Large-scale cortical network properties predict future sound-to-word learning success
Journal of Cognitive Neuroscience, ISSN: 0898-929X, Vol: 24, Issue: 5, Page: 1087-1103
2012
- 42Citations
- 85Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations42
- Citation Indexes42
- 42
- CrossRef33
- Captures85
- Readers85
- 85
Article Description
The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants' future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-toword learning abilities among healthy, younger adults. © 2012 Massachusetts Institute of Technology.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84859151158&origin=inward; http://dx.doi.org/10.1162/jocn_a_00210; http://www.ncbi.nlm.nih.gov/pubmed/22360625; https://direct.mit.edu/jocn/article/24/5/1087/27775/Large-scale-Cortical-Network-Properties-Predict; http://www.mitpressjournals.org/doi/abs/10.1162/jocn_a_00210
MIT Press - Journals
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