Dynamic changes of resting state connectivity related to the acquisition of a lexico-semantic skill

The brain undergoes adaptive changes during learning. Spontaneous neural activity has been proposed to play an important role in acquiring new information and/or improve the interaction of task related brain regions. A promising approach is the investigation of resting state functional connectivity...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 146; pp. 429 - 437
Main Authors:	Schlaffke, L., Schweizer, L., Rüther, N.N., Luerding, R., Tegenthoff, M., Bellebaum, C., Schmidt-Wilcke, T.
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01-02-2017 Elsevier Limited
Subjects:	Adaptation Adult Automation Brain Brain - physiology Brain mapping Brain Mapping - methods Female Functional magnetic resonance imaging Humans Language Learning Learning - physiology Magnetic Resonance Imaging Male Neural networks Neural Pathways - physiology Neuronal Plasticity Neuroplasticity Reading Reading comprehension Resting state connectivity Resting state – fMRI Semantics Standard error of measurement Studies Success Young Adult Germany Neuroplasticity DMN IPL ICA SMA iFC LANG Learning fMRI Resting state – fMRI rs-fc Resting state connectivity Language FDR FWE MC BOLD FNC SEM ASN BA OTC
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Summary:	The brain undergoes adaptive changes during learning. Spontaneous neural activity has been proposed to play an important role in acquiring new information and/or improve the interaction of task related brain regions. A promising approach is the investigation of resting state functional connectivity (rs-fc) and resting state networks, which rely on the detection of interregional correlations of spontaneous BOLD fluctuations. Using Morse Code (MC) as a model to investigate neural correlates of lexico-semantic learning we sought to identify patterns in rs-fc that predict learning success and/or undergo dynamic changes during a 10-day training period. Thirty-five participants were trained to decode twelve letters of MC. Rs-fMRI data were collected before and after the training period and rs-fc analyses were performed using a group independent component analysis. Baseline connectivity between the language-network (LANG) and the anterior-salience-network (ASN) predicted learning success and learning was associated with an increase in LANG – ASN connectivity. Furthermore, a disconnection between the default mode network (DMN) and the ASN as well as the left fusiform gyrus, which is critically involved in MC deciphering, was observed. Our findings demonstrate that rs-fc can undergo behaviorally relevant changes within 10 training days, reflecting a learning dependent modulation of interference between task specific networks.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1053-8119 1095-9572
DOI:	10.1016/j.neuroimage.2016.08.065