Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state func...

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Hlavní autoři: John R. Pruett, Jr., Sridhar Kandala, Sarah Hoertel, Abraham Z. Snyder, Jed T. Elison, Tomoyuki Nishino, Eric Feczko, Nico U.F. Dosenbach, Binyam Nardos, Jonathan D. Power, Babatunde Adeyemo, Kelly N. Botteron, Robert C. McKinstry, Alan C. Evans, Heather C. Hazlett, Stephen R. Dager, Sarah Paterson, Robert T. Schultz, D. Louis Collins, Vladimir S. Fonov, Martin Styner, Guido Gerig, Samir Das, Penelope Kostopoulos, John N. Constantino, Annette M. Estes, Steven E. Petersen, Bradley L. Schlaggar, Joseph Piven
Médium: Artigo
Jazyk:Inglês
Vydáno: Elsevier 2015-04-01
Edice:Developmental Cognitive Neuroscience
Témata:
Functional connectivity magnetic resonance imaging (fcMRI)
Infant
Development
Multivariate pattern analysis (MVPA)
Support vector machine (SVM)
Functional brain networks
On-line přístup:http://www.sciencedirect.com/science/article/pii/S1878929315000171
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