Tools
Tools
Ghio, Marta, Vaghi, Matilde Maria Serena 
ORCID: https://orcid.org/0000-0002-0999-9055, Perani, Daniela and Tettamanti, Marco
(2016)
Decoding the neural representation of fine-grained conceptual categories.
NeuroImage, 132.
pp. 93-103.
ISSN 1053-8119
Abstract
Neuroscientific research on conceptual knowledge based on the grounded cognition framework has shed light on the organization of concrete concepts into semantic categories that rely on different types of experiential information. Abstract concepts have traditionally been investigated as an undifferentiated whole, and have only recently been addressed in a grounded cognition perspective. The present fMRI study investigated the involvement of brain systems coding for experiential information in the conceptual processing of fine-grained semantic categories along the abstract–concrete continuum. These categories consisted of mental state-, emotion-, mathematics-, mouth action-, hand action-, and leg action-related meanings. Thirty-five sentences for each category were used as stimuli in a 1-back task performed by 36 healthy participants. A univariate analysis failed to reveal category-specific activations. Multivariate pattern analyses, in turn, revealed that fMRI data contained sufficient information to disentangle all six fine-grained semantic categories across participants. However, the category-specific activity patterns showed no overlap with the regions coding for experiential information. These findings demonstrate the possibility of detecting specific patterns of neural representation associated with the processing of fine-grained conceptual categories, crucially including abstract ones, though bearing no anatomical correspondence with regions coding for experiential information as predicted by the grounded cognition hypothesis.
| Item Type: | Article |
|---|---|
| Faculty \ School: | Faculty of Social Sciences > School of Psychology |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 04 Oct 2022 14:15 |
| Last Modified: | 07 Mar 2024 02:39 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/88835 |
| DOI: | 10.1016/j.neuroimage.2016.02.009 |
Actions (login required)
 |
View Item |