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INCREASE

Innovations in Neural Conceptual Representation: Exploring Aspects of Semantics

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EC-Contrib. €

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Partnership

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Project "INCREASE" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITY COLLEGE LONDON 

Organization address
address: GOWER STREET
city: LONDON
postcode: WC1E 6BT
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://sites.google.com/view/mariamontefinese/increase
 Total cost 183˙454 €
 EC max contribution 183˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2016
 Duration (year-month-day) from 2016-10-15   to  2018-10-14

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITY COLLEGE LONDON UK (LONDON) coordinator 183˙454.00

Map

 Project objective

Semantic representation –the knowledge that we have of the world– is an essential component of our mind whose nature can be inferred from similarity measures, which we use every day to compare entities on the basis of their meaning. Many research efforts have been made to understand our knowledge, proposing that it could be based upon data deriving from our sensorimotor experience or from any sort of regularity in spoken and/or written language. Recently, models combining these two data sources obtained semantic representations that are more informative and similar to human ones. However, 1) what information is used to represent meaning and 2) the way our brains organize semantic representations still remain hot topics of debate in the field. The project aims to address these queries, by investigating, for the first time, the relation between semantic representations at three different levels: behaviour, models and brain activity. We will derive similarity measures and combined similarity models using different data sources (text corpora, semantic feature norms, ratings studies). Next, in an fMRI study, adult English speakers will perform implicit (lexical decision) and explicit (categorization) tasks. We will use (1) a state-of-the-art technique (Representational Similarity Analysis) that has heralded a new research era in the study of semantics since it allows one-to-one mappings between patterns of brain-activity measurement, behavioural and computational models, and (2) dimensionality-reduction approaches. Results will provide new knowledge on the nature of semantic structure: they will allow a better characterization of different similarity measures, adjudicating between the different similarity models and behavioural data as well as identifying differences between similarity models linked to differences in neural activity. This will reveal the different neural contributions to different aspects of meaning, opening up new research agendas.

 Publications

year authors and title journal last update
List of publications.
2019 Maria Montefinese, Glyn Hallam, Hannah Elizabeth Thompson, Elizabeth Jefferies
The interplay between control processes and feature relevance: Evidence from dual-task methodology
published pages: 174702181987716, ISSN: 1747-0218, DOI: 10.1177/1747021819877163
Quarterly Journal of Experimental Psychology 2019-10-29
2019 Maria Montefinese
Semantic representation of abstract and concrete words: a minireview of neural evidence
published pages: 1585-1587, ISSN: 0022-3077, DOI: 10.1152/jn.00065.2019
Journal of Neurophysiology 121/5 2019-10-29
2017 Montefinese M., Vinson D.
Resemblance among similarity measures in semantic representation
published pages: , ISSN: , DOI:
2019-05-13
2018 Maria Montefinese, David Vinson, Ettore Ambrosini
Recognition memory and featural similarity between concepts: The pupil’s point of view
published pages: 159-169, ISSN: 0301-0511, DOI: 10.1016/j.biopsycho.2018.04.004
Biological Psychology 135 2019-05-13
2018 Maria Montefinese, Ettore Ambrosini, Eka Roivainen
No grammatical gender effect on affective ratings: evidence from Italian and German languages
published pages: 1-7, ISSN: 0269-9931, DOI: 10.1080/02699931.2018.1483322
Cognition and Emotion 2019-05-13
2019 Maria Montefinese, David Vinson, Gabriella Vigliocco, Ettore Ambrosini
Italian Age of Acquisition Norms for a Large Set of Words (ItAoA)
published pages: , ISSN: 1664-1078, DOI: 10.3389/fpsyg.2019.00278
Frontiers in Psychology 10 2019-05-13

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The information about "INCREASE" are provided by the European Opendata Portal: CORDIS opendata.

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