# Internal modeling of upcoming speech: A causal role of the right posterior cerebellum in non-motor aspects of language production

Elin Runnqvist, Mireille Bonnard, Hanna S. Gauvin, Shahram Attarian, Agnès Trébuchon, Robert J. Hartsuiker, F. -Xavier Alario

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## To cite this version:

Elin Runnqvist, Mireille Bonnard, Hanna S. Gauvin, Shahram Attarian, Agnès Trébuchon, et al. Internal modeling of upcoming speech: A causal role of the right posterior cerebellum in non-motor aspects of language production. Cortex, 2016, 81, pp.203-214. 10.1016/j.cortex.2016.05.008. hal-01431288

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Submitted on 6 Nov 2018

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Internal modeling of upcoming speech: A causal role of the right posterior cerebellum in non-motor aspects of language production

Elin Runnqvistª, Mireille Bonnardᵇ, Hanna S. Gauvinᶜ, Shahram Attarianᵈ, Agnes

Trebuchonᵇ,ᵉ, Robert J. Hartsuikerᶜ, & F.-Xavier Alariof

a - Aix-Marseille Université, CNRS, LPL UMR 7309, 5 Avenue Pasteur, 13604 Aix-en-Provence, France

b - Aix-Marseille Université, INSERM, INS UMR S 1106, Faculté de Médecine, 27 Boulevard Jean Moulin, 13005 Marseille, France

c - Ghent University, Department of Experimental Psychology, Henri Dunantlaan 2, 9000 Ghent, Belgium

d - Aix-Marseille Université, Inserm UMR 910, Reference center for Neuromuscular disorders and ALS CHU La Timone, 264 Rue Saint-Pierre, 13385 Marseille, France

e - Assistance Publique-Hôpitaux Marseille, 13005 Marseille, France

f - Aix-Marseille Université, CNRS, LPC UMR 7290, 3 place Victor Hugo, 13331 Marseille, France

Corresponding author:

Elin Runnqvist

elin_runnquist@yahoo.es
Abstract

Some language processing theories propose that, just as for other somatic
actions, self-monitoring of language production is achieved through internal
modeling. The cerebellum is the proposed center of such internal modeling in
motor control, and the right cerebellum has been linked to an increasing number
of language functions, including predictive processing during comprehension.
Relating these findings, we tested whether the right posterior cerebellum has a
causal role for self-monitoring of speech errors. Participants received 1Hz
repetitive transcranial magnetic stimulation during 15 minutes to lobules Crus I
and II in the right hemisphere, and, in counterbalanced orders, to the
contralateral area in the left cerebellar hemisphere (control) in order to induce a
temporary inactivation of one of these zones. Immediately afterwards, they
engaged in a speech production task priming the production of speech errors.
Language production was impaired after right compared to left hemisphere
stimulation, a finding that provides evidence for a causal role of the cerebellum
during language production. We interpreted this role in terms of internal
modeling of upcoming speech through a verbal working memory process used to
prevent errors.

Keywords: language production, cerebellum, internal modeling, self monitoring,
verbal working memory
# 1. Introduction

Evidence indicates that sensory and motor information forms an integral part of language acquisition, representation, and processing beyond auditory and visual perception or articulation (e.g., Pulvermuller & Fadiga, 2010). This has motivated research into commonalities in the neural structures and dynamics responsible for lower (i.e., sensory-motor) and higher order cognitive abilities (i.e., language) (e.g., Pickering & Garrod, 2013; Hickok, 2012). Here we aimed at further contributing to this endeavor by investigating the causal role of the cerebellum in a particular aspect of language processing, namely self-monitoring of language production beyond its pure motor aspects.

## 1.1 Functional Topography of the Cerebellum

During the last century, the conception of the cerebellum has progressively evolved from that of a pure motor control device to that of a modulator of the cognitive functions tied to any area in cortex to which it is reciprocally connected (e.g., Andreasen & Pierson, 2008; Mariën et al., 2001; Stoodley & Schmahmann, 2010). The cerebellum has reciprocal links through pontine and dentate nuclei and thalamus mainly to frontal and association areas of the cerebral cortex (e.g., Mariën & Manto, 2015). These links include not only frontal motor areas, but also language-related areas such as Broca's region (Desmond et al., 2005; Mariën et al., 2001). As highlighted by Murdoch (2010), "this reciprocal connectivity forms a series of segregated neural loops that are hypothesized to facilitate linguistic function in the same way that the cerebellum enhances motor functions (Leiner et al., 1989)."
In parallel with the expansion regarding the functionality of the cerebellum,
there has been substantial progress in our knowledge concerning its functional
topography (e.g., Stoodley & Schmahmann, 2010). Of special importance for the
present purposes are two functional topographic distinctions: regions involved
in motor versus non-motor functions, and regions involved in linguistic
functions.

Based on connectivity and functional activation patterns, Stoodley and
Schmahmann (2009; 2010; see also Desmond & Fiez, 1998 and Ito, 2008 for
similar topographical distinctions) distinguish three topographic functional
regions: a “sensorimotor region” comprising the anterior lobe (I-V), lobule VIII,
and lobule VI to a lesser extent; a “cognitive region” comprising lobules VI, VII
and dentate nucleus -though it has been observed that within the dentate, motor
and non-motor domains can also be distinguished (e.g., Dum & Strick, 2003); and
a “limbic region” comprising vermis and fastigial nucleus (see figure 1a). In the
particular case of language production both pure motor (speech articulation)
and more cognitive aspects (linguistic processing) can be distinguished. In line
with the functional topographic division outlined above, there is evidence for the
anterior lobe being implicated in articulatory processes (e.g., Urban et al., 2003;
Ackermann et al., 1992), and the posterior lobe being implicated in higher order
processes such as phonological, semantic and word generation when factoring
out articulation (e.g., Stoodley & Schmahmann, 2009).

Anatomical and functional evidence also speak to the localization of
linguistic function within the cerebellum. Several authors have argued that
language processing is mostly confined to the right cerebellum (e.g., Stoodley &
Schahmann, 2010; Mariën et al., 2001). Anatomically, projections between the
cerebral and cerebellar cortices are largely (though not exclusively) contralateral (e.g., Brodal, 1979). The lateralization is also supported by fMRI findings that linguistic functions are mainly localized in the right hemisphere of the cerebellum, though often involving a small component of the contralateral lobule (e.g., Stoodley & Schmahmann, 2009). Finally, most clinical reports suggest that language impairments such as impaired verbal fluency and agrammatism generally arise following right cerebellar hemisphere lesions (Gebhart et al., 2002; Hassid, 1995; Hokkanen et al., 2006; Marien et al., 2001; Riva and Giorgi, 2000; Silveri et al., 1994; Zettin et al., 1997; Scott et al., 2001). In this context, it should be mentioned that a small number of neuropsychological studies have also reported linguistic deficits following left cerebellar hemisphere lesions (e.g., Fabbro et al., 2000; Cook et al., 2004; Murdoch & Whelan, 2007). Though one possibility is that the pathophysiological mechanism underlying these lesions was crossed cerebellocerebral diaschisis (e.g., Cook et al., 2004), it is equally possible that they reflect ipsilateral cerebellar cerebral diaschisis, implying that the cerebellum might be bilaterally involved in language processing (Murdoch & Whelan, 2007). Another exception to the lateralization of linguistic function is to be found in prosodic and auditory language processing, that both seem to be left lateralized within the cerebellum (e.g., Callan et al., 2007; Petacchi et al., 2005).

These latter findings suggest an even more fine-grained functional cerebellar specialization mirroring the cortical hemispheric specialization. Nevertheless, though the involvement of the left cerebellar hemisphere in linguistic function certainly merits further investigation, the global impression provided by the previous literature, especially in what concerns the cognitive components of
language production, is that the right hemisphere has a predominant, though not exclusive, role for linguistic functions.

In sum, the combination of these two topographic functional distinctions leaves posterior lobules VI and Crus I and II in the right cerebellar hemisphere as prime candidates for hosting processes of language production beyond its pure motor aspects. A further question is exactly what type of cognitive function(s) the cerebellum is involved in. Concerning language, this function should be rather indirect (i.e., not directly concerning linguistic representations or their access) since damage to the cerebellum is not strongly tied to central disturbances of production and comprehension (e.g., Ito, 2008; Desmond & Fiez, 1998). More generally, several authors highlight that although many functions have been ascribed to the cerebellum, the uniformity of its synaptic organization suggests that a single, characteristic computation may be common to all (e.g., Medina & Mauk, 2000). This hypothesis of neural computation homogeneity has lent itself to hypotheses of cognitive computation homogeneity across different regions of the cerebellum (i.e., motor and cognitive regions). One example of this which we will focus on in the present study is that the cerebellum is devoted to internal modeling of self-generated actions, whether motor or cognitive in nature (e.g., Ito, 2008).

## 1.2 Internal modeling of upcoming speech

In the domain of motor control it is widely held that control of somatic movement involves internal modeling, allowing for the correction of motor commands by producing expectations of their sensory consequences before their effective output as physical actions (i.e., corollary discharge or efference copies;
McCloskey, 1981; Jeannerod, 1988). These sensory outcome predictions are then
compared with the actual sensory input; whatever matches the outcome
predictions is inhibited (i.e., reafference cancellation). In that way, a means is
provided to detect any unpredicted sensorial data entailing that correction of the
motor command is required (Wolpert, Ghahramani & Jordan, 1995). The
posterior lobes of the cerebellum (laterality depending on the task) constitute
the hypothetical center of this internal modeling of motor actions (Blakemore &
Sirigu, 2003; Blakemore et al., 1998; Blakemore et al., 2001; Imamizu et al., 2000;
Miall & King, 2008). Cerebellar activity is modulated by the presence and
predictability of the consequences of self-generated movements (e.g., Blakemore
et al., 1998; 2001). Ito (2008) proposed to extend the domain of internal models
from sensori-motor actions to mental activities based on a review of anatomical
(i.e., appropriate neural wiring between the cerebellum and the cerebral cortex),
functional (appropriate mental activity involving the cerebellum) and
neuropsychological data (the association of some mental disorders with
cerebellar dysfunction).

The idea of internal models has also been incorporated into theories and
empirical investigations of language processing (Pickering & Garrod, 2013;
Pickering & Garrod, 2014; Hickok, 2012; Lesage at al., 2012; Argyropoulos et al.,
2011; 2013; 2015). In the domain of language production, certain theories
propose that internal models are used to self-monitor (prevent and detect
speech errors) some or all levels of our utterances. For example, Hickok (2012)
conceives of internal models of speech motor control, and proposed that higher
levels (phonological encoding) of such control are modeled through temporo-
parietal cortex; while the lower level (phonetic encoding) would be modeled
through the cerebellum. Empirical evidence suggestive of a role for internal modeling of articulation actions (i.e., detecting and correcting errors in the programming and execution of speech articulation) can be found in the literature (e.g., Houde, Nagarajan, Sekihara, & Merzenich, 2002; Heinks-Maldonado, Mathalon, Gray, Ford, 2005; Ghosh, Tourville, & Guenther, 2008). More hypothetical and less explored is the hypothesis that also levels beyond pure motor aspects of language might be monitored through internal models as proposed by Pickering and Garrod (e.g., Alario & Hamamé, 2013; Hartsuiker, 2013; Pickering & Garrod, 2013; Pickering & Garrod, 2014; Strijkers, Runnqvist, Costa & Holcomb, 2013). Given the above-mentioned (section 1.1) lack of central disturbances following cerebellar lesions, one might wonder whether it makes sense to hypothesize about cerebellar involvement in such a general mechanism as internal modeling. However, internal modeling of upcoming speech, while indeed being a mechanism of a general nature in the sense that it is supposed to always co-occur with the preparation of speech, is arguably a process whose incorrect functioning could be difficult to detect in comparison with many other components of language processing. This is because the consequences of internal modeling only become apparent when the speaker is preparing an erroneous utterance, which is not the default situation. In contrast, other general processes such as lexical access, phonological and phonetic encoding etc. are not only always present during language processing, but they are essential to it as no language comprehension/production can take place without them. Elsewhere it has been argued that high-level linguistic disturbances subsequent to cerebellar lesions may be more accurately detected and characterized by high-level assessments that evaluate the proficiency of more complex language processes
beyond single word hierarchies (Murdoch, 2010). Such high-level assessments
would consist in tasks demanding frontal lobe support in the manipulation of
novel situations, lexical- semantic operations, the development of language
strategies, and the organization and monitoring of responses (Copland et al.,
2000). As we will describe below, our experimental task was designed keeping in
mind this potential difficulty of detecting internal modeling functioning.

Insert Figure 1 about here

1.3 The current study

Here we wanted to test whether monitoring language production levels
beyond pure motor aspects of speech is achieved through internal modeling, and
whether the cerebellum has a necessary role in such modeling. We used
repetitive transcranial magnetic stimulation rTMS at a frequency of 1Hz, which is
known to temporarily inactivate the stimulated area. Guiding our predictions by
the two functional topographic distinctions reviewed above, we expected that
disrupting cerebellar function in the right posterior lobules Crus I and II might
lead to an impaired speech production monitoring (see Figure 1a). As a control
condition (and in counterbalanced orders), the same participants received
stimulation to the contralateral area in the left hemisphere of the cerebellum,
which should be less related to the linguistic processing of language production.
Participants engaged in a speeded language production task designed to prime
the production of errors (see Figure 1b). By creating a situation of high load on
the speech production monitor through the speeded nature of the task and by
priming speech errors, we aimed at providing the ideal circumstances for
observing a high-level linguistic impairment that would most probably be
undetectable with standard language test batteries (e.g., Copland et al., 2000; Murdoch, 2010). To have an additional marker of self-monitoring beyond global error rates, we manipulated the lexical status of the primed error outcomes. Previous research has shown that speakers are more likely to produce errors resulting in new words than pseudowords, indicating that lexicality is a filter used to intercept errors during speech production (Baars, Motley, & MacKay, 1975; Hartsuiker, Corley & Martensen, 2005; Nooteboom, 2005). Returning to our task, the following three predictions can be made: 1) Impaired language processing of any sort (including monitoring) would be apparent through slower response times and/or higher error rates; 2) Impaired self-monitoring for accuracy would be indexed by an overall increased error-rate; 3) Impaired self-monitoring for lexicality would result in a modulation of errors as a function of their lexical status.

## 2. Methods

The study received appropriate ethical approval (filed under "ID-RCB-2009-A01059-48" at "Comité de Protection des Personnes Sud Méditerranée I") and was performed in accordance with the declaration of Helsinki.

### 2.1. Participants

Sixteen (ten females, six males) right-handed native speakers of French took part in the study in exchange for a monetary compensation. The average age of participants was 24 (SD 3), with an average of 16 (SD 2) years of education. No participant reported any history of language or neurological disorders.

### 2.2. Materials

Target stimuli consisted of 160 printed French words (see appendix A). For illustrative purposes the examples in the text are given in English. Across
subjects, each word was used twice in combination with another word (e.g., *mole sail*, *mole fence*). When exchanging the first letters of these combinations, one of them resulted in a new word pair (*sole mail*, lexical error outcome) and the other in a non-word pair (*fole mence*, non-lexical error outcome). All combinations for which initial sound exchange resulted in new word-pairs (*mole sail*) were used also in the exchanged format (*sole mail*). A given subject was only presented with one combination for each word (lexical or non-lexical outcome), and was only presented with one of the words differing in only the first sound (*mole* or *sole*). This resulted in the creation of four experimental lists with 80 word pairs (40 lexical and 40 non-lexical error outcome). Each subject received one such list divided in two separate blocks of 40 pairs each (20 lexical and 20 non-lexical outcome). Stimuli pertaining to the two blocks were matched for lexical frequency of the first word in the combination, overall lexical frequency, neighborhood density, word length, and phonetic distance.

During the experiment, each target word combination was preceded by three priming word pairs. The first two shared the initial consonants and the third pair had further phonological overlap with the error being primed (*sun mall – sand mouth – soap mate – mole sail*). In each of the two experimental blocks, subjects were also presented with 70 filler pairs that had no specific relationship to the target pairs. One to three such filler pairs were presented to subjects before each sequence of primes and target. Thus, each subject was presented with 460 unique word combinations divided in two blocks of 230 word pairs each (40 targets, 120 primes and 70 fillers). Each experimental block contained three sub-blocks in which these 230 words were repeated three times in different orders. Subjects were instructed to read all target word pairs aloud,
all prime pairs silently, 41% of the filler pairs aloud, and 59% of the filler pairs silently.

## 2.3. Procedure

### 2.3.1. Pre-stimulation protocol.

Participants first received written and oral information about the rTMS technique, and they underwent a brief examination by a neurologist. They were then asked to fill in a questionnaire and sign an informed consent. Next, they were familiarized with the experimental task through written and oral instructions and through several practice trials.

### 2.3.2. rTMS protocol.

A frameless stereotaxic system was used to position the TMS coil on the scalp in order to stimulate a precise anatomical region-of-interest. All volunteers participated in a separate MRI session where a high resolution anatomical scan was acquired. During the TMS session, a Polaris Spectra infrared camera (Northern Digital Inc., Canada) tracked participants' head and registered it to their MRI scan. The neuronavigation (Navigation Brain System, Nexstim 2.3, Helsinki, Finland) was used both to target and to visualize the sites during stimulation. The areas targeted for stimulation (i.e., lobules Crus I and II of the right cerebellum and the contralateral area of the left cerebellum) were marked on each participant's MRI and checked by a neurologist. Topographic mapping studies of the human motor cortex, using a figure of eight coil with 4.5 cm loop diameter, suggest a practical spatial resolution of TMS of 0.5 cm (e.g., Brasil-Neto et al., 1992). This suggests we can be rather confident that we stimulated at least part if not the complete region of interest, while not affecting untargeted areas.

The choice of stimulation control-site is an important asset of the current study:
besides serving as a control for any non-specific effects of the stimulation, it also
keeps the variable of physical discomfort constant across conditions. This is
especially important since cerebellar TMS has been reported to induce muscle
discomfort and twitching (e.g., Théoret et al., 2001; Harrington & Hammond-
Tooke, 2015), making it difficult to dissociate any impact on behavior from a
general attention decline induced by this discomfort. Repetitive transcranial
magnetic stimulation (rTMS) was effectuated with a figure-of-eight coil at 1Hz at
60% of maximum stimulator output intensity, using a Medtronic Magpro X100
TMS system. Each session was carried out in two parts: (1) 15 min stimulation
(900 pulses) followed by 3*5 min of experimental task; (2) 15 min stimulation
(to the opposite hemisphere) followed by 3*5 min of experimental task. The
order of stimulation (left/right first) was counterbalanced across participants.
The duration of the off-line effects of low frequency rTMS is estimated to be
between 60 and 100% of the duration of the stimulation (e.g., Nyffeler et al.,
2006; Eisenegger et al., 2008; Chen et al., 1997). This means that we could be
rather confident that the effects of inactivation would last between 9-15 minutes
of the experimental task following the stimulation of each hemisphere, and that
the effects of stimulating one hemisphere would not carry over to performance
on the experimental task after stimulating the other hemisphere.

2.3.3. *Experimental task protocol.*

Participants wore headphones and they were told to silently read word
pairs, but to name aloud the last word pair they had seen whenever an
exclamation mark was presented. All targets and 41% of the filler items were
followed by an exclamation mark presented for 500 ms. Each word pair was
presented for 700 ms and was followed by a blank screen for 200 ms. In order to
encourage participants to speak fast, a tone sounded 500 ms after the
presentation of the exclamation mark. The next item was presented 1000 ms
after the beginning of the tone. Stimulus presentation was controlled using
Eprime software. Productions were recorded both through Eprime and with a
separate recorder and were processed off-line.

2.4. Data processing

2.4.1. Errors.

A person naïve to the purpose of the experiment transcribed
orthographically all productions. The transcriptions were scored as correct,
errors, partial responses (e.g., only one word produced), dysfluencies or
omissions. The errors were classified as “priming related errors” or “other
errors”. “Priming related errors” included full exchanges (*mole sail => sole mail*),
partial exchanges (anticipations, e.g., *mole sail => sole sail*, perseverations, e.g.,
*mole sail => mole mail*, other partial exchanges, e.g., *mole sail => sole saint*),
repaired and interrupted exchanges (*mole sail => so...mole sail*), full and partial
competing errors (*mole sail => star milk/star sail*), and other related errors (*mole
sail => mail sole*). “Other errors” included diverse phonological substitutions that
were unrelated to the priming manipulation (e.g., *mole sail => hole saint/ro..mole
sail/...saint*).

2.4.2. Response times.

Another person naïve to the purpose of the experiment measured the
response times for all individual recordings using the software check-vocal
(Protopapas, 2007).

2.5. Statistical analyses
The data were analyzed using the lme4 package (Bates et al., 2015) in R version 3.2.2 (R Development Core Team, 2015). Errors were analyzed using generalized linear mixed models (GLMM) with a binomial link function (e.g., Jaeger, 2008), estimating the conditional probability of a response given the random effects and covariate values. Response times were analyzed with linear mixed models (LMM), estimating the influence of fixed and random covariates on the response. One difference between GLMMs and LMMs concerns the type of hypothesis testing that can be used, which is related to the knowledge about the dispersion parameter in both cases. In GLMMs of binomial data, the dispersion parameter is fixed at 1 (e.g., Chen & Conomos, 2015), while in linear mixed models the residual variance has to be estimated. For this reason, z-scores can be used in GLMMs while t-values are used in LMMs. Because both z-scores and p-values are related to the standard normal distribution, p-values can reliably be obtained from z-scores. The summary output of the GLMM function of lme4 in R provides p-values based on asymptotic Wald tests, which is common practice for generalized linear models (e.g., Bolker et al., 2009). The Wald statistic is asymptotically distributed as a standard normal distribution and uses the z-score to calculate the p-value. In contrast, the summary output of the LMM function only provides t-values. Consequently, we report p-values for error-rates and t-values for response times. Following common practice (e.g., Fisher 1925), we take t-values to approximate z-scores and assume that absolute values above 1.96 reflect significant effects.

A common protocol was used for building and comparing both GLMMs and LMMs. In order to determine which fixed effects and interactions to include in the models, a forward selection procedure was used in which each of the
variables was entered into the analysis individually, followed by interaction
terms, and only variables or interaction terms that were significant (i.e., with a T-
value above 1.96 or a p-value below .05) were kept in the analyses. In those cases
where a newly added variable was significant and changed the significance of
another variable, the anova function of R was used to compare both models and
non-significant p-values were taken to indicate that the more parsimonious
model should be preferred.

In all models, Participants and Items were included as crossed random
effects (i.e., intercept estimates), allowing to tease apart the influence of
subjects/items on their repeated observations from the influence of the fixed
effects of theoretical interest. Errors (i.e., both related and other errors) were
fitted with a first series of models to evaluate a non-specific impairment of self-
monitoring after right hemisphere stimulation. These models included the fixed
factors hemisphere and block. Next, the subset of priming-related errors were
fitted in separate models to evaluate the output-tied lexicality bias (i.e., the
tendency to make more lexical than non-lexical errors) and its interaction with
hemisphere. These models thus included the fixed factors lexicality, hemisphere,
and block.

For response times, a Box-Cox test (Box & Cox, 1964) indicated that a
logarithmic transformation was the most appropriate to approximate a normal
distribution, and this is what was used. For clarity, however, we also report
approximate estimates of the effect sizes in milliseconds obtained by running
identical models with the untransformed response times. The fixed factors
included in the models were hemisphere and block as well as the interactions.

2.6. Results
### 2.6.1. Errors.

Mean error-rates for overall errors and the subset of priming-related errors are reported in Tables 1a and b respectively, and the final models are summarized in Tables 1c and d respectively. Out of the 3840 target trials, there were 500 errors (13% of the data). As shown in Figure 2a, there were more errors after stimulation to the Right hemisphere (14.2% of 1920 target trials) compared to the Left hemisphere (11.8% of 1920 target trials). Overall, there was a progressive decrease in errors in each experimental block (1st: 15.3%, 2nd: 12.9%, 3rd: 10.9%). For the subset of 161 priming related errors (4.2%), more errors were made in the lexical outcome condition (6.4% overall: 7.3% RH and 5.5% LH) than in the non-lexical outcome condition (2%: 2.1% RH and 1.9% LH); thus, there was a lexical bias effect. No other significant effects of interest were found.

<table><caption>Table 1a. Overall mean error-rates in each experimental condition; numbers in parenthesis represent the standard error of the mean.</caption><thead><tr><th>Block</th><th>Right hemisphere</th><th>Left hemisphere</th></tr></thead><tbody><tr><td>1</td><td>15.6 (1.4)</td><td>15.0 (1.4)</td></tr><tr><td>2</td><td>14.2 (1.4)</td><td>11.6 (1.3)</td></tr><tr><td>3</td><td>12.8 (1.3)</td><td>8.9 (1.1)</td></tr></tbody></table>

<table><caption>Table 1b. Mean error-rates of priming-related errors in each experimental condition; numbers in parenthesis represent the standard error of the mean.</caption><thead><tr><th rowspan="2">Block</th><th colspan="3">Right hemisphere</th><th colspan="3">Left hemisphere</th></tr><tr><th>Lexical</th><th>Non-lexical</th><th>Av.</th><th>Lexical</th><th>Non-lexical</th><th>Av.</th></tr></thead><tbody><tr><td>1</td><td>8.4<br>(1.6)</td><td>1.6<br>(0.7)</td><td>5.0<br>(0.9)</td><td>6.6<br>(1.4)</td><td>1.9<br>(0.8)</td><td>4.2<br>(0.8)</td></tr></tbody></table>
<table><caption>Table 1c. All errors (significant effects)</caption><tr><td>2</td><td>7.8<br>(1.5)</td><td>2.2<br>(0.8)</td><td>5.0<br>(0.9)</td><td>5.6<br>(1.3)</td><td>2.5<br>(0.9)</td><td>4.1<br>(0.8)</td></tr><tr><td>3</td><td>5.6<br>(1.3)</td><td>2.5<br>(0.9)</td><td>4.1<br>(0.8)</td><td>4.4<br>(1.1)</td><td>1.3<br>(0.6)</td><td>2.8<br>(0.7)</td></tr></table>

<table><caption>Table 1d. Priming related errors (significant effects)</caption><thead><tr><th></th><th>Effect estimate</th><th>Std.err</th><th>z-value</th><th>p-value</th></tr></thead><tbody><tr><td>(Intercept)</td><td>-2.25</td><td>0.22</td><td>-10.28</td><td>&lt;0.01</td></tr><tr><td>Hemisphere (Right)</td><td>0.21</td><td>0.10</td><td>2.06</td><td>0.04</td></tr><tr><td>Block (2)</td><td>-0.24</td><td>0.12</td><td>-2.00</td><td>0.05</td></tr><tr><td>Block (3)</td><td>-0.46</td><td>0.12</td><td>-3.77</td><td>&lt;0.01</td></tr></tbody></table>

<table><thead><tr><th></th><th>Effect estimate</th><th>Std.err</th><th>z-value</th><th>p-value</th></tr></thead><tbody><tr><td>(Intercept)</td><td>-3.10</td><td>0.21</td><td>-14.55</td><td>&lt;0.01</td></tr><tr><td>Lexicality (non-lexical)</td><td>-1.25</td><td>0.22</td><td>-5.80</td><td>&lt;0.01</td></tr></tbody></table>

### 2.6.2. Response Times.

Mean response times are reported in Table 2a and the final model is summarized in Table 2b. After excluding the 500 errors (13%), 38 dysfluencies (1%), 57 partial responses (1.5%) 38 non-responses (1%), and 74 recording failures (1.6%), the remaining 3133 correct responses (81.6% of the data) were included in the response time analysis. In the first experimental block, participants were slower after right (457ms) compared to left hemisphere (435ms) stimulation (see figure 2b). No other significant effects of interest were found.

Table 2a. Mean response times in each experimental condition; numbers in parenthesis represent the standard error of the mean.
<table><caption>Table 2b. Response times in trials with correct responses (significant effects)</caption><thead><tr><th>Block</th><th>Right hemisphere</th><th>Left hemisphere</th></tr></thead><tbody><tr><td>1</td><td>457 (4.9)</td><td>435 (4.3)</td></tr><tr><td>2</td><td>441 (4.9)</td><td>448 (4.7)</td></tr><tr><td>3</td><td>440 (4.9)</td><td>443 (5)</td></tr></tbody></table>

<table><thead><tr><th></th><th>Effect estimate</th><th>In ms</th><th>Std.Error</th><th>t value</th></tr></thead><tbody><tr><td>(Intercept)</td><td>6.06</td><td>438</td><td>0.04</td><td>159.35</td></tr><tr><td>Hemisphere (Right)</td><td>0.05</td><td>25</td><td>0.01</td><td>4.66</td></tr><tr><td>Block (2)</td><td>0.03</td><td>14</td><td>0.01</td><td>2.56</td></tr><tr><td>Block (3)</td><td>0.00</td><td>5</td><td>0.01</td><td>0.26</td></tr><tr><td>Hemisphere (Right) x Block (2)</td><td>-0.07</td><td>-32</td><td>0.02</td><td>-4.53</td></tr><tr><td>Hemisphere (Right) x Block (3)</td><td>-0.05</td><td>-27</td><td>0.02</td><td>-3.49</td></tr></tbody></table>

Insert Figure 2 about here

### 3. General Discussion

The aim of this paper was to explore the causal role of the right posterior cerebellum in language production. Specifically, we tested the hypothesis that self-monitoring of not exclusively motor related aspects of language might be achieved through internal models of upcoming speech, instantiated through the cerebellum. To this end, participants received rTMS to the right and left posterior hemispheres of the cerebellum in counterbalanced orders, and then engaged in a task that maximized the load of speech production monitoring by requiring speeded responses and by priming the production of speech errors.

Furthermore, to have an index of a particular type of self-monitoring beyond
global error-rates, we manipulated the lexical status of the potential error outcomes (pseudoword errors are intercepted more often than word errors).

The following three predictions were made: 1) Impaired language processing of any sort (including self-monitoring) would be apparent through slower response times and/or higher error rates; 2) Impaired self-monitoring for accuracy would be indexed by an overall increased error-rate; and 3) Impaired self-monitoring for lexicality would result in a modulation of errors as a function of their lexical status. In line with our first two predictions, we observed that after stimulation to the right hemisphere of the cerebellum compared to the left hemisphere, participants committed more errors (all three blocks) and took longer in starting to produce correct responses (first block). Contrary to our third prediction, this effect was independent of the lexical status of the error outcome (this non-confirmed prediction will be further discussed below).

In general terms, an implication of the right cerebellar lobules Crus I and II in cognitive aspects of language production had already been highlighted by functional activation studies and neuropsychological studies (e.g., Stoodley & Schmahmann, 2009; Mariën et al., 2001). An important contribution of our study is that it shows within the same participants that this area has a causal role in language production, and that in a context in which compensatory changes or rewiring has not had a chance to occur (e.g., as might occur following a stroke). Furthermore, by including a dependent variable (error-rates) that can be directly linked to a particular (though admittedly broad) cognitive process (self-monitoring), this study helps constraining the functional role that the cerebellum might have in the process of producing language. It should be noted that an increase in response times as observed in the first block is also consistent with
an impaired self-monitoring ability: for example, a delay in the interception and
inner repair of speech errors might lead to such a pattern. However, though
parsimony favors a common origin of the increased error-rates and the response
time delay, other possible accounts such as impairment in the temporal
organization of the sound structure of utterances (e.g., Ackermann et al., 2007)
remain equally possible for the response time delay.

Theoretically, these data are consistent with the view that internal models
are used to self-monitor speech production (e.g., Pickering & Garrod, 2013;
Pickering & Garrod, 2014; Hickok, 2012). In what follows we will try to shed
some light at the issue of what level(s) of language production might be subject
to this internal modeling. A first candidate level, which would not assume the
current results to reflect the involvement of any linguistic processing proper, is
articulation. Trouble with the control of motor production might indeed lead to
certain speech errors in the form of pure dysfluencies or mispronunciations,
though many problems of speech motor control will rather be reflected in
properties that do not affect accuracy such as lengthening of certain segments,
vocal quality, pitch, tone, volume, strength, steadiness, speed etc. However, the
errors included in our analyses involved *phonological* units (speakers added,
deleted, or exchanged phonemes), which, in our opinion, is not predicted by an
impaired motor control function. Furthermore, speech motor control is not
expected to be affected by the stimulation to Crus I and II of the right hemisphere
(e.g., Stoodley and Schmahmann, 2009). Disorders related to articulatory aspects
of language production such as dysarthria has been shown to involve lesions in
the upper paravermal region of the right cerebellar hemisphere, the site of
coordination of articulatory movements of the tongue and orofacial muscles (e.g.,
Ackermann et al., 1992; Urban et al., 2003). Even though TMS lacks focal
precision at the millimeter level as discussed previously (section 2.3.3), the
posterior areas we targeted here should be at a sufficient distance from the
anterior regions responsible for speech motor control.

A second candidate level to locate our effects can be found moving a little
further along the cognitive continuum of language production. As mentioned in
the Introduction (1.2), the language production model of Hickok (2012)
conceives a role of the cerebellum for the internal modeling of phonetic aspects
of language production. However, this explanation is not satisfactory either to
account for the observed error pattern involving phonological units.

Finally, moving upwards in the cognitive continuum of language
production, also a third candidate level can be excluded since we found no
evidence for an implication of the cerebellum in the monitoring of lexical
processing. That is, speakers intercepted and repaired internally non-lexical
items about to be produced to the same extent regardless of stimulation site. Of
course, being based on a null effect, this interpretation should be taken with
caution. In sum, our data suggest that the cerebellum, besides having a role for
speech motor control of phonetic aspects of speech, is also implicated in the
supervision of phonological aspects but not of higher levels of language
production.

One possibility is that our findings reflect a difficulty of maintaining a
phonological speech goal (i.e., auditory target in terminology of Hickok, 2012),
perhaps due to interference with verbal working memory. That is, the referent of
comparison in the internal modeling process might be more easily disrupted
because of verbal working memory failure, resulting in phonological errors of
both lexical and non-lexical types going undetected. Supporting this
interpretation is the fact that selective activation in tasks involving verbal
working memory in conjunction with language has been reported in posterior
parts of the cerebellum, predominantly in the right hemisphere, within a
network that also involves Broca's area and the supplementary motor area
(SMA) (e.g., Desmond & Fiez, 1998). Desmond and Fiez propose that the
cerebellum might serve to enhance working memory performance by comparing
the output of subvocal articulation with acoustically based phonological
representations in a short-term store. This is supposed to occur especially as the
memory load increases and the need for more accurate and efficient rehearsal
becomes more critical, as was presumably the case in our study in which
speakers were instructed to say aloud the latest word pair they had read
whenever an unpredictable beep sounded. Relevant for the ability of self-
monitoring, discrepancies between actual versus intended motor trajectories are
hypothesized to result in an error-correction that would serve to maintain the
integrity of the rehearsed items. (e.g., Desmond et al., 1997; Desmond & Fiez,
1998). This interpretation suggests that an accurate model of language
production and self-monitoring should integrate both domain-general cognitive
computations such as internal modeling, and interfacing cognitive systems such
as verbal working memory.

4. Conclusion

In conclusion, the research presented here supports a causal role of the
right posterior cerebellum for language production beyond its pure motor
aspects. A plausible specification of this role is that the cerebellum is involved in
internal modeling of upcoming speech that is used to detect errors, concretely by
maintaining in verbal working memory acoustically based phonological
representations which can afterwards be compared with the output of subvocal
articulation processes.

Acknowledgements

Elin Runnqvist was supported by a postdoctoral grant from the People
Programme (Marie Curie Actions) of the European Union's Seventh Framework
Programme (FP7/2007-2013) under REA grant agreement n° PIEF-GA-2012-
329339. We acknowledge support from the Brain & Language Research Institute
(Aix-Marseille Université: AMIDEX grant ANR-11-IDEX-0001-02 and Labex grant
ANR-11-LABX-0036). The authors are grateful to Jerome Gaychet for help with
stimuli selection, and to Elie Fabiani and Mourad Kherrab for help with data
processing.
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Appendix A.

LEXICAL

<table><thead><tr><th>Set A</th><th></th><th>Set B</th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>malade</td><td>sinus</td><td>durée</td><td>pédale</td><td>légion</td><td>barreau</td><td>bouton</td></tr><tr><td>dentier</td><td>répit</td><td>raison</td><td>maquette</td><td>ciment</td><td>belote</td><td>loto</td></tr><tr><td>faveur</td><td>semelle</td><td>ragot</td><td>fumeur</td><td>poker</td><td>sapin</td><td>primeur</td></tr><tr><td>tenue</td><td>voiture</td><td>marine</td><td>fission</td><td>musée</td><td>peinture</td><td>fournée</td></tr><tr><td>rosier</td><td>gâteau</td><td>coteau</td><td>coupon</td><td>lavoir</td><td>moisson</td><td>boulette</td></tr><tr><td>matin</td><td>passage</td><td>tonus</td><td>boucan</td><td>monteur</td><td>filleul</td><td>poulet</td></tr><tr><td>pillage</td><td>sommier</td><td>lutin</td><td>bocal</td><td>tracas</td><td>recteur</td><td>couture</td></tr><tr><td>cadeau</td><td>rocher</td><td>garage</td><td> palette</td><td>cuisson</td><td>manière</td><td>têtard</td></tr><tr><td>verger</td><td>bison</td><td>nature</td><td>ration</td><td>gardon</td><td>façon</td><td>croupier</td></tr><tr><td>ministre</td><td>seringue</td><td>crochet</td><td>briquet</td><td>tonton</td><td>rouleau</td><td>paresse</td></tr><tr><td> titre</td><td>voile</td><td>clé</td><td>bol</td><td>vieux</td><td>brique</td><td>mâche</td></tr><tr><td> ciel</td><td>fil</td><td>gag</td><td>troupe</td><td>robe</td><td>coeur</td><td>lueur</td></tr><tr><td> lierre</td><td>poupe</td><td>foire</td><td>prime</td><td>masque</td><td>fosse</td><td>plaque</td></tr><tr><td> flic</td><td>coin</td><td>douche</td><td>salle</td><td>veste</td><td>singe</td><td>place</td></tr><tr><td> butte</td><td>lave</td><td>gaule</td><td>tare</td><td>boule</td><td>lampe</td><td>four</td></tr><tr><td> dame</td><td>rose</td><td>banque</td><td>marque</td><td>roc</td><td>panne</td><td>braise</td></tr><tr><td> serre</td><td>valve</td><td>natte</td><td>pièce</td><td>course</td><td>forge</td><td>grange</td></tr><tr><td> mec</td><td>bise</td><td>note</td><td>puits</td><td>vase</td><td>pion</td><td>liège</td></tr><tr><td> rage</td><td>cap</td><td>dune</td><td>lieu</td><td>selle</td><td>fiche</td><td>suite</td></tr><tr><td> casse</td><td>tube</td><td>soir</td><td>lac</td><td>soupe</td><td>foudre</td><td>cause</td></tr><tr><td> gosier</td><td>râteau</td><td>blé</td><td>col</td><td>lecteur</td><td>joker</td><td>toison</td></tr><tr><td> patin</td><td>massage</td><td>loir</td><td>sac</td><td>lanière</td><td>fêtard</td><td>gamelle</td></tr><tr><td> sillage</td><td>pommier</td><td>mise</td><td>bec</td><td>maçon</td><td>journée</td><td>pilon</td></tr><tr><td> radeau</td><td>cocher</td><td>rap</td><td>cage</td><td>bouleau</td><td>moto</td><td>traction</td></tr><tr><td> berger</td><td>vision</td><td>tag</td><td>groupe</td><td>poussin</td><td>savoir</td><td>carreau</td></tr><tr><td> sinistre</td><td>meringue</td><td>vitre</td><td>toile</td><td>fonction</td><td>troupier</td><td>pelote</td></tr><tr><td> saveur</td><td>femelle</td><td>verre</td><td>salve</td><td>molosse</td><td>lardon</td><td>lapin</td></tr><tr><td> fagot</td><td>rumeur</td><td>poire</td><td>frime</td><td>cordée</td><td>frimeur</td><td>ceinture</td></tr><tr><td> farine</td><td>mission</td><td>souche</td><td>dalle</td><td>pointure</td><td>conteur</td><td>boisson</td></tr><tr><td> poteau</td><td>coupon</td><td>gare</td><td>taule</td><td>caverne</td><td>mouton</td><td>tilleul</td></tr><tr><td> cil</td><td>fiel</td><td>salade</td><td>minus</td><td>pelle</td><td>risque</td><td>crique</td></tr><tr><td> pierre</td><td>loupe</td><td>rentier</td><td>dépit</td><td>case</td><td>sueur</td><td>coupe</td></tr><tr><td> foin</td><td>clic</td><td>maison</td><td>raquette</td><td>verbe</td><td>tour</td><td>bosse</td></tr><tr><td> lutte</td><td>bave</td><td>venue</td><td>toiture</td><td>sable</td><td>poudre</td><td>linge</td></tr><tr><td> rame</td><td>dose</td><td>purée</td><td>dédale</td><td>vague</td><td>foule</td><td>rampe</td></tr><tr><td> barque</td><td>manque</td><td>bonus</td><td> toucan</td><td>pause</td><td>mouche</td><td>casque</td></tr><tr><td> patte</td><td>nièce</td><td>butin</td><td>local</td><td>tâche</td><td>piège</td><td>gorge</td></tr><tr><td> pote</td><td>nuits</td><td>parage</td><td>galette</td><td>fête</td><td>lobe</td><td>lion</td></tr><tr><td> lune</td><td>dieu</td><td>rature</td><td>nation</td><td>doc</td><td>geste</td><td>biche</td></tr><tr><td> tasse</td><td>cube</td><td>brochet</td><td>criquet</td><td>glace</td><td>fuite</td><td>flaque</td></tr><tr><td> cause</td><td>panne</td><td>selle</td><td>pomme</td><td>clé</td><td>pièce</td><td>butte</td></tr><tr><td> soupe</td><td>coeur</td><td>vase</td><td>cote</td><td>ciel</td><td>tare</td><td>mec</td></tr></tbody></table>

NON-LEXICAL

<table><thead><tr><th>Set B</th><th></th><th></th></tr></thead><tbody><tr><td>bouton</td><td>coussin</td></tr><tr><td>loto</td><td>jonction</td></tr><tr><td>primeur</td><td>colosse</td></tr><tr><td>fournée</td><td>bordée</td></tr><tr><td>boulette</td><td>jointure</td></tr><tr><td>poulet</td><td>taverne</td></tr><tr><td>couture</td><td>poison</td></tr><tr><td>têtard</td><td>lamelle</td></tr><tr><td>croupier</td><td>filon</td></tr><tr><td>paresse</td><td>fraction</td></tr><tr><td>panne</td><td>pomme</td></tr><tr><td>braise</td><td>contre</td></tr><tr><td>grange</td><td>touche</td></tr><tr><td>liège</td><td>tête</td></tr><tr><td>suite</td><td>disque</td></tr><tr><td>cause</td><td>gousse</td></tr><tr><td>toison</td><td>boulet</td></tr><tr><td>gamelle</td><td>ponton</td></tr><tr><td>pilon</td><td>bouture</td></tr><tr><td>traction</td><td>piment</td></tr><tr><td>carreau</td><td>rotlette</td></tr><tr><td>pelote</td><td>fracas</td></tr><tr><td>lapin</td><td>fusée</td></tr><tr><td>ceinture</td><td>région</td></tr><tr><td>boisson</td><td>caresse</td></tr><tr><td>tilleul</td><td> buisson</td></tr><tr><td>crique</td><td>pousse</td></tr><tr><td>coupe</td><td>frange</td></tr><tr><td>bosse</td><td>montre</td></tr><tr><td>linge</td><td>bourse</td></tr><tr><td>rampe</td><td>soeur</td></tr><tr><td>casque</td><td>fraise</td></tr><tr><td>gorge</td><td>canne</td></tr><tr><td>lion</td><td>vote</td></tr><tr><td>biche</td><td>dieux</td></tr><tr><td>flaque</td><td>somme</td></tr><tr><td>butte</td><td>cap</td></tr><tr><td>mec</td><td>lave</td></tr></tbody></table>
<table>
  <tr>
    <td>boule</td>
    <td>fosse</td>
    <td>veste</td>
    <td>gerbe</td>
    <td>lierre</td>
    <td>valve</td>
    <td>rage</td>
    <td>bise</td>
  </tr>
  <tr>
    <td>lueur</td>
    <td>singe</td>
    <td>suite</td>
    <td>fable</td>
    <td>flic</td>
    <td>salle</td>
    <td>gag</td>
    <td>marque</td>
  </tr>
  <tr>
    <td>robe</td>
    <td>lampe</td>
    <td>vieux</td>
    <td>dague</td>
    <td>natte</td>
    <td>coin</td>
    <td> titre</td>
    <td>fil</td>
  </tr>
  <tr>
    <td>masque</td>
    <td>contre</td>
    <td>course</td>
    <td>brique</td>
    <td>note</td>
    <td>lieu</td>
    <td>serre</td>
    <td>rose</td>
  </tr>
  <tr>
    <td>grange</td>
    <td>forge</td>
    <td>mâche</td>
    <td>touche</td>
    <td>dune</td>
    <td>prime</td>
    <td>foire</td>
    <td>troupe</td>
  </tr>
  <tr>
    <td>liège</td>
    <td>pion</td>
    <td>four</td>
    <td>tête</td>
    <td>casse</td>
    <td>voile</td>
    <td>douche</td>
    <td>puits</td>
  </tr>
  <tr>
    <td>braise</td>
    <td>fiche</td>
    <td>roc</td>
    <td>disque</td>
    <td>dame</td>
    <td>bol</td>
    <td>gaule</td>
    <td>lac</td>
  </tr>
  <tr>
    <td>plaque</td>
    <td>foudre</td>
    <td>place</td>
    <td>gousse</td>
    <td>soir</td>
    <td>tube</td>
    <td>banque</td>
    <td>poupe</td>
  </tr>
  <tr>
    <td>ciment</td>
    <td>peinture</td>
    <td>couture</td>
    <td>bordée</td>
    <td>tenue</td>
    <td>sinus</td>
    <td>pillage</td>
    <td>briquet</td>
  </tr>
  <tr>
    <td>bouton</td>
    <td>moisson</td>
    <td>poker</td>
    <td>jointure</td>
    <td>durée</td>
    <td>gâteau</td>
    <td>coteau</td>
    <td>bocal</td>
  </tr>
  <tr>
    <td>tracas</td>
    <td>filleul</td>
    <td>croupier</td>
    <td>taverne</td>
    <td>rosier</td>
    <td>sommier</td>
    <td>tonus</td>
    <td>seringue</td>
  </tr>
  <tr>
    <td>légion</td>
    <td>recteur</td>
    <td>tonton</td>
    <td>poison</td>
    <td>matin</td>
    <td>rocher</td>
    <td>lutin</td>
    <td>fission</td>
  </tr>
  <tr>
    <td>loto</td>
    <td>manière</td>
    <td>gardon</td>
    <td>lamelle</td>
    <td>cadeau</td>
    <td>voiture</td>
    <td>garage</td>
    <td>ration</td>
  </tr>
  <tr>
    <td>musée</td>
    <td>façon</td>
    <td>primeur</td>
    <td>filon</td>
    <td>verger</td>
    <td>coupon</td>
    <td>nature</td>
    <td>bison</td>
  </tr>
  <tr>
    <td>boulette</td>
    <td>rouleau</td>
    <td>têtard</td>
    <td>fraction</td>
    <td>crochet</td>
    <td>fumeur</td>
    <td>ministre</td>
    <td>boucan</td>
  </tr>
  <tr>
    <td>paresse</td>
    <td>coussin</td>
    <td>cuisson</td>
    <td>barreau</td>
    <td>faveur</td>
    <td>maquette</td>
    <td>malade</td>
    <td>répit</td>
  </tr>
  <tr>
    <td>fournée</td>
    <td>jonction</td>
    <td>poulet</td>
    <td>belote</td>
    <td>ragot</td>
    <td> palette</td>
    <td>dentier</td>
    <td>passage</td>
  </tr>
  <tr>
    <td>monteur</td>
    <td>colosse</td>
    <td>lavoir</td>
    <td>sapin</td>
    <td>marine</td>
    <td>semelle</td>
    <td>raison</td>
    <td>pédale</td>
  </tr>
  <tr>
    <td>coupe</td>
    <td>sœur</td>
    <td>linge</td>
    <td>sueur</td>
    <td>pote</td>
    <td>fiel</td>
    <td>blé</td>
    <td>taule</td>
  </tr>
  <tr>
    <td>bosse</td>
    <td>foule</td>
    <td>verbe</td>
    <td>geste</td>
    <td>lune</td>
    <td>cage</td>
    <td>mise</td>
    <td>nuits</td>
  </tr>
  <tr>
    <td>case</td>
    <td>vote</td>
    <td>flaque</td>
    <td>poudre</td>
    <td>tasse</td>
    <td>salve</td>
    <td>rap</td>
    <td>dieu</td>
  </tr>
  <tr>
    <td>rampe</td>
    <td>lobe</td>
    <td>vague</td>
    <td>dieux</td>
    <td>patte</td>
    <td>col</td>
    <td>tag</td>
    <td>loupe</td>
  </tr>
  <tr>
    <td>casque</td>
    <td>montre</td>
    <td>pause</td>
    <td>canne</td>
    <td>cil</td>
    <td>nièce</td>
    <td>vitre</td>
    <td>dose</td>
  </tr>
  <tr>
    <td>sable</td>
    <td>fuite</td>
    <td>tâche</td>
    <td>mouche</td>
    <td>pierre</td>
    <td>manque</td>
    <td>verre</td>
    <td>bave</td>
  </tr>
  <tr>
    <td>lion</td>
    <td>piège</td>
    <td>fête</td>
    <td>tour</td>
    <td>foin</td>
    <td>dalle</td>
    <td>poire</td>
    <td>groupe</td>
  </tr>
  <tr>
    <td>biche</td>
    <td>fraise</td>
    <td>doc</td>
    <td>risque</td>
    <td>lutte</td>
    <td>cube</td>
    <td>souche</td>
    <td>frime</td>
  </tr>
  <tr>
    <td>gorge</td>
    <td>frange</td>
    <td>glace</td>
    <td>pousse</td>
    <td>rame</td>
    <td>bec</td>
    <td>gare</td>
    <td>sac</td>
  </tr>
  <tr>
    <td>pelle</td>
    <td>somme</td>
    <td>crique</td>
    <td>bourse</td>
    <td>loir</td>
    <td>toile</td>
    <td>barque</td>
    <td>clic</td>
  </tr>
  <tr>
    <td>ceinture</td>
    <td>piment</td>
    <td>cordée</td>
    <td>bouture</td>
    <td>patin</td>
    <td>femelle</td>
    <td>gosier</td>
    <td>toiture</td>
  </tr>
  <tr>
    <td>boisson</td>
    <td>mouton</td>
    <td>pointure</td>
    <td>joker</td>
    <td>sillage</td>
    <td>râteau</td>
    <td>butin</td>
    <td>coupon</td>
  </tr>
  <tr>
    <td>tilleul</td>
    <td>fracas</td>
    <td>maçon</td>
    <td>fusée</td>
    <td>raveau</td>
    <td>mission</td>
    <td>salade</td>
    <td>dépit</td>
  </tr>
  <tr>
    <td>lecteur</td>
    <td>région</td>
    <td>toison</td>
    <td>ponton</td>
    <td>berger</td>
    <td>minus</td>
    <td>rentier</td>
    <td>pommier</td>
  </tr>
  <tr>
    <td>lanière</td>
    <td>moto</td>
    <td>gamelle</td>
    <td>lardon</td>
    <td>brochet</td>
    <td>dédale</td>
    <td>maison</td>
    <td>cocher</td>
  </tr>
  <tr>
    <td>caverne</td>
    <td>troupier</td>
    <td>pilon</td>
    <td>frimeur</td>
    <td>saveur</td>
    <td>massage</td>
    <td>venue</td>
    <td>raquette</td>
  </tr>
  <tr>
    <td>bouleau</td>
    <td>roulette</td>
    <td>traction</td>
    <td>fêtard</td>
    <td>fagot</td>
    <td>toucan</td>
    <td>purée</td>
    <td>rumeur</td>
  </tr>
  <tr>
    <td>poussin</td>
    <td>caresse</td>
    <td>carreau</td>
    <td>buisson</td>
    <td>farine</td>
    <td>galette</td>
    <td>parage</td>
    <td>criquet</td>
  </tr>
  <tr>
    <td>fonction</td>
    <td>journée</td>
    <td>pelote</td>
    <td>boulet</td>
    <td>poteau</td>
    <td>vision</td>
    <td>rature</td>
    <td>local</td>
  </tr>
  <tr>
    <td>molosse</td>
    <td>conteur</td>
    <td>lapin</td>
    <td>savoir</td>
    <td>bonus</td>
    <td>meringue</td>
    <td>sinistre</td>
    <td>nation</td>
  </tr>
</table>
<caption>Figure1</caption>

A

<figure><img src="image_3.png" /></figure>

B

<figure><img src="image_4.png" /></figure>
Figure 1. Schematic representation of the stimulation sites and the experimental task.

A, top: Areas targeted for stimulation in the right and left cerebellum marked in the MRI of one experimental subject. A, bottom: Division of the cerebellum into ten lobules (adapted from Schlerf et al., 2014). B, top: An example sequence of events in a trial priming for a lexical error outcome. B, bottom: An example sequence of events in a trial priming for a non-lexical error outcome.
A

<figure><img src="image_5.png" /></figure>

B

<figure><img src="image_6.png" /></figure>
Figure 2. Error-rates and Response times

(A) Percent of overall errors out of the 1920 trials in each hemisphere broken down by cerebellar hemisphere of stimulation and experimental block. (B)

Response times, similar break down. Error bars represent standard errors of the mean.