Hostname: page-component-76fb5796d-r6qrq Total loading time: 0 Render date: 2024-04-28T08:35:46.569Z Has data issue: false hasContentIssue false

Catching the intangible: a role for emotion?

Published online by Cambridge University Press:  19 June 2020

Maria Montefinese
Affiliation:
Department of General Psychology, University of Padova, 35131Padova, Italymaria.montefinese@unipd.it antonino.visalli@unipd.ithttps://sites.google.com/view/mariamontefinese https://www.researchgate.net/profile/Antonino_Visalli
Ettore Ambrosini
Affiliation:
Department of General Psychology, University of Padova, 35131Padova, Italymaria.montefinese@unipd.it antonino.visalli@unipd.ithttps://sites.google.com/view/mariamontefinese https://www.researchgate.net/profile/Antonino_Visalli Department of Neuroscience, University of Padova, 35128Padova, Italyettore.ambrosini@unipd.it https://www.researchgate.net/profile/Ettore_Ambrosini
Antonino Visalli
Affiliation:
Department of General Psychology, University of Padova, 35131Padova, Italymaria.montefinese@unipd.it antonino.visalli@unipd.ithttps://sites.google.com/view/mariamontefinese https://www.researchgate.net/profile/Antonino_Visalli
David Vinson
Affiliation:
Department of Experimental Psychology, University College London, LondonWC1E 6BT, UK. d.vinson@ucl.ac.uk https://www.ucl.ac.uk/pals/research/experimental-psychology/person/david-vinson/

Abstract

A crucial aspect of Gilead and colleagues’ ontology is the dichotomy between tangible and intangible representations, but the latter remains rather ill-defined. We propose a fundamental role for interoceptive experience and the statistical distribution of entities in language, especially for intangible representations, that we believe Gilead and colleagues’ ontology needs to incorporate.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bestgen, Y. & Vincze, N. (2012) Checking and bootstrapping lexical norms by means of word similarity indexes. Behavior Research Methods 44:9981006.CrossRefGoogle ScholarPubMed
Bhatia, S., Richie, R. & Zou, W. (2019) Distributed semantic representations for modeling human judgment. Current Opinion in Behavioral Sciences 29:3136.CrossRefGoogle Scholar
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 of London B: Biological Sciences 373(1752):20170143. doi: 10.1098/rstb.2017.0143.CrossRefGoogle ScholarPubMed
Crutch, S. J., Troche, J., Reilly, J. & Ridgway, G. R. (2013) Abstract conceptual feature ratings: The role of emotion, magnitude, and other cognitive domains in the organization of abstract conceptual knowledge. Frontiers in Human Neuroscience 7:186.CrossRefGoogle ScholarPubMed
Crutch, S. J. & Warrington, E. K. (2004) Abstract and concrete concepts have structurally different representational frameworks. Brain 128(3):615–27.CrossRefGoogle ScholarPubMed
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(1):14.CrossRefGoogle ScholarPubMed
Landauer, T. K. & Dumais, S. T. (1997) A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review 104:211–40.CrossRefGoogle Scholar
Lenci, A., Lebani, G. E. & Passaro, L. C. (2018) The emotions of abstract words: A distributional semantic analysis. Topics in Cognitive Science 10(3):550–72.CrossRefGoogle ScholarPubMed
Montefinese, M. (2019) Semantic representation of abstract and concrete words: A minireview of neural evidence. Journal of neurophysiology 121(5):1585–87.CrossRefGoogle ScholarPubMed
Montefinese, M., Ambrosini, E., Fairfield, B. & Mammarella, N. (2013) The “subjective” pupil old/new effect: Is the truth plain to see? International Journal of Psychophysiology 89(1):4856.CrossRefGoogle Scholar
Paivio, A. (1971) Imagery and verbal processes. Holt, Rinehart, & Winston.Google Scholar
Recchia, G. & Louwerse, M. M. (2015) Reproducing affective norms with lexical co-occurrence statistics: Predicting valence, arousal, and dominance. The Quarterly Journal of Experimental Psychology 68:1584–98.CrossRefGoogle ScholarPubMed
Rotaru, A. S., Vigliocco, G. & Frank, S. L. (2018) Modeling the structure and dynamics of semantic processing. Cognitive Science 42(8):2890–917.CrossRefGoogle ScholarPubMed
Vankrunkelsven, H., Verheyen, S., Storms, G. & De Deyne, S. (2018) Predicting lexical norms: A comparison between a word association model and text-based word co-occurrence models. Journal of Cognition 1(1).CrossRefGoogle ScholarPubMed
Vigliocco, G., Kousta, S. T., Della Rosa, P. A., Vinson, D. P., Tettamanti, M., Devlin, J. T. & Cappa, S. F. (2013) The neural representation of abstract words: The role of emotion. Cerebral Cortex 24(7):1767–77.CrossRefGoogle ScholarPubMed
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):1459–68.CrossRefGoogle ScholarPubMed
Wang, X., Wu, W., Ling, Z., Xu, Y., Fang, Y., Wang, X., Binder, J. R., Men, W., Gao, J. H. & Bi, Y. (2018) Organizational principles of abstract words in the human brain. Cerebral Cortex 28(12):4305–18. https://doi.org/10.1093/cercor/bhx283.CrossRefGoogle ScholarPubMed