Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

• Published in: Frontiers in neuroinformatics Vol. 11; p. 61
• Main Authors: Meszlényi, Regina J., Buza, Krisztian, Vidnyánszky, Zoltán
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 17.10.2017; Frontiers Media S.A
• Subjects: Artificial intelligence; Brain; Classification; Cognitive ability; connectome; convolutional neural network; Datasets; Deep learning; Design; Dynamic Time Warping; Functional magnetic resonance imaging; Learning algorithms; Machine learning; Neighborhoods; Neural networks; Neuroscience; resting state connectivity; Sparsity; Hungary; connectome; Dynamic Time Warping; classification; resting state connectivity; convolutional neural network; functional magnetic resonance imaging

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this p...