References

Al-Azary, H., Yu, T., & McRae, K. (2022). Can you touch the N400? The interactive effects of body-object interaction and task demands on N400 amplitudes and decision latencies. Brain and Language, 231, 105147. https://doi.org/10.1016/j.bandl.2022.105147
Albers, C., & Lakens, D. (2018). When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias. Journal of Experimental Social Psychology, 74, 187–195. https://doi.org/10.1016/j.jesp.2017.09.004
Amsel, B. D. (2011). Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials. Neuropsychologia, 49(5), 970–983. https://doi.org/10.1016/j.neuropsychologia.2011.01.003
Amsel, B. D., Urbach, T. P., & Kutas, M. (2014). Empirically grounding grounded cognition: The case of color. NeuroImage, 99, 149–157. https://doi.org/10.1016/j.neuroimage.2014.05.025
Anderson, C. J., Bahník, Š., Barnett-Cowan, M., Bosco, F. A., Chandler, J., Chartier, C. R., Cheung, F., Christopherson, C. D., Cordes, A., Cremata, E. J., Della Penna, N., Estel, V., Fedor, A., Fitneva, S. A., Frank, M. C., Grange, J. A., Hartshorne, J. K., Hasselman, F., Henninger, F., … Zuni, K. (2016). Response to Comment on Estimating the reproducibility of psychological science.” Science, 351(6277), 1037–1037. https://doi.org/10.1126/science.aad9163
Anderson, M. L. (2010). Neural reuse: A fundamental organizational principle of the brain. Behavioral and Brain Sciences, 33(4), 245–266. https://doi.org/10.1017/S0140525X10000853
Andrews, M., Frank, S., & Vigliocco, G. (2014). Reconciling embodied and distributional accounts of meaning in language. Topics in Cognitive Science, 6(3), 359–370. https://doi.org/10.1111/tops.12096
Andrews, M., Vigliocco, G., & Vinson, D. (2009). Integrating experiential and distributional data to learn semantic representations. Psychological Review, 116(3), 463–498. https://doi.org/10.1037/a0016261
Aujla, H. (2021). Language experience predicts semantic priming of lexical decision. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale, 75(3), 235. https://doi.org/10.1037/cep0000255
Aust, F., & Barth, M. (2020). papaja: Create APA manuscripts with R Markdown. https://github.com/crsh/papaja
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. https://doi.org/10.1016/j.jml.2007.12.005
Balota, D. A., & Lorch, R. F. (1986). Depth of automatic spreading activation: Mediated priming effects in pronunciation but not in lexical decision. Journal of Experimental Psychology: Learning, Memory, and Cognition, 12(3), 336–345. https://doi.org/10.1037/0278-7393.12.3.336
Balota, D. A., Yap, M. J., Cortese, M. J., & Watson, J. M. (2008). Beyond mean response latency: Response time distributional analyses of semantic priming. Journal of Memory and Language, 59(4), 495–523. https://doi.org/10.1016/j.jml.2007.10.004
Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., Neely, J. H., Nelson, D. L., Simpson, G. B., & Treiman, R. (2007). The English Lexicon Project. Behavior Research Methods, 39, 445–459. https://doi.org/10.3758/BF03193014
Banks, B., Wingfield, C., & Connell, L. (2021). Linguistic distributional knowledge and sensorimotor grounding both contribute to semantic category production. Cognitive Science, 45(10), e13055. https://doi.org/10.1111/cogs.13055
Barca, L., Mazzuca, C., & Borghi, A. (2020). Overusing the pacifier during infancy sets a footprint on abstract words processing. Journal of Child Language, 47(5), 1084–1099. https://doi.org/10.1017/S0305000920000070
Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 255–278. https://doi.org/10.1016/j.jml.2012.11.001
Barsalou, L. W. (1999a). Perceptual symbol systems. Behavioral and Brain Sciences, 22(4), 577–660. https://doi.org/10.1017/S0140525X99002149
Barsalou, L. W. (1999b). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577–660. https://doi.org/10.1017/S0140525X99002149
Barsalou, L. W. (2003). Situated simulation in the human conceptual system. Language and Cognitive Processes, 18(5-6), 513–562. https://doi.org/10.1080/01690960344000026
Barsalou, L. W. (2016). On staying grounded and avoiding quixotic dead ends. Psychonomic Bulletin & Review, 23(4), 1122–1142. https://doi.org/10.3758/s13423-016-1028-3
Barsalou, L. W. (2019). Establishing generalizable mechanisms. Psychological Inquiry, 30(4), 220–230. https://doi.org/10.1080/1047840X.2019.1693857
Barsalou, L. W., Santos, A., Simmons, W. K., & Wilson, C. D. (2008). Language and simulation in conceptual processing. In Symbols and Embodiment. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199217274.003.0013
Barton, J. J. S., Hanif, H. M., Eklinder Björnström, L., & Hills, C. (2014). The word-length effect in reading: A review. Cognitive Neuropsychology, 31(5-6), 378–412. https://doi.org/10.1080/02643294.2014.895314
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48. https://doi.org/10.18637/jss.v067.i01
Bates, D., Maechler, M., Bolker, B., Walker, S., Christensen, R. H. B., Singmann, H., Dai, B., Scheipl, F., Grothendieck, G., Green, P., Fox, J., Brauer, A., & Krivitsky, P. N. (2021). Package ’lme4. CRAN. https://cran.r-project.org/web/packages/lme4/lme4.pdf
Becker, S., Moscovitch, M., Behrmann, M., & Joordens, S. (1997). Long-term semantic priming: A computational account and empirical evidence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(5), 1059–1082. https://doi.org/10.1037/0278-7393.23.5.1059
Beilock, S. L., Lyons, I. M., Mattarella-Micke, A., Nusbaum, H. C., & Small, S. L. (2008). Sports experience changes the neural processing of action language. Proceedings of the National Academy of Sciences, 105(36), 13269–13273. https://doi.org/10.1073/pnas.0803424105
Bernabeu, P. (2017). Modality switches occur early and extend late in conceptual processing: Evidence from ERPs. PsyArXiv. https://doi.org/10.31234/osf.io/5gjvk
Bernabeu, P. (2018). Dutch modality exclusivity norms for 336 properties and 411 concepts. PsyArXiv. https://doi.org/10.31234/osf.io/s2c5h
Bernabeu, P., Lynott, D., & Connell, L. (2021). Preregistration: The interplay between linguistic and embodied systems in conceptual processing. OSF. https://osf.io/ftydw
Bernabeu, P., & Tillman, R. (2019). More refined typology and design in linguistic relativity: The case of motion event encoding. Dutch Journal of Applied Linguistics, 8(2), 163–171. https://doi.org/10.1075/dujal.15019.ber
Bernabeu, P., Willems, R. M., & Louwerse, M. M. (2017). Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (pp. 1629–1634). Cognitive Science Society. https://doi.org/10.31234/osf.io/a5pcz
Beyersmann, E., Grainger, J., & Taft, M. (2020). Evidence for embedded word length effects in complex nonwords. Language, Cognition and Neuroscience, 35(2), 235–245. https://doi.org/10.1080/23273798.2019.1659989
Binder, J. R., & Desai, R. H. (2011). The neurobiology of semantic memory. Trends in Cognitive Sciences, 15(11), 527–536. https://doi.org/10.1016/j.tics.2011.10.001
Bonner, M. F., Vesely, L., Price, C., Anderson, C., Richmond, L., Farag, C., Avants, B., & Grossman, M. (2009). Reversal of the concreteness effect in semantic dementia. Cognitive Neuropsychology, 26(6), 568–579. https://doi.org/10.1080/02643290903512305
Borghesani, V., Pedregosa, F., Buiatti, M., Amadon, A., Eger, E., & Piazza, M. (2016). Word meaning in the ventral visual path: A perceptual to conceptual gradient of semantic coding. NeuroImage, 143, 128–140. https://doi.org/10.1016/j.neuroimage.2016.08.068
Borghi, A. M., Barca, L., Binkofski, F., Castelfranchi, C., Pezzulo, G., & Tummolini, L. (2019). Words as social tools: Language, sociality and inner grounding in abstract concepts. Physics of Life Reviews, 29, 120–153. https://doi.org/10.1016/j.plrev.2018.12.001
Borghi, A. M., Shaki, S., & Fischer, M. H. (2022). Abstract concepts: External influences, internal constraints, and methodological issues. Psychological Research. https://doi.org/10.1007/s00426-022-01698-4
Bottini, R., Bucur, M., & Crepaldi, D. (2016). The nature of semantic priming by subliminal spatial words: Embodied or disembodied? Journal of Experimental Psychology: General, 145(9), 1160–1176. https://doi.org/10.1037/xge0000197
Bottini, R., Morucci, P., D’Urso, A., Collignon, O., & Crepaldi, D. (2021). The concreteness advantage in lexical decision does not depend on perceptual simulations. Journal of Experimental Psychology: General. https://doi.org/10.1037/xge0001090
Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., … Schonberg, T. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature, 582(7810, 7810), 84–88. https://doi.org/10.1038/s41586-020-2314-9
Brauer, M., & Curtin, J. J. (2018). Linear mixed-effects models and the analysis of nonindependent data: A unified framework to analyze categorical and continuous independent variables that vary within-subjects and/or within-items. Psychological Methods, 23(3), 389–411. https://doi.org/10.1037/met0000159
Brunellière, A., Perre, L., Tran, T., & Bonnotte, I. (2017). Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects. Quarterly Journal of Experimental Psychology, 70(9), 1922–1934. https://doi.org/10.1080/17470218.2016.1215479
Brysbaert, M. (2019). How many participants do we have to include in properly powered experiments? A tutorial of power analysis with reference tables. Journal of Cognition, 2(1, 1), 16. https://doi.org/10.5334/joc.72
Brysbaert, M. (2022). Word recognition II. In M. J. Snowling, C. Hulme, & K. Nation, The science of reading (pp. 79–101). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781119705116.ch4
Brysbaert, M., Mandera, P., & Keuleers, E. (2018). The word frequency effect in word processing: An updated review. Current Directions in Psychological Science, 27(1), 45–50. https://doi.org/10.1177/0963721417727521
Brysbaert, M., & Stevens, M. (2018). Power analysis and effect size in mixed effects models: A tutorial. Journal of Cognition, 1(1), 9. https://doi.org/10.5334/joc.10
Brysbaert, M., Stevens, M., Mandera, P., & Keuleers, E. (2016). The impact of word prevalence on lexical decision times: Evidence from the Dutch Lexicon Project 2. Journal of Experimental Psychology: Human Perception and Performance, 42(3), 441–458. https://doi.org/10.1037/xhp0000159
Brysbaert, M., Warriner, A. B., & Kuperman, V. (2014). Concreteness ratings for 40 thousand generally known English word lemmas. Behavior Research Methods, 46, 904–911. https://doi.org/10.3758/s13428-013-0403-5
Bullinaria, J. A., & Levy, J. P. (2007). Extracting semantic representations from word co-occurrence statistics: A computational study. Behavior Research Methods, 39(3), 510–526. https://doi.org/10.3758/BF03193020
Bürkner, P.-C. (2018). Advanced Bayesian multilevel modeling with the R package brms. The R Journal, 10(1), 395–411. https://journal.r-project.org/archive/2018/RJ-2018-017/index.html
Bürkner, P.-C., Gabry, J., Weber, S., Johnson, A., Modrak, M., Badr, H. S., Weber, F., Ben-Shachar, M. S., & Rabel, H. (2022). Package ’brms. CRAN. https://cran.r-project.org/web/packages/brms/brms.pdf
Burman, D., Bitan, T., & Both, J. (2008). Sex differences in neural processing of language among children. Neuropsychologia, 46, 5, 1349–1362. https://doi.org/10.1016/j.neuropsychologia.2007.12.021
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(5, 5), 365–376. https://doi.org/10.1038/nrn3475
Calvo-Merino, B., Glaser, D. E., Grèzes, J., Passingham, R. E., & Haggard, P. (2005). Action observation and acquired motor skills: An FMRI study with expert dancers. Cerebral Cortex, 15(8), 1243–1249. https://doi.org/10.1093/cercor/bhi007
Cerni, T., Velay, J.-L., Alario, F.-X., Vaugoyeau, M., & Longcamp, M. (2016). Motor expertise for typing impacts lexical decision performance. Trends in Neuroscience and Education, 5(3), 130–138. https://doi.org/10.1016/j.tine.2016.07.007
Charbonnier, J., & Wartena, C. (2019). Predicting word concreteness and imagery. Proceedings of the 13th International Conference on Computational Semantics - Long Papers, 176–187. https://doi.org/10.18653/v1/W19-0415
Charbonnier, J., & Wartena, C. (2020). Predicting the concreteness of German words. Proceedings of the 5th Swiss Text Analytics Conference (SwissText), 2624. https://doi.org/10.25968/opus-2075
Chen, I.-H., Zhao, Q., Long, Y., Lu, Q., & Huang, C.-R. (2019). Mandarin Chinese modality exclusivity norms. PLOS ONE, 14(2), e0211336. https://doi.org/10.1371/journal.pone.0211336
Chen, S.-C., de Koning, B. B., & Zwaan, R. A. (2020). Does object size matter with regard to the mental simulation of object orientation? Experimental Psychology, 67(1), 56–72. https://doi.org/10.1027/1618-3169/a000468
Chen, S.-C., Szabelska, A., Chartier, C. R., Kekecs, Z., Lynott, D., Bernabeu, P., Jones, B. C., DeBruine, L. M., Levitan, C., Werner, K. M., Wang, K., Milyavskaya, M., Musser, E. D., Papadatou-Pastou, M., Coles, N. A., Janssen, S., Özdoğru, A. A., Storage, D., Manley, H., … Schmidt, K. (2018). Investigating object orientation effects across 14 languages [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/t2pjv
Cohen, J. (1983). The cost of dichotomization. Applied Psychological Measurement, 7(3), 249–253. https://doi.org/10.1177/014662168300700301
Coleman, L., & Kay, P. (1981). Prototype semantics: The English word Lie. Language, 57(1), 26–44. https://doi.org/10.2307/414285
Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82, 407–428. https://doi.org/10.1037/0033-295X.82.6.407
Collins, J., Pecher, D., Zeelenberg, R., & Coulson, S. (2011). Modality switching in a property verification task: An ERP study of what happens when candles flicker after high heels click. Frontiers in Psychology, 2(10). https://doi.org/10.3389/fpsyg.2011.00010
Conca, F., Catricalà, E., Canini, M., Petrini, A., Vigliocco, G., Cappa, S. F., & Della Rosa, P. A. (2021). In search of different categories of abstract concepts: A fMRI adaptation study. Scientific Reports, 11(1, 1), 22587. https://doi.org/10.1038/s41598-021-02013-8
Connell, L. (2019). What have labels ever done for us? The linguistic shortcut in conceptual processing. Language, Cognition and Neuroscience, 34(10), 1308–1318. https://doi.org/10.1080/23273798.2018.1471512
Connell, L., & Lynott, D. (2012). Strength of perceptual experience predicts word processing performance better than concreteness or imageability. Cognition, 125(3), 452–465. https://doi.org/10.1016/j.cognition.2012.07.010
Connell, L., & Lynott, D. (2013). Flexible and fast: Linguistic shortcut affects both shallow and deep conceptual processing. Psychonomic Bulletin & Review, 20, 3, 542–550. https://doi.org/10.3758/s13423-012-0368-x
Connell, L., & Lynott, D. (2014a). I see/hear what you mean: Semantic activation in visual word recognition depends on perceptual attention. Journal of Experimental Psychology: General, 143(2), 527–533. https://doi.org/10.1037/a0034626
Connell, L., & Lynott, D. (2014b). Principles of representation: Why you can’t represent the same concept twice. Topics in Cognitive Science, 6(3), 390–406. https://doi.org/10.1111/tops.12097
Connell, L., & Lynott, D. (2016). Do we know what we’re simulating? Information loss on transferring unconscious perceptual simulation to conscious imagery. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(8), 1218–1232. https://doi.org/10.1037/xlm0000245
Connell, L., Lynott, D., & Banks, B. (2018). Interoception: The forgotten modality in perceptual grounding of abstract and concrete concepts. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1752), 20170143. https://doi.org/10.1098/rstb.2017.0143
Contreras Kallens, P., Dale, R., & Christiansen, M. H. (2022). Quantifying interdisciplinarity in cognitive science and beyond. Topics in Cognitive Science. https://doi.org/10.1111/tops.12609
Corker, K. S., Lynott, D., Wortman, J., Connell, L., Donnellan, M. B., Lucas, R. E., & O’Brien, K. (2014). High quality direct replications matter: Response to Williams (2014). Social Psychology, 45(4), 324–326.
Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 25(1), 7–29. https://doi.org/10.1177/0956797613504966
Daidone, D., & Darcy, I. (2021). Vocabulary size is a key factor in predicting second language lexical encoding accuracy. Frontiers in Psychology, 12, 688356. https://doi.org/10.3389/fpsyg.2021.688356
Davies, R. A., Arnell, R., Birchenough, J. M., Grimmond, D., & Houlson, S. (2017). Reading through the life span: Individual differences in psycholinguistic effects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(8), 1298. https://doi.org/10.1037/xlm0000366
Davis, C. P., & Yee, E. (2021). Building semantic memory from embodied and distributional language experience. WIREs Cognitive Science, 12(5), e1555. https://doi.org/10.1002/wcs.1555
De Deyne, S., Navarro, D. J., Collell, G., & Perfors, A. (2021). Visual and affective multimodal models of word meaning in language and mind. Cognitive Science, 45(1), e12922. https://doi.org/10.1111/cogs.12922
De Deyne, S., Navarro, D. J., Perfors, A., Brysbaert, M., & Storms, G. (2019). The Small World of Words English word association norms for over 12,000 cue words. Behavior Research Methods, 51, 987–1006. https://doi.org/10.3758/s13428-018-1115-7
De Deyne, S., Navarro, D. J., & Storms, G. (2013). Better explanations of lexical and semantic cognition using networks derived from continued rather than single-word associations. Behavior Research Methods, 45(2), 480–498. https://doi.org/10.3758/s13428-012-0260-7
De Deyne, S., Perfors, A., & Navarro, D. (2016). Predicting human similarity judgments with distributional models: The value of word associations. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 1861–1870.
de Koning, B. B., Wassenburg, S. I., Bos, L. T., & van der Schoot, M. (2017). Mental simulation of four visual object properties: Similarities and differences as assessed by the sentence–picture verification task. Journal of Cognitive Psychology, 29(4), 420–432. https://doi.org/10.1080/20445911.2017.1281283
de Wit, B., & Kinoshita, S. (2015). The masked semantic priming effect is task dependent: Reconsidering the automatic spreading activation process. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41(4), 1062–1075. https://doi.org/10.1037/xlm0000074
DeLuca, V., Rothman, J., Bialystok, E., & Pliatsikas, C. (2019). Redefining bilingualism as a spectrum of experiences that differentially affects brain structure and function. Proceedings of the National Academy of Sciences, 116(15), 7565–7574. https://doi.org/10.1073/pnas.1811513116
Diaz, M. T., Karimi, H., Troutman, S. B. W., Gertel, V. H., Cosgrove, A. L., & Zhang, H. (2021). Neural sensitivity to phonological characteristics is stable across the lifespan. NeuroImage, 225, 117511. https://doi.org/10.1016/j.neuroimage.2020.117511
Dijkstra, T., Wahl, A., Buytenhuijs, F., Halem, N. V., Al-Jibouri, Z., Korte, M. D., & Rekké, S. (2019). Multilink: A computational model for bilingual word recognition and word translation. Bilingualism: Language and Cognition, 22(4), 657–679. https://doi.org/10.1017/S1366728918000287
Dils, A. T., & Boroditsky, L. (2010). Visual motion aftereffect from understanding motion language. Proceedings of the National Academy of Sciences, 107(37), 16396–16400. https://doi.org/10.1073/pnas.1009438107
Diveica, V., Pexman, P. M., & Binney, R. J. (2022). Quantifying social semantics: An inclusive definition of socialness and ratings for 8388 English words. Behavior Research Methods. https://doi.org/10.3758/s13428-022-01810-x
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J. R. G., Gruber, B., Lafourcade, B., Leitão, P. J., Münkemüller, T., McClean, C., Osborne, P. E., Reineking, B., Schröder, B., Skidmore, A. K., Zurell, D., & Lautenbach, S. (2013). Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27–46. https://doi.org/10.1111/j.1600-0587.2012.07348.x
Dove, G. (2020). More than a scaffold: Language is a neuroenhancement. Cognitive Neuropsychology, 37(5-6), 288–311. https://doi.org/10.1080/02643294.2019.1637338
Duñabeitia, J. A., Avilés, A., Afonso, O., Scheepers, C., & Carreiras, M. (2009). Qualitative differences in the representation of abstract versus concrete words: Evidence from the visual-world paradigm. Cognition, 110(2), 284–292. https://doi.org/10.1016/j.cognition.2008.11.012
Faust, M. E., Balota, D. A., Spieler, D. H., & Ferraro, F. R. (1999). Individual differences in information-processing rate and amount: Implications for group differences in response latency. Psychological Bulletin, 125, 777–799. https://doi.org/10.1037/0033-2909.125.6.777
Fernandino, L., Binder, J. R., Desai, R. H., Pendl, S. L., Humphries, C. J., Gross, W. L., Conant, L. L., & Seidenberg, M. S. (2016). Concept representation reflects multimodal abstraction: A framework for embodied semantics. Cerebral Cortex, 26(5), 2018–2034. https://doi.org/10.1093/cercor/bhv020
Fernandino, L., Tong, J.-Q., Conant, L. L., Humphries, C. J., & Binder, J. R. (2022). Decoding the information structure underlying the neural representation of concepts. Proceedings of the National Academy of Sciences, 119(6). https://doi.org/10.1073/pnas.2108091119
Fetterman, A. K., Wilkowski, B. M., & Robinson, M. D. (2018). On feeling warm and being warm: Daily perceptions of physical warmth fluctuate with interpersonal warmth. Social Psychological and Personality Science, 9(5), 560–567. https://doi.org/10.1177/1948550617712032
Fillmore, C. J. (1975). An alternative to checklist theories of meaning. Annual Meeting of the Berkeley Linguistics Society, 1, 123–131.
Fleur, D. S., Flecken, M., Rommers, J., & Nieuwland, M. S. (2020). Definitely saw it coming? The dual nature of the pre-nominal prediction effect. Cognition, 204, 104335. https://doi.org/10.1016/j.cognition.2020.104335
Flores d’Arcais, G. B., Schreuder, R., & Glazenborg, G. (1985). Semantic activation during recognition of referential words. Psychological Research, 47(1), 39–49. https://doi.org/10.1007/BF00309217
Fox, J. (2016). Generalized linear models. In Applied regression analysis and generalized linear models (Third Edition, pp. 418–472). SAGE.
Frome, A., Corrado, G. S., Shlens, J., Bengio, S., Dean, J., Ranzato, M., & Mikolov, T. (2013). DeViSE: A deep visual-semantic embedding model. In C. J. Burges, L. Bottou, M. Welling, Z. Ghahramani, & K. Q. Weinberger (Eds.), Advances in neural information processing systems (Vol. 26). Curran Associates, Inc. https://proceedings.neurips.cc/paper/2013/file/7cce53cf90577442771720a370c3c723-Paper.pdf
Gagné, C. L., Spalding, T. L., & Nisbet, K. A. (2016). Processing English compounds: Investigating semantic transparency. SKASE Journal of Theoretical Linguistics, 13(2), 2–22. https://link.gale.com/apps/doc/A469757337/LitRC?u=anon~b6a332f4&xid=9960afc7
Gallese, V., & Lakoff, G. (2005). The Brain’s concepts: The role of the Sensory-motor system in conceptual knowledge. Cognitive Neuropsychology, 22(3-4), 455–479. https://doi.org/10.1080/02643290442000310
Garcea, F., Dombovy, M., & Mahon, B. Z. (2013). Preserved Tool Knowledge in the Context of Impaired Action Knowledge: Implications for Models of Semantic Memory. Frontiers in Human Neuroscience, 7, 120. https://doi.org/10.3389/fnhum.2013.00120
García, A. M., Hesse, E., Birba, A., Adolfi, F., Mikulan, E., Caro, M. M., Petroni, A., Bekinschtein, T. A., del Carmen García, M., Silva, W., Ciraolo, C., Vaucheret, E., Sedeño, L., & Ibáñez, A. (2020). Time to face language: Embodied mechanisms underpin the inception of face-related meanings in the human brain. Cerebral Cortex, 30(11), 6051–6068. https://doi.org/10.1093/cercor/bhaa178
Gelman, A., & Carlin, J. (2014). Beyond power calculations: Assessing type S (sign) and type M (magnitude) errors. Perspectives on Psychological Science, 9(6), 641–651. https://doi.org/10.1177/1745691614551642
Gelman, A., Meng, X., & Stern, H. (1996). Posterior predictive assessment of model fitness via realized discrepancies. Statistica Sinica, 733–807.
Gilbert, D. T., King, G., Pettigrew, S., & Wilson, T. D. (2016). Comment on Estimating the reproducibility of psychological science.” Science, 351(6277), 1037–1037. https://doi.org/10.1126/science.aad7243
Green, P., & MacLeod, C. J. (2016). SIMR: An R package for power analysis of generalized linear mixed models by simulation. Methods in Ecology and Evolution, 7(4), 493–498. https://doi.org/10.1111/2041-210X.12504
Günther, F., Dudschig, C., & Kaup, B. (2015). LSAfun: An r package for computations based on latent semantic analysis. Behavior Research Methods, 47(4), 930–944. https://doi.org/10.3758/s13428-014-0529-0
Günther, F., Dudschig, C., & Kaup, B. (2016a). Latent semantic analysis cosines as a cognitive similarity measure: Evidence from priming studies. Quarterly Journal of Experimental Psychology, 69(4), 626–653. https://doi.org/10.1080/17470218.2015.1038280
Günther, F., Dudschig, C., & Kaup, B. (2016b). Predicting lexical priming effects from distributional semantic similarities: A replication with extension. Frontiers in Psychology, 7, 1646. https://doi.org/10.3389/fpsyg.2016.01646
Günther, F., Dudschig, C., & Kaup, B. (2018). Symbol grounding without direct experience: Do words inherit sensorimotor activation from purely linguistic context? Cognitive Science, 42(S2), 336–374. https://doi.org/10.1111/cogs.12549
Günther, F., Press, S. A., Dudschig, C., & Kaup, B. (2021). The limits of automatic sensorimotor processing during word processing: Investigations with repeated linguistic experience, memory consolidation during sleep, and rich linguistic learning contexts. Psychological Research. https://doi.org/10.1007/s00426-021-01620-4
Hagoort, P. (2017). The core and beyond in the language-ready brain. Neuroscience & Biobehavioral Reviews, 81, 194–204. https://doi.org/10.1016/j.neubiorev.2017.01.048
Hald, L. A., Bastiaansen, M. C. M., & Hagoort, P. (2006). EEG theta and gamma responses to semantic violations in online sentence processing. Brain and Language, 96(1), 90–105. https://doi.org/10.1016/j.bandl.2005.06.007
Hald, L. A., Hocking, I., Vernon, D., Marshall, J. A., & Garnham, A. (2013). Exploring modality switching effects in negated sentences: Further evidence for grounded representations. Frontiers in Psychology, 4, 93. https://doi.org/10.3389/fpsyg.2013.00093
Hald, L. A., Marshall, J. A., Janssen, D. P., & Garnham, A. (2011). Switching modalities in a sentence verification task: ERP evidence for embodied language processing. Frontiers in Psychology, 2, 45. https://doi.org/10.3389/fpsyg.2011.00045
Harnad, S. (1990). The symbol grounding problem. Physica D: Nonlinear Phenomena, 42(1), 335–346. https://doi.org/10.1016/0167-2789(90)90087-6
Harrison, X. A., Donaldson, L., Correa-Cano, M. E., Evans, J., Fisher, D. N., Goodwin, C., Robinson, B. S., Hodgson, D. J., & Inger, R. (2018). A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ, 6, 4794. https://doi.org/10.7717/peerj.4794
Hauk, O. (2016). Only time will tell – why temporal information is essential for our neuroscientific understanding of semantics. Psychonomic Bulletin & Review, 23(4), 1072–1079. https://doi.org/10.3758/s13423-015-0873-9
Hedge, C., Powell, G., & Sumner, P. (2018). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods, 50(3), 1166–1186. https://doi.org/10.3758/s13428-017-0935-1
Heyman, T., Bruninx, A., Hutchison, K. A., & Storms, G. (2018). The (un)reliability of item-level semantic priming effects. Behavior Research Methods, 50(6), 2173–2183. https://doi.org/10.3758/s13428-018-1040-9
Hickok, G. (2014). The myth of mirror neurons: The real neuroscience of communication and cognition (p. 292). W W Norton & Co.
Hoedemaker, R. S., & Gordon, P. C. (2014). It takes time to prime: Semantic priming in the ocular lexical decision task. Journal of Experimental Psychology: Human Perception and Performance, 40(6), 2179–2197. https://doi.org/10.1037/a0037677
Hoenig, J. M., & Heisey, D. M. (2001). The Abuse of Power. The American Statistician, 55(1), 19–24. https://doi.org/10.1198/000313001300339897
Hoffman, P., & Lambon Ralph, M. A. (2011). Reverse concreteness effects are not a typical feature of semantic dementia: Evidence for the hub-and-spoke model of conceptual representation. Cerebral Cortex, 21(9), 2103–2112. https://doi.org/10.1093/cercor/bhq288
Holt, L. E., & Beilock, S. L. (2006). Expertise and its embodiment: Examining the impact of sensorimotor skill expertise on the representation of action-related text. Psychonomic Bulletin & Review, 13(4), 694–701. https://doi.org/10.3758/BF03193983
Hultén, A., Vliet, M. van, Kivisaari, S., Lammi, L., Lindh-Knuutila, T., Faisal, A., & Salmelin, R. (2021). The neural representation of abstract words may arise through grounding word meaning in language itself. Human Brain Mapping, 42(15), 4973–4984. https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.25593
Hutchinson, S., & Louwerse, M. M. (2013). Language statistics and individual differences in processing primary metaphors. Cognitive Linguistics, 24(4), 667–687. https://doi.org/10.1515/cog-2013-0023
Hutchison, K. A. (2003). Is semantic priming due to association strength or feature overlap? A microanalytic review. Psychonomic Bulletin & Review, 10(4), 785–813. https://doi.org/10.3758/BF03196544
Hutchison, K. A., Balota, D. A., Cortese, M. J., & Watson, J. M. (2008). Predicting semantic priming at the item level. Quarterly Journal of Experimental Psychology, 61(7), 1036–1066. https://doi.org/10.1080/17470210701438111
Hutchison, K. A., Balota, D. A., Neely, J. H., Cortese, M. J., Cohen-Shikora, E. R., Tse, C.-S., Yap, M. J., Bengson, J. J., Niemeyer, D., & Buchanan, E. (2013). The semantic priming project. Behavior Research Methods, 45, 1099–1114. https://doi.org/10.3758/s13428-012-0304-z
Hutchison, K. A., Heap, S. J., Neely, J. H., & Thomas, M. A. (2014). Attentional control and asymmetric associative priming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(3), 844–856. https://doi.org/10.1037/a0035781
James, A. N., Fraundorf, S. H., Lee, E. K., & Watson, D. G. (2018). Individual differences in syntactic processing: Is there evidence for reader-text interactions? Journal of Memory and Language, 102, 155–181. https://doi.org/10.1016/j.jml.2018.05.006
Jared, D., & O’Donnell, K. (2017). Skilled adult readers activate the meanings of high-frequency words using phonology: Evidence from eye tracking. Memory & Cognition, 45(2), 334–346. https://doi.org/10.3758/s13421-016-0661-4
Jones, C. R., Chang, T. A., Coulson, S., Michaelov, J. A., Trott, S., & Bergen, B. (2022). Distrubutional semantics still can’t account for affordances. Proceedings of the Annual Meeting of the Cognitive Science Society, 44(44). https://escholarship.org/uc/item/44z7r3j3
Jones, M. N., Kintsch, W., & Mewhort, D. J. (2006). High-dimensional semantic space accounts of priming. Journal of Memory and Language, 55(4), 534–552. https://doi.org/10.1016/j.jml.2006.07.003
Joordens, S., & Becker, S. (1997). The long and short of semantic priming effects in lexical decision. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(5), 1083–1105. https://doi.org/10.1037/0278-7393.23.5.1083
Jung, M., Mody, M., Fujioka, T., Kimura, Y., Okazawa, H., & Kosaka, H. (2019). Sex differences in white matter pathways related to language ability. Frontiers in Human Neuroscience, 13, 898. https://doi.org/10.3389/fnins.2019.00898
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
Khatin-Zadeh, O., Eskandari, Z., Cervera-Torres, S., Ruiz Fernández, S., Farzi, R., & Marmolejo-Ramos, F. (2021). The strong versions of embodied cognition: Three challenges faced. Psychology & Neuroscience, 14(1), 16–33. https://doi.org/10.1037/pne0000252
Kiefer, M., Pielke, L., & Trumpp, N. M. (2022). Differential temporo-spatial pattern of electrical brain activity during the processing of abstract concepts related to mental states and verbal associations. NeuroImage, 252, 119036. https://doi.org/10.1016/j.neuroimage.2022.119036
Kiela, D., & Bottou, L. (2014). Learning image embeddings using convolutional neural networks for improved multi-modal semantics. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP, 36–45. https://doi.org/10.3115/v1/D14-1005
Kim, M., Crossley, S. A., & Skalicky, S. (2018). Effects of lexical features, textual properties, and individual differences on word processing times during second language reading comprehension. Reading and Writing, 31(5), 1155–1180. https://doi.org/10.1007/s11145-018-9833-x
Knief, U., & Forstmeier, W. (2021). Violating the normality assumption may be the lesser of two evils. Behavior Research Methods. https://doi.org/10.3758/s13428-021-01587-5
Koller, M. (2016). robustlmm: An R package for robust estimation of linear mixed-effects models. Journal of Statistical Software, 75(6), 1–24. https://doi.org/10.18637/jss.v075.i06
Kos, M., Van den Brink, D., & Hagoort, P. (2012). Individual variation in the late positive complex to semantic anomalies. Frontiers in Psychology, 3(318). https://doi.org/10.3389/fpsyg.2012.00318
Koster, D., Cadierno, T., & Chiarandini, M. (2018). Mental simulation of object orientation and size: A conceptual replication with second language learners. Journal of the European Second Language Association, 2(1), 38. https://doi.org/10.22599/jesla.39
Kousta, S.-T., Vigliocco, G., Vinson, D. P., Andrews, M., & Del Campo, E. (2011). The representation of abstract words: Why emotion matters. Journal of Experimental Psychology: General, 140, 14–34. https://doi.org/10.1037/a0021446
Kruschke, J. K., & Liddell, T. M. (2018). The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychonomic Bulletin & Review, 25(1), 178–206. https://doi.org/10.3758/s13423-016-1221-4
Kuhnke, P., Kiefer, M., & Hartwigsen, G. (2021). Task-dependent functional and effective connectivity during conceptual processing. Cerebral Cortex, 31(7), 3475–3493. https://doi.org/10.1093/cercor/bhab026
Kumar, A. A. (2021). Semantic memory: A review of methods, models, and current challenges. Psychonomic Bulletin & Review, 28(1), 40–80. https://doi.org/10.3758/s13423-020-01792-x
Kumar, A. A., Balota, D. A., & Steyvers, M. (2020). Distant connectivity and multiple-step priming in large-scale semantic networks. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46(12), 2261–2276. https://doi.org/10.1037/xlm0000793
Kumle, L., Võ, M. L.-H., & Draschkow, D. (2021). Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R. Behavior Research Methods. https://doi.org/10.3758/s13428-021-01546-0
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. https://doi.org/10.18637/jss.v082.i13
Lam, K. J., Dijkstra, T., & Rueschemeyer, S. A. (2015). Feature activation during word recognition: Action, visual, and associative-semantic priming effects. Frontiers in Psychology, 6, 659. https://doi.org/10.3389/fpsyg.2015.00659
Lamiell, J. T. (2019). Statistical thinking in psychology: Some needed critical perspective on what “everyone knows.” In J. T. Lamiell (Ed.), Psychology’s Misuse of Statistics and Persistent Dismissal of its Critics (pp. 99–121). Springer International Publishing. https://doi.org/10.1007/978-3-030-12131-0_5
Landauer, T. K., Foltz, P. W., & Laham, D. (1998). An introduction to latent semantic analysis. Discourse Processes, 25(2-3), 259–284. https://doi.org/10.1080/01638539809545028
Lebois, L. A. M., Wilson-Mendenhall, C. D., & Barsalou, L. W. (2015). Are automatic conceptual cores the gold standard of semantic processing? The context-dependence of spatial meaning in grounded congruency effects. Cognitive Science, 39(8), 1764–1801. https://doi.org/10.1111/cogs.12174
Lee, M. D., & Wagenmakers, E.-J. (2014). Bayesian cognitive modeling: A practical course. Cambridge University Press. https://doi.org/10.1017/CBO9781139087759
Lerche, V., von Krause, M., Voss, A., Frischkorn, G. T., Schubert, A.-L., & Hagemann, D. (2020). Diffusion modeling and intelligence: Drift rates show both domain-general and domain-specific relations with intelligence. Journal of Experimental Psychology: General, 149(12), 2207–2249. https://doi.org/10.1037/xge0000774
Lewandowski, D., Kurowicka, D., & Joe, H. (2009). Generating random correlation matrices based on vines and extended onion method. Journal of Multivariate Analysis, 100(9), 1989–2001. https://doi.org/10.1016/j.jmva.2009.04.008
Lievers, F. S., Bolognesi, M., & Winter, B. (2021). The linguistic dimensions of concrete and abstract concepts: Lexical category, morphological structure, countability, and etymology. Cognitive Linguistics, 32(4), 641–670. https://doi.org/10.1515/cog-2021-0007
Lim, R. Y., Yap, M. J., & Tse, C.-S. (2020). Individual differences in Cantonese Chinese word recognition: Insights from the Chinese Lexicon Project. Quarterly Journal of Experimental Psychology, 73(4), 504–518. https://doi.org/10.1177/1747021820906566
Lo, S., & Andrews, S. (2015). To transform or not to transform: Using generalized linear mixed models to analyse reaction time data. Frontiers in Psychology, 6, 1171. https://doi.org/10.3389/fpsyg.2015.01171
Loftus, E. F. (1975). Spreading activation within semantic categories: Comments on Rosch’s "Cognitive representation of semantic categories.". Journal of Experimental Psychology: General, 104, 234–240. https://doi.org/10.1037/0096-3445.104.3.234
Loken, E., & Gelman, A. (2017). Measurement error and the replication crisis. Science, 355(6325), 584–585. https://doi.org/10.1126/science.aal3618
Louwerse, M. M. (2011). Symbol interdependency in symbolic and embodied cognition. Topics in Cognitive Science, 3(2), 273–302. https://doi.org/10.1111/j.1756-8765.2010.01106.x
Louwerse, M. M., & Connell, L. (2011). A taste of words: Linguistic context and perceptual simulation predict the modality of words. Cognitive Science, 35(2), 381–398. https://doi.org/10.1111/j.1551-6709.2010.01157.x
Louwerse, M. M., & Hutchinson, S. (2012). Neurological evidence linguistic processes precede perceptual simulation in conceptual processing. Frontiers in Psychology, 3, 385. https://doi.org/10.3389/fpsyg.2012.00385
Louwerse, M. M., Hutchinson, S., Tillman, R., & Recchia, G. (2015). Effect size matters: The role of language statistics and perceptual simulation in conceptual processing. Language, Cognition and Neuroscience, 30(4), 430–447. https://doi.org/10.1080/23273798.2014.981552
Louwerse, M. M., & Zwaan, R. A. (2009). Language encodes geographical information. Cognitive Science, 33(1), 51–73. https://doi.org/10.1111/j.1551-6709.2008.01003.x
Lüdecke, D. (2021). sjPlot: Data visualization for statistics in social science. https://CRAN.R-project.org/package=sjPlot
Luke, S. G. (2017). Evaluating significance in linear mixed-effects models in R. Behavior Research Methods, 49(4), 1494–1502. https://doi.org/10.3758/s13428-016-0809-y
Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28(2), 203–208. https://doi.org/10.3758/BF03204766
Lund, K., Burgess, C., & Atchley, R. A. (1995). Semantic and associative priming in high-dimensional semantic space. Proceedings of the Cognitive Science Society, 660–665.
Lynott, D., & Connell, L. (2009). Modality exclusivity norms for 423 object properties. Behavior Research Methods, 41(2), 558–564. https://doi.org/10.3758/BRM.41.2.558
Lynott, D., Connell, L., Brysbaert, M., Brand, J., & Carney, J. (2020). The Lancaster Sensorimotor Norms: Multidimensional measures of perceptual and action strength for 40,000 English words. Behavior Research Methods, 52, 1271–1291. https://doi.org/10.3758/s13428-019-01316-z
Lynott, D., Corker, K. S., Wortman, J., Connell, L., Donnellan, M. B., Lucas, R. E., & O’Brien, K. (2014). Replication of Experiencing physical warmth promotes interpersonal warmth” by Williams and Bargh (2008). Social Psychology, 45(3), 216–222. https://doi.org/10.1027/1864-9335/a000187
Mahon, B. Z., & Caramazza, A. (2008). A critical look at the embodied cognition hypothesis and a new proposal for grounding conceptual content. Journal of Physiology-Paris, 102(1), 59–70. https://doi.org/10.1016/j.jphysparis.2008.03.004
Mahon, B. Z., & Hickok, G. (2016). Arguments about the nature of concepts: Symbols, embodiment, and beyond. Psychonomic Bulletin & Review, 23(4), 941–958. https://doi.org/10.3758/s13423-016-1045-2
Majid, A., & Burenhult, N. (2014). Odors are expressible in language, as long as you speak the right language. Cognition, 130(2), 266–270. https://doi.org/10.1016/j.cognition.2013.11.004
Majid, A., & Levinson, S. C. (2011). The senses in language and culture. The Senses and Society, 6(1), 5–18. https://doi.org/10.2752/174589311X12893982233551
Majid, A., & van Staden, M. (2015). Can nomenclature for the body be explained by embodiment theories? Topics in Cognitive Science, 7(4), 570–594. https://doi.org/10.1111/tops.12159
Mak, M., & Willems, R. M. (2019). Mental simulation during literary reading: Individual differences revealed with eye-tracking. Language, Cognition and Neuroscience, 34(4), 511–535. https://doi.org/10.1080/23273798.2018.1552007
Mandera, P., Keuleers, E., & Brysbaert, M. (2017). Explaining human performance in psycholinguistic tasks with models of semantic similarity based on prediction and counting: A review and empirical validation. Journal of Memory and Language, 92, 57–78. https://doi.org/10.1016/j.jml.2016.04.001
Marek, S., Tervo-Clemmens, B., Calabro, F. J., Montez, D. F., Kay, B. P., Hatoum, A. S., Donohue, M. R., Foran, W., Miller, R. L., Hendrickson, T. J., Malone, S. M., Kandala, S., Feczko, E., Miranda-Dominguez, O., Graham, A. M., Earl, E. A., Perrone, A. J., Cordova, M., Doyle, O., … Dosenbach, N. U. F. (2022). Reproducible brain-wide association studies require thousands of individuals. Nature, 1–7. https://doi.org/10.1038/s41586-022-04492-9
Matuschek, H., Kliegl, R., Vasishth, S., Baayen, H., & Bates, D. (2017). Balancing Type I error and power in linear mixed models. Journal of Memory and Language, 94, 305–315. https://doi.org/10.1016/j.jml.2017.01.001
Matzke, D., & Wagenmakers, E.-J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: A diffusion model analysis. Psychonomic Bulletin & Review, 16(5), 798–817. https://doi.org/10.3758/PBR.16.5.798
McDonald, S., & Brew, C. (2002). A distributional model of semantic context effects in lexical processing. Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, 17–24. http://dblp.uni-trier.de/db/conf/acl/acl2004.html#McDonaldB04
Mendes, P. S., & Undorf, M. (2021). On the pervasive effect of word frequency in metamemory. Quarterly Journal of Experimental Psychology, 17470218211053329. https://doi.org/10.1177/17470218211053329
Miceli, A., Wauthia, E., Lefebvre, L., Ris, L., & Simoes Loureiro, I. (2021). Perceptual and interoceptive strength norms for 270 french words. Frontiers in Psychology, 12. https://www.frontiersin.org/article/10.3389/fpsyg.2021.667271
Miceli, A., Wauthia, E., Lefebvre, L., Vallet, G. T., Ris, L., & Loureiro, I. S. (2022). Differences related to aging in sensorimotor knowledge: Investigation of perceptual strength and body object interaction. Archives of Gerontology and Geriatrics, 102, 104715. https://doi.org/10.1016/j.archger.2022.104715
Michaelov, J. A., Coulson, S., & Bergen, B. K. (2022). So cloze yet so far: N400 amplitude is better predicted by distributional information than human predictability judgements. IEEE Transactions on Cognitive and Developmental Systems, 1–1. https://doi.org/10.1109/TCDS.2022.3176783
Michel, C. (2021). Overcoming the modal/amodal dichotomy of concepts. Phenomenology and the Cognitive Sciences, 20(4), 655–677. https://doi.org/10.1007/s11097-020-09678-y
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space (Version 3). arXiv. https://doi.org/10.48550/arXiv.1301.3781
Milek, A., Butler, E. A., Tackman, A. M., Kaplan, D. M., Raison, C. L., Sbarra, D. A., Vazire, S., & Mehl, M. R. (2018). Eavesdropping on happiness” revisited: A pooled, multisample replication of the association between life satisfaction and observed daily conversation quantity and quality. Psychological Science, 29(9), 1451–1462. https://doi.org/10.1177/0956797618774252
Milton, F., Fulford, J., Dance, C., Gaddum, J., Heuerman-Williamson, B., Jones, K., Knight, K. F., MacKisack, M., Winlove, C., & Zeman, A. (2021). Behavioral and neural signatures of visual imagery vividness extremes: Aphantasia versus hyperphantasia. Cerebral Cortex Communications, 2(2), 035. https://doi.org/10.1093/texcom/tgab035
Montero-Melis, G. (2021). Consistency in motion event encoding across languages. Frontiers in Psychology, 12(625153). https://doi.org/10.3389/fpsyg.2021.625153
Montero-Melis, G., Eisenbeiss, S., Narasimhan, B., Ibarretxe-Antuñano, I., Kita, S., Kopecka, A., Lüpke, F., Nikitina, T., Tragel, I., Jaeger, T. F., & Bohnemeyer, J. (2017). Satellite- vs. Verb-framing underpredicts nonverbal motion categorization: Insights from a large language sample and simulations. Cognitive Semantics, 3(1), 36–61. https://doi.org/10.1163/23526416-00301002
Montero-Melis, G., van Paridon, J., Ostarek, M., & Bylund, E. (2022). No evidence for embodiment: The motor system is not needed to keep action verbs in working memory. Cortex, 150, 108–125. https://doi.org/10.1016/j.cortex.2022.02.006
Moran, G. E., Cunningham, J. P., & Blei, D. M. (2022). The posterior predictive null. Bayesian Analysis, 1(1). https://doi.org/10.1214/22-BA1313
Morey, R. D., Kaschak, M. P., Díez-Álamo, A. M., Glenberg, A. M., Zwaan, R. A., Lakens, D., Ibáñez, A., García, A., Gianelli, C., Jones, J. L., Madden, J., Alifano, F., Bergen, B., Bloxsom, N. G., Bub, D. N., Cai, Z. G., Chartier, C. R., Chatterjee, A., Conwell, E., … Ziv-Crispel, N. (2022). A pre-registered, multi-lab non-replication of the action-sentence compatibility effect (ACE). Psychonomic Bulletin & Review, 29(2), 613–626. https://doi.org/10.3758/s13423-021-01927-8
Morucci, P., Bottini, R., & Crepaldi, D. (2019). Augmented modality exclusivity norms for concrete and abstract Italian property words. Journal of Cognition, 2(1), 42. https://doi.org/10.5334/joc.88
Muraki, 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. https://doi.org/10.1037/xlm0001039
Nakagawa, S., Johnson, P. C. D., & Schielzeth, H. (2017). The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. Journal of The Royal Society Interface, 14(134), 20170213. https://doi.org/10.1098/rsif.2017.0213
Negri, G. A. L., Rumiati, R. I., Zadini, A., Ukmar, M., Mahon, B. Z., & Caramazza, A. (2007). What is the role of motor simulation in action and object recognition? Evidence from apraxia. Cognitive Neuropsychology, 24(8), 795–816. https://doi.org/10.1080/02643290701707412
Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (2004). The University of South Florida free association, rhyme, and word fragment norms. Behavior Research Methods, Instruments, & Computers, 36(3), 402–407. https://doi.org/10.3758/BF03195588
Newcombe, P., Campbell, C., Siakaluk, P., & Pexman, P. (2012). Effects of emotional and sensorimotor knowledge in semantic processing of concrete and abstract nouns. Frontiers in Human Neuroscience, 6(275). https://doi.org/10.3389/fnhum.2012.00275
Newman, J. (2002). A cross-linguistic overview of the posture verbs “sit,” “stand,” and “lie.” In J. Newman (Ed.), Typological Studies in Language (Vol. 51, pp. 1–24). John Benjamins Publishing Company. https://doi.org/10.1075/tsl.51.02new
Noah, T., Schul, Y., & Mayo, R. (2018). When both the original study and its failed replication are correct: Feeling observed eliminates the facial-feedback effect. Journal of Personality and Social Psychology, 114, 657–664. https://doi.org/10.1037/pspa0000121
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716. https://doi.org/10.1126/science.aac4716
Ostarek, M., & Bottini, R. (2021). Towards strong inference in research on embodiment – Possibilities and limitations of causal paradigms. Journal of Cognition, 4(1), 5. https://doi.org/10.5334/joc.139
Ostarek, M., & Huettig, F. (2017). A task-dependent causal role for low-level visual processes in spoken word comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(8), 1215–1224. https://doi.org/10.1037/xlm0000375
Ostarek, M., & Huettig, F. (2019). Six challenges for embodiment research. Current Directions in Psychological Science, 28(6), 593–599. https://doi.org/10.1177/0963721419866441
Pacini, A. M., & Barnard, P. J. (2021). Exocentric coding of the mapping between valence and regions of space: Implications for embodied cognition. Acta Psychologica, 214, 103264. https://doi.org/10.1016/j.actpsy.2021.103264
Padó, S., & Lapata, M. (2007). Dependency-based construction of semantic space models. Computational Linguistics, 33(2), 161–199. https://doi.org/10.1162/coli.2007.33.2.161
Paivio, A. (1990). Mental representations: A dual coding approach. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195066661.001.0001
Papeo, L., Negri, G. A. L., Zadini, A., & Ida Rumiati, R. (2010). Action performance and action-word understanding: Evidence of double dissociations in left-damaged patients. Cognitive Neuropsychology, 27(5), 428–461. https://doi.org/10.1080/02643294.2011.570326
Pearson, J., & Kosslyn, S. M. (2015). The heterogeneity of mental representation: Ending the imagery debate. Proceedings of the National Academy of Sciences, 112(33), 10089–10092. https://doi.org/10.1073/pnas.1504933112
Pecher, D., Zeelenberg, R., & Barsalou, L. W. (2003). Verifying different-modality properties for concepts produces switching costs. Psychological Science, 14(2), 119–124. https://doi.org/10.1111/1467-9280.t01-1-01429
Pecher, D., Zeelenberg, R., & Raaijmakers, J. G. W. (1998). Does pizza prime coin? Perceptual priming in lexical decision and pronunciation. Journal of Memory and Language, 38(4), 401–418. https://doi.org/10.1006/jmla.1997.2557
Perfetti, C. A., & Hart, L. (2002). The lexical quality hypothesis. In L. Verhoeven, C. Elbro, & P. Reitsma (Eds.), Studies in Written Language and Literacy (Vol. 11, pp. 189–213). John Benjamins Publishing Company. https://doi.org/10.1075/swll.11.14per
Perret, C., & Bonin, P. (2019). Which variables should be controlled for to investigate picture naming in adults? A Bayesian meta-analysis. Behavior Research Methods, 51(6), 2533–2545. https://doi.org/10.3758/s13428-018-1100-1
Petilli, M. A., Günther, F., Vergallito, A., Ciapparelli, M., & Marelli, M. (2021). Data-driven computational models reveal perceptual simulation in word processing. Journal of Memory and Language, 117, 104194. https://doi.org/10.1016/j.jml.2020.104194
Pexman, P. M., Heard, A., Lloyd, E., & Yap, M. J. (2017). The Calgary semantic decision project: Concrete/abstract decision data for 10,000 English words. Behavior Research Methods, 49(2), 407–417. https://doi.org/10.3758/s13428-016-0720-6
Pexman, P. M., & Yap, M. J. (2018). Individual differences in semantic processing: Insights from the Calgary semantic decision project. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(7), 1091–1112. https://doi.org/10.1037/xlm0000499
Planchuelo, C., Buades-Sitjar, F., Hinojosa, J. A., & Duñabeitia, J. A. (2022). The Nature of Word Associations in Sentence Contexts. Experimental Psychology. https://doi.org/10.1027/1618-3169/a000547
Plaut, D. C., & Booth, J. R. (2000). Individual and developmental differences in semantic priming: Empirical and computational support for a single-mechanism account of lexical processing. Psychological Review, 107(4), 786–823. https://doi.org/10.1037/0033-295X.107.4.786
Ponari, M., Norbury, C. F., Rotaru, A., Lenci, A., & Vigliocco, G. (2018). Learning abstract words and concepts: Insights from developmental language disorder. Philosophical Transactions of the Royal Society B: Biological Sciences, 373, 20170140. https://doi.org/10.1098/rstb.2017.0140
Ponari, M., Norbury, C. F., & Vigliocco, G. (2018). Acquisition of abstract concepts is influenced by emotional valence. Developmental Science, 21(2), 12549. https://doi.org/10.1111/desc.12549
Ponari, M., Norbury, C. F., & Vigliocco, G. (2020). The role of emotional valence in learning novel abstract concepts. Developmental Psychology, 56(10), 1855–1865. https://doi.org/10.1037/dev0001091
Pregla, D., Lissón, P., Vasishth, S., Burchert, F., & Stadie, N. (2021). Variability in sentence comprehension in aphasia in German. Brain and Language, 222, 105008. https://doi.org/10.1016/j.bandl.2021.105008
Pulvermüller, F. (1999). Words in the brain’s language. Behavioral and Brain Sciences, 22, 253–336. https://doi.org/10.1017/S0140525X9900182X
Pulvermüller, F. (2013). How neurons make meaning: Brain mechanisms for embodied and abstract-symbolic semantics. Trends in Cognitive Sciences, 17(9), 458–470. https://doi.org/10.1016/j.tics.2013.06.004
Pylyshyn, Z. W. (1973). What the mind’s eye tells the mind’s brain: A critique of mental imagery. Psychological Bulletin, 80(1), 1–24. https://doi.org/10.1037/h0034650
R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Ratcliff, R., Thapar, A., & McKoon, G. (2010). Individual differences, aging, and IQ in two-choice tasks. Cognitive Psychology, 60, 127–157. https://doi.org/10.1016/j.cogpsych.2009.09.001
Reggin, L. D., Muraki, E. J., & Pexman, P. M. (2021). Development of abstract word knowledge. Frontiers in Psychology, 12, 2115. https://doi.org/10.3389/fpsyg.2021.686478
Reilly, J., Flurie, M., & Peelle, J. E. (2020). The English lexicon mirrors functional brain activation for a sensory hierarchy dominated by vision and audition: Point-counterpoint. Journal of Neurolinguistics, 55, 100895. https://doi.org/10.1016/j.jneuroling.2020.100895
Riccardi, N., Yourganov, G., Rorden, C., Fridriksson, J., & Desai, R. H. (2019). Dissociating action and abstract verb comprehension post-stroke. Cortex, 120, 131–146. https://doi.org/10.1016/j.cortex.2019.05.013
Roads, B. D., & Love, B. C. (2020). Learning as the unsupervised alignment of conceptual systems. Nature Machine Intelligence, 2(1, 1), 76–82. https://doi.org/10.1038/s42256-019-0132-2
Rodríguez-Ferreiro, J., Aguilera, M., & Davies, R. (2020). Semantic priming and schizotypal personality: Reassessing the link between thought disorder and enhanced spreading of semantic activation. PeerJ, 8, e9511. https://doi.org/10.7717/peerj.9511
Rommers, J., Meyer, A. S., & Huettig, F. (2013). Object shape and orientation do not routinely influence performance during language processing. Psychological Science, 24(11), 2218–2225. https://doi.org/10.1177/0956797613490746
Roque, L. S., Kendrick, K. H., Norcliffe, E., Brown, P., Defina, R., Dingemanse, M., Dirksmeyer, T., Enfield, N. J., Floyd, S., Hammond, J., Rossi, G., Tufvesson, S., Putten, S. van, & Majid, A. (2015). Vision verbs dominate in conversation across cultures, but the ranking of non-visual verbs varies. Cognitive Linguistics, 26(1), 31–60. https://doi.org/10.1515/cog-2014-0089
Rosch, E. (1975a). Cognitive representations of semantic categories. Journal of Experimental Psychology: General, 104, 192–233. https://doi.org/10.1037/0096-3445.104.3.192
Rosch, E. (1975b). Reply to Loftus. Journal of Experimental Psychology: General, 104, 241–243. https://doi.org/10.1037/0096-3445.104.3.241
Rouder, J. N., & Haaf, J. M. (2019). A psychometrics of individual differences in experimental tasks. Psychonomic Bulletin & Review, 26(2), 452–467. https://doi.org/10.3758/s13423-018-1558-y
Rouder, J. N., Haaf, J. M., & Vandekerckhove, J. (2018). Bayesian inference for psychology, part IV: Parameter estimation and Bayes factors. Psychonomic Bulletin & Review, 25(1), 102–113. https://doi.org/10.3758/s13423-017-1420-7
Santos, A., Chaigneau, S. E., Simmons, W. K., & Barsalou, L. W. (2011). Property generation reflects word association and situated simulation. Language and Cognition, 3(1), 83–119. https://doi.org/10.1515/langcog.2011.004
Sassenhagen, J., & Alday, P. M. (2016). A common misapplication of statistical inference: Nuisance control with null-hypothesis significance tests. Brain and Language, 162, 42–45. https://doi.org/10.1016/j.bandl.2016.08.001
Sato, M., Mengarelli, M., Riggio, L., Gallese, V., & Buccino, G. (2008). Task related modulation of the motor system during language processing. Brain and Language, 105(2), 83–90. https://doi.org/10.1016/j.bandl.2007.10.001
Schielzeth, H., Dingemanse, N. J., Nakagawa, S., Westneat, D. F., Allegue, H., Teplitsky, C., Réale, D., Dochtermann, N. A., Garamszegi, L. Z., & Araya‐Ajoy, Y. G. (2020). Robustness of linear mixed‐effects models to violations of distributional assumptions. Methods in Ecology and Evolution, 11(9), 1141–1152. https://doi.org/10.1111/2041-210X.13434
Schloerke, B., Cook, D., Larmarange, J., Briatte, F., Marbach, M., Thoen, E., Elberg, A., & Crowley, J. (2021). GGally: Extension to ’ggplot2’. https://CRAN.R-project.org/package=GGally
Schmalz, X., Biurrun Manresa, J., & Zhang, L. (2021). What is a Bayes factor? Psychological Methods. https://doi.org/10.1037/met0000421
Schmidtke, D., Van Dyke, J. A., & Kuperman, V. (2018). Individual variability in the semantic processing of English compound words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(3), 421–439. https://doi.org/10.1037/xlm0000442
Schoot, R. van de, Depaoli, S., Gelman, A., King, R., Kramer, B., Märtens, K., Tadesse, M. G., Vannucci, M., Willemsen, J., & Yau, C. (2021). Bayesian statistics and modelling. Nature Reviews Methods Primers, 1, 3. https://doi.org/10.1038/s43586-020-00003-0
Schreuder, R., Flores d’Arcais, G. B., & Glazenborg, G. (1984). Effects of perceptual and conceptual similarity in semantic priming. Psychological Research, 45(4), 339–354. https://doi.org/10.1007/BF00309710
Shebani, Z., Nestor, P. J., & Pulvermüller, F. (2021). What’s “up”? Impaired spatial preposition processing in posterior cortical atrophy. Frontiers in Human Neuroscience, 15, 718. https://doi.org/10.3389/fnhum.2021.731104
Shebani, Z., & Pulvermüller, F. (2018). Flexibility in Language Action Interaction: The Influence of Movement Type. Frontiers in Human Neuroscience, 12. https://www.frontiersin.org/article/10.3389/fnhum.2018.00252
Simmons, W. K., Hamann, S. B., Harenski, C. L., Hu, X. P., & Barsalou, L. W. (2008). fMRI evidence for word association and situated simulation in conceptual processing. Journal of Physiology-Paris, 102(1), 106–119. https://doi.org/10.1016/j.jphysparis.2008.03.014
Simmons, W. K., Ramjee, V., Beauchamp, M. S., McRae, K., Martin, A., & Barsalou, L. W. (2007). A common neural substrate for perceiving and knowing about color. Neuropsychologia, 45(12), 2802–2810. https://doi.org/10.1016/j.neuropsychologia.2007.05.002
Singmann, H., Bolker, B., Westfall, J., Aust, F., & Ben-Shachar, M. S. (2021). afex: Analysis of factorial experiments. https://CRAN.R-project.org/package=afex
Singmann, H., & Kellen, D. (2019). An introduction to mixed models for experimental psychology. In D. H. Spieler & E. Schumacher (Eds.), New methods in cognitive psychology (pp. 4–31). Psychology Press.
Skeide, M. A., & Friederici, A. D. (2016). The ontogeny of the cortical language network. Nature Reviews Neuroscience, 17(5, 5), 323–332. https://doi.org/10.1038/nrn.2016.23
Sleegers, W. W. A., Proulx, T., & van Beest, I. (2021). Pupillometry and hindsight bias: Physiological arousal predicts compensatory behavior. Social Psychological and Personality Science, 12(7), 1146–1154. https://doi.org/10.1177/1948550620966153
Snefjella, B., & Blank, I. (2020). Semantic norm extrapolation is a missing data problem. PsyArXiv. https://doi.org/10.31234/osf.io/y2gav
Solovyev, V. (2021). Concreteness/abstractness concept: State of the art. In B. M. Velichkovsky, P. M. Balaban, & V. L. Ushakov (Eds.), Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics (pp. 275–283). Springer International Publishing. https://doi.org/10.1007/978-3-030-71637-0_33
Speed, L. J., & Brybaert, M. (2021). Dutch sensory modality norms. Behavior Research Methods. https://doi.org/10.3758/s13428-021-01656-9
Speed, L. J., & Majid, A. (2020). Grounding language in the neglected senses of touch, taste, and smell. Cognitive Neuropsychology, 37(5-6), 363–392. https://doi.org/10.1080/02643294.2019.1623188
Speed, L. J., van Dam, W. O., Hirath, P., Vigliocco, G., & Desai, R. H. (2017). Impaired comprehension of speed verbs in parkinson’s disease. Journal of the International Neuropsychological Society, 23(5), 412–420. https://doi.org/10.1017/S1355617717000248
Stanfield, R. A., & Zwaan, R. A. (2001). The effect of implied orientation derived from verbal context on picture recognition. Psychological Science, 12(2), 153–156. https://doi.org/10.1111/1467-9280.00326
Stasenko, A., Garcea, F. E., Dombovy, M., & Mahon, B. Z. (2014). When concepts lose their color: A case of object-color knowledge impairment. Cortex, 58, 217–238. https://doi.org/10.1016/j.cortex.2014.05.013
Stone, K., Malsburg, T. von der, & Vasishth, S. (2020). The effect of decay and lexical uncertainty on processing long-distance dependencies in reading. PeerJ, 8, e10438. https://doi.org/10.7717/peerj.10438
Stone, K., Veríssimo, J., Schad, D. J., Oltrogge, E., Vasishth, S., & Lago, S. (2021). The interaction of grammatically distinct agreement dependencies in predictive processing. Language, Cognition and Neuroscience, 36(9), 1159–1179. https://doi.org/10.1080/23273798.2021.1921816
Suárez, L., Tan, S. H., Yap, M. J., & Goh, W. D. (2011). Observing neighborhood effects without neighbors. Psychonomic Bulletin & Review, 18(3), 605–611. https://doi.org/10.3758/s13423-011-0078-9
Tendeiro, J. N., & Kiers, H. A. L. (2019). A review of issues about null hypothesis Bayesian testing. Psychological Methods, 24(6), 774–795. https://doi.org/10.1037/met0000221
Tendeiro, J. N., & Kiers, H. A. L. (in press). On the white, the black, and the many shades of gray in between: Our reply to van Ravenzwaaij and Wagenmakers (2021). Psychological Methods.
Tillman, R., Hutchinson, S., & Louwerse, M. M. (2015). How sharp is Occam’s razor? Language statistics in cognitive processing. In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 2404–2409). Cognitive Science Society. https://cogsci.mindmodeling.org/2015/papers/0413/paper0413.pdf
Tiokhin, L., Yan, M., & Morgan, T. J. H. (2021). Competition for priority harms the reliability of science, but reforms can help. Nature Human Behaviour, 5(7, 7), 857–867. https://doi.org/10.1038/s41562-020-01040-1
Troche, J., Crutch, S. J., & Reilly, J. (2017). Defining a conceptual topography of word concreteness: Clustering properties of emotion, sensation, and magnitude among 750 English words. Frontiers in Psychology, 8, 1787. https://doi.org/10.3389/fpsyg.2017.01787
Trumpp, N. M., Traub, F., & Kiefer, M. (2013). Masked priming of conceptual features reveals differential brain activation during unconscious access to conceptual action and sound information. PLOS ONE, 8(5), e65910. https://doi.org/10.1371/journal.pone.0065910
Tulving, E. (2007). Are there 256 different kinds of memory? The Foundations of Remembering: Essays in Honor of Henry L. Roediger, III., 39–52.
Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110. https://doi.org/10.1037/h0031322
Ullman, M. T., Miranda, R. A., & Travers, M. L. (2008). Sex differences in the neurocognition of language. In J. B. Becker, K. J. Berkley, N. Geary, E. Hampson, J. Herman, & E. Young (Eds.), Sex on the brain: From genes to behavior (pp. 291–309). Oxford University Press.
Uttl, B. (2002). North American Adult Reading Test: Age norms, reliability, and validity. Journal of Clinical and Experimental Neuropsychology, 24(8), 1123–1137. https://doi.org/10.1076/jcen.24.8.1123.8375
van Ravenzwaaij, D., van der Maas, H. L. J., & Wagenmakers, E.-J. (2012). Optimal decision making in neural inhibition models. Psychological Review, 119(1), 201–215. https://doi.org/10.1037/a0026275
van Ravenzwaaij, D., & Wagenmakers, E.-J. (2021). Advantages masquerading as “issues” in Bayesian hypothesis testing: A commentary on Tendeiro and Kiers (2019). Psychological Methods. https://doi.org/10.1037/met0000415
Vannuscorps, G., Dricot, L., & Pillon, A. (2016). Persistent sparing of action conceptual processing in spite of increasing disorders of action production: A case against motor embodiment of action concepts. Cognitive Neuropsychology, 33(3-4), 191–219. https://doi.org/10.1080/02643294.2016.1186615
Vasishth, S., & Gelman, A. (2021). How to embrace variation and accept uncertainty in linguistic and psycholinguistic data analysis. Linguistics, 59(5), 1311–1342. https://doi.org/10.1515/ling-2019-0051
Vasishth, S., Mertzen, D., Jäger, L. A., & Gelman, A. (2018). The statistical significance filter leads to overoptimistic expectations of replicability. Journal of Memory and Language, 103, 151–175. https://doi.org/10.1016/j.jml.2018.07.004
Vasishth, S., Nicenboim, B., Beckman, M. E., Li, F., & Kong, E. J. (2018). Bayesian data analysis in the phonetic sciences: A tutorial introduction. Journal of Phonetics, 71, 147–161. https://doi.org/10.1016/j.wocn.2018.07.008
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., & Burkner, P.-C. (2021). Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC. Bayesian Analysis, 16(2), 667–718. https://doi.org/10.1214/20-BA1221
Vergallito, A., Petilli, M. A., & Marelli, M. (2020). Perceptual modality norms for 1,121 Italian words: A comparison with concreteness and imageability scores and an analysis of their impact in word processing tasks. Behavior Research Methods, 52(4), 1599–1616. https://doi.org/10.3758/s13428-019-01337-8
Verkerk, A. (2014). The correlation between motion event encoding and path verb lexicon size in the Indo-European language family. Folia Linguistica, 48, 307–358. https://doi.org/10.1515/flih.2014.009
Versace, R., Bailloud, N., Magnan, A., & Ecalle, J. (2021). The impact of embodied simulation in vocabulary learning. The Mental Lexicon, 16(1), 2–22. https://doi.org/10.1075/ml.20011.ver
Vigliocco, G., Kousta, S.-T., Della Rosa, P. A., Vinson, D. P., Tettamanti, M., Devlin, J. T., & Cappa, S. F. (2014). The neural representation of abstract words: The role of emotion. Cerebral Cortex, 7(24), 1767–1777. https://doi.org/10.1093/cercor/bht025
Vigliocco, G., Meteyard, L., Andrews, M., & Kousta, S. (2009). Toward a theory of semantic representation. 1(2), 219–247. https://doi.org/10.1515/LANGCOG.2009.011
Vigliocco, G., Ponari, M., & Norbury, C. (2018). Learning and processing abstract words and concepts: Insights from typical and atypical development. Topics in Cognitive Science, 10, 533–549. https://doi.org/10.1111/tops.12347
Villalonga, M. B., Sussman, R. F., & Sekuler, R. (2021). Perceptual timing precision with vibrotactile, auditory, and multisensory stimuli. Attention, Perception, & Psychophysics, 83(5), 2267–2280. https://doi.org/10.3758/s13414-021-02254-9
Vitale, F., Monti, I., Padrón, I., Avenanti, A., & de Vega, M. (2021). The neural inhibition network is causally involved in the disembodiment effect of linguistic negation. Cortex. https://doi.org/10.1016/j.cortex.2021.11.015
von der Malsburg, T., & Angele, B. (2017). False positives and other statistical errors in standard analyses of eye movements in reading. Journal of Memory and Language, 94, 119–133. https://doi.org/10.1016/j.jml.2016.10.003
Vukovic, N., Feurra, M., Shpektor, A., Myachykov, A., & Shtyrov, Y. (2017). Primary motor cortex functionally contributes to language comprehension: An online rTMS study. Neuropsychologia, 96, 222–229. https://doi.org/10.1016/j.neuropsychologia.2017.01.025
Vukovic, N., & Williams, J. N. (2015). Individual differences in spatial cognition influence mental simulation of language. Cognition, 142, 110–122. https://doi.org/10.1016/j.cognition.2015.05.017
Wagenmakers, E.-J., Beek, T., Dijkhoff, L., Gronau, Q. F., Acosta, A., Adams, R. B., Albohn, D. N., Allard, E. S., Benning, S. D., Blouin-Hudon, E.-M., Bulnes, L. C., Caldwell, T. L., Calin-Jageman, R. J., Capaldi, C. A., Carfagno, N. S., Chasten, K. T., Cleeremans, A., Connell, L., DeCicco, J. M., … Zwaan, R. A. (2016). Registered Replication Report: Strack, Martin, & Stepper (1988). Perspectives on Psychological Science, 11(6), 917–928. https://doi.org/10.1177/1745691616674458
Wagenmakers, E.-J., Sarafoglou, A., & Aczel, B. (2022). One statistical analysis must not rule them all. Nature, 605(7910), 423–425. https://doi.org/10.1038/d41586-022-01332-8
Wallentin, M. (2020). Chapter 6 - Gender differences in language are small but matter for disorders. In R. Lanzenberger, G. S. Kranz, & I. Savic (Eds.), Handbook of Clinical Neurology (Vol. 175, pp. 81–102). Elsevier. https://doi.org/10.1016/B978-0-444-64123-6.00007-2
Wang, J., Conder, J. A., Blitzer, D. N., & Shinkareva, S. V. (2010). Neural representation of abstract and concrete concepts: A meta-analysis of neuroimaging studies. Human Brain Mapping, 31(10), 1459–1468. https://doi.org/10.1002/hbm.20950
Wang, X., Li, G., Zhao, G., Li, Y., Wang, B., Lin, C.-P., Liu, X., & Bi, Y. (2021). Social and emotion dimensional organizations in the abstract semantic space: The neuropsychological evidence. Scientific Reports, 11(1, 1), 23572. https://doi.org/10.1038/s41598-021-02824-9
Weiss, D. A. (2022). apa7’ – Format documents in APA style (7th Edition). CTAN. https://ctan.org/pkg/apa7
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Willems, R. M., & Casasanto, D. (2011). Flexibility in Embodied Language Understanding. Frontiers in Psychology, 0. https://doi.org/10.3389/fpsyg.2011.00116
Williams, L. E. (2014). Improving psychological science requires theory, data, and caution: Reflections on Lynott et al. (2014). Social Psychology, 45(4), 321–323.
Wingfield, C., & Connell, L. (2022a). Sensorimotor distance: A grounded measure of semantic similarity for 800 million concept pairs. Behavior Research Methods. https://doi.org/10.3758/s13428-022-01965-7
Wingfield, C., & Connell, L. (2022b). Understanding the role of linguistic distributional knowledge in cognition. Language, Cognition and Neuroscience, 1–51. https://doi.org/10.1080/23273798.2022.2069278
Winter, B., Perlman, M., & Majid, A. (2018). Vision dominates in perceptual language: English sensory vocabulary is optimized for usage. Cognition, 179, 213–220. https://doi.org/10.1016/j.cognition.2018.05.008
Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). Woodcock Johnson III tests of cognitive abilities. Riverside Publishing.
Xie, Y., Dervieux, C., & Riederer, E. (2020). R markdown cookbook. Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown-cookbook
Yap, M. J., & Balota, D. A. (2009). Visual word recognition of multisyllabic words. Journal of Memory and Language, 60(4), 502–529. https://doi.org/10.1016/j.jml.2009.02.001
Yap, M. J., Balota, D. A., Sibley, D. E., & Ratcliff, R. (2012). Individual differences in visual word recognition: Insights from the English Lexicon Project. Journal of Experimental Psychology: Human Perception and Performance, 38, 1, 53–79. https://doi.org/10.1037/a0024177
Yap, M. J., Balota, D. A., & Tan, S. E. (2013). Additive and interactive effects in semantic priming: Isolating lexical and decision processes in the lexical decision task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(1), 140–158. https://doi.org/10.1037/a0028520
Yap, M. J., Hutchison, K. A., & Tan, L. C. (2017). Individual differences in semantic priming performance: Insights from the semantic priming project. In M. N. Jones (Ed.), Frontiers of cognitive psychology. Big data in cognitive science (pp. 203–226). Routledge/Taylor & Francis Group.
Yap, M. J., Tse, C.-S., & Balota, D. A. (2009). Individual differences in the joint effects of semantic priming and word frequency revealed by RT distributional analyses: The role of lexical integrity. Journal of Memory and Language, 61(3), 303–325. https://doi.org/10.1016/j.jml.2009.07.001
Yarkoni, T., Balota, D., & Yap, M. J. (2008). Moving beyond Coltheart’s N: A new measure of orthographic similarity. Psychonomic Bulletin & Review, 15(5), 971–979. https://doi.org/10.3758/PBR.15.5.971
Yee, E., Ahmed, S. Z., & Thompson-Schill, S. L. (2012). Colorless green ideas (can) prime furiously. Psychological Science, 23(4), 364–369. https://doi.org/10.1177/0956797611430691
Yee, E., Huffstetler, S., & Thompson-Schill, S. L. (2011). Function follows form: Activation of shape and function features during object identification. Journal of Experimental Psychology: General, 140(3), 348–363. https://doi.org/10.1037/a0022840
Zeman, A., Milton, F., Della Sala, S., Dewar, M., Frayling, T., Gaddum, J., Hattersley, A., Heuerman-Williamson, B., Jones, K., & MacKisack, M. (2020). Phantasia—the psychological significance of lifelong visual imagery vividness extremes. Cortex, 130, 426–440. https://doi.org/10.1016/j.cortex.2020.04.003
Zhong, Y., Wan, M., Ahrens, K., & Huang, C.-R. (2022). Sensorimotor norms for Chinese nouns and their relationship with orthographic and semantic variables. Language, Cognition and Neuroscience, 0(0), 1–23. https://doi.org/10.1080/23273798.2022.2035416
Zwaan, R. A. (2014). Replications should be performed with power and precision: A response to Rommers, Meyer, and Huettig (2013). Psychological Science, 25(1), 305–307. https://doi.org/10.1177/0956797613509634
Zwaan, R. A. (2021). Two challenges to “embodied cognition” research and how to overcome them. Journal of Cognition, 4(1, 1), 14. https://doi.org/10.5334/joc.151
Zwaan, R. A., & Pecher, D. (2012). Revisiting Mental Simulation in Language Comprehension: Six Replication Attempts. PLoS ONE, 7(12), e51382. https://doi.org/10.1371/journal.pone.0051382



Pablo Bernabeu, 2022. Licence: CC BY 4.0.
Thesis: https://doi.org/10.17635/lancaster/thesis/1795.

Online book created using the R package bookdown.