RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed

ABSTRACT:

Objective

Naming speed, behaviorally measured via the serial Rapid automatized naming (RAN) test, is one of the most examined underlying cognitive factors of reading development and reading difficulties (RD). However, the unconstrained-reading format of serial RAN has made it challenging for traditional EEG analysis methods to extract neural components for studying the neural underpinnings of naming speed. The present study aims to explore a novel approach to isolate neural components during the serial RAN task that are (a) informative of group differences between children with dyslexia (DYS) and chronological age controls (CAC), (b) improve the power of analysis, and (c) are suitable for deciphering the neural underpinnings of naming speed.

Methods

We propose a novel mac

SUBMITTER: Christoforou C 

PROVIDER: S-EPMC10319123 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature