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ARS Home » Southeast Area » Little Rock, Arkansas » Arkansas Children's Nutrition Center » Microbiome and Metabolism Research » Research » Publications at this Location » Publication #396268

Research Project: Impact of Maternal Influence and Early Dietary Factors on Child Growth, Development, and Metabolic Health

Location: Microbiome and Metabolism Research

Title: Correspondences across 16 group-level functional brain network atlases

item KONG, RUBY - National University Of Singapore
item SPRENG, NATHAN - McGill University - Canada
item NICKERSON, LISA - Harvard Medical School
item FORNITO, ALEX - Monash University
item LAIRD, ANGELA - Florida International University
item RAZI, ADEEL - Monash University
item YENDIKI, ANASTATIA - Harvard University
item GORDON, EVANS - Washington University School Of Medicine
item LARSON-PRIOR, LINDA - University Arkansas For Medical Sciences (UAMS)
item COHEN, JESSICA - University Of North Carolina

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/15/2022
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Population-average functional network atlases are widely used in cognitive and network neuroscience. However, functional networks are not consistently named across brain atlases, resulting in potential confusion in the literature (Uddin et al., 2019). For example, a study of schizophrenia using the Yeo2011 17-network atlas might report significant effects for the salience/ventral attention network-A. Another study of schizophrenia using theGordon2017 17-network atlas might report significant effects for the cingulo-opercular network. This difference in nomenclature would suggest divergence across the two studies, but as will be shown below, the salience/ventral attention network-A from the Yeo2011 17-network atlas overlaps significantly with the cingulo-opercular network from the Gordon2017 17-network atlas, suggesting convergence across the two studies. The opposite situation might occur in which two similarly named networks from two different network atlases might actually have very little spatial overlap. Here, we investigated the consistency of network labels across 16 widely used group-level network atlases.