title: Classification and Extraction of Resting State Networks Using Healthy and Epilepsy fMRI Data.
abstract: Functional magnetic resonance imaging studies have significantly expanded the field's understanding of functional brain activity of healthy and patient populations. Resting state (rs-) fMRI, which does not require subjects to perform a task, eliminating confounds of task difficulty, allows examination of neural activity and offers valuable functional mapping information. The purpose of this work was to develop an automatic resting state network (RSN) labeling method which offers value in clinical workflow during rs-fMRI mapping by organizing and quickly labeling spatial maps into functional networks. Here independent component analysis (ICA) and machine learning were applied to rs-fMRI data with the goal of developing a method for the clinically oriented task of extracting and classifying spatial maps into auditory, visual, default-mode, sensorimotor, and executive control RSNs from 23 epilepsy patients (and for general comparison, separately for 30 healthy subjects). ICA revealed distinct and consistent functional network components across patients and healthy subjects. Network classification was successful, achieving 88% accuracy for epilepsy patients with a naïve Bayes algorithm (and 90% accuracy for healthy subjects with a perceptron). The method's utility to researchers and clinicians is the provided RSN spatial maps and their functional labeling which offer complementary functional information to clinicians' expert interpretation.
authors.affiliation: Medical Physics, University of Wisconsin-MadisonMadison, WI, USA; Radiology, University of Wisconsin-MadisonMadison, WI, USA.
authors.forename: Svyatoslav
authors.initials: S
authors.lastname: Vergun
authors.affiliation: Radiology, University of Wisconsin-MadisonMadison, WI, USA; Prism Clinical Imaging, Inc.,Elm Grove, WI, USA.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Gaggl
authors.affiliation: Radiology, University of Wisconsin-Madison Madison, WI, USA.
authors.forename: Veena A
authors.initials: VA
authors.lastname: Nair
authors.affiliation: Radiology, University of Wisconsin-Madison Madison, WI, USA.
authors.forename: Joshua I
authors.initials: JI
authors.lastname: Suhonen
authors.affiliation: Medical Physics, University of Wisconsin-MadisonMadison, WI, USA; Psychiatry, University of Wisconsin-MadisonMadison, WI, USA.
authors.forename: Rasmus M
authors.initials: RM
authors.lastname: Birn
authors.affiliation: Neurological Surgery, University of Wisconsin-Madison Madison, WI, USA.
authors.forename: Azam S
authors.initials: AS
authors.lastname: Ahmed
authors.affiliation: Medical Physics, University of Wisconsin-MadisonMadison, WI, USA; Radiology, University of Wisconsin-MadisonMadison, WI, USA; Biomedical Engineering, University of Wisconsin-MadisonMadison, WI, USA.
authors.forename: M Elizabeth
authors.initials: ME
authors.lastname: Meyerand
authors.affiliation: Prism Clinical Imaging, Inc., Elm Grove, WI, USA.
authors.forename: James
authors.initials: J
authors.lastname: Reuss
authors.affiliation: Radiology, Medical College of WisconsinMilwaukee, WI, USA; Cell Biology, Neurobiology and Anatomy, Medical College of WisconsinMilwaukee, WI, USA; Biophysics, Medical College of WisconsinMilwaukee, WI, USA.
authors.forename: Edgar A
authors.initials: EA
authors.lastname: DeYoe
authors.affiliation: Medical Physics, University of Wisconsin-MadisonMadison, WI, USA; Radiology, University of Wisconsin-MadisonMadison, WI, USA; Psychiatry, University of Wisconsin-MadisonMadison, WI, USA; Biomedical Engineering, University of Wisconsin-MadisonMadison, WI, USA; Psychology, University of Wisconsin-MadisonMadison, WI, USA.
authors.forename: Vivek
authors.initials: V
authors.lastname: Prabhakaran
keywords: classification; independent component analysis; machine learning; resting state fMRI; resting state networks