Opendata, web and dolomites

L2STAT SIGNED

Statistical learning and L2 literacy acquisition: Towards a neurobiological theory of assimilating novel writing systems

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 L2STAT project word cloud

Explore the words cloud of the L2STAT project. It provides you a very rough idea of what is the project "L2STAT" about.

hebrew    neural    statistical    experimentation    skills    world    capacities    spain    biologically    overarching    shape    informative    english    plausible    shapes    first    computational    machine    types    priori    psychometrically    parallel    exposure    writing    framework    visual    sensitivity    precisely    eeg    chinese    reading    probe    spanish    representations    characterization    modalities    predictions    taiwan    languages    assimilation    neurally    linguistic    representation    time    employ    l2stat    understand    regarding    inspired    neurobiology    interdisciplinary    track    learned    learners    axes    techniques    learning    turn    sites    behavioral    extract    individuals    l2    principles    generate    underpinning    conduct    tunes    sl    neuroimaging    literacy    mechanisms    contrasting    neurobiological    acquisition    exposed    detecting    meg    environment    longitudinally    israel    mutually    environments    statistics    linguistics    tests    theoretical    auditory    street    launches    models    regularities    fmri   

Project "L2STAT" data sheet

The following table provides information about the project.

Coordinator
THE HEBREW UNIVERSITY OF JERUSALEM 

Organization address
address: EDMOND J SAFRA CAMPUS GIVAT RAM
city: JERUSALEM
postcode: 91904
website: www.huji.ac.il

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 Israel [IL]
 Total cost 2˙500˙000 €
 EC max contribution 2˙500˙000 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-AdG
 Funding Scheme ERC-ADG
 Starting year 2016
 Duration (year-month-day) from 2016-07-01   to  2021-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE HEBREW UNIVERSITY OF JERUSALEM IL (JERUSALEM) coordinator 1˙700˙000.00
2    BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE ES (SAN SEBASTIAN) participant 800˙000.00

Map

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

The overarching goal of L2STAT is to understand L2 literacy acquisition by bringing together, for the first time, recent advances in the neurobiology of statistical learning (SL), a detailed statistical characterization of the world’s writing systems, and neurally-plausible general principles of learning, representation, and processing. L2STAT aims to provide a new theoretical framework that considers L2 learning and SL a two-way street: SL, on the one hand, tunes learners to the regularities of a new linguistic environment, and on the other hand, L2 environment shapes learners’ sensitivity to its specific types of statistical properties. The project will focus on the assimilation of reading skills in four novel linguistic environments, and investigate how exposure to their distinct writing systems shape, in turn, SL. L2STAT is an interdisciplinary project that launches in parallel five mutually informative research axes: 1) we employ advanced methods from computational linguistics and machine learning to precisely characterize the statistics of four highly contrasting writing systems (English, Spanish, Hebrew, Chinese). 2) We study the learning that results from biologically-inspired computational models that are exposed to these statistics, to generate a priori predictions regarding what statistical properties can (or cannot) be learned, and how neural mechanisms constrain the representations learned during L2 literacy acquisition. 3) We develop psychometrically reliable behavioral tests of individuals’ capacities to extract regularities in the visual and auditory modalities. 4) We use state of the art neuroimaging techniques including EEG, MEG, fMRI to probe the neurobiological underpinning for detecting regularities in the visual and auditory modalities. 5) We conduct behavioral experimentation in four sites (Israel, Spain, Taiwan to track literacy acquisition longitudinally in the four different languages.

 Publications

year authors and title journal last update
List of publications.
2018 Noam Siegelman, Louisa Bogaerts, Amit Elazar, Joanne Arciuli, Ram Frost
Linguistic entrenchment: Prior knowledge impacts statistical learning performance
published pages: 198-213, ISSN: 0010-0277, DOI: 10.1016/j.cognition.2018.04.011
Cognition 177 2019-10-09
2019 Henry Brice, William Einar Mencl, Stephen J. Frost, Atira Sara Bick, Jay G. Rueckl, Kenneth R. Pugh, Ram Frost
Neurobiological signatures of L2 proficiency: Evidence from a bi-directional cross-linguistic study
published pages: 7-16, ISSN: 0911-6044, DOI: 10.1016/j.jneuroling.2018.02.004
Journal of Neurolinguistics 50 2019-08-30
2016 Noam Siegelman, Louisa Bogaerts, Morten H. Christiansen, Ram Frost
Towards a theory of individual differences in statistical learning
published pages: 20160059, ISSN: 0962-8436, DOI: 10.1098/rstb.2016.0059
Philosophical Transactions of the Royal Society B: Biological Sciences 372/1711 2019-06-14
2017 Martijn Baart, Blair C. Armstrong, Clara D. Martin, Ram Frost, Manuel Carreiras
Cross-modal noise compensation in audiovisual words
published pages: 42055, ISSN: 2045-2322, DOI: 10.1038/srep42055
Scientific Reports 7 2019-06-14
2016 Blair C. Armstrong, Ram Frost, Morten H. Christiansen
The long road of statistical learning research: past, present and future
published pages: 20160047, ISSN: 0962-8436, DOI: 10.1098/rstb.2016.0047
Philosophical Transactions of the Royal Society B: Biological Sciences 372/1711 2019-06-14
2017 Noam Siegelman, Louisa Bogaerts, Ofer Kronenfeld, Ram Frost
Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?
published pages: , ISSN: 0364-0213, DOI: 10.1111/cogs.12556
Cognitive Science 2019-06-14
2018 Louisa Bogaerts, Noam Siegelman, Tali Ben-Porat, Ram Frost
Is the Hebb repetition task a reliable measure of individual differences in sequence learning?
published pages: 17470218.2017.1, ISSN: 1747-0218, DOI: 10.1080/17470218.2017.1307432
Quarterly Journal of Experimental Psychology 2019-06-14

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "L2STAT" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "L2STAT" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

HyperCube (2020)

HyperCube: Gram scale production of ferrite nanocubes and thermo-responsive polymer coated nanocubes for medical applications and further exploitation in other hyperthermia fields

Read More  

SoftHandler (2019)

Commercial feasibility of an integrated soft robotic system for industrial handling

Read More  

PGErepro (2019)

How to break Mendel’s laws? The role of sexual conflict in the evolution of unusual transmission genetics

Read More