Serviceeinschränkungen vom 12.-22.02.2026 - weitere Infos auf der UB-Homepage
  • Predicting reading ability fro...

Treffer: Predicting reading ability from brain anatomy and function: From areas to connections.

Title:
Predicting reading ability from brain anatomy and function: From areas to connections.
Authors:
Kristanto D; Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong., Liu M; Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong., Liu X; Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong; Department of Psychology, Carl von Ossietzky University of Oldenburg, Germany., Sommer W; Department of Psychology, Humboldt University at Berlin, Berlin, Germany. Electronic address: werner.sommer@cms.hu-berlin.de., Zhou C; Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong. Electronic address: cszhou@hkbu.edu.hk.
Source:
NeuroImage [Neuroimage] 2020 Sep; Vol. 218, pp. 116966. Date of Electronic Publication: 2020 May 18.
Publication Type:
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Academic Press Country of Publication: United States NLM ID: 9215515 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-9572 (Electronic) Linking ISSN: 10538119 NLM ISO Abbreviation: Neuroimage Subsets: MEDLINE
Imprint Name(s):
Original Publication: Orlando, FL : Academic Press, c1992-
MeSH Terms:
Reading*, Brain/*anatomy & histology , Brain/*physiology , Psychomotor Performance/*physiology, Adult ; Brain/diagnostic imaging ; Brain Mapping ; Cerebral Cortex/diagnostic imaging ; Cerebral Cortex/physiology ; Comprehension ; Connectome ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Myelin Sheath/physiology ; Nerve Net/diagnostic imaging ; Nerve Net/physiology ; Neural Pathways/diagnostic imaging ; Neural Pathways/physiology ; Predictive Value of Tests ; Recognition, Psychology ; Young Adult
Grant Information:
U54 MH091657 United States MH NIMH NIH HHS
Contributed Indexing:
Keywords: Area measures; Connection measures; Prediction; Reading
Entry Date(s):
Date Created: 20200523 Date Completed: 20210219 Latest Revision: 20210219
Update Code:
20250114
DOI:
10.1016/j.neuroimage.2020.116966
PMID:
32439534
Database:
MEDLINE

Weitere Informationen

Reading is a complex task involving different brain areas. As a crystallized ability, reading is also known to have effects on brain structure and function development. However, there are still open questions about what are the elements of the reading networks and how structural and functional brain measures shape the reading ability. The present study used a data-driven approach to investigate whether reading-related brain structural measures of cortical thickness, myelination, sulcus depth and structural connectivity and functional connectivity from the whole brain can predict individual differences in reading skills. It used different brain measures and performance scores from the Oral Reading Recognition Test (ORRT) measuring reading ability from 998 participants. We revealed reading-related brain areas and connections, and evaluated how well area and connection measures predict reading performance. Interestingly, the combination of all brain measures obtained the best predictions. We further grouped reading-related areas into positive and negative networks, each with four different levels (Core Regions, Extended-Regions 1, 2, 3), representing different correlation levels with the reading scores, and the non-correlated Region irrelevant to reading ability. The Core Regions are composed of areas that are most strongly correlated with reading performance. Insular and frontal opercular cortex, lateral temporal cortex, and early auditory cortex occupy the positive Core Region, while inferior temporal and motor cortex occupy the negative Core Region. Aside from those areas, the present study also found more reading-related areas including visual and language-related areas. In addition, connections predicting reading scores are denser inside the reading-related networks than outside. Together, the present study reveals extended reading networks of the brain and provides an extended data-driven analytical framework to study interpretable brain-behavior relationships, which are transferable also to studying other abilities.
(Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)