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Recognition memory performance can be estimated based on brain activation networks
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4635636
Author(s) Petrovska, Jana; Loos, Eva; Coynel, David; Egli, Tobias; Papassotiropoulos, Andreas; de Quervain, Dominique J.-F.; Milnik, Annette
Author(s) at UniBasel Papassotiropoulos, Andreas
de Quervain, Dominique
Coynel, David
Milnik, Annette
Year 2021
Title Recognition memory performance can be estimated based on brain activation networks
Journal Behavioural Brain Research
Volume 408
Pages / Article-Number 113285
Keywords Independent component analysis (ICA); Memory; Prediction; Recognition; fMRI
Mesh terms Adult; Brain, physiology; Brain Mapping; Female; Humans; Magnetic Resonance Imaging; Male; Nerve Net, physiology; Pattern Recognition, Visual, physiology; Recognition, Psychology, physiology; Young Adult
Abstract Recognition memory is an essential ability for functioning in everyday life. Establishing robust brain networks linked to recognition memory performance can help to understand the neural basis of recognition memory itself and the interindividual differences in recognition memory performance.; We analysed behavioural and whole-brain fMRI data from 1'410 healthy young adults during the testing phase of a picture-recognition task. Using independent component analysis (ICA), we decomposed the fMRI contrast for previously seen vs. new (old-new) pictures into networks of brain activity. This was done in two independent samples (training sample: N = 645, replication sample: N = 665). Next, we investigated the relationship between the identified brain networks and interindividual differences in recognition memory performance by conducting a prediction analysis. We estimated the prediction accuracy in a third independent sample (test sample: N = 100).; We identified 12 robust and replicable brain networks using two independent samples. Based on the activity of those networks we could successfully estimate interindividual differences in recognition memory performance with high accuracy in a third independent sample (r = 0.5, p = 1.29 × 10; -07; ).; Given the robustness of the ICA decomposition as well as the high prediction estimate, the identified brain networks may be considered as potential biomarkers of recognition memory performance in healthy young adults and can be further investigated in the context of health and disease.
Publisher Elsevier
ISSN/ISBN 0166-4328 ; 1872-7549
edoc-URL https://edoc.unibas.ch/85898/
Full Text on edoc Available
Digital Object Identifier DOI 10.1016/j.bbr.2021.113285
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/33819531
ISI-Number 000646453600008
Document type (ISI) Journal Article
 
   

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