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STATLEARN SIGNED

The reading brain as a statistical learning machine

Total Cost €

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EC-Contrib. €

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Partnership

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 STATLEARN project word cloud

Explore the words cloud of the STATLEARN project. It provides you a very rough idea of what is the project "STATLEARN" about.

units    theories    hypothesis    fundamental    letters    psycholinguistic    unfolds    seek    free    learning    languages    diversity    flawlessly    understand    kindness    frequency    identification    human    involve    fourth    progressively    data    transitional    adults    genetic    performance    patterns    signs    letter    morphemes    drive    largely    constraints    statlearn    probabilities    internal    meg    oriented    issue    written    nearly    brings    tools    newly    adult    perceptual    larger    advantage    unknown    mechanisms    recurrent    representations    ness    tracking    primates    contextual    happens    word    fmri    array    read    faces    erp    orthographic    encountered    basis    mechanism    vary    literate    efficient    language    error    statistical    readers    endowment    structure    behavioural    impressive    tests    artificial    co    positional    extremely    amount    infants    despite    smaller    cognitive    building    packages    objects    chunk    eye    astonishingly    contrasts    reading    visual    nonhuman    lines    experiments    underlies   

Project "STATLEARN" data sheet

The following table provides information about the project.

Coordinator
SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE 

Organization address
address: VIA BONOMEA 265
city: TRIESTE
postcode: 34136
website: www.sissa.it

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 Italy [IT]
 Project website https://lrlac.sissa.it/projects/statistical-learning-and-reading
 Total cost 1˙498˙210 €
 EC max contribution 1˙498˙210 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-STG
 Funding Scheme ERC-STG
 Starting year 2016
 Duration (year-month-day) from 2016-09-01   to  2021-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE IT (TRIESTE) coordinator 1˙498˙210.00

Map

 Project objective

Despite written language is not part of our genetic endowment, literate adults process an impressive amount of information as they read, and do that extremely flawlessly and nearly error-free. How this happens is largely unknown, and represents a fundamental issue for theories of human learning. Building on data from nonhuman primates, human infants and psycholinguistic experiments on word internal structure, STATLEARN tests the hypothesis that one fundamental cognitive mechanism underlies visual word identification, i.e., statistical learning. Human infants learn to chunk smaller perceptual units (e.g., oriented lines) into larger, meaningful objects (e.g., tools, faces), taking advantage of recurrent patterns in their distribution. As developing readers, they would apply this very same mechanisms to a newly–encountered type of visual objects, i.e., letters. On this basis, they would build progressively higher–order orthographic units, which eventually make their visual word identification as adult readers astonishingly efficient. The project is composed of four work packages. One aims at identifying which principle(s) drive(s) statistical learning, and contrasts overall frequency, contextual diversity, and letter transitional probabilities. Because these factors co-vary in real languages, a second work package will involve adult readers in learning artificial languages, where we will build in any statistical properties we might need to test. A third package will seek signs of statistical learning directly into the performance of developing readers. A fourth package will assess positional constraints in the identification of morphemes (e.g., kind and ness in kindness). These work packages include behavioural, eye tracking, ERP, MEG and fMRI work. Bringing together evidence from such a wide array of approaches will allow to understand how statistical learning unfolds, and what kind of representations it brings into the human reading system.

 Publications

year authors and title journal last update
List of publications.
2019 Maria Ktori, Mara De Rosa, Hector Yamil Vidal Dos Santos, Davide Crepaldi
Morpheme-specific neural representations in skilled adult readers: Evidence from fast periodic visual stimulation
published pages: , ISSN: , DOI:
2019-11-07
2019 Katarina Marjanovič, Davide Crepaldi
Morphological priming of inflectional suffixes
published pages: , ISSN: , DOI:
2019-11-07
2019 Jaroslaw Lelonkiewicz, Davide Crepaldi
Discovering the Lexicon\'s Statistical Structure in Reading
published pages: , ISSN: , DOI:
2019-11-07
2018 Hector Yamil Vidal Dos Santos, Davide Crepaldi
From Letters to Words, Through Bigrams
published pages: , ISSN: , DOI:
2019-11-07
2018 Pescuma V.N., Ktori M., Cevoli B., Lomi E., Franzon F. & Crepaldi D.
An eye-tracking database of natural reading in Italian children
published pages: , ISSN: , DOI:
2019-06-19
2018 De Rosa M. & Crepaldi D.
Morpho-orthographic analysis does not depend on affix frequency
published pages: , ISSN: , DOI:
2019-06-19
2017 Crepaldi D., Pescuma V., Ktori M., Cevoli B., Franzon F. and Lomi E.
Statistical Learning and Learning to Read
published pages: , ISSN: , DOI:
2019-06-19
2017 Pescuma V., Ktori M., Cevoli B., Lomi E., Franzon F. & Crepaldi D.
An eye-tracking investigation of natural reading in children
published pages: , ISSN: , DOI:
2019-06-19
2017 http://v.calameo.com/?bkcode=003272336398fb9b8fabb&mode=full
Una scuola ai vertici europei
published pages: 81, ISSN: , DOI:
PLATINUM - Le chiavi per lo sviluppo (ricerca&innovazione) July 2017 2019-06-19
2017 Pescuma V., Ktori M., Cevoli B., Lomi E., Franzon F. & Crepaldi D.
Statistical Learning and Visual Word Identification: An eye-tracking investigation of natural reading in children
published pages: , ISSN: , DOI:
2019-06-19

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

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