Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture

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Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán;
  • Publisher: Frontiers Media S.A.
  • Journal: Frontiers in Neuroinformatics,volume 11 (eissn: 1662-5196)
  • Publisher copyright policies & self-archiving
  • Related identifiers: pmc: PMC5651030, doi: 10.3389/fninf.2017.00061
  • Subject: Dynamic Time Warping | Computer Science - Computer Vision and Pattern Recognition | Statistics - Machine Learning | Neuroscience | Methods | convolutional neural network | 68T99 | I.5.2 | classification | resting state connectivity | Computer Science - Learning | I.5.1 | connectome | functional magnetic resonance imaging
    arxiv: Quantitative Biology::Neurons and Cognition

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... View more
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