Innovations in Neural Conceptual Representation: Exploring Aspects of Semantics

Información del proyecto

INCREASE

Identificador del acuerdo de subvención: 702655

DOI

10.3030/702655

Proyecto cerrado

Fecha de la firma de la CE 4 Marzo 2016

Fecha de inicio 15 Octubre 2016

Fecha de finalización 14 Octubre 2018

Financiado con arreglo a

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coste total

€ 183 454,80

Aportación de la UE

€ 183 454,80

Coordinado por

UNIVERSITY COLLEGE LONDON
United Kingdom

Objetivo

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.

Ámbito científico (EuroSciVoc)

• ciencias sociales › psicología › psicología del comportamiento
• ciencias naturales › informática y ciencias de la información › ingeniería del conocimiento
• ciencias naturales › informática y ciencias de la información › inteligencia artificial › reconocimiento de patrones
• ciencias sociales › psicología › psicología cognitiva
• ciencias naturales › ciencias físicas › óptica › espectroscopia

Programa(s)

• H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions PROGRAMA PRINCIPAL
  
• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
  

Tema(s)

• MSCA-IF-2015-EF - Marie Skłodowska-Curie Individual Fellowships (IF-EF)
  

Régimen de financiación

MSCA-IF-EF-ST - Standard EF

Convocatoria de propuestas

H2020-MSCA-IF-2015

Coordinador

UNIVERSITY COLLEGE LONDON

• Aportación neta de la UEn: € 183 454,80
• Dirección: GOWER STREET ; WC1E 6BT London ; Reino Unido
• Región: London › Inner London — West › Camden and City of London
• Tipo de actividad: Higher or Secondary Education Establishments
• Coste total: € 183 454,80