title: A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy.
abstract: Pattern recognition approaches to the analysis of neuroimaging data have brought new applications such as the classification of patients and healthy controls within reach. In our view, the reliance on expensive neuroimaging techniques which are not well tolerated by many patient groups and the inability of most current biomarker algorithms to accommodate information about prior class frequencies (such as a disorder's prevalence in the general population) are key factors limiting practical application. To overcome both limitations, we propose a probabilistic pattern recognition approach based on cheap and easy-to-use multi-channel near-infrared spectroscopy (fNIRS) measurements. We show the validity of our method by applying it to data from healthy controls (n = 14) enabling differentiation between the conditions of a visual checkerboard task. Second, we show that high-accuracy single subject classification of patients with schizophrenia (n = 40) and healthy controls (n = 40) is possible based on temporal patterns of fNIRS data measured during a working memory task. For classification, we integrate spatial and temporal information at each channel to estimate overall classification accuracy. This yields an overall accuracy of 76% which is comparable to the highest ever achieved in biomarker-based classification of patients with schizophrenia. In summary, the proposed algorithm in combination with fNIRS measurements enables the analysis of sub-second, multivariate temporal patterns of BOLD responses and high-accuracy predictions based on low-cost, easy-to-use fNIRS patterns. In addition, our approach can easily compensate for variable class priors, which is highly advantageous in making predictions in a wide range of clinical neuroimaging applications.
authors.affiliation: Department of Cognitive Psychology II, Johann Wolfgang Goethe University Frankfurt/Main, Frankfurt am Main, Germany. TimHahn@gmx.net
authors.forename: Tim
authors.initials: T
authors.lastname: Hahn
authors.forename: Andre F
authors.initials: AF
authors.lastname: Marquand
authors.forename: Michael M
authors.initials: MM
authors.lastname: Plichta
authors.forename: Ann-Christine
authors.initials: AC
authors.lastname: Ehlis
authors.forename: Martin W
authors.initials: MW
authors.lastname: Schecklmann
authors.forename: Thomas
authors.initials: T
authors.lastname: Dresler
authors.forename: Tomasz A
authors.initials: TA
authors.lastname: Jarczok
authors.forename: Elisa
authors.initials: E
authors.lastname: Eirich
authors.forename: Christine
authors.initials: C
authors.lastname: Leonhard
authors.forename: Andreas
authors.initials: A
authors.lastname: Reif
authors.forename: Klaus-Peter
authors.initials: KP
authors.lastname: Lesch
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Brammer
authors.forename: Janaina
authors.initials: J
authors.lastname: Mourao-Miranda
authors.forename: Andreas J
authors.initials: AJ
authors.lastname: Fallgatter
mesh_terms: D000328:Adult; D001931:Brain Mapping; D005260:Female; D007839:Functional Laterality; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D008297:Male; D008570:Memory, Short-Term; D008875:Middle Aged; D008960:Models, Psychological; D009211:Myoglobin / Q000378:metabolism; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation; D011237:Predictive Value of Tests; D011336:Probability; D015203:Reproducibility of Results; D012559:Schizophrenia / Q000145:classification / Q000175:diagnosis; D019265:Spectroscopy, Near-Infrared; D014793:Visual Cortex / Q000502:physiology*; D014825:Vocabulary; D055815:Young Adult
chemical_list: D006454:Hemoglobins; D009211:Myoglobin