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Discrimination of Resting-State fMRI for Schizophrenia Patients with Lattice Computing Based Features

  • Darya Chyzhyk
  • Manuel Graña
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8073)

Abstract

Resting state fMRI data can be used to find biomarkers of specific neurological conditions, such as schizophrenia. In this paper we report results on the discrimination between schizophrenia patients and healthy control, as well as the discrimination of subpopulations of schizophrenia patients with and without auditory hallucinations. Data features for classification are obtained as follows: a Multivariate reduced ordering based on a h-function constructed from Lattice Autoassociative Memories recall. The Pearson correlation coefficient between the h-function values and the categorical variable at each voxel site allows to identify the most informative voxel sites. Feature vectors are constructed as the h-function values at these sites. Results on a database of healthy controls and schizophrenia patients with and without auditory hallucinations show that the approach can provide accurate discrimination between these populations.

Keywords

Functional Connectivity Independent Component Analysis Schizophrenia Patient Independent Component Analysis Auditory Hallucination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Darya Chyzhyk
    • 1
  • Manuel Graña
    • 1
  1. 1.Computational Intelligence Group Dept. CCIAUPV/EHUSan SebastianSpain

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