کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5631353 | 1580864 | 2017 | 9 صفحه PDF | دانلود رایگان |
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.
Journal: NeuroImage - Volume 146, 1 February 2017, Pages 429-437