title: Novel method to classify hemodynamic response obtained using multi-channel fNIRS measurements into two groups: exploring the combinations of channels.
abstract: Near-infrared spectroscopy (NIRS) in psychiatric studies has widely demonstrated that cerebral hemodynamics differs among psychiatric patients. Recently we found that children with attention-deficit/hyperactivity disorder (ADHD) and children with autism spectrum disorders (ASD) showed different hemodynamic responses to their own mother's face. Based on this finding, we may be able to classify the hemodynamic data into two those groups and predict to which diagnostic group an unknown participant belongs. In the present study, we proposed a novel statistical method for classifying the hemodynamic data of these two groups. By applying a support vector machine (SVM), we searched the combination of measurement channels at which the hemodynamic response differed between the ADHD and the ASD children. The SVM found the optimal subset of channels in each data set and successfully classified the ADHD data from the ASD data. For the 24-dimensional hemodynamic data, two optimal subsets classified the hemodynamic data with 84% classification accuracy, while the subset contained all 24 channels classified with 62% classification accuracy. These results indicate the potential application of our novel method for classifying the hemodynamic data into two groups and revealing the combinations of channels that efficiently differentiate the two groups.
authors: Department of Psychology, Chuo University Tokyo, Japan ; Research and Development Initiative, Chuo University Tokyo, Japan ; Japan Society for the Promotion of Sciences Tokyo, Japan.
authors: Hiroko
authors: H
authors: Ichikawa
authors: Department of Complexity Science and Engineering, The University of Tokyo Kashiwa, Japan.
authors: Jun
authors: J
authors: Kitazono
authors: Department of Complexity Science and Engineering, The University of Tokyo Kashiwa, Japan.
authors: Kenji
authors: K
authors: Nagata
authors: Department of Complexity Science and Engineering, The University of Tokyo Kashiwa, Japan.
authors: Akira
authors: A
authors: Manda
authors: Department of Pediatrics, Dokkyo Medical University Koshigaya Hospital Koshigaya, Japan ; Center for Child Development and Psychosomatic Medicine, Dokkyo Medical University Koshigaya Hospital Koshigaya, Japan.
authors: Keiichi
authors: K
authors: Shimamura
authors: Department of Pediatrics, Dokkyo Medical University Koshigaya Hospital Koshigaya, Japan ; Center for Child Development and Psychosomatic Medicine, Dokkyo Medical University Koshigaya Hospital Koshigaya, Japan.
authors: Ryoichi
authors: R
authors: Sakuta
authors: Department of Complexity Science and Engineering, The University of Tokyo Kashiwa, Japan ; RIKEN Brain Science Institute Wako, Japan.
authors: Masato
authors: M
authors: Okada
authors: Department of Psychology, Chuo University Tokyo, Japan ; Research and Development Initiative, Chuo University Tokyo, Japan.
authors: Masami K
authors: MK
authors: Yamaguchi
authors: Department of Psychology, Japan Women's University Kawasaki, Japan.
authors: So
authors: S
authors: Kanazawa
authors: Department of Integrative Physiology, National Institute for Physiological Sciences Okazaki, Japan.
authors: Ryusuke
authors: R
authors: Kakigi
keywords: attention-deficit/hyperactivity disorder (ADHD); autism spectrum disorders (ASD); hemodynamic data; near-infrared spectroscopy (NIRS); sparse modeling; support vector machine (SVM)