title: SCoRS--A Method Based on Stability for Feature Selection and Mapping inNeuroimaging [corrected].
abstract: Feature selection (FS) methods play two important roles in the context of neuroimaging based classification: potentially increase classification accuracy by eliminating irrelevant features from the model and facilitate interpretation by identifying sets of meaningful features that best discriminate the classes. Although the development of FS techniques specifically tuned for neuroimaging data is an active area of research, up to date most of the studies have focused on finding a subset of features that maximizes accuracy. However, maximizing accuracy does not guarantee reliable interpretation as similar accuracies can be obtained from distinct sets of features. In the current paper we propose a new approach for selecting features: SCoRS (survival count on random subsamples) based on a recently proposed Stability Selection theory. SCoRS relies on the idea of choosing relevant features that are stable under data perturbation. Data are perturbed by iteratively sub-sampling both features (subspaces) and examples. We demonstrate the potential of the proposed method in a clinical application to classify depressed patients versus healthy individuals based on functional magnetic resonance imaging data acquired during visualization of happy faces.
authors.forename: Jane M
authors.initials: JM
authors.lastname: Rondina
authors.forename: Tim
authors.initials: T
authors.lastname: Hahn
authors.forename: Leticia
authors.initials: L
authors.lastname: de Oliveira
authors.forename: Andre F
authors.initials: AF
authors.lastname: Marquand
authors.forename: Thomas
authors.initials: T
authors.lastname: Dresler
authors.forename: Thomas
authors.initials: T
authors.lastname: Leitner
authors.forename: Andreas J
authors.initials: AJ
authors.lastname: Fallgatter
authors.forename: John
authors.initials: J
authors.lastname: Shawe-Taylor
authors.forename: Janaina
authors.initials: J
authors.lastname: Mourao-Miranda
mesh_terms: D001931:Brain Mapping / Q000379:methods*; D003863:Depression / Q000175:diagnosis* / Q000503:physiopathology*; D005074:Evoked Potentials, Visual; D006240:Happiness; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014793:Visual Cortex / Q000503:physiopathology*; D014796:Visual Perception
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