• Daisuke Tsuzuki and Ippeita Dan.
• Functional Brain Science Laboratory, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan; Applied Cognitive Neuroscience Laboratory, Research and Development Initiatives, Chuo University, 1-13-27 Kasuga, Bunkyo-ward, Tokyo 112-8551, Japan. Electronic address: tsuzukid@tamacc.chuo-u.ac.jp.
• Neuroimage. 2014 Jan 15; 85 Pt 1: 92-103.

AbstractFunctional near-infrared spectroscopy (fNIRS) has now become widely accepted as a common functional imaging modality. In order for fNIRS to achieve genuine neuroimaging citizenship, it would ideally be equipped with functional and structural image analyses. However, fNIRS measures cortical activities from the head surface without anatomical information of the object being measured. In this review article, we will present a methodological overview of spatial registration of fNIRS data to overcome this technical drawback of fNIRS. We first introduce and explore the use of standard stereotaxic space and anatomical labeling. Second, we explain different ways of describing scalp landmarks using 10-20 based systems. Third, we describe the simplest case of fNIRS data co-registration to a subject's own MRI. Fourth, we extend the concept to fNIRS data registration of group data. Fifth, we describe probabilistic registration methods, which use a reference-MRI database instead of a subject's own MRIs, and thus enable MRI-free registration for standalone fNIRS data. Sixth, we further extend the concept of probabilistic registration to three-dimensional image reconstruction in diffuse optical tomography. Seventh, we describe a 3D-digitizer-free method for the virtual registration of fNIRS data. Eighth, we provide practical guidance on how these techniques are implemented in software. Finally, we provide information on current resources and limitations for spatial registration of child and infant data. Through these technical descriptions, we stress the importance of presenting fNIRS data on a common platform to facilitate both intra- and inter-modal data sharing among the neuroimaging community. © 2013 Elsevier Inc. All rights reserved.

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