BabyMindReader: a multivariate NIRS-EEG neural decoder to decipher newborns' inital representations of speech prosody

Project Information

BabyMindReader

Grant agreement ID: 101031716

DOI

10.3030/101031716

Project closed

EC signature date 23 April 2021

Start date 1 January 2022

End date 22 November 2024

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 183 473,28

EU contribution

€ 183 473,28

Coordinated by

UNIVERSITA DEGLI STUDI DI PADOVA
Italy

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (3)

A Within-Subject Multimodal NIRS-EEG Classifier for Infant Data

Author(s): Jessica Gemignani, Judit Gervain
Published in: Sensors, Issue 24, 2024, Page(s) 4161, ISSN 1424-8220
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s24134161

Reproducibility of infant fNIRS studies: a meta-analytic approach

Author(s): Jessica Gemignani, Irene de la Cruz-Pava, Anna Martinez, Caroline Nallet, Alessia Pasquini, Gaia Lucarini, Francesca Cavicchiolo, Judit Gervain
Published in: Neurophotonics, Issue 10, 2024, ISSN 2329-423X
Publisher: SPIE
DOI: 10.1117/1.nph.10.2.023518

Brain responses to repetition-based rule-learning do not exhibit sex differences: an aggregated analysis of infant fNIRS studies

Author(s): Jessica Gemignani, Judit Gervain
Published in: Scientific Reports, Issue 14, 2024, ISSN 2045-2322
Publisher: Nature Publishing Group
DOI: 10.1038/s41598-024-53092-2