Internship report
By
Ana Lucía Rivas Paz
Supervisors: Adrià Rofes PhD, and Ann-Katrin Ohlerth
Master of Science
(Clinical Linguistics)
at the Joint European Erasmus Mundus Master’s Programme in Clinical Linguistics (EMCL) UNIVERSITY OF GRONINGEN August, 2020 Student’s information Student’s number: S3856925 E-mail: a.l.rivas.paz@student.rug.nl
Address: Kamerlingh Onnesstraat 103, Groningen, The Netherlands
1 TABLE OF CONTENTS Internship report Introduction ………. 1 Validation process ………. 3 Participants ……… 3 Materials ……… 3 Procedure ……….. 4 Reflection ………. 6 References ……… 7 Appendices Appendix A. ………. 8 Appendix B. ………. 9 Appendix C. ………. 12 Appendix D………... 18 Appendix E……… 19
2 Internship report
Language testing used for intra-operative language mapping during awake surgery varies widely depending on the country and surgery team that is performing the surgery (Rofes & Miceli, 2014). There are a wide variety of language tests used for mapping that can go from simple tasks of word repetition (phonological level) to more complex tasks such as sentence completion or translating paragraphs , which would vary the challenge of the task and the linguistic level that is meant to identify -semantic, lexical, lexical-grammatical or syntactic level (Rofes et al., 2014). Object naming is still the most used test due to its accessibility, since the participant only needs to see a picture and retrieve its name, and it targets linguistic key points such as semantics and lexical retrieval (Rofes et al., 2017).
There is still a long way to go on the area of intraoperative and pre-operative language mapping, due to the fact that the tests may not even be standardized and the outcomes may not be as accurate as when a well-designed test is used (Rofes et al., 2014). This varies from country to country. For instance, Nuñez-Velasco and colleagues in their Mexican guideline for awake surgery, only provides the recommendation of certain type of tests paradigms for intra-operative language mapping such as sentence completion, language fluency, picture naming, picture/word association, language production, or the Pyramids and Palm trees test (Nuñez-Velazco, et al., 2020). However, the rules and regulations do not emphasize on the use of a proper test designed specifically for intra-operative or pre-operative language mapping. When considering a language test for intraoperative language mapping some important factors need to be considered such as time constraints, and that it should have a certain level of complexity to mimic the natural language of the participant (Ohlerth et al., 2019). Thus, it is of main importance that when designing a language test, not only the semantical and lexical level are tapped but also the syntactic level is tap.
Ohlerth and colleagues designed and standardized the Verb and noun test for peri-operative testing (VAN-POP, Ohlerth et al., 2019) and it is currently available for German, Dutch and English speakers. The VAN-POP test is used during language mapping of cortical and subcortical regions of the brain under navigated Transcranial Stimulation (nTMS) and Direct Electrical Stimulation (DES) with people of different ages and backgrounds (Ohlerth et al., 2019). It is
3 divided into object naming and action naming in present tense and it also has a third section of action naming in past tense, mainly used in English (Ohlerth et al., 2019).
During my internship I worked with the VAN-POP test by adapting it to Mexican Spanish, since there seems to be a gap on standardization of language tests in Mexico. I worked on the first two steps of the standardization process. During the next sections I will describe the steps taken in order to complete the validation stage.
Validation process
Object naming
The images for the object naming consist of black and white drawings of everyday objects. The images chosen for the adaptation to Mexican Spanish were a total of 79 images. The images were programmed in a Power Point Presentation with the lead-in phrase “Esto es…” (This is…). The participant looked at the picture and would name it by reading the lead-in phrase and complete it with the correct article, e.g. “Esto es un perro” (This is a dog).
Action naming
The images for the action naming consist of black and white drawings of everyday activities. The images chosen for the adaptation to Mexican Spanish were a total of 140 images depicting actions. Similar to the object naming, the images were programmed in a Power Point presentation with the lead-in phrase “El hombre / La mujer…” (The man / The woman). The participant looked at the picture, read the lead-in phrase and would complete a short phrase in simple present, e.g. “El hombre corre” (The man runs).
Participants
15 native speakers of Mexican Spanish were interviewed. The participants were 13 women and 2 men, mean age 41 (sd= 9.93; range= 27-62), and mean years of education, 20 (sd= 3.27, range= 16-28). None of the participants presented previous neurological or language disorders. Participants were not included if they were not native speakers of Mexican Spanish.
4 Materials
The adaptation of the VAN-POP test into Mexican Spanish. The items were chosen accordingly, by eliminating the objects or actions that would denotate a compound word (e.g. “tijeras" (scissors)) or a full phrase (e.g. “El hombre juega pelota” (The man plays with the ball)). The nouns were controlled for Frequency, Age of Acquisition, Length in syllables and Animacy by using the ESPAL database (Duchon, Perea & Sebastián-Gallés, 2013), for the Age of Acquisition the database of Alonso and colleagues was used (2015). Since Spanish articles mark the gender of the noun, the lead-in phrase showed only the neutral article, Esto (It), to avoid any gender priming (Jescheniak, 1999).
The verbs were controlled for Frequency, Age of Acquisition, Length of Syllables, Regularity, Transitivity, Number of arguments, Instrumentality and Name relatedness to a noun, by using ESPAL (Duchon et al., 2013), and the different dictionaries of the Real Academia Española (RAE by its acronym in Spanish), which is the institution that dictates the rules, grammar and vocabulary that Spanish language should use; the Age of Acquisition was retrieved from Alonso and colleagues (2016).
Procedure
The current validation study was approved by the Research Ethical Review Committee (CETO) of the Faculties of Arts, Philosophy, and Theology and Religious Studies of the University of Groningen. Before doing the tests, each participant read the consent-form (See Appendix A.) and provided their consent orally.
The interviews were conducted by either Skype or Zoom since the participants live in Mexico, and the whole process lasted around 30 minutes. During the interviews, the responses were scored on a scoresheet and audio-recorded with the oral consent of each participant. Participants started with the object naming test, followed by action naming test. Participants looked at the Power Point presentation, which was shared by the researcher by the “share screen” function with no time constraints. Participants were instructed to look at the picture and name it with the first word that came to their mind by reading the lead-in phrase and completing the phrase (e.g. “Esto es un perro” (This is a dog)). If the participants did not know the noun or action that the image depicted, they would say that they did not know or did not recognize it.
5 All audio-recordings were analyzed, and the annotations were made accordingly. Refer to Appendix B to see the naming ratings for the object naming task, and Appendix C to see the naming ratings for the action naming task. Once all the annotations were done, the cut-off point to discard an image was 80%, following the procedure by Ohlerth and colleagues (2019). If the image depicted more than two synonyms, the image was also discarded. A total of 21 images were discarded for the Object naming task, due to the use of different synonyms for an image (e.g. tutú (tutu), falda (skirt), bailarina (dancer)) or participants were not able to understand the image (e.g. ski (ski), curita (plaster). The final noun list, that can be used as a battery for future research can be found in Appendix D. On the other hand, action naming task had more images discarded, a total of 43 verbs, since they were either named differently (e.g. jalar (to pull)-> se esfuerza (makes an effort), estira (stretches) no sé (I do not know)), or the participants were not able to name the picture at all. The final verb list can be found in Appendix E. See Table 1. for an overview of the linguistic values of the final list for both object naming and action naming.
Table 1. Linguistic variables of both picture naming tests
Linguistic variable Object naming (N=56) Action naming (N=92)
Frequency Mean: 29.1471 (sd= 52.3881;
Range= 0.042239 - 34.319145)
Mean:11.0842 (sd= 17.37979; Range= 0.006498 - 394.6973) Age of acquisition Mean: 4.43 (sd=1.56;
Range= 2.22- 7.8)
Mean: 5.7 (sd= 2.01; Range= 3.02-12.88)
Length of syllables Mean: 2.7 (sd=0.83; Range= 1-5) Mean= 2.43 (sd= 0.59;range= 1-4)
Regularity X Regular=74
Irregular=20
Transitivity X Transitive= 65
Intransitive= 23 Pronominal= 6
Number of arguments X 1 Argument= 27
2 Arguments= 67
Instrumentality X Instrumental= 37
6 Name relatedness to a noun X Related= 21 Non-related= 73 Reflection
The adaptation to Mexican Spanish of the VAN-POP and the validation process was an interesting hands-on project where I was able to implement some of the knowledge acquired during my time in EMCL. This was an important project for me because it does not only target intraoperative language mapping, but it targets Mexican population that could benefit from these first steps towards a standardized test.
Mexican Spanish varies quite a lot across the different regions, and even within the same region a word can be said in different ways. Choosing the most neutral word and following the rules by the RAE did not work, participants used different words and even words that were not recognized by the RAE (e.g. serruchar (to saw)), or more than two synonyms for one word. This stage reminded me of the beauty of a language, it evolves with the culture and it is of main importance to adapt language tests accordingly. It would be of main importance for the next steps, during the standardization process, that the if the researcher notices a different word being used, to do the necessary annotations and add it to the list.
Furthermore, this was a very productive exercise because I was able to study the VAN-POP tests in a more in-depth form. I believe that the VAN-VAN-POP test adaptation in Mexican Spanish would be a good asset to have for the Mexican population, since awake surgeries are increasingly being performed in various hospitals in Mexico City, Guadalajara, among others. It would be important to convey the need to have a standardized test target to Mexican population, and not only homemade tests or literal translations of tests used in different countries, to improve the outcome of the speech of the patient after the surgery. I believe this is a first step towards achieving this goal, and future research should keep improving the battery of the VAN-POP in Mexican Spanish.
7 References
Alonso, M.Á., Díez, E., & Fernandez, A., (2016). Subjective age-of-acquisition norms for 4,640 verbs in Spanish. Behav Res 48, 1337–1342. https://doi.org/10.3758/s13428-015-0675-z Alonso, M.A., Fernandez, A. & Díez, E, (2015). Subjective age-of-acquisition norms for 7,039
Spanish words. Behav Res 47, 268–274. https://doi.org/10.3758/s13428-014-0454-2 Duchon, A., Perea, M., Sebastián-Gallés, N. et al. EsPal: One-stop shopping for Spanish word
properties. Behav Res 45, 1246–1258 (2013). https://doi.org/10.3758/s13428-013-0326-1 Jescheniak, J.D. Gender Priming in Picture Naming: Modality and Baseline Effects. J
Psycholinguist Res 28, 729–737 (1999). https://doi.org/10.1023/A:1023229329967. ESPAL
Núñez-Velasco, S., Moreno-Jiménez, S., Avendaño-Méndez, J., Gómez-Amador, J., Navarro-Bonet, J., García-Iturbide, R., Molina-Martínez, C., Pech-Cervantes, C., Pérez-Castillo, A., Lucio-Soria, J., Ochoa-Martínez, E., Arellano-Reynoso, A. & Mejía-Pérez, S. (2020). Ohlerth, A. K., Valentin, A., Vergani, F., Ashkan, K., & Bastiaanse, R. (2020). The verb and
noun test for peri-operative testing (VAN-POP): standardized language tests for navigated transcranial magnetic stimulation and direct electrical stimulation. Acta Neurochirurgica, 162(2), 397–406. https://doi.org/10.1007/s00701-019-04159-x Rofes, A., Capasso, R., & Miceli, G. (2015). Verb production tasks in the measurement of
communicative abilities in aphasia. Journal of Clinical and Experimental
Neuropsychology, 37(5), 483–502. https://doi.org/10.1080/13803395.2015.1025709 Rofes, A., & Miceli, G. (2014). Language mapping with verbs and sentences in awake surgery:
A review. Neuropsychology Review, 24(4), 185–199. https://doi.org/10.1007/s11065-014-9258-5
8 Appendix A
Consentimiento Informado
El principal objetivo de este experimento es la nominación de imágenes que demuestran sustantivos y verbos. Usted deberá leer la frase introductora y completar con una oración sencialla. Se le dará información adicional y ejemplos de manera oral. También se le preguntará información demográfica. Tenga la seguiridad de que sus respuestas serán completamente confidenciales. La información demográfica será ligada con sus respuestas, pero todo será estrictamente anónimo y de ninguna manera se podrá rastrear la información proporsionada hacia usted.
El estudio tomará aproximadamente 30 minutos en total, y no recibirá ningún financiamiento monetareo por su participación. Su participación es totalmente voluntaria. Tiene el derecho de dejar el estudio por cualquier razón y sin necesidad de explicación alguna. También podrá decidir no contestar alguna de las preguntas. Podrá pedir ver su información o que se destruya aún 48 horas después de terminado el experimento. Si quisiera contactar al investigador principal para discutir el experimento, favor de enviar un correo al Dr. Adrià Rofes (Universidad de Groningen, Groningen, Paises Bajos: A.Rofes@rug.nl). Si quisiera saber más información sobre el objetivo de este estudio, puede contactar ala investigadora que lo lleva a cabo: Ana Lucía Rivas Paz (a.l.rivas.paz@student.rug.nl) o al Investigador Principal.
Usted acepta que es mayor de 18 años y que su participación en este estudio es totalmente voluntaria. Así también, que podrá retirarse de este estudio en cualquier momento y por cualquier razón sin proveer explicación alguna.
Este proyecto ha sido aprovado por el Research Ethical Review Committee (CETO) de la Facultad de Artes, Filosofía y Teología y Estudios Religiosos de la Universidad de Groningen. Para mayor información o quejas, favor de contactar al investigador principal (A.Rofes@rug.nl) o al CETO (ceto@rug.nl)
9 Appendix B
Table 2. Object naming agreement rating, synonyms accepted and linguistic variables. English Spanish Synonym Name
agreement ratings % Frequency Length in syllables AoA Animacy match shuttle bell church fireman drill scarf mosque computer tutu cup drums trolley cake bicycle whistle cow comb mountain eye sock pan baby mouth book vase ruler cerillo gallito campana iglesia bombero taladro bufanda mezquita computadora tutú taza batería carrito pastel bicicleta silbato vaca peine montaña ojo calcetin cacerola bebé boca libro jarrón regla niño 100 60 100 93 100 100 100 26 93 53 100 100 40 100 100 93 100 86 86 100 100 13 93 60 100 66 100 0.162458 1.049476 11.859407 216.325337 1.445873 0.828534 1.033231 9.01315 11.251816 0.120219 6.17339 35.051859 2.124946 4.477332 7.395072 0.890268 14.624436 1.692809 42.151258 39.571431 0.526363 0.968248 13.243546 86.200021 210.866761 0.952002 32.338817 3 3 3 3 3 3 3 3 5 2 2 4 3 2 4 3 2 2 3 2 3 4 2 2 2 2 2 6.26 4.66 4.28 4.62 5.06 7.14 4.8 9.22 7.8 4.2 3.74 7.2 3.62 3.18 3.76 5.56 3.08 3.22 3.72 2.72 3.34 6.62 2.22 2.34 3.32 4.76 5.12 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0
10 apple glass puzzle nose skate chess board moustache gun painting spider pen ski bed bread knife garden hose stamp vaccum cleaner car racket drum ring braid bird kite stadium bathtub hand saw sieve microphone chair swimming pool manzana vaso rompecabezas nariz patín ajedrez bigote rifle pintura araña pluma esquí cama pan cuchillo manguera sello aspiradora carro raqueta tambor anillo trenza pájaro papalote estadio bañera mano sierra coladera microfono silla alberca pajarito cometa tina serrucho colador piscina 100 100 93 100 73 60 86 93 53 100 86 46 100 80 100 100 93 100 60 100 100 100 60 93 93 86 100 100 100 100 100 100 100 8.126131 15.050075 2.193178 20.281211 0.903264 14.205296 3.924976 3.846997 43.827821 12.125838 17.915828 8.684985 45.514131 50.166918 17.106789 0.750554 29.291112 0.256683 16.75588 0.906514 7.853202 23.692821 1.020234 17.698135 6.043424 65.697867 1.806529 234.319145 66.906552 0.042239 4.25639 24.804032 0.84478 3 2 5 2 2 3 3 2 3 3 2 2 2 1 3 3 2 5 2 3 2 3 2 3 3 3 3 2 2 4 4 2 3 2.72 2.8 3.88 2.54 5.78 6.98 4.2 7.8 4 3.32 5.48 7.2 2.42 2.32 3.98 4.34 6.82 4.36 4.9 5.1 3.92 4.02 4.48 3.42 4.78 7.26 3.1 2.22 7.44 6.26 5.58 3.18 4.06 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
11 dog beer tap farmer spade basketball steering wheel ship clothes pin camara hoe balloon rake kitchen tool trampoline shoe plaster ball perro grifo (cerveza) granjero pala pelota volante barco pinza cámara azada globo rastrillo batidor brincolín zapato curita balón agricultor trampolín 80 13 80 100 46 93 86 46 100 0 100 60 33 93 100 33 40 69.970503 2.293902 1.813027 4.116676 17.512933 7.664751 42.739355 1.023483 134.498676 0.698568 16.944331 0.737558 0.201447 1.83902 3.418109 0.175454 21.93503 2 2 3 2 3 3 2 2 3 3 2 3 3 3 3 3 2 2.58 3.58 6.2 4.42 2.32 5.92 3.3 5.02 5.26 2.42 5.84 5.26 2.78 5.3 3.04 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
12 Appendix C
Table 3. Action naming agreement ratings, synonyms accepted and linguistic variables including: regularity, transitivity, number of arguments, instrumentality and name relatedness to a noun.
English Spanish Synonym Name agreement %
Frequency Length in syllables
AoA Reg. Trans. # of
arguments Instrument Name to noun To run To bandage to shave to throw to take off to clean to knit to play to iron to row to dig to blow to eat to marry to hammer to light to climb to shout correr vendar rasurar aventar despegar limpiar tejer jugar planchar remar cavar soplar comer casarse martillar encender escalar gritar afeitar volar pintar clavar prender 100 40 80 26 100 100 86 100 100 66 13 33 100 100 86 86 100 80 34.054369 0.181953 0.120219 0.194949 3.366122 7.349583 2.446612 64.407954 0.402895 0.867524 5.380597 2.056714 67.735086 12.220063 0.123468 5.309116 4.246643 9.909916 2 2 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 2 3.9 6.54 12.88 10.67 6.56 5.04 8.02 3.14 6.28 6.6 7.06 4.56 3.24 6.38 7.7 4.5 6.73 4.1 R R R I R R R I R R R R R R R I R R I T Pronominal I T T T T T I T I I Pronominal T T T T and I 1 2 1 1 2 2 2 2 2 1 2 1 1 2 2 2 2 2 0 1 1 0 0 1 1 0 1 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0
13 to ring the bell
to yawn to play to stroll to measure to sled to inflate to cough to cook to bow to pick to wallpaper to sting to bless to fly to hunt to demolish to break to dip to march to shiver to knead to shave (ref) to shower (ref) to sweep to mop timbrar bostezar jugar caminar medir deslizarse inflar toser cocinar reverenciar picar tapizar inyectar bendecir volar atrapar destruir romper sopear marchar tiritar amasar rasurarse bañarse barrer trapear estornudar picotear cazar desfilar 73 53 100 66 100 46 93 100 100 6 93 6 93 60 100 93 93 60 6 86 73 86 80 100 100 100 0.022744 0.30867 64.407954 18.692375 17.620155 1.627825 0.367154 0.744056 3.421358 0.211195 1.299661 0.094225 1.283415 1.38089 18.67613 4.360363 27.539818 25.557835 0.006498 9.334816 0.220942 0.682322 0.03899 1.416631 1.933246 0.006498 2 3 2 3 2 4 2 2 3 4 2 3 3 3 2 3 3 2 2 2 3 3 4 3 2 3 10.2 5.12 3.14 3.62 6.61 6.8 5.68 4.52 7.66 10.88 6.22 11.04 8.32 7.14 4.38 6.76 6.76 4.66 7.86 6.18 7.3 7.98 12.88 3.86 5.56 5.62 R I I R I I R R R R I I R I I R R R R R R R R R R R T I I I T Pronominal T I T T T T T T I T T T T I I T T Pronominal T T 2 1 1 1 2 1 2 1 2 2 2 2 2 2 1 2 2 2 2 1 1 2 2 1 2 2 1 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 1
14 to pray to blow to curl to pour to spread to carry to dive to snorkel to smell to lick to plough to solder to pull to sing to type to bake to saw to drink to cry to swim to wink to go upstairs to feed to point to crawl to sweat rezar inflar rizar servir untar cargar clavarse bucear oler lamer arar soldar jalar cantar escribir hornear cortar beber llorar nadar guiñar subir alimentar apuntar gatear sudar serruchar tomar 86 86 6 26 53 100 33 93 100 20 26 93 60 100 73 60 100 100 86 100 80 93 40 13 100 100 4.922466 0.367154 0.149461 45.341926 0.46138 8.304834 0.246936 0.565353 1.501109 0.552356 1.299661 0.49712 0.243686 25.639064 56.06413 0.172205 14.195548 18.568908 19.121264 5.543054 0.15271 27.237647 8.161872 5.045934 0.15271 1.211934 2 2 2 2 2 2 3 3 2 2 2 2 2 2 3 3 2 2 2 2 2 2 4 3 3 2 6.06 5.68 5.9 5.52 7.35 7.2 6.9 7.66 4.48 6.36 9.54 10.69 7.49 4.06 4.14 9.1 4.14 3.52 3.4 4.4 7.49 3.98 4.76 6.49 3.86 6.1 R R I I R R R R I R R I R R R R R R R R R R R R R R T T T I T T I I T T T T T I T T T I I I T I T T I I 2 2 2 1 2 2 1 1 2 2 2 2 2 1 2 2 2 1 1 1 2 1 2 2 1 1 0 0 1 0 1 0 0 1 0 0 1 1 0 0 1 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
15 to beg to jump to spin to vacuum to flutter to call to tear apart to paint to chop to dig to plant to drill to whistle to sow to sit to laugh to listen to pick up to collect to compose to rescue to sleep to wash to erase to shoot to prune pedir saltar tejer aspirar ondear llamar romper pintar cortar cavar plantar taladrar silbar sembrar sentarse sonreír escuchar acomodar recolectar componer rescatar dormir lavar borrar disparar podar brincar hablar excavar sembrar chiflar salvar cortar 80 100 53 93 33 100 53 100 46 86 100 86 80 93 66 86 100 26 26 46 86 93 100 73 100 93 64.141523 13.100584 2.446612 6.027178 0.617339 56.583994 25.557835 7.645256 14.195548 5.380597 4.821743 0.354158 0.006499 4.990699 10.787187 4.262888 39.110051 1.3419 2.053465 9.230843 9.081382 27.585306 4.308376 6.010932 10.312811 0.30542 2 2 2 3 3 2 2 2 2 2 2 3 2 2 3 3 3 4 4 3 3 2 2 2 3 2 4.34 4.4 8.02 9.16 10.13 4.02 4.66 3.22 4.14 7.06 4.86 8.9 5.46 6.74 3.38 3.8 4.36 9.52 8.14 9.14 7.48 3.26 4.96 4.44 6.1 8.8 I R R R R R R R R R R R R I I I R R R I R I R R R R T T T T T T T T T T T T I T I I T T T T T I T T T T 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 1 2 2 2 2 2 1 2 2 2 2 0 0 1 1 0 0 0 1 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
16 to count to dance to grate to sharpen to extinguish to clean to fish to teach to scratch to clap to kiss to read to sneeze to sew to graze to wave to fold to bath to sail to hide to peel to toast to sting to hug to frisk to water contar bailar rallar afilar extinguir limpiar pescar enseñar rascar(se) aplaudir besar leer estornudar coser pastar saludar doblar bañar navegar esconder(se) pelar brindar picar abrazar catear regar comer 93 86 73 100 73 93 100 86 86 93 100 100 93 93 93 86 100 100 53 83 93 86 100 100 26 100 22383 10.212087 0.094225 0.646581 1.621327 7.349583 5.663273 14.367753 1.946242 2.336141 3.944471 46.557109 0.321666 2.173683 1.208685 6.884955 3.999707 0.851278 5.257129 7.447058 2.690298 5.900461 1.299661 3.48959 0.016246 1.673314 2 2 2 3 3 2 2 3 3 3 2 2 4 2 2 3 2 2 3 4 2 2 2 3 3 2 4.18 4.22 6.57 5.52 9.28 5.04 5.2 5.18 4.9 4.7 5.4 4.6 4.76 6.4 8.46 4.2 5.36 3.62 7.78 4.54 5.94 7.84 6.22 3.78 5.08 5.73 I R R R I R R R I R R I R R R R R R I R R R I I R I T I T T T T T T Pronominal T T T I T T T T T I Pronominal T I T T T T 2 1 2 2 2 2 2 2 1 2 2 2 1 2 2 2 2 2 1 1 2 1 2 2 2 2 0 0 1 1 1 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
17 to brush to comb to stop to cut to watch togo downstairs to push to put to sleep to surf to hang to watch to cut to skate to kick to shear to tune cepillar peinar(se) parar picar ver bajar empujar acostar surfear colgar ver cortar patinar patear esquilar ajustar peinar cortar tender observar 93 86 13 93 66 100 100 13 93 93 93 100 100 33 0 73 0.194949 0.315168 20.316952 1.299661 394.697322 21.671848 2.940483 1.377641 0.188451 2.79752 394.697322 14.195548 0.42239 0.591346 0.155959 5.851724 3 3 2 2 1 2 3 3 3 2 1 2 3 3 3 3 4.82 4.5 5.2 6.22 4.08 3.86 5.24 3.64 11.9 5.18 4.08 4.14 5.2 7.52 11.9 9.12 R R R I I R R R R I I R R R R R T T T T T I T T I T T T I T T T 2 2 2 2 2 1 2 2 1 2 2 2 1 2 2 2 1 1 0 0 0 1 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0
18 Appendix D.
Final list of nouns for the VAN-POP object naming test in Mexican Spanish
cerillo campana iglesia bombero taladro bufanda computadora taza batería pastel bicicleta silbato vaca peine montaña ojo calcetin bebé libro regla manzana vaso rompecabezas nariz bigote rifle araña pluma cama pan cuchillo manguera sello aspiradora raqueta tambor anillo pájaro cometa estadio bañera mano sierra coladera micrófono silla alberca perro granjero pala volante barco cámara globo trampolín zapato
19 Appendix E.
Final list of verbs for the VAN-POP action naming test in Mexican Spanish
correr rasurar despegar limpiar tejer jugar planchar comer casar(se) martillar encender escalar gritar jugar medir inflar columpiarse toser cocinar picar inyectar volar atrapar destruir marchar amasar rasurar(se) bañar(se) barrer trapear rezar inflar cargar bucear oler cantar cortar beber llorar nadar guiñar subir gatear sudar pedir saltar aspirar llamar pintar cavar plantar silbar sembrar sonreir escuchar rescatar dormir lavar disparar podar contar bailar afilar limpiar pescar enseñar rascar(se) aplaudir besar leer estornudar coser pastar saludar doblar bañar esconder(se) pelar brindar picar abrazar regar cepillar peinar(se) picar bajar empujar surfear colgar ver cortar patinar
