References
- 1Amsel, B. D., Urbach, T. P., & Kutas, M. (2012). Perceptual and motor attribute ratings for 559 object concepts. Behavior Research Methods, 44(4), 1028–1041. 10.3758/s13428-012-0215-z
- 2Ballot, C., Mathey, S., & Robert, C. (2022). Age-related evaluations of imageability and subjective frequency for 1286 neutral and emotional French words: Ratings by young, middle-aged, and older adults. Behavior Research Methods, 54(1), 196–215. 10.3758/s13428-021-01621-6
- 3Balota, D. A., Cortese, M. J., Sergent-Marshall, S. D., Spieler, D. H., & Yap, M. J. (2004). Visual word recognition of single-syllable words. Journal of Experimental Psychology-General, 133(2), 283–316. 10.1037/0096-3445.133.2.283
- 4Batchelor, J. H., & Miao, C. (2016).
Extreme Response Style: A Meta-Analysis . Journal of Organizational Psychology, 16(2), Article2 .https://articlearchives.co/index.php/JOP/article/view/3628 - 5Brysbaert, M., Mandera, P., McCormick, S. F., & Keuleers, E. (2019). Word prevalence norms for 62,000 English lemmas. Behavior Research Methods, 51(2), 467–479. 10.3758/s13428-018-1077-9
- 6Cayol, Z., Rotival, C., Paulignan, Y., & Nazir, T. A. (2020). “Embodied” language processing: Mental motor imagery aptitude predicts word-definition skill for high but not for low imageable words in adolescents. Brain and Cognition, 145,
105628 . 10.1016/j.bandc.2020.105628 - 7Donoff, C. M., Madan, C. R., & Singhal, A. (2018). Handedness effects of imagined fine motor movements. Laterality: Asymmetries of Body, Brain and Cognition, 23(2), 228–248. 10.1080/1357650X.2017.1354870
- 8Gilet, A.-L., Grühn, D., Studer, J., & Labouvie-Vief, G. (2012). Valence, arousal, and imagery ratings for 835 French attributes by young, middle-aged, and older adults: The French Emotional Evaluation List (FEEL). European Review of Applied Psychology, 62(3), 173–181. 10.1016/j.erap.2012.03.003
- 9Gobin, P., Camblats, A.-M., Faurous, W., & Mathey, S. (2017). Une base de l’émotionalité (valence, arousal, catégories) de 1286 mots français selon l’âge (EMA). European Review of Applied Psychology, 67(1), 25–42. 10.1016/j.erap.2016.12.001
- 10Grandy, T. H., Lindenberger, U., & Schmiedek, F. (2020). Vampires and nurses are rated differently by younger and older adults—Age-comparative norms of imageability and emotionality for about 2500 German nouns. Behavior Research Methods, 52(3), 980–989. 10.3758/s13428-019-01294-2
- 11Grühn, D., & Smith, J. (2008). Characteristics for 200 words rated by young and older adults: Age-dependent evaluations of German adjectives (AGE). Behavior Research Methods, 40(4), 1088–1097. 10.3758/BRM.40.4.1088
- 12Haro, J., Hinojosa, J. A., & Ferré, P. (2024). The role of individual differences in emotional word recognition: Insights from a large-scale lexical decision study. Behavior Research Methods. 10.3758/s13428-024-02488-z
- 13Heard, A., Madan, C. R., Protzner, A. B., & Pexman, P. M. (2019). Getting a grip on sensorimotor effects in lexical-semantic processing. Behavior Research Methods, 51(1), 1–13. 10.3758/s13428-018-1072-1
- 14Keuleers, E., & Balota, D. A. (2015). Megastudies, crowdsourcing, and large datasets in psycholinguistics: An overview of recent developments. Quarterly Journal of Experimental Psychology, 68(8), 1457–1468. 10.1080/17470218.2015.1051065
- 15Muraki, E. J., Dahm, S. F., & Pexman, P. M. (2023). Meaning in hand: Investigating shared mechanisms of motor imagery and sensorimotor simulation in language processing. Cognition, 240,
105589 . 10.1016/j.cognition.2023.105589 - 16Muraki, E. J., & Pexman, P. M. (2021). Simulating semantics: Are individual differences in motor imagery related to sensorimotor effects in language processing? Journal of Experimental Psychology: Learning, Memory, and Cognition, 47(12), 1939–1957. 10.1037/xlm0001039
- 17Muraki, E. J., Reggin, L. D., Feddema, C. Y., & Pexman, P. M. (2023). The Development of Abstract Word Meanings. Journal of Child Language, 1–13. 10.1017/S0305000923000569
- 18Muraki, E. J., Siddiqui, I. A., & Pexman, P. M. (2022). Quantifying children’s sensorimotor experience: Child body–object interaction ratings for 3359 English words. Behavior Research Methods, 54, 2864–2877. 10.3758/s13428-022-01798-4
- 19Muraki, E. J., Speed, L. J., & Pexman, P. M. (2023). Insights into embodied cognition and mental imagery from aphantasia. Nature Reviews Psychology, 1–15. 10.1038/s44159-023-00221-9
- 20Ochipa, C., Rapcsak, S. Z., Maher, L. M., Gonzalez Rothi, L. J., Bowers, D., & Heilman, K. M. (1997). Selective deficit of praxis imagery in ideomotor apraxia. Neurology, 49(2), 474–480. 10.1212/wnl.49.2.474
- 21Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh Inventory. Neuropsychologia, 9, 97–113. 10.1016/0028-3932(71)90067-4
- 22Paisios, D., Huet, N., & Labeye, E. (2023). Addressing the Elephant in the Middle: Implications of the Midscale Disagreement Problem Through the Lens of Body-Object Interaction Ratings. Collabra: Psychology, 9(1),
84564 . 10.1525/collabra.84564 - 23Pavan, A., & Baggio, G. (2013). Linguistic representations of motion do not depend on the visual motion system. Psychological Science, 24(2), 181–188. 10.1177/0956797612450882
- 24Pexman, P. M., Muraki, E., Sidhu, D. M., Siakaluk, P. D., & Yap, M. J. (2019). Quantifying sensorimotor experience: Body-object interaction ratings for more than 9,000 English words. Behavior Research Methods, 51(2), 453–466. 10.3758/s13428-018-1171-z
- 25Pollock, L. (2018). Statistical and methodological problems with concreteness and other semantic variables: A list memory experiment case study. Behavior Research Methods, 50(3), 1198–1216. 10.3758/s13428-017-0938-y
- 26R Core Team. (2024). R: A language and environment for statistical computing. (Version 4.4.1) [Computer software]. R Foundation for Statistical Computing.
https://www.R-project.org/ - 27Roberts, R., Callow, N., Hardy, L., Markland, D., & Bringer, J. (2008). Movement imagery ability: Development and assessment of a revised version of the Vividness of Movement Imagery Questionnaire. Journal of Sports & Exercise Psychology, 30, 200–221.
https://doi.org/10/gf5crw ; 10.1123/jsep.30.2.200 - 28Siakaluk, P. D., Pexman, P. M., Aguilera, L., Owen, W. J., & Sears, C. R. (2008). Evidence for the activation of sensorimotor information during visual word recognition: The body-object interaction effect. Cognition, 106(1), 433–443. 10.1016/j.cognition.2006.12.011
- 29Siew, C. S. Q. (2024). A comparison of word humor ratings across speakers of North American, British, and Singapore English. Memory & Cognition. 10.3758/s13421-024-01587-8
- 30Teismann, H., Kissler, J., & Berger, K. (2020). Investigating the roles of age, sex, depression, and anxiety for valence and arousal ratings of words: A population-based study. BMC Psychology, 8(1),
118 . 10.1186/s40359-020-00485-3 - 31Warriner, A. B., Kuperman, V., & Brysbaert, M. (2013). Norms of valence, arousal, and dominance for 13,915 English lemmas. Behavior Research Methods, 45(4), 1191–1207. 10.3758/s13428-012-0314-x
- 32Winter, B. (2022).
Managing Semantic Norms for Cognitive Linguistics, Corpus Linguistics, and Lexicon Studies . In A. L. Berez-Kroeker, B. McDonnell, E. Koller, & L. B. Collister (Eds.), The Open Handbook of Linguistic Data Management (pp. 489–498). The MIT Press. 10.7551/mitpress/12200.003.0047