of significant activations specific for this contrast at the group level. We used a threshold of p o 0.05, corrected for multiple comparisons at the cluster level (using family-wise error (FWE)), with a height threshold at the voxel level of p o0.001, uncorrected. For each task we calculated the following contrast images: first, the main effects of CONDITION (task–baseline_patient 4 task–baseline_controls, and task– baseline_controls 4task–baseline_ patient), then we performed a conjunction null analysis (Friston, Holmes, Price, Büchel, & Worsley, 1999), showing the common activated network for both tasks (task–baseline_ patient \task–baseline_controls) using a threshold of p o0.05, corrected for multiple comparisons at the cluster level (using FWE), with a height threshold at the voxel level of p o 0.001, uncorrected. The anatomical interpretation of the functional imaging results was performed using the SPM Anatomy toolbox (Eickhoff et al., 2005).

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2.4.4. DTI data processing Diffusion-weighted images were analysed using the Functional Magnetic Resonance Imaging of the Brain Software Library (FSL; http://www.fmrib.ox.ac. uk/fsl) as previously described (Tomasino et al., 2013).

2.5. Intra-operative methods The patient was informed in detail about the direct electrical stimulation (DES) mapping as early as during the initial contact with our Department. During surgery, a navigation system was used (StealthStation TReon plus; Medtronic SofamorDanek) showing the T1-weighted and T2-weighted high-resolution 3D images loaded with fMRI and DTI. Awake surgery was performed. Cortical and subcortical functional mapping was performed using direct electrical stimulation following conventional methods (Berger, Ojemann, & Lettich, 1990; Berger & Ojemann, 1992; Szelenyi et al., 2010). We used a coaxial bipolar stimulator which has a very circumscribed effect allowing the appreciation of different DES effects as compared to the classical bipolar stimulation which has an effect on bigger cortical areas. The external diameter is 2.0 mm and works as cathode, the central point works a anode and the inter-electrode distance is about 0.5 mm. Cortical stimulation mapping included counting and object naming tasks as well as sensorimotor mapping. For the naming task, we used the same 28 black and white pictures as used in the fMRI paradigm. The patient was asked to produce the correct name by saying the Italian translation of “this is a…”. The duration of each stimulation block was set at 2.5 s on the homemade stimulation software. The picture was presented for 2 s 500 msec after the stimulation starting point. Audio/ video data were recorded by a video system. Cortical mapping was performed immediately after opening the dura in order to avoid brain shift. The real position of the probe on the brain surface indicating the DES positive site was acquired and sent to the neuronavigation system to be projected on T1 or T2 images and saved as snapshot.

2.5.1. Neurosurgery The patient received only a slight sedation, so she was awake right from the start. A craniotomy was performed using the navigator system. Some functional areas surrounding the tumour were exposed, as evidenced by the fMRI mapping. The possible onset of seizures was monitored by continuous ECOG.

Fig. 2. A) Intraoperative coordinates of the site where switching is evoked by the cortical stimulation mapping, taken from the neuronavigation system. B) Intraoperative coordinates of the site where speech arrest is evoked by the cortical stimulation mapping, taken from the neuronavigation system. C) After conversion to MNI space the coordinates are used to perform a small volume correction (SVC) on the conjunction L1 and L2 fMRI map for object naming (C), verb generation (D) and on the conjunction analysis showing common activations for the patient and controls during counting (E) (all ps o 0.05, FWE corrected at the cluster level). (F) The positive language switching site (shown as a ROI in red), the IFOF (inferior fronto-occipital fasciculus, in magenta), the ILF (inferior longitudinal fasciculus, in green) and the SLF (superior longitudinal fasciculus, in blue) are overlapped on a T2 image.

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3. Results 3.1. Intraoperative mapping Cortical stimulation of the tumour did not produce any positive response, while stimulation of the surrounding functional tissue elicited two different patterns of effects. Superior to the lesion, stimulation of the superior temporal gyrus evoked involuntary language switching from L2 to L1 (see Fig. 2A). The effect was obtained four times during four consecutive series of 1–10 counting. The patient was asked to count in L2 while she suddenly and involuntarily switched to L1. At the end of the stimulation she returned to L2. Language switching occurred always in the same direction. When we changed the languages asking her to count in L1 for seven consecutive series of 1–10 counting, no language switching was evoked. We then asked her to count in L2. The involuntary switch to L1 was replicated following stimulation of the same point in the superior posterior temporal gyrus. Furthermore, stimulation effects on language switching were selective, namely, interfered with counting behaviour but not with object naming. Anterior and superior to the lesion (see Fig. 2B), stimulation in the inferior frontal gyrus evoked speech arrest, which resulted from a disruption of language processing (Ojemann, Fried, & Lettich, 1989; Penfield & Rasmussen, 1949) during counting and during a naming task. Stimulation at this site did not elicit

language switching. The mapping for motor and language functions continued throughout the resection and thereafter to ensure that functional areas would not be disrupted. The online video recorded by the microscope camera indicated the real position of the probe on the brain surface. The corresponding coordinates of the location of the language switching positive site were sent to the neuronavigation system and overlapped on three-dimensional MR images. In addition, each positive cortical site was marked using a sterile tag on the brain surface.

3.2. Post-processing of the DES data The coordinates of the language switching site detected by the neuronavigation system were converted into MNI space (x¼ 61 y¼ 30 and z ¼18, see Fig. 2A). As we were interested to test whether this site was part of a common L1 and L2 language network, we used a hypothesis-driven ROI-based approach (Friston, 1997). In the conjunction analysis, which evidences common activations to L1 and L2 during the object naming task we performed a small volume correction (SVC) analysis within a spherical ROI (8-mm radius), centred on the x, y, and z coordinates corresponding to the language switching positive site. We found a significant cluster in a region encompassing the left superior temporal gyrus/supramarginal gyrus (peak coordinates: 56, 38, 24; z ¼4.26, po0.05, FWE corrected for the ROI, see

Fig. 3. A) L1 (Serbian, in red) and L2 (Italian, in green) task-related networks. Common (B) and differential (C, D) neural networks associated with object naming on the left side of the panel and with verb generation on the right side of the panel (p o 0.05, FWE corrected at the cluster level).


Fig. 2C). We then used the SVC in the conjunction analysis showing common activations to both L1 and L2 during the verb generation task. Again, we found a significant cluster in a region encompassing the left superior temporal gyrus (peak coordinates: 52, 38, 28; p o0.05, z ¼5.75, FWE corrected for the ROI, see Fig. 2E). We also used the SVC in the conjunction analysis, showing common activations in both the patient and the controls during the counting task. Again, we found a significant cluster in a region encompassing the left superior temporal gyrus (peak coordinates: 58, 38, 20; z¼4.42, po 0.05, FWE corrected for the ROI, see Fig. 2D). Lastly, no suprathreshold activation emerged from the SVC analysis performed on the L1 4L2 contrast during both the object naming and the verb generation tasks, which showed activations exclusively related to L1. 3.3. fMRI results The neural networks underlying the linguistic tasks were assessed by a whole brain analysis (po 0.05, FWE corrected for multiple comparisons at the cluster level, with a height threshold at the voxel level of p o0.001). 3.3.1. L1 (Serb) vs. L2 (Italian) comparisons 3.3.1.1. Common activations to L1 and L2: conjunction analysis. The common network for L1 (Serb) and L2 (Italian) consisted of activation clusters as follows (see the Supplementary material for a list of the coordinates in MNI space and for a figure showing brain regions with significant relative increases in BOLD response associated with each task displayed on a rendered brain template provided by spm5 both for L1 and L2). The common network for the silent object naming task (object naming 4baseline in Serb\ object naming 4baseline in Italian) included: i) the middle and superior occipital gyri extending to the inferior temporal gyrus bilaterally, ii) the left inferior parietal lobule, iii) the left SMG, iv) the left SMA, and v) the right cerebellum (see Fig. 3 and Table 1). The silent verb generation task commonly activated the following areas in L1 and L2: i) the inferior and middle occipital gyri bilaterally, ii) the left inferior and superior parietal lobules, iii) the right precuneus, iv) the left SMG extending to the left STG, v) the left MTG, vi) the right angular gyrus, vi) the left precentral gyrus and the left Rolandic operculum, vii) the IFG (pars triangularis) bilaterally, viii) the SMA bilaterally, ix) the right insula, x) the middle frontal gyrus bilaterally and xi) the cerebellum bilaterally (see Fig. 3 and Table 2).

3.3.1.2. Main effect of language: L1 vs. L2 (and vice versa). The network of areas differentially recruited by L1 (vs. L2) for each fMRI task involved clusters of activity as follows. Silent naming (vs. rest) in L1 (vs. L2) differentially activated the right IFG (pars opercularis). The reverse comparison (L2 vs. L1) showed a differential activation of i) the superior occipital gyrus bilaterally, ii) the left middle occipital gyrus, iii) the left precuneus and the left superior parietal lobule, iv) the SMA, the IFG (pars opercularis) and the precentral gyrus bilaterally, v) the right middle frontal gyrus and vi) the right cerebellum (see Fig. 3 and Table 1). Silent verb generation (vs. rest) in L1 (vs. L2) differentially activated: i) the angular gyrus and the SMG bilaterally, ii) the right precuneus, iii) the SMA and the insula bilaterally, iv) the right IFG (pars triangularis), the right superior orbital gyrus and the right superior frontal gyrus, and v) the middle frontal gyrus bilaterally. The reverse comparison (L2 vs. L1) showed a differential activation of i) the superior occipital gyrus and middle occipital gyrus bilaterally, ii) the left cuneus and left superior parietal lobule, iii) the right inferior temporal gyrus, and iv) the left IFG (pars triangularis) (see Fig. 3 and Table 2).

93

Table 1 Brain regions showing significant increase in BOLD response for object naming that is i) common to both L1 and L2, ii) in L24L1, and iii) in L14 L2. Region

Object naming: Serbian \ Italian Middle occipital gyrus Superior occipital gyrus Inferior temporal gyrus Middle occipital gyrus Inferior temporal gyrus Calcarine gyrus Inferior parietal lobule Supramarginal gyrus SMA Cerebellum Object naming: Serbian 4Italian Inferior frontal gyrus (pars opercularis) Object naming: Italian 4 Serbian Lingual gyrus Superior occipital gyrus Middle occipital gyrus Superior occipital gyrus Precuneus Superior parietal lobule SMA SMA Inferior frontal gyrus (pars opercularis) Precentral gyrus Inferior frontal gyrus (pars opercularis) Cerebellum Precentral gyrus Middle frontal gyrus

x

y

z

Z Cluster size Vox

R R R L L L L L L R

34 24 44 40 44 10 26 50 4 34

90 100 68 88 78 102 68 38 4 64

6 8 8 8 10 12 42 26 52 24

6.15 1208 6.13 5.95 6.14 1046 5.97 5.12 45 4.80 51 4.67 85 4.27 37 4.08 36

R

50

12

24

4.53

R L R L L L R L L R R R L R

16 18 48 10 8 16 10 0 54 52 46 26 50 36

88 92 76 86 80 78 6 2 8 4 14 36 2 4

14 2 8 40 50 46 50 52 14 50 38 22 38 38

Inf 5412 7.59 6.03 752 6.35 65 5.34 3.60 4.91 39 4.40 4.89 28 4.86 43 4.34 4.48 69 3.94 33 3.83 43

Side MNI

27

For each region of activation, the coordinates in MNI space are provided with reference to the maximally activated voxel within an area of activation, as indicated by the highest Z-value (P_0.05, corrected for multiple comparisons at the cluster level, height threshold P_0.001, uncorrected). L/R¼ left/right hemisphere.

3.3.2. Patient vs. controls We evidenced the pattern of clusters of activation of the patient and the control subjects (see the Supplementary material for a list of the coordinates in MNI space and for a figure showing brain regions with significant relative increases in BOLD response associated with each task displayed on a rendered brain template provided by spm5 both for the patient and the control subjects). 3.3.2.1. Common activations: conjunction analysis. The common network for the patient and the control subjects consisted of activation clusters as follows. The common network for counting aloud (counting 4 baseline in the patient \ counting 4 baseline in controls) included: i) the precentral and postcentral gyri bilaterally, ii) the STG bilaterally and iii) the right SMG (see Fig. 4 and Table 3). The common network activated during the silent object naming task included: i) the middle occipital gyrus bilaterally, ii) the inferior temporal gyrus bilaterally, iii) the left temporal pole, left STG and MTG, iv) the hippocampus bilaterally, v) the left post- and pre-central gyri, and the right precentral gyrus, vi) the left IFG (pars opercularis and triangularis), vii) the right middle frontal gyrus, viii) the insula bilaterally and ix) the left SMA (see Fig. 4 and Table 4). The silent verb generation task commonly activated in the patient and in controls: (i) the left inferior occipital gyrus, extending to the right calcarine gyrus, ii) the left temporal pole, the STG bilaterally and the left SMG, iii) the right cerebellum, iv) the IFG extending to the precentral gyrus bilaterally, v) the left SMA, vi) the insula bilaterally, vii) the middle frontal gyrus bilaterally, viii) the left hippocampus, and ix) the left caudate nucleus and putamen (see Fig. 4 and Table 5).

94


Table 2 Brain regions showing significant increase in BOLD response for verb generation that is i) common to both L1 and L2, ii) in L24 L1, and iii) in L1 4L2. Verb generation: Serbian \ Italian Inferior occipital gyrus Middle occipital gyrus Fusiform gyrus Inferior occipital gyrus Inferior parietal lobule Superior parietal lobule Rolandic operculum Inferior frontal gyrus (pars triangularis) SMA SMA Insular lobe Precuneus Supramagrinal gyrus Superior temporal gyrus Precentral gyrus Precentral gyrus Middle frontal gyrus Angular gyrus Cerebellum Inferior frontal gyrus (pars triangularis) Inferior frontal gyrus (pars triangularis) Superior occipital gyrus Middle temporal gyrus Middle frontal gyrus Cerebellum Verb generation: Serbian 4Italian SMA Insula Precuneus Angular gyrus Angular gyrus Inferior frontal gyrus (pars triangularis) Insula Superior orbital gyrus Supramarginal gyrus Middle frontal gyrus Superior occipital gyrus SMA SMA Middle frontal gyrus Superior frontal gyrus Supramarginal gyrus Middle frontal gyrus Verb generation: Italian 4Serbian Superior occipital gyrus Fusiform gyrus Middle occipital gyrus Cuneus Superior parietal lobule Inferior temporal gyrus Inferior frontal gyrus (pars triangularis) Superior occipital gyrus Middle occipital gyrus Superior parietal lobule

L L R R L L L L L R R R L L L L R R R R L R L L L

44 44 32 44 32 30 56 52 2 2 32 8 52 58 2 40 38 36 24 50 40 26 54 40 34

82 74 80 76 64 66 4 28 4 12 22 70 38 40 18 0 44 56 38 30 42 70 54 44 68

10 6 16 10 38 50 8 26 56 48 6 50 28 22 46 48 24 46 22 30 6 42 10 24 22

6.49 6.26 6.37 6.06 6.36 5.61 6.05 5.69 5.98 4.58 5.90 5.75 5.75 4.56 5.62 5.29 5.21 5.02 4.86 4.84 4.84 4.78 4.62 4.02 3.62

L R R R L R L R L R R R L L R R R

8 32 8 38 36 54 30 22 54 38 28 4 2 30 26 60 42

14 18 70 56 56 28 16 54 46 34 66 12 22 50 46 38 44

44 6 52 46 38 26 8 6 28 40 38 48 46 16 20 32 4

5.68 5.48 5.15 5.12 4.82 4.97 4.93 4.92 4.83 4.79 4.77 4.68 3.56 4.45 4.24 4.22 4.11

31 41 66 102 117 46 29 41 108 38 43 38

L L R L L R L R L L

26 40 40 4 20 50 44 22 24 24

90 78 84 94 64 54 22 70 82 72

24 18 8 26 46 12 20 46 40 42

7.80 7.12 6.00 5.90 5.20 5.10 4.68 4.51 4.01 3.51

718 2585 440 58 73 28 45 32 41

1170 2017 477 497 184 68 51 240 66 231 115 51 32 55 138 64 51 45 37

31 72 61 54

For each region of activation, the coordinates in MNI space are provided with reference to the maximally activated voxel within an area of activation, as indicated by the highest Z-value (P_0.05, corrected for multiple comparisons at the cluster level, height threshold P_0.001, uncorrected). L/R¼ left/right hemisphere.

3.3.2.2. Main effect of condition: patients vs. control subjects (and vice versa). The network of areas differentially recruited by the patient (vs. the controls) for each fMRI task involved clusters of activity as follows. The counting aloud task (vs. baseline) in the patient (vs. control subjects) differentially activated: i) the left precentral gyrus, ii) the left SMA extending to the right middle cingulate gyrus, iii) the right middle frontal gyrus and iv) the cerebellum bilaterally. The reverse comparison (controls vs. patient) showed that the control subjects differentially activated: i) the postcentral gyrus bilaterally extending to the left superior temporal

gyrus, ii) the left insula, iii) the right precentral gyrus, and iv) the left amygdala (see Fig. 4 and Table 3). Silent naming (vs. rest) in the patient (vs. the control subjects) differentially activated: i) the right fusiform gyrus extending to the left middle occipital gyrus and lingual gyrus bilaterally and to the calcarine gyrus bilaterally, ii) the left precentral gyrus, iii) the left SMG, and iv) the right cerebellum. The reverse comparison (controls vs. patient) showed a differential activation of i) the left inferior temporal gyrus extending to the middle occipital gyrus, ii) the left inferior and superior parietal lobule, iii) the left precentral gyrus (Area 6), iv) the left IFG (pars opercularis) extending to the left temporal pole, v) the right IFG (pars triangularis and opercularis) extending to the insula, vi) the SMA bilaterally, vii) the anterior cingulate cortex, viii) the hippocampus bilaterally and ix) the left putamen (see Fig. 4 and Table 4). Silent verb generation (vs. rest) in the patient (vs. the control subjects) differentially activated: i) the left middle occipital gyrus extending to the right fusiform gyrus and right calcarine gyrus, ii) the left superior parietal lobule, iii) the right cerebellum, iv) the left cuneus, v) the left IFG (pars triangularis), vi) the precentral gyrus bilaterally, and vii) the right middle frontal gyrus. The reverse comparison (controls vs. patient) showed a differential activation of i) the right superior occipital gyrus extending to the left inferior occipital gyrus, ii) the left postcentral gyrus, iii) the right precentral gyrus extending to the right IFG (pars opercularis), iv) the SMA bilaterally, v) the left middle frontal gyrus, vi) the posterior cingulate cortex, vii) the right putamen and caudate nucleus, viii) the right cerebellum ad ix) the right amygdala (see Fig. 4 and Table 5). 3.4. DTI As shown in Fig. 2F, there is no overlap between the positive point at which stimulation induced language switching and the inferior fronto-occipital fasciculus (IFOF), the inferior longitudinal fasciculus (ILF) and the superior longitudinal fasciculus (SLF).

4. Discussion In the present study we explored the functional neuroanatomy of a Serbian–Italian L2 learner who switched from L2 (Italian) to L1 (Serbian) following electro-cortical stimulation of the left posterior superior temporal gyrus. Since the patient was not aphasic one could argue that her language testing gives an idea of her language proficiency. By dividing her L2 naming performances according to frequency it emerged that the patient had more difficulty on low frequency items as compared to high frequency ones: she was 57% correct at oral nouns naming (73% for high frequency nouns and 40% for low frequency nouns) and 61% at oral actions naming (64% for high frequency actions and 57% for low frequency actions). In addition, a detailed questionnaire (for details see Wartenburger et al. (2003)) showed that the patient reported that her Italian proficiency was good. In a typical day she was more exposed to L2 (talking with her husband, with friends, reading newspaper, watching television, etc.) than L1. During a clinical assessment we inferred a good language comprehension (of L2). We observed different stimulation effects. Stimulation of the left posterior superior temporal gyrus produced very rapid and automatic language switching, whereas stimulation of the left IFG did not. At this site, stimulation produced speech arrest. Stimulation effects on language switching were selective, namely, interfered with counting behaviour but not with object naming. The switching phenomenon occurred always in one direction, from L2 to L1. This had already been documented by previous studies showing that language switching can occur in a selective direction.


95

Fig. 4. Common network (on the left side of the panel) for counting (A), object naming (B) and verb generation (C), and network of areas differentially recruited by the patient (vs. the controls in the centre) and (C) by the controls (vs. the patient on the right side of the panel). Activations are superimposed on a rendered brain template provided by spm5.

For example, some authors showed that direct stimulation always elicited language switching from L1 to L2 and interpreted this asymmetry as L1 being more densely represented than L2 (Wang et al., 2012). However, our fMRI data showed that L1 and L2 overlapped at the site where stimulation induced language switching. Some authors (Moritz-Gasser & Duffau, 2009a) underlined the importance of direct brain stimulation data, since this technique induces a transient virtual lesion and indicates whether a given area is essential for a given cognitive process. Our study does not simply add a further neuropsychological case to those claiming that language switching is a consequence of electrocortical stimulation during awake surgery (Kho et al., 2007; Moritz-Gasser & Duffau, 2009b; Wang et al., 2012). At variance with previous reports, we presented functional and DTI data that could contribute to the understanding of the language switching mechanism. In addition, we integrated our data within a different perspective based on current neurolinguistic models of speech production (Golfinopoulos et al., 2010; Hickok et al., 2011). 4.1. Combining intra-operative and functional imaging data First, we would like to discuss some general aspects evidenced by our fMRI data. The combination of intra-operative and functional mapping was essential. Although DES involved overt articulation, in order to minimize head motion-related artefacts, in the fMRI study we asked the patient to respond silently (covertly). In presurgical planning fMRI language tasks that are covert are often used since several studies showed that overt and covert modalities activate the same clusters, e.g. see for verb generation (Yetkin et al., 1995), or for silent and overt naming of letters and animals (Huang, Carr, & Cao, 2002), with a difference in the volume of activation, which is usually increased in the motor strip during vocalized speech (Petrovich et al., 2005) and in the amount of artefacts, which are fewer in silent vs. aloud modality (Yetkin et al., 1995). We acknowledge that including a monolingual control group could appear completely inappropriate because in bilinguals, the acquisition of a L2 has effects on the cerebral organization of L1. The comparisons between our patient's and the control subjects' fMRI maps during counting, object naming and verbs naming revealed very similar networks of activations in L2. Nonetheless, comparing patient vs. controls would have been crucial if the main

aim of the analysis was investigating differences between the patient and healthy participants in order to interpret a deficit. The main use of fMRI maps in our study was overlapping the patient's positive intra-operative stimulation site inducing switching to the patient's fMRI maps related to Italian and Serbian. In interpreting the effects of stimulation, it has been argued that language switching induced by stimulation should not be necessarily interpreted as the effect of interference with language selection (Hervais-Adelman et al., 2011). Some authors (HervaisAdelman et al., 2011) reasoned that since different languages are represented in different areas, stimulation may have simply inhibited or excited one of the two languages. In our study, the fMRI mapping was essential to understand the nature of the language switching, since the coordinates of the positive site were part of a cluster of activation common to both L1 and L2 (see below). We acknowledge that strong claims about the functional organization are not always possible with brain tumour patients. However, see for two different opinions on this (Karnath & Steinbach, 2011; Shallice & Skrap, 2011). Brain tumours grow slowly in the brain and give enough time for functional areas to reorganize. The use of fMRI in such cases is extremely useful as the comparison between healthy control group and the patient fMRI maps can test whether in the patient the tumour has induced a functional reorganization of the areas or the expected network is found activated. The comparisons between our patient's and the control subjects' fMRI maps during counting, object naming and verbs naming revealed that the patient and the healthy control group shared very similar networks of activations in all the three fMRI tasks they performed in Italian, which were consistent with the previous literature [for counting, (Petrovich Brennan et al., 2007; Sveljo, Koprivsek, Lucic, Prvulovic, & Culic, 2010), for object naming, e.g. see the control group in Tomasino et al. (2013), as well as for verb generation, (Esopenko et al., 2012; Maieron, Marin, Fabbro, & Skrap, 2013; Peran et al., 2009)]. Controls (relative to the patient) showed a differential increase in activity all over the networks, meaning that the cluster size in the control group was larger than that of the patient. By contrast, in the patient (relative to the controls), the tasks additionally increased the activity of the frontal lobe (SMA, precentral and middle frontal gyrus) in counting, the left supramarginal gyrus and precentral gyrus in object naming and left superior parietal lobule, precentral gyrus and middle frontal gyrus in verb generation. An interesting point of

96


Table 3 Brain regions showing significant increase in BOLD response for counting that is i) common to both the patient and the controls, ii) in controls4the patient, and iii) in the patient 4controls. Region

Counting: patient \ controls Precentral gyrus (areas 6, 4p, 3a) Postcentral gyrus (area 3b) PrecentralgGyrus (areas 6, 4p, 3a) Superior temporal gyrus Supramarginal gyrus Superior temporal gyrus Counting: patient 4controls Precentral gyrus (crea 6) SMA Middle cingulate cortex Middle frontal gyrus Middle frontal gyrus Cerebellum Cerebellum Counting: controls4patient Postcentral gyrus (OP1) Postcentral gyrus (areas 3a,4p) ext to superior temporal gyrus Postcentral gyrus (areas 4p, 3b, 1) ext to superior temporal gyrus Insula lobe Precentral gyrus (area 6) Postcentral (area 4p) Area 4p Superior temporal gyrus Insula lobe Amygdala

Side

Z

MNI

Cluster size

x

y

z

R R L R R L

48 54 48 62 66 46

8 4 4 30 26 38

40 44 50 14 20 20

6.45 5.86 6.09 4.80 4.74 4.70

L L R R R R L

48 2 4 38 26 26 16

6 0 16 34 46 64 66

54 52 34 42 18 22 14

5.09 4.85 4.43 4.82 4.56 4.55 4.19

29 144

L L R L R R L L L L

58 50 50 26 24 24 18 46 40 26

18 6 10 26 20 30 28 2 0 2

16 28 38 8 60 60 54 10 2 12

5.44 5.30 5.05 4.67 4.31 3.70 4.26 4.18 3.98 3.85

1401

Vox

771 777 47 48

49 27 96 65

974 36 54 55 69 44

For each region of activation, the coordinates in MNI space are provided with reference to the maximally activated voxel within an area of activation, as indicated by the highest Z-value (P_0.05, corrected for multiple comparisons at the cluster level, height threshold P_0.001, uncorrected). L/R ¼ left/right hemisphere.

discussion regarding fMRI results is the activation we found in areas included in the control and executive mechanisms-related network, known to be involved in language switching mechanism (Hernandez, 2009; Rodriguez-Fornells et al., 2002), such as the middle frontal gyrus and dorsolateral prefrontal cortex. In addition, the inferior parietal lobule was found activated for both L1 and L2. This region has been related to lexical processing in bilingualism as Mechelli et al. (2004) showed that L2 vocabulary acquisition induced structural changes dependent on language proficiency, as detected by the VBM technique in this region. On the other hand, L2 as compared to L1 differentially recruited the left superior parietal lobule. The left superior and inferior parietal cortices have been found activated during task switching and translation (Braver, Reynolds, & Donaldson, 2003; Wang et al., 2007, 2009). Interestingly, in a review of neuroimaging studies (Abutalebi & Green, 2007) it has been shown that the inferior parietal cortex is part of the language control network. Authors argued that during language control the left basal ganglia and the anterior cingulated cortex (ACC) modulate the activity in the left prefrontal cortex, providing a normal modulatory influence on the systems mediating word production (as the left prefrontal cortex and the inferior parietal lobe) (Abutalebi & Green, 2007). 4.2. The coordinates of the positive site are localized in the left superior temporal gyrus We found that the coordinates of the positive site at which stimulation induced language switching during counting overlapped with a cluster of fMRI activation in the left superior temporal/supramarginal gyrus shared by L2 and L1 during naming and verb generation. Furthermore, the same coordinates overlapped with a cluster of activation in the left superior temporal gyrus shared by the patient and healthy controls during the counting task. Importantly, performing language fMRI tasks

covertly or overtly have no effect of spT activation; it has been shown that Spt is activated both during the passive perception of speech and during covert (subvocal) speech articulation (Buchsbaum, Hickok, & Humphries, 2001; Buchsbaum et al., 2005; Hickok, Buchsbaum, Humphries, & Muftuler, 2003; Hickok et al., 2011). Authors (Hickok et al., 2011) explained that covert speech was used to ensure that overt auditory feedback was not driving the activation. Previous studies found that the left superior temporal gyrus was involved in language switching. First, the positive site found in our patient is very similar to that reported by previous authors (Moritz-Gasser & Duffau, 2009b) in which electro-cortical stimulation of this area elicited language switching. Unfortunately, this study did not present fMRI data nor theoretical interpretations of the observed data explaining why stimulation of the superior temporal gyrus induced language switching. In addition, a PET study found that language switching elicited activation in the left supramarginal gyrus (Price et al., 1999). Our positive site was localized in a cluster of activation related to naming encompassing the posterior superior temporal gyrus and including part of the cluster found in the supramarginal gyrus. Some authors (Price et al., 1999) argued that switching modulates word processing at a phonological stage as demands placed on orthographic to phonological mapping increase as participants alternate between L1 and L2. In our patient switching occurred between two languages with very different phonological constraints and very different pronunciations. When we detected language switching the patient was not processing pictures nor written words, she was carrying out an automatic language task (i.e. counting). Indeed stimulation affected on language switching selectively during counting but not during object naming. This finding indicates that dissociation between DES effects on automatic vs. lexical–semantic language functions. We argue that during the naming task the effect induced by DES is not sufficient


97

Table 4 Brain regions showing significant increase in BOLD response for object naming that is i) common to both the patient and the controls, ii) in controls4 the patient, and iii) in the patient 4controls. Region

Object naming: patient \ controls Inferior temporal gyrus Middle occipital gyrus Inferior occipital gyrus ext to inf T Hippocampus Postcentral gyrus (area 4a) Precentral gyrus (area 6) Precentral gyrus Inferior frontal gyrus (pars opercularis) Inferior frontal gyrus (pars triangularis) SMA Hippocampus Temporal pole Inferior frontal gyrus (pars triangularis) Insula lobe Precentral gyrus Superior temporal gyrus Middle temporal gyrus Insula lobe Middle frontal gyrus Object naming: patient 4controls Fusiform gyrus Middle occipital gyrus Inferior occipital gyrus Precentral gyrus (area 6) Supramarginal gyrus Lingual gyrus Lingual gyrus Calcarine gyrus Cerebellum Calcarine gyrus Object naming: controls4patient Inferior temporal gyrus Middle occipital gyrus Precentral gyrus (area 6) Inferior frontal gyrus (pars opercularis) ext to the left temporal pole Hippocampus Hippocampus SMA SMA Inferior frontal gyrus (pars triangularis) Insula lobe Inferior frontal gyrus (pars opercularis) Inferior parietal lobule Superior parietal lobule Putamen Parahippocampal gyrus Anterior cingulate cortex Inferior frontal gyrus (pars opercularis)

Side

Z

MNI

Cluster size

x

y

z

L L R L L L L L L L R L L L R L L R R

44 26 38 24 52 42 44 52 40 4 26 48 40 30 48 54 54 42 32

48 92 72 32 6 2 8 8 14 12 32 12 22 28 4 40 42 22 0

16 12 10 2 44 52 30 10 24 48 0 6 2 2 40 18 6 6 58

Inf Inf Inf 7.38 7.11 6.15 6.70 5.50 4.76 6.55 6.21 5.31 5.17 4.55 4.98 4.87 4.87 4.80 4.52

92 8194

R L R L L L R L R R

28 30 38 52 46 14 16 18 26 16

80 92 78 4 38 70 46 78 38 70

16 20 16 50 30 2 4 6 22 18

Inf Inf Inf 5.87 5.82 5.51 5.09 4.97 4.95 4.37

5248

L L L L L R L R R R R L L L L M R

44 28 52 52 24 26 2 6 44 42 44 26 32 22 16 2 56

46 88 4 10 32 30 10 14 28 24 10 50 56 4 0 0 16

18 14 42 6 0 2 50 50 16 6 28 46 56 4 18 30 0

Inf 7.67 7.04 6.44 7.02 6.82 6.29 4.78 5.73 5.65 5.60 5.60 5.54 5.35 4.94 4.92 3.86

6112

Vox

79 389 415

403 61 85

300 30 37 50 38

30 64 62 184 57 68 28

2545 1896 336 1772

880 211 128 27 42


to disturb in a significant manner the lexical/semantic network underlying the correct performance in the naming task, i.e. proper name production. On the contrary, in the counting task, which is a task tapping automatic language processing in which the lexical/ semantic processing is not required, it follows that the DES effect interfered with the phonological processing underlying the task. This task related dissociation may reflect language switching implicating cognitive control per se, or a mechanism by which the brain defaults to L1, perhaps due to insufficient cognitive control or articulatory processing. As to the first view, DES to the superior posterior temporal gyrus should have exerted its interference as a distant effect on the cognitive control-related areas of the frontal lobe. However results of the DTI analysis revealed that there was no overlap between the positive point at which stimulation induced language switching and the IFOF, the ILF and the SLF. We thus reasoned that the simulation-induced effect

we reported interfered with motor–sensory articulation processing. A new perspective on bilingualism proposed that speaking in a second language increases demands on articulation to a greater extent than when articulating in the first language (Simmonds et al., 2011b). The focus is on auditory and somatosensory cortices which integrate auditory memories of the target sounds and on the post-articulatory auditory and somatosensory feedback (Simmonds et al., 2011b) necessary to monitor the articulation of the utterance. It is held that learners adopt and use their interlanguage phonologies (Simmonds et al., 2011b). See also Alario, Goslin, Michel, and Laganaro (2010) for a fMRI study addressing phonology in L1 and L2 in early and late bilinguals). Other authors have looked at the greater phonological processing necessary for bilingual subjects (Rodriguez-Fornells et al., 2002). fMRI activation was found in a series of areas related to phonological processing. These authors suggested that bilinguals use an indirect

98


Table 5 Brain regions showing significant increase in BOLD response for verb generation that is i) common to both the patient and the controls, ii) in controls4the patient, and iii) in the patient 4controls. Region

Verb generation: patient \ controls Inferior occipital gyrus Calcarine gyrus SMA Inferior frontal gyrus (pars opercularis) Precentral gyrus Temporal pole Precentral gyrus Inferior frontal gyrus (pars opercularis) Precentral gyrus Inferior frontal gyrus (pars triangularis) Hippocampus Insula Superior temporal gyrus Supramarginal gyrus Insula lobe Middle frontal gyrus Superior temporal gyrus Middle frontal gyrus Caudate nucleus Putamen Cerebellum Inferior frrontal gyrus (pars orbitalis) Inferior frrontal gyrus (pars triangularis) Verb generation: patient 4controls Middle occipital gyrus Fusiform gyrus Inferior frontal gyrus (pars triangularis) Cuneus Precentral gyrus (Area 6) Superior parietal lobule Inferior frontal gyrus (pars triangularis) Precentral gyrus (area 6) Calcarine gyrus Middle frontal gyrus Cerebellum Verb generation: controls4patient Superior occipital gyrus Inferior occipital gyrus Precentral gyrus Inferior frontal gyrus (pars opercularis) Putamen SMA SMA Middle frontal gyrus Postcentral gyrus Caudate nucleus Posterior cingulate cortex Cerebellum Calcarine gyrus Fusiform gyrus Amygdala

Side

MNI

Z

Cluster size

x

y

z

Vox

L R L R R L L L L L L R L L L L R R L L R L L

46 20 8 44 42 52 46 54 38 40 24 36 56 56 28 44 62 34 14 18 4 46 44

66 92 12 12 6 12 8 6 6 14 30 20 40 44 22 48 38 2 4 8 44 20 18

12 0 44 28 42 4 46 8 32 30 6 0 20 30 6 8 22 54 12 6 2 4 6

Inf Inf 7.39 6.55 5.68 6.45 6.36 6.07 5.64 5.34 5.97 5.85 5.61 4.02 5.58 5.49 5.41 5.16 5.15 3.77 4.65 4.20 4.14

8613

L R L L L L L R R R R

28 40 42 4 46 30 40 52 28 44 14

92 74 20 94 4 68 38 2 64 48 84

22 14 28 26 54 48 4 50 4 22 38

Inf 7.26 6.82 5.90 5.69 5.32 5.23 5.10 4.81 4.46 4.26

4524

R L R R R L R L L R M R L R R

28 46 48 56 28 0 4 30 50 14 0 0 0 36 26

66 62 8 28 18 14 12 6 4 8 44 64 74 40 2

42 12 30 8 6 44 50 50 40 6 12 12 8 14 12

Inf Inf Inf 6.59 4.19 6.80 5.79 6.35 5.88 4.93 5.38 5.20 5.03 4.66 4.12

9376

399 303 52 149 794

48 212 88 57 28 47 44 51 26 56

31 49 75 34 60 34 50 64 53

1791 296 206 758 427 47 38 26 32 31


phonological access route to the lexicon of the target language to avoid interference. In a similar fashion, as our patient was required to count in Italian, she had to avoid interference between L1 and L2 and maintain her attention focused on the target language (L2). Stimulation of the left superior posterior temporal gyrus might have perturbed phonological processing and triggered interference between L1 and L2 resulting in a language switch. 4.3. Integrating language switching data within the DIVA (Directions Into Velocities of Articulators) model Although monolingual speech production models are not necessarily sufficient to explain bilingual speech production (Simmonds

et al., 2011b), we integrate the pattern of our study with the current Directions Into Velocities of Articulators (DIVA) model (Golfinopoulos et al., 2010; Hickok et al., 2011). We focused on the role of an auditory-sensorimotor feedback control mechanism and we hypothesized it could have been perturbed by the stimulation of the left posterior superior temporal gyrus.gyrus. This model has previously been applied to explain the pattern of results we observed in a case of foreign accent syndrome (Tomasino et al., 2013). From an anatomical point of view, in integrating the lesion localization within the model, the localization of language switching as found in the cortical mapping corresponds to the auditory feedback mechanism named Stp area (Hickok et al., 2011), located in the Sylvian fissure at the parietal–temporal boundary.


According to the DIVA model (Golfinopoulos et al., 2010), this area contains the cells of the auditory target and the auditory error maps. Together with the planum temporale and in addition to the somatosensory cortex and to the anterior supramarginal gyrus, it is the essential node of the feedback control mechanism, which compares the sensory expectations of a speech motor programme and the incoming sensory feedback produced by the articulation of that sound, detects errors and corrects the current speech output. This system can predict the likely sensory consequences of a motor command prior to the arrival of actual sensory feedback and can use such erroneous estimate predictions to provide rapid corrective feedback to the motor controllers, if the likely sensory outcome differs from the intended outcome. It has been argued that the movements necessary to articulation of native speech are automatic, whereas those in a late learned language are not. The auditory and somatosensory inputs do not match internal representations and thus involve a greater engagement of the motor sensory feedback systems (Simmonds et al., 2011b). An fMRI study investigated motor sensory control during language switching (Simmonds et al., 2011a) and found that altered feedback processing in the second language caused an increased activity in somatosensory and auditory areas. According to this, it can be argued that stimulation interfered with the auditory and somatosensory feedback for L2, which is more effortful, and left intact the feedback system for L1, which is well learned and automatic, so that the patient switched to L1 to continue carrying out the counting task. The ROI analysis showed that the coordinates of the positive site at which language switching occurred overlapped with a cluster of activation in the left superior temporal/supramarginal gyrus shared by L2 and L1 during both naming and verb generation. The fact that object naming and verb generation were carried out silently is irrelevant, as the Stp area is activated also by covert speech (Hickok et al., 2011). Furthermore, we found that that area was not exclusively activated by the patient but it was found activated in the conjunction analysis, which showed that the left superior temporal gyrus activation was shared by the patient and healthy controls during the counting task. Prior to entering the feedback control mechanism, the speech signals have been processed by the feedforward control which drives speech production in articulating speech sound targets based on well-learned speech motor programmes (Golfinopoulos et al., 2010; Hickok et al., 2011). Also, the nodes of the feedforward control mechanism were found differentially activated by L2 vs. L1, confirming that native speech articulation involves movements that are automatic, whereas late learned languages do not. According to the DIVA model, this control mechanism is initiated in the left IFG and ventral Pm cortex, where the speech sound maps encoding the lexical representation of a sound as auditory and articulatory information are activated (Hickok et al., 2011). Our fMRI data showed that L2 as compared to L1 increased activation of the inferior frontal gyrus (pars opercularis) and the precentral gyrus bilaterally for object naming, and the left inferior frontal gyrus (pars triangularis) for verb generation. Then, excitatory feedforward commands corresponding to motor programs (Hickok et al., 2011) are sent via a trans-cerebellar pathway to the caudoventral portion of the precentral gyrus containing articulator position and velocity maps describing jaw height, tongue shape, tongue body position, tongue tip position, lip protrusion, larynx height, upper lip height, and lower lip height. Our patient displayed an increased activation in the precentral gyrus for L2 vs. L1. The so-called articulators receive the go signal for producing the speech signals from an initiation map, localized bilaterally in the SMA, mediated by the basal ganglion (Golfinopoulos et al., 2010). In our patient, the fMRI data showed an increased activation of the SMA bilaterally for L2 as compared to L1.

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5. Conclusion In conclusion, we reported that stimulation of the left superior posterior temporal gyrus near the Stp area elicited language switching and at this site language-related fMRI activation was shared by L1 and L2. Given the role of this area in phonological processing, we argue that this language switching case should be thought of as a disorder of the auditory feedback processing which is believed to lie along the bilateral planum temporale and in the superior temporal gyrus (Golfinopoulos et al., 2010). Stimulation may also have interfered with the language control network (Abutalebi & Green, 2007) as this area is close to the parietal cortex/supramarginal gyrus which is part of the language control network.

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.neuropsychologia. 2014.07.011.Appendix. Supporting information

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