English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  MRT-basierte Bestimmung des Risikos für die Lese-Rechtschreib-Störung im Vorschulalter

Skeide, M. A. (2017). MRT-basierte Bestimmung des Risikos für die Lese-Rechtschreib-Störung im Vorschulalter. Klinische Neurophysiologie, 48(3), 164-167. doi:10.1055/s-0043-105960.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-F8F1-E Version Permalink: http://hdl.handle.net/21.11116/0000-0003-5F18-9
Genre: Journal Article
Other : Predicting the risk for developmental dyslexia before school age with MRI

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Skeide, Michael A.1, Author              
Affiliations:
1Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

Content

show
hide
Free keywords: Developmental dyslexia; Magnetic resonance imaging (MRI); Fusiform gyrus; NRSN1
 Abstract: Developmental dyslexia (DD) is considered to be the most common among all learning disorders. About 5% of the population in Germany and 7% in the USA suffer from the psychological and social consequences of severe deficits in learning how to read and spell. DD arises from the complex interplay of genetic and environmental factors (e. g. home literacy environment). Moreover, numerous previous magnetic resonance imaging (MRI) studies have shown that the left fusiform gyrus (FFG, “visual word form area”) of the brain plays a crucial role in literacy acquisition. The present work suggests that the cortical plasticity of the FFG might be limited in individuals with DD because they carry a risk variant of the gene NRSN1 that codes proteins regulating neurite growth. NRSN1 turned out to be significantly associated with the volume of the left FFG that was estimated by conducting a voxel-based morphometry (VBM) analysis of MR images. Using volumetric profiles determined by genetic association in children, DD could be predicted 10 months before school entry with a classification accuracy of 75%. These data might make it possible in the future to diagnose DD so early that affected children might be able to compensate their deficits before school enrollment by making use of early intervention programs.

Details

show
hide
Language(s): deu - German
 Dates: 2017-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1055/s-0043-105960
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Klinische Neurophysiologie
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Stuttgart : Thieme
Pages: - Volume / Issue: 48 (3) Sequence Number: - Start / End Page: 164 - 167 Identifier: ISSN: 1434-0275
CoNE: /journals/resource/954925623269