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A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy

Hahn, T; Marquand, AF; Plichta, MM; Ehlis, AC; Schecklmann, MW; Dresler, T; Jarczok, TA; ... Fallgatter, AJ; + view all (2013) A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy. Human Brain Mapping , 34 (5) 1102 - 1114. 10.1002/hbm.21497. Green open access

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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.

Type: Article
Title: A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/hbm.21497
Publisher version: http://dx.doi.org/10.1002/hbm.21497
Language: English
Additional information: © 1999-2013 John Wiley & Sons, Inc. All Rights Reserved. Full text made available to UCL Discovery by kind permission of Wiley.
Keywords: Disease prevalence, Single subject classification, Schizophrenia, Temporal classification
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1378095
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