NDLI: The Neuronal Correlates of Digits Backward Are Revealed by Voxel-Based Morphometry and Resting-State Functional Connectivity Analyses

Content Provider	PubMed Central
Author	Li, Rui Qin, Wen Zhang, Yunting Jiang, Tianzi Yu, Chunshui
Editor	Chialvo, Dante R.
Copyright Year	2012
Abstract	Digits backward (DB) is a widely used neuropsychological measure that is believed to be a simple and effective index of the capacity of the verbal working memory. However, its neural correlates remain elusive. The aim of this study is to investigate the neural correlates of DB in 299 healthy young adults by combining voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) analyses. The VBM analysis showed positive correlations between the DB scores and the gray matter volumes in the right anterior superior temporal gyrus (STG), the right posterior STG, the left inferior frontal gyrus and the left Rolandic operculum, which are four critical areas in the auditory phonological loop of the verbal working memory. Voxel-based correlation analysis was then performed between the positive rsFCs of these four clusters and the DB scores. We found that the DB scores were positively correlated with the rsFCs within the salience network (SN), that is, between the right anterior STG, the dorsal anterior cingulate cortex and the right fronto-insular cortex. We also found that the DB scores were negatively correlated with the rsFC within an anti-correlation network of the SN, between the right posterior STG and the left posterior insula. Our findings suggest that DB performance is related to the structural and functional organizations of the brain areas that are involved in the auditory phonological loop and the SN.
Related Links	http://dx.doi.org/10.1371/journal.pone.0031877
Starting Page	31877
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	2
Volume Number	7
Language	English
Publisher	Public Library of Science
Publisher Date	2012-02-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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