Neuropsychologia 70 (2015) 185–195

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Cortical regions involved in semantic processing investigated by repetitive navigated transcranial magnetic stimulation and object naming Nico Sollmann a,b,c, Noriko Tanigawa d, Lorena Tussis a,b, Theresa Hauck a,b, Sebastian Ille a,b, Stefanie Maurer a,b, Chiara Negwer a, Claus Zimmer b,c, Florian Ringel a, Bernhard Meyer a, Sandro M. Krieg a,b,n a

Department of Neurosurgery, Germany TUM-Neuroimaging Center, Germany Section of Neuroradiology, Department of Radiology; Klinikum rechts der Isar, TU München, Germany d Faculty of Linguistics, Philology, & Phonetics, University of Oxford, UK b c

art ic l e i nf o

a b s t r a c t

Article history: Received 12 November 2014 Received in revised form 23 February 2015 Accepted 24 February 2015 Available online 28 February 2015

Background: Knowledge about the cortical representation of semantic processing is mainly derived from functional magnetic resonance imaging (fMRI) or direct cortical stimulation (DCS) studies. Because DCS is regarded as the gold standard in terms of language mapping but can only be used during awake surgery due to its invasive character, repetitive navigated transcranial magnetic stimulation (rTMS)—a non-invasive modality that uses a similar technique as DCS—seems highly feasible for use in the investigation of semantic processing in the healthy human brain. Methods: A total number of 100 (50 left-hemispheric and 50 right-hemispheric) rTMS-based language mappings were performed in 50 purely right-handed, healthy volunteers during an object-naming task. All rTMS-induced semantic naming errors were then counted and evaluated systematically. Furthermore, since the distribution of stimulations within both hemispheres varied between individuals and cortical regions stimulated, all elicited errors were standardized and subsequently related to their cortical sites by projecting the mapping results into the cortical parcellation system (CPS). Results: Overall, the most left-hemispheric semantic errors were observed after targeting the rTMS to the posterior middle frontal gyrus (pMFG; standardized error rate: 7.3‰), anterior supramarginal gyrus (aSMG; 5.6‰), and ventral postcentral gyrus (vPoG; 5.0‰). In contrast to that, the highest right-hemispheric error rates occurred after stimulation of the posterior superior temporal gyrus (pSTG; 12.4‰), middle superior temporal gyrus (mSTG; 6.2‰), and anterior supramarginal gyrus (aSMG; 6.2‰). Conclusions: Although error rates were low, the rTMS-based approach of investigating semantic processing during object naming shows convincing results compared to the current literature. Therefore, rTMS seems a valuable, safe, and reliable tool for the investigation of semantic processing within the healthy human brain. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Cortical mapping Language Object naming Semantic processing Transcranial magnetic stimulation

Abbreviations: CPS, Cortical parcellation system; DCS, Direct cortical stimulation; DT, Display time; EHI, Edinburgh Handedness Inventory; FDR, False discovery rate; IFG, Inferior frontal gyrus; ITG, Inferior temporal gyrus; IPI, Inter-picture-interval; IPNP, International Picture Naming Project; fMRI, Functional magnetic resonance imaging; MEG, Magnetoencephalography; MRI, Magnetic resonance imaging; MTG, Middle temporal gyrus; opIFG, Opercular inferior frontal gyrus; PrG, Precentral gyrus; PTI, Pictureto-trigger-interval; RMT, Resting motor threshold; rTMS, Repetitive navigated transcranial magnetic stimulation; SD, Standard deviation; SMG, Supramarginal gyrus; STG, Superior temporal gyrus; TMS, Transcranial magnetic stimulation; VAS, Visual analog scale; vPrG, Ventral precentral gyrus n Corresponding author at: Department of Neurosurgery, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 Munich, Germany. Fax: þ49 89 4140 4889. E-mail addresses: [email protected] (N. Sollmann), [email protected] (N. Tanigawa), [email protected] (L. Tussis), [email protected] (T. Hauck), [email protected] (S. Ille), [email protected] (S. Maurer), [email protected] (C. Negwer), [email protected] (C. Zimmer), [email protected] (F. Ringel), [email protected] (B. Meyer), [email protected] (S.M. Krieg). http://dx.doi.org/10.1016/j.neuropsychologia.2015.02.035 0028-3932/& 2015 Elsevier Ltd. All rights reserved.

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1. Introduction

written informed consent prior to MRI.

The current knowledge about the cortical representation of semantic processing in both hemispheres of the human brain is predominantly based on findings using functional magnetic resonance imaging (fMRI) (Pulvermuller et al., 2009; Vigneau et al., 2006, 2011) but also on results derived from intraoperative language mapping by direct cortical stimulation (DCS) during awake surgery (Corina et al., 2010; Duffau et al., 2013; Moritz-Gasser et al., 2013; Ojemann, 2003). However, DCS, which is regarded as the current gold standard in terms of functional testing of cortical function, cannot be used for the examination of language subfunctions in the healthy brain due to its highly invasive character, and fMRI is likely to be too inaccurate for language mapping, at least when applied in patients with intracerebral lesions (FitzGerald et al., 1997; Giussani et al., 2010; Sollmann et al., 2013b). Repetitive navigated transcranial magnetic stimulation (rTMS) combines the advantages of both the DCS and fMRI methods, because comparable to DCS, it elicits an electric field within the cortex and therefore induces a temporary functional lesion, and it is non-invasive, as fMRI is. Moreover, rTMS has been repeatedly used to identify cortical areas causally related with different language subfunctions by influencing language performance within the frame of causing different types of naming errors (Lioumis et al., 2012; Pascual-Leone et al., 1991; Rosler et al., 2014; Sollmann et al., 2014; Tarapore et al., 2013; Wassermann et al., 1999). However, semantic paraphasias as a reflection of rTMS-induced impairment of semantic processing was only observed infrequently in recent mapping studies and has therefore not been in the main focus of rTMS research (Lioumis et al., 2012; Sollmann et al., 2014). Consequently, we investigated 50 left-hemispheric and 50 right-hemispheric rTMS language mappings for semantic paraphasias, which were performed in healthy volunteers during an object-naming task. The results will then be compared and discussed in relation to the current literature on fMRI, DCS, and rTMS studies dealing with the cortical representation of semantic processing.

2.3. Navigational MRI

2. Materials and methods 2.1. Mappings For the present study, we reevaluated 100 rTMS language mapping sessions, which were performed in our department with the same protocol for investigating various questions of rTMS language mapping. Yet, semantic processing was not investigated in these preceding and partially published trials (Picht et al., 2013; Sollmann et al., 2014). In 50 out of these 100 mappings, the left hemisphere was investigated, while the right hemisphere was stimulated in the remaining 50 sessions. All mappings were performed in the same 50 healthy, monolingual, and purely righthanded volunteers. Inclusion criteria were right handedness (assessed by the Edinburgh Handedness Inventory ¼EHI), German as mother tongue and only primary language, age above 18 years, and written informed consent. The exclusion criteria were previous seizures, general rTMS exclusion criteria (pacemaker, cochlear implant), ambidexterity, simultaneous bilingual subjects, and pathological findings on cranial magnetic resonance imaging (MRI). 2.2. Ethics The experimental protocol was approved by the ethical committee of our university (registration number: 2793/10) in accordance with the declaration of Helsinki. All volunteers provided

After obtaining written informed consent, all volunteers underwent a navigational MRI on the same clinical 3 Tesla MR scanner (Achieva 3T, Philips Medical Systems, the Netherlands B. V.) by use of an 8-channel phased array head coil. The scanning protocol consisted of a 3D gradient echo sequence (TR/TE 9/4 ms, 1 mm2 isovoxel covering the whole head, 6 min 58 s acquisition time), which was performed without intravenous contrast administration. Subsequently to scanning, the individual 3D MRI dataset was transferred to the rTMS system using the DICOM standard. 2.4. Language mapping by rTMS 2.4.1 rTMS procedure and stimulation parameter selection All cortical language mappings were performed with the Nexstim eXimia NBS system version 4.3 with a NexSpeechs 4 module (Nexstim Oy, Helsinki, Finland) as repeatedly published by our and other groups (Krieg et al., 2014a, 2014b; Picht et al., 2013; Rosler et al., 2014; Sollmann et al., 2013a; Sollmann et al., 2014; Tarapore et al., 2013). In short, individual T1-weighted MRI data were used to reconstruct each participant's 3D brain image, which was used as an anatomical reference, co-registered to the subject's brain to localize the stimulated brain area during the individual mapping session. The subject's head position was tracked by reflectors fastened to the head with an elastic strap; thus, head movements did not cause data acquisition problems unlike with MRI or magnetoencephalography (MEG) imaging. For precisely tracking the position of the magnetic coil with respect to the volunteer's head, the rTMS system used a stereotactic camera. Taking all information of the neuronavigation together, the rTMS system was then able to visualize the targeted stimulation points and the electric field induced by the magnetic coil over the above-mentioned brain's 3D reconstruction image, while the examiner moved the coil across the volunteer's head (Ruohonen and Karhu, 2010). All intracranial points of stimulation were automatically saved for later examination (Ruohonen and Karhu, 2010). To prepare for rTMS mapping sessions, stimulation parameters, like the stimulation intensity and frequency, had to be determined. Both parameters were personalized based on the following protocol, and the individual RMT, stimulation intensity, and frequency were documented: 1. The resting motor threshold (RMT) of the left hemisphere was determined by motor mapping of M1 for the abductor pollicis brevis muscle; 2. A train of 5–7 rTMS bursts was administered to ventral precentral gyrus (vPrG) and opercular inferior frontal gyrus (opIFG): a. 5 Hz, 5 pulses, 100% RMT b. 7 Hz, 5 pulses, 100% RMT c. 7 Hz, 7 pulses, 100% RMT 3. The setup (a–c), which caused the highest error rate (¼ number of errors/number of stimulations), was identified by the volunteer's and examiner's impressions; 4. If there was no clear difference in the effect on language, the most comfortable frequency was chosen; 5. If naming was not interrupted by rTMS, the intensity was increased to 110–120% RMT, and step 1 was repeated; and 6. If significant pain was reported, the stimulation intensity was decreased to 80–90% RMT to avoid any discomfort interfering with the consecutive response evaluation (Epstein et al., 1996). This adjustment was also applied if 100% RMT was severely painful.

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2.4.2 Baseline testing and mapping procedure The baseline testing and rTMS language mapping procedure, as used in this study, have already been described in earlier publications (Krieg et al., 2014a; Picht et al., 2013; Rosler et al., 2014; Sollmann et al., 2013a; Sollmann et al., 2014; Tarapore et al., 2013). The object-naming task was used since it involves all three major language production functions (meaning, form, and articulation) (Indefrey, 2011) to identify cortical regions causally related to these language functions by causing a virtual functional lesion by rTMS (Candidi et al., 2008; Knops and Nuerk, 2006; Orosz et al., 2012; Pascual-Leone et al., 2000). For this task, the objects were presented as 131 colored photographs of common objects, displayed at an inter-picture-interval (IPI) of 2.5 s and a display time (DT) of 700 ms. These photographs portrayed familiar living as well as non-living objects (e.g., dog, house, book), similar to a set of objects selected in the Snodgrass and Vanderwart pictures (Snodgrass and Vanderwart, 1980). The assortment of objects was provided by the Nexstim NexSpeechs 4 module (Nexstim Oy, Helsinki, Finland) and is standardly used in rTMS language mapping studies of ours and other groups (Hernandez-Pavon et al., 2014; Krieg et al., 2014a; Lioumis et al., 2012; Picht et al., 2013; Rosler et al., 2014; Sollmann et al., 2013a; Sollmann et al., 2014; Tarapore et al., 2013). During baseline testing without stimulation, all objects were displayed on a screen in front of the volunteer, and the subject was instructed to name the objects in German as quickly and precisely as possible. Misnamed objects, indicating that there was any problem with the naming of an object (e.g., hesitation), were discarded from the stimulus sequence. For name agreement, we referred to the German data portion of the International Picture Naming Project (IPNP) database (Szekely et al., 2004) but used our own dominant name decision when object names were not listed in the IPNP database (e.g., Taschenrechner [calculator], Tastatur [computer keyboard]) and when object names for which dominant/non-dominant reversals from the IPNP database were systematically observed in our participant group (e.g., Krawatte [necktie] instead of Schlips, Orange [orange] instead of Apfelsine, Melone [watermelon] instead of Wassermelone). A second baseline testing with the remaining object stack was carried out in an analogous way immediately after the first testing, and the total number of baseline naming errors was documented. Only objects, which were correctly named twice were used for the mapping session. During rTMS-based language mapping, the individual set of objects was presented while time-locked to a train of rTMS pulses at a picture-to-trigger interval (PTI) of 300 ms according to our current knowledge of the timing of naming-related activity reported in previous MEG and rTMS studies (Indefrey, 2011; Salmelin et al., 2000; Wheat et al., 2013). Furthermore, the objects were presented in a randomized order to minimize the priming effect. The stimulation coil was randomly moved between the displays of two objects (IPI), and it was placed tangential to the skull and with the field in strict anterior–posterior orientation to achieve maximum field induction (Epstein et al., 1996; Lioumis et al., 2012; Wassermann et al., 1999). For later analysis of mapping results, the baseline performance as well as the rTMS language mapping session were digitally video recorded (Hernandez-Pavon et al., 2014; Krieg et al., 2014a; Lioumis et al., 2012; Picht et al., 2013; Rosler et al., 2014; Sollmann et al., 2013a; Sollmann et al., 2014; Tarapore et al., 2013). 2.4.3 Evaluation of discomfort After the individual mapping session, each volunteer was asked to rate any discomfort or pain perceived during stimulation according to the visual analog scale (VAS) from 0 (no pain) to 10 (maximum pain).

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2.5. Video analysis Each session video was systematically analyzed by the same investigator who had already performed the individual language mapping, as described repeatedly (Krieg et al., 2014b; Lioumis et al., 2012; Picht et al., 2013; Sollmann et al., 2014; Tarapore et al., 2013). Thus, the video material was evaluated by the first author (MD with linguistic analysis experience since 2011), who was assisted by the second author (MD student with mapping/video analysis experience since 2012), and supervised by the last author (MD with linguistic/mapping/video analysis experience since 2009). In addition to that, a collaborating trained linguist was available for the evaluation of unclear cases. However, since semantic naming errors represent a rather easily definable category when compared to other categories that are typically evaluated in rTMS language mappings (e.g., hesitations), the help of the linguist was only necessary during the evaluation of approximately 10 out of 100 mappings. In short, each video recorded during rTMS language mapping was screened, and any potential semantic naming error was compared to the corresponding baseline performance several times in order to guarantee that only clear semantic naming errors were taken into account for further evaluation. All clear semantic errors, which are characterized by a substitution of a semantically related or associated word for the target word (e.g., the target word “cow” is replaced by the word “horse”) were counted. Moreover, during video analysis, the examiner was strictly blinded to the corresponding sites of cortical stimulation. 2.6. Data evaluation We used the cortical parcellation system (CPS) for anatomyrelated analysis and visualization of mapping data (Corina et al., 2005; Corina et al., 2010) (Table 1; Fig. 1). By using the CPS, the cortical surface is systematically parcellated into 37 individual anatomical regions, and the cortical gyri belonging to these anatomical regions were identified from 3D MRIs (Corina et al., 2005). All rTMS data were manually projected on the parcellated cortex by the same person who had performed rTMS language mapping and video analysis. Since our mapping approach led to a variation in the number of stimulations between individual CPS regions and subjects, standardization of error rates was performed. We employed the method of direct standardization, which requires two components: (1) The crude within-participant CPS-specific error rate, and (2) the proportion of the participant's stimulation trains in the entire data set. The product of (1) and (2) represents the weighted withinparticipant CPS-specific error rate. The sum of the weighted within-participant CPS-specific error rates is the standardized overall CPS-specific error rate. The crude within-participant CPS-specific error rate is defined as the number of errors in a CPS region in a participant divided by the number of stimulation trains in a CPS region in a participant. Ci stands for this term for participant i. Furthermore, the proportion of the participant's stimulation trains in the entire data set is defined as the number of all the stimulation trains of a participant divided by the number of all the stimulation trains in the standard entire data set. Psi stands for this term for participant i. Moreover, Cd stands for the crude overall CPS-specific error rate standardized by the direct standardization method. Per definition, the calculation is formulated as follows:

Cd =

∑ (CixPsi)

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Table 1 Abbreviations of the cortical parcellation system (CPS) Abbreviation

Anatomy

aITG aMFG aMTG anG aSFG aSMG aSTG dLOG dPoG dPrG mITG mMFG mMTG mPoG mPrG mSFG mSTG opIFG orIFG pITG pMFG pMTG polIFG polITG polLOG polMFG polMTG polSFG polSTG pSFG pSMG pSTG SPL trIFG vLOG vPoG vPrG

Anterior inferior temporal gyrus Anterior middle frontal gyrus Anterior middle temporal gyrus Angular gyrus Anterior superior frontal gyrus Anterior supramarginal gyrus Anterior superior temporal gyrus Dorsal lateral occipital gyrus Dorsal postcentral gyrus Dorsal precentral gyrus Middle inferior temporal gyrus Middle middle frontal gyrus Middle middle temporal gyrus Middle postcentral gyrus Middle precentral gyrus Middle superior frontal gyrus Middle superior temporal gyrus Opercular inferior frontal gyrus Orbital part of the inferior frontal gyrus Posterior inferior temporal gyrus Posterior middle frontal gyrus Posterior middle temporal gyrus Polar inferior frontal gyrus Polar inferior temporal gyrus Polar lateral occipital gyrus Polar middle frontal gyrus Polar middle temporal gyrus Polar superior frontal gyrus Polar superior temporal gyrus Posterior superior frontal gyrus Posterior supramarginal gyrus Posterior superior temporal gyrus Superior parietal lobe Triangular inferior frontal gyrus Ventral lateral occipital gyrus Ventral postcentral gyrus Ventral precentral gyrus

This table lists all anatomical names and corresponding abbreviations of cortical regions included in the CPS according to Corina et al. (2005).

By using this formula, the standardized overall CPS-specific error rate was computed for each of the CPS regions with stimulation trains. Then, Cd (per million) for each CPS region was tested

for statistical significance by computing the percentile rank from the top in the Poisson distribution that has the crude overall error rate of the standard entire data set (per million) as the mean. The percentile rank from the top corresponds to the probability of the computed Cd being greater than the mean by chance. At maximum, 74 tests were to be performed. Accordingly, the alpha level was set to 0.0001, and the corresponding significant probability values ( o0.00005) were FDR-corrected (FDR ¼false discovery rate). These testing procedures were performed by using the ppois function and the p.adjust function in R (The R Foundation for Statistical Computing, Vienna, Austria).

3. Results 3.1. Subject-related characteristics Table 2 provides information about subject-related characteristics, including mean age and gender. Additionally, this table gives an overview of mapping parameters, such as individual RMT, stimulation intensity, and stimulation frequency, which were personalized according to the protocol described in the materials and methods section. Furthermore, the average strength of the electrical field applied to the left and right hemisphere during rTMS is reported. Regarding potential stimulation-related discomfort, no volunteer asked for reduction of stimulation intensity or frequency due to intolerable pain, and no adverse events were observed. In this context, VAS scores can also be found in Table 2. 3.2. Spatial stimulation restrictions The spatial extent of rTMS was restricted due to unacceptable pain in the orIFG, polSTG, polMTG, aMTG, and polar regions of the frontal lobe (polSFG, polMFG, polIFG), because these regions have proven to be especially painful in previous studies of our group (Krieg et al., 2014a; Sollmann et al., 2013a). According to that, we categorically decided not to stimulate them to avoid pain-related confounding of our results as far as possible. Due to the greater distance between the scalp and the cortex, and therefore, too-low stimulation intensity (electrical field strength o55 V/m), the inferior temporal gyrus (ITG) was also not

Fig. 1. CPS of the left hemisphere. This figure visualizes all left-hemispheric anatomical areas of the CPS according to Corina et al. (2005). The parcellation of the right hemisphere appears mirror-inverted.

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investigated (Sollmann et al., 2013a). In this context, the electrical field strength applied to the cortex was Z 55 V/m in all CPS regions stimulated in the present study, and this is also true for temporoparietal regions.

Table 2 Subject-related characteristics and mapping parameters Mean age (years)

25.9 75.4

Gender (%; M/F) RMT (% of stimulator output) Electrical field strength (V/m)

50/50 36.2 76.6 Left hemisphere Right hemisphere 101.4 7 5.1 5 Hz /5 pulses 7 Hz /5 pulses 7 Hz /7 pulses Convexity Temporal

Mapping intensity (% of RMT) Mapping frequency / number of pulses

Pain (VAS)

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87.7 722.2 93.3 7 29.7 17 18 15 2.0 7 1.3 5.3 7 1.7

Subject-related characteristics (mean age, gender) as well as language mapping parameters (RMT¼resting motor threshold, mean electrical field strength of all left- and right-hemispheric cortical regions respectively, mapping intensity, mapping frequency in Hz¼Hertz, pain according to the VAS¼visual analog scale) are presented in this table.

3.3. Semantic naming errors within the left hemisphere Altogether, 22 left-hemispheric cortical regions were stimulated with varying stimulation numbers during all rTMS language mapping sessions, and 15 of them were prone to semantic errors to a variable extent (Table 3). Stimulation was possible in all enrolled subjects, and it led to an error mean of 1.48 72.69 (range: 0–24 errors). In total, 31 out of 50 left-hemispheric rTMS sessions resulted in the occurrence of semantic paraphasias, meaning that no semantic errors were elicited in the remaining 19 trials. The highest error rates after direct standardization were observed after

Table 3 Language mapping results Left hemisphere Area

Errors

Right hemisphere Stimulation trains

(participant ratio) aITG aMFG aMTG anG aSFG aSMG aSTG dLOG dPoG dPrG mITG mMFG mMTG mPoG mPrG mSFG mSTG opIFG orIFG pITG pMFG pMTG polIFG polITG polLOG polMFG polMTG polSFG polSTG pSFG pSMG pSTG SPL trIFG vLOG vPoG vPrG SUM MEAN SD MIN MAX MEDIAN

0 0 0 2 (2/48) 0 9 (8/50) 1 (1/27) 0 0 (0/48) 1 (1/50) 0 6 (3/27) 0 (0/11) 1 (1/50) 3 (3/50) 0 (0/1) 2 (2/50) 7 (7/50) 0 0 24 (14/50) 0 (0/3) 0 0 0 0 0 0 0 1 (1/35) 2 (2/50) 0 (0/46) 0 (0/18) 2 (1/27) 0 7 (7/50) 6 (6/50) 74 2.0 4.4 0 24 0

0 15 0 1446 0 1566 159 0 396 567 0 864 105 855 1149 18 681 2229 0 0 3204 21 0 0 0 0 0 0 0 495 822 291 159 735 0 1344 2684 19805 535.3 808.5 0 3204 105

Error rates (in ‰)

Errors

Crude

Standardized

(participant ratio)

 0.0  1.4  5.7 6.3  0.0 1.8  6.9 0.0 1.2 2.6 0.0 2.9 3.1   7.5 0.0        2.0 2.4 0.0 0.0 2.7  5.2 2.2 53.9 2.5 2.4 0.0 7.5 2.1

 0.0  1.2  5.6* 0.9  0.0 1.5  3.1 0.0 1.0 3.2 0.0 3.0 2.9   7.3* 0.0        1.5 2.5 0.0 0.0 1.3  5.0* 2.3 24.4 1.3 1.2 0.0 3.2 1.2

0 0 0 1 (1/49) 0 4 (4/50) 0 (0/32) 0 0 (0/38) 1 (1/40) 0 1 (1/34) 1 (1/13) 1 (1/50) 0 (0/50) 0 4 (4/49) 4 (3/47) 0 0 2 (2/50) 1 (1/5) 0 0 0 0 0 0 0 0 (0/15) 2 (2/50) 2 (2/42) 0 (0/19) 1 (1/30) 0 0 (0/50) 2 (2/50) 27 0.7 1.2 0 4 0

Stimulation trains

0 0 0 990 0 1113 210 0 243 306 0 507 135 531 600 0 570 612 0 0 1316 30 0 0 0 0 0 0 0 132 558 213 165 300 0 603 705 9839 265.9 353.6 0 1316 132

Error rates (in ‰) Crude

Standardized

   1.0  3.6 0.0  0.0 3.3  2.0 7.4 1.9 0.0  7.0 6.5   1.5 33.3        0.0 3.6 9.4 0.0 3.3  0.0 2.8 86.6 4.3 7.4 0.0 33.3 2.4

   0.9  6.2* 0.0  0.0 6.0*  0.9 1.7 1.1 0.0  6.2* 4.8*   1.5 2.8        0.0 3.7* 12.4* 0.0 3.1  0.0 2.4 14.4 1.0 1.1 0.0 3.1 0.9

This table provides the language mapping results of the left as well as right hemispheres. The number of errors, the participant ratio ( ¼number of subjects with semantic errors/number of subjects that were stimulated per CPS region), the number of stimulation trains, and the corresponding error rates (crude ¼ non-standardized and standardized, in ‰) pooled across all subjects for each cortical area of the CPS are presented (*: p o0.00005). Furthermore, mean, median, minimum and maximum values, and standard deviations (SD) were calculated.

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Fig. 2. Left-hemispheric distribution of semantic naming error rates. The scheme visualizes the standardized semantic naming error rates (in ‰) within the CPS of the left hemisphere. All data are derived from Table 3.

targeted rTMS to the pMFG (standardized error rate: 7.3‰), aSMG (5.6‰), and vPoG (5.0‰) during object naming (Table 3; Fig. 2). Overall, error rates for semantic errors were considerably low.

hemispheric error rates after direct standardization occurred after stimulation of the pSTG (standardized error rate: 12.4‰), mSTG (6.2‰), and aSMG (6.2‰) (Table 3; Fig. 3). Like in the left hemisphere, semantic error rates were considerably low.

3.4. Semantic naming errors within the right hemisphere 3.5. Standardized error rates In total, 20 cortical areas of the right hemisphere were stimulated to a variable extent, and rTMS to 14 of them caused semantic naming errors (Table 3). On average, rTMS elicited 0.54 70.93 semantic errors in the enrolled subjects (range: 0–4 errors). 18 out of 50 right-hemispheric rTMS sessions led to the occurrence of semantic paraphasias, meaning that no semantic errors were registered in the remaining 32 mappings. The highest right-

Out of 74 CPS regions, the Cd was computed for 41 CPS regions that received stimulation trains. In 9 out of 41 CPS regions, the Cd was significantly higher than the crude overall error rate (3407 per million) of the standard entire data set (Table 3). FRD corrected probability values were all less than 0.00005. These CPS regions are, in descending order of standardized error rates in each

Fig. 3. Right-hemispheric distribution of semantic naming error rates. This graph illustrates the standardized semantic naming error rates (in ‰) within the CPS of the right hemisphere. The underlying data can be found in Table 3.

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hemisphere: left pMFG, left aSMG, and left vPoG; right pSTG, right mSTG, right aSMG, right dPrG, right opIFG, and right pSMG (Table 3). For the right pMTG, which had the highest crude over all error rate (33333 per million) and the smallest total number of stimulation trains (30), the Cd (2834 per million) shrunk significantly below the crude overall error rate of the standard entire data set (3407 per million) (Table 3). For the left pMFG, which had the second highest crude over all error rate (7491 per million) and the largest total number of stimulation trains (3204), the Cd (7343 per million) did not shrink as drastically as for the right pMTG, remaining far above the mean (Table 3).

4. Discussion 4.1. Discomfort associated with rTMS As shown by Table 2, discomfort due to stimulation was clearly higher over temporal targets when compared to rTMS of the convexity. However, there was no need to reduce stimulation intensity or frequency in order to avoid pain associated with stimulation in any volunteer, which strengthens the role of rTMS as a safe and well-tolerated tool for language mapping in healthy subjects. Especially when applied over temporal muscle areas, rTMS is not completely painless under any circumstance, but it is well-tolerable when performed with an intensity of 100 up to 120% of the individual RMT and frequencies of 5 or 7 Hz, as used in the present study. With these adjustments, rTMS is likely to cause semantic naming errors, at least in the majority of investigated subjects. Therefore, these adjustments can be taken for reliable rTMS-based language mapping, which should then not be significantly confounded by naming errors primarily due to discomfort rather than being the result of targeted stimulation. Regarding the rating of stimulation discomfort, Rosler et al. (2014), which used a similar protocol for rTMS language mapping in healthy volunteers and patients, reported on a mean VAS score of 2.3 for the whole mapping session (Rosler et al., 2014). In our present work, we decided to present two values for temporal stimulation regions, which are expected to be the most painful areas, and the convexity respectively. As displayed in Table 2, the mean VAS score for the convexity accounted for 2.0, and was therefore slightly lower than the value documented by Rosler et al. (2014). However, the corresponding temporal score is clearly higher (5.3; Table 2), but it cannot be directly compared to Rosler et al. (2014) due to the lack of an analog value for temporal regions only . Out of all areas stimulated in the present study, rTMS to the opIFG and trIFG is most painful, and these areas are potential spots for confounding of the mapping results due to stimulation-related pain. However, our experience is that pain during stimulation predominantly leads to other kinds of errors, especially to no responses or hesitations. As the present investigation only focusses on semantic errors, these types of naming disturbances are not incorporated into the analysis a priori, and can therefore not distort the results. 4.2. Distribution within the left hemisphere According to Table 3, crude and standardized rates for semantic naming errors were considerably low and variable between subjects, especially when compared to other naming error categories investigated in previous studies of ours and other groups (Hernandez-Pavon et al., 2014; Lioumis et al., 2012; Sollmann et al., 2013a). Regarding the discussion of mapping results, we refer to the standardized error rates (Table 3; Fig. 2). Semantic naming errors are likely to be the result of rTMS-

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related disturbance of cortical network functions to a greater extent than is the case for no responses, for example, which should be primarily caused by direct interruption of motor-related areas (Price, 2000). We therefore assume that semantic errors occur only infrequently due to the more complex underlying network mechanisms, which are harder to interrupt when compared to other kinds of naming errors. However, this interpretation of results is speculative, and the comparatively low semantic error rates could also be related to the PTI, which accounted for 300 ms in the present study. Principally, there is evidence available for immediate (PTI¼ 0 ms) and delayed (e. g., PTI ¼300 ms) stimulation onset (Indefrey, 2011; Salmelin et al., 2000; Wheat et al., 2013), but the distinct relationship between different rTMS onset times and the occurrence of semantic paraphasias during object naming has not been under systematic investigation yet. Preliminary data of our group concerning an onset comparison revealed that a stimulation onset of 300 ms was able to elicit a similar rate for semantic errors when compared to rTMS applied with 0 ms, and therefore, we currently favor the hypothesis of more complex brain networks underlying semantic processing. In a study using DCS to elicit naming errors during object naming in a cohort of brain tumor and epilepsy patients, Corina et al. (2010) observed the highest semantic error ratios within the mPoG, aSMG, and pMTG, with other temporal regions approaching prominence (Corina et al., 2010). Although clear and reproducible semantic errors were observed in their study, the corresponding ratios were also relatively low when compared to other naming error types, like no responses and performance errors, for example (Corina et al., 2010). As reflected by the mapping results, the aSMG was also especially prone to semantic errors in comparison to other regions in our study (Table 3; Fig. 2). However, stimulation to the pMTG did not elicit any semantic error, most likely to the low number of trials applied to this CPS region (Table 3; Fig. 2). Furthermore, frontal areas, such as the pMFG and mMFG, for example, did not show high semantic error ratios in the study of Corina et al. (2010), but this circumstance can be attributed to the fact that these errors did not show any (mMFG) or just one (pMFG) naming error at all (Corina et al., 2010), which is comparatively sparse in comparison to other mapping approaches (Ojemann et al., 1989; Sanai et al., 2008). The study of Lioumis et al. (2012) described rTMS-based language mapping of six cortical areas in four healthy subjects and reported that the supramarginal gyrus (SMG) was the most reproducible site in terms of semantic paraphasias (Lioumis et al., 2012). Again, this finding is covered by the results of this study, which include the aSMG as a CPS region with a high semantic error rate (Table 3; Fig. 2). While only stimulation to the aSMG was able to elicit semantic errors in three out of four subjects in Lioumis et al. (2012), this kind of naming error was also observed after rTMS to the anG and precentral gyrus (PrG) in one volunteer (Lioumis et al., 2012). Another recent rTMS-based trial investigated the cortical distribution of naming errors in 15 healthy volunteers and 50 patients suffering from different brain tumor entities (Rosler et al., 2014). Within the group of healthy subjects, rTMS elicited semantic paraphasias in the left-hemispheric opIFG (0.3%), pMTG (1.0%), aSMG (1.6%), pSMG (2.0%), and anG (0.6%) (Rosler et al., 2014). Obviously, this distribution pattern does not completely overlap with our results, especially not in terms of frontal regions (pMFG, mMFG; Table 3; Fig. 2). Hence, the findings of the two described rTMS publications outline the principal inter-individual variability in brain regions that are involved in object naming as also observed in the present study, and this circumstance has already been addressed in earlier cortical mapping approaches as well (Corina et al., 2010; Haglund et al., 1994; Ojemann et al., 1989; Sanai et al., 2008).

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With regard to the reproducibility of semantic naming errors elicited by rTMS within the left hemisphere, 10 of the 50 subjects investigated in the present study were mapped another two times in a recent trial of our group (Sollmann et al., 2013a). Overall, there was only a partial correspondence between the three mappings with regard to all error categories investigated (no responses, performance errors, hesitations, neologisms, phonological paraphasias, and semantic paraphasias), and the reproducibility varied among different error categories during object naming. However, semantic errors—together with no responses and hesitations— were better reproducible than the remaining categories (performance errors, neologisms, phonological paraphasias) in the comparison of the first and second, but also in the comparison of the second and third mapping (Sollmann et al., 2013a). In an extensive large-scale meta-analysis of Vigneau et al. (2006), which included fMRI-based study results of investigations in healthy subjects, the authors reported on the identification of four frontal and seven temporal clusters for semantic processing (Vigneau et al., 2006). Simplified, the four frontal clusters mainly covered the inferior frontal gyrus (IFG) and the transition area to the PrG, while the seven temporally located clusters overlapped the superior (STG), middle (MTG), and inferior temporal gyrus (ITG) (Vigneau et al., 2006). In the present study, a comparatively high semantic naming error rate was observed after stimulation to the mSTG, which should spatially cover some of the temporal semantic clusters presented in the meta-analysis of Vigneau et al. (2006) (Table 3; Fig. 2). The aSTG, which should lie between two of the widely distributed semantic clusters of Vigneau et al. (2006), was also prone to semantic naming errors, but obviously to a lesser extent when compared to the mSTG (Table 3; Fig. 2). Generally, most of the current language organization models associate the temporal lobe with aspects of semantic processing (Grabowski et al., 2001; Martin and Chao, 2001), which should be reflected by the error rates for semantic paraphasias within the described subregions of the temporal lobe. However, other stimulated temporal areas (pSTG, pMTG, mMTG) were not prone to semantic errors, most likely due to the low number of stimulation trains applied to these regions (Table 3; Fig. 2). When it comes to the aforementioned frontal clusters (IFG, PrG), no significant error rates were elicited by rTMS in the present study (Table 3; Fig. 2). With respect to the functional role of the IFG in semantic processing, this gyrus has been repeatedly implicated in controlled semantic selection and semantic retrieval in several publications (Thompson-Schill et al., 1997; ThompsonSchill et al., 1999). Accordingly, a probable reason for the lack of semantic errors within the IFG could be that the stimuli were sufficiently rich such that there were few demands for controlled differentiation of potential lexical candidates (Corina et al., 2010). In addition, anterior regions like the IFG and vPrG have proven to be predominantly prone to other error types in previous studies (Krieg et al., 2014a; Lioumis et al., 2012; Sollmann et al., 2013a). As a consequence, the occurrence of semantic naming errors within these areas could have been inhibited by the provocation of other error types, like no responses or performance errors, for example. Despite the role of the IFG and PrG for semantic processing described in Vigneau et al. (2006), these frontal regions are also known to play a distinct role in the execution of motor parts of language processing (Indefrey, 2011). Therefore, the lack of semantic errors after rTMS to these gyri does not deny its involvement in semantic processing per se, but shows that rTMS rather interferes with motor-related components of language when carried out over these areas, at least when applied during an objectnaming task. Furthermore, we also have to keep in mind that there is a considerably high degree of variability in the frontal lobe for brain regions that are involved in object naming in general, at least when investigation of semantic processing is performed by

mapping techniques (Ojemann et al., 1989). 4.3. Distribution within the right hemisphere Right-hemispheric crude and standardized semantic error rates were comparatively low and variable between subjects (Table 3), and we relate that finding to the same reasons as already described for the left hemisphere. Again, we refer to the standardized error rates in the discussion of mapping results (Table 3; Fig. 3). At least to our knowledge, the right hemisphere of healthy subjects has only rarely been under systematic investigation using a cortical mapping technique with regard to semantic processing. Indeed, there are some publications available on targeted mapping of the right hemisphere by rTMS or DCS, but these studies only included diseased subjects (Chang et al., 2011; Naeser et al., 2005; Thiel et al., 2005; Winhuisen et al., 2005), performed stimulation solely in left-handers (Duffau et al., 2008), or were primarily focused on other naming error categories (Sollmann et al., 2014). In addition, the rTMS-based language mapping study of Lioumis et al. (2012) reported on stimulation of the right hemisphere, but the authors were not able to disturb language performance during the mapping sessions at all (Lioumis et al., 2012). However, the important role of the right, non-dominant hemisphere for human language function has already been illustrated in the past, resolving that it is significantly involved in the ability to contextualize, integrate, and infer meaning from language (Beeman et al., 2000; Bookheimer, 2002; Lindell, 2006; Marini et al., 2005). To pay attention to the increasing evidence about the right hemisphere's involvement in language, the aforementioned meta-analysis of Vigneau et al. (2006) concerning lefthemispheric semantic representation was followed by a corresponding analysis of the contribution of the right counterpart (Vigneau et al., 2006, 2011). In this follow-up evaluation of righthemispheric fMRI data, the authors reported on clearly less involvement of the right hemisphere in semantic function when compared to the other hemisphere, and the spatial pattern of activation primarily included spots within the frontal and temporal lobe (Vigneau et al., 2011). Furthermore, unilateral activation peaks within the right hemisphere were too scattered to be clustered (Vigneau et al., 2011), meaning that clear unilateral hotspots of activation were not detectable in the frontal nor in the temporal lobe. However, the authors were able to identify two bilateral activation clusters in the frontal lobe, which were located in junction between the inferior frontal sulcus and the precentral sulcus in the upper part of the opIFG on the one hand and in the orbital part of the IFG on the other hand (Vigneau et al., 2011). The first bilateral cluster was most likely represented by the high semantic error rate of the opIFG (Table 3; Fig. 3), while the second one is situated outside of the areas stimulated in the present study. According to the results section, less frontal and parietal cortical regions of the right hemisphere were prone to semantic naming errors when compared to their left-hemispheric counterparts (Table 3; Figs. 2 and 3), which indicates a similar trend as the one described in this meta-analysis (Vigneau et al., 2011). As an interpretation, this suggests that frontal and parietal regions of the right hemisphere should be less involved in semantic processing than the analogous regions of the other one, at least during an object-naming task as used in our study. Interestingly, semantic naming errors were still observed at a clearly detectable level during rTMS, and high error rates primarily occurred after stimulation to subregions of the temporal lobe (pSTG, mSTG), which should cover most of the aforementioned, widespread temporal activation spots without the clustering illustrated in Vigneau et al. (2011) (Vigneau et al., 2011) (Table 3; Fig. 3). Moreover, there are comparatively high error rates within the right-hemispheric homolog of Wernicke's area when compared to the left

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hemisphere (Table 3; Figs. 2 and 3). Since there is not much literature on semantic errors elicited by rTMS of the right hemisphere, future studies might hopefully be able to clarify the role of the right-hemispheric homolog of Wernicke's area in the context of rTMS language mapping for semantic naming errors. Overall, the frequent occurrence of semantic errors within the right hemisphere appears to oppose the rTMS results of Lioumis et al. (2012) and Rosler et al. (2014), who did not elicit any semantic paraphasias during stimulation of the right hemisphere in healthy volunteers (Lioumis et al., 2012; Rosler et al., 2014). Since rTMS protocols were highly comparable between our approach and the study of Lioumis et al. (2012), we assume that the reason for that lies in the spatially more-circumscribed mapping presented in their publication and, first of all, in the comparatively low number of enrolled subjects and stimulation trains (Lioumis et al., 2012). Since we observed negative mapping results in a considerable large amount of volunteers, it seems to be likely that the enrollment of more subjects would have principally led to the occurrence of this error category in the study of Lioumis et al. (2012) and Rosler et al. (2014) (Lioumis et al., 2012; Rosler et al., 2014). Consequently, one of the main strengths of our study seems to be the uniquely high number of investigated volunteers, who were also homogenously analyzed by one investigator. 4.4. Safety aspects of rTMS At least two publications have explicitly focused on safety aspects of cortical mapping by transcranial magnetic stimulation (TMS) up to now (Rossi et al., 2009; Wassermann, 1998). However, most of the suggested safety guidelines illustrated in both studies were derived from studies that applied TMS to the motor cortex and not to other cortical areas, yet the authors conclude that these guidelines should be reasonably safe for TMS applications on cortical spots outside the motor cortex, although exact relationships between the excitability of motor and non-motor brain regions still have to be determined in the future (Rossi et al., 2009; Wassermann, 1998). Regarding potential adverse events related to TMS mappings, the authors Wassermann, (1998) described seizures as well as hearing deterioration and effects on mood and cognition (Wassermann, 1998). In fact, early TMS-based investigations reporting on the induction of seizures within several patients exist, but none of these supposedly TMS-induced seizures resulted in a lasting physical sequelae (Fauth et al., 1992; Kandler, 1990). Taking these reports into account, the estimation of Rossi et al. (2009) regarding the risk of seizures due to high-frequency rTMS—as used in the present approach—accounts for less than 1% among healthy subjects (Rossi et al., 2009). Moreover, our research group has not yet observed any seizure or other adverse event related to language mapping by rTMS in healthy subjects or brain tumor patients, and therefore, we can confirm this estimation emphasizing that the seizure risk might even be lower than 1%. For that reason, we can conclude that rTMS is a safe and useful tool for efficient cortical language mapping in general, and adverse effects can be regarded as absolute exceptions. 4.5. Limitations Although rTMS was able to reliably induce semantic paraphasias during object naming, we have to keep certain limitations in mind. First of all, the comparison of rTMS-based and DCS language mapping in brain tumor patients has revealed that rTMS has a lower positive predictive value than DCS (positive predictive value of rTMS: 35.6%) (Picht et al., 2013). For that reason, CPS regions that were prone to semantic naming errors are probably not essential for language function in a strict sense and should

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therefore rather be regarded as language-involved. As a consequence, the rTMS language mapping approach could not clearly distinguish between solely associated and distinctly crucial semantic regions up to now. Another limitation concerns rTMS stimulation parameters for language investigations per se: Up to now, there has been no standardized protocol available that guarantees optimal mapping results. It is already known that mapping results obviously depend on different parameters, like the coil angulation, stimulation frequency, and intensity, for example, and that the change of only one of these parameters already has an impact on language performance (Epstein et al., 1996; Tarapore et al., 2013). Although our present protocol was able to elicit semantic naming errors during object naming, we do not claim that it represents the optimal protocol. Indeed, it can be used for effective, reliable, and comparatively painless cortical language mapping while fulfilling mapping safety guidelines, but nevertheless, investigations on protocol improvements and standardization possibilities should follow in the near future. Furthermore, the considerable high variance in stimulation trials within each hemisphere can also be regarded as a limitation (Table 3). This issue can be negotiated by determining cortical spots before mapping, which can then be stimulated with a predefined stimulation trial number during the session. This approach should also allow for more frequent rTMS to the temporal lobe, which was stimulated in a below-average level in the present study (Table 3). Although there only few publications available on cortical language stimulation by rTMS, neuroimaging studies have already shown that temporal subregions are clearly involved in semantic processing (Vigneau et al., 2006, 2011), which should encourage future rTMS language trials to include temporal regions to a greater extent. The selection of pictures included in the object-naming task could also have limited the present study's results since the object assortment covered different semantic categories and consisted of objects with different amounts of syllables. Although the stack of 131 images is standardly used in our language mappings and was chosen in accordance to the pictures of Snodgrass and Vanderwart (Snodgrass and Vanderwart, 1980), the restriction of objects to only one semantic category could principally change mapping results.

5. Conclusions The rTMS-based approach presented in this study was able to map cortical regions of the left and right hemispheres being involved in semantic processing during object naming in a uniquely large number of mapping sessions among healthy subjects. During stimulation of both hemispheres, the highest standardized error rates were observed primarily within cortical areas of the frontal (left hemisphere: pMFG, mMFG; right hemisphere: opIFG) and temporal lobe (left hemisphere: mSTG; right hemisphere: pSTG, mSTG) but also within the parietal lobe (left hemisphere: vPoG, aSMG; right hemisphere: aSMG), respectively, which finding is mainly in good accordance with previous cortical mapping and fMRI-based studies. In addition to that, no adverse events occurred, and the comparatively extensive stimulation sessions could be successfully finished in all subjects. Therefore, rTMS can be regarded as a valuable, safe, and reliable tool for further investigations of semantic processing within the human brain, yet keeping its limitations in mind. Disclosure FR and SK are consultants for BrainLAB AG (Feldkirchen,

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Germany). The study was completely financed by institutional grants from the Department of Neurosurgery and the Section of Neuroradiology, and the authors declare that they have no conflict of interest affecting this study or the findings specified in this manuscript.

Acknowledgements We would like to thank the Commission for Clinical Research of Our University for funding SK within the scope of a faculty-intern grant.

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