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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.

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

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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