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Assessing Functional Brain Network Dynamics in Dyslexia from fNIRS Data

Nicolás J. Gallego-Molina

Department of Communications Engineering, University of Malaga, Málaga 29071, Spain

Andalusian Research Institute in Data, Science and Computational Intelligence, Spain

E-mail Address: [email protected]

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Andrés Ortiz

Department of Communications Engineering, University of Malaga, Málaga 29071, Spain

Andalusian Research Institute in Data, Science and Computational Intelligence, Spain

E-mail Address: [email protected]

Corresponding author.

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Francisco J. Martínez-Murcia

Department of Signal Theory, Networking and Communications, University of Granada, Granada 18010, Spain

Andalusian Research Institute in Data, Science and Computational Intelligence, Spain

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Ignacio Rodríguez-Rodríguez

Department of Communications Engineering, University of Malaga, Málaga 29071, Spain

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, and

Juan L. Luque

Department of Developmental and Educational Psychology, University of Málaga, Málaga 29071, Spain

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https://doi.org/10.1142/S012906572350017XCited by:5 (Source: Crossref)

Abstract

Developmental dyslexia is characterized by a deficit of phonological awareness whose origin is related to atypical neural processing of speech streams. This can lead to differences in the neural networks that encode audio information for dyslexics. In this work, we investigate whether such differences exist using functional near-infrared spectroscopy (fNIRS) and complex network analysis. We have explored functional brain networks derived from low-level auditory processing of nonspeech stimuli related to speech units such as stress, syllables or phonemes of skilled and dyslexic seven-year-old readers. A complex network analysis was performed to examine the properties of functional brain networks and their temporal evolution. We characterized aspects of brain connectivity such as functional segregation, functional integration or small-worldness. These properties are used as features to extract differential patterns in controls and dyslexic subjects. The results corroborate the presence of discrepancies in the topological organizations of functional brain networks and their dynamics that differentiate between control and dyslexic subjects, reaching an Area Under ROC Curve (AUC) up to 0.89 in classification experiments.

Keywords:

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