OBJECTIVE: The use of functional near-infrared spectroscopy (fNIRS) is growing, leading to a need for methods to summarise data from multiple studies. However, this is difficult using the current channel-based methods when experiments do not share a common channel (CH) arrangement. Thus, we proposed and implemented a CH-independent analysis method for summarising fNIRS data. METHODS: We defined sub-regions as spatial bins to organise fNIRS data. Sub-regions were defined on the standard brain surface based on macro- and micro-structural information. After probabilistically estimating CH location in standard stereotaxic brain space, the CH-based data were reorganised into these spatial bins to evaluate sub-region-based activation. RESULTS: Sub-regions with sizes corresponding to fNIRS spatial resolution were defined. We demonstrated this method by integrating data from two of our fNIRS studies that shared the same region of interest but used different channel arrangements. CONCLUSIONS: Using this method, data from multiple fNIRS studies with different CH arrangements can be integrated in standard brain space, while keeping in mind the brain structure-function relationship. SIGNIFICANCE: The current method will facilitate an effective use of accumulating fNIRS data by allowing integration of data from multiple studies.
OBJECTIVE: The use of functional near-infrared spectroscopy (fNIRS) is growing, leading to a need for methods to summarise data from multiple studies. However, this is difficult using the current channel-based methods when experiments do not share a common channel (CH) arrangement. Thus, we proposed and implemented a CH-independent analysis method for summarising fNIRS data. METHODS: We defined sub-regions as spatial bins to organise fNIRS data. Sub-regions were defined on the standard brain surface based on macro- and micro-structural information. After probabilistically estimating CH location in standard stereotaxic brain space, the CH-based data were reorganised into these spatial bins to evaluate sub-region-based activation. RESULTS: Sub-regions with sizes corresponding to fNIRS spatial resolution were defined. We demonstrated this method by integrating data from two of our fNIRS studies that shared the same region of interest but used different channel arrangements. CONCLUSIONS: Using this method, data from multiple fNIRS studies with different CH arrangements can be integrated in standard brain space, while keeping in mind the brain structure-function relationship. SIGNIFICANCE: The current method will facilitate an effective use of accumulating fNIRS data by allowing integration of data from multiple studies.
Authors: Franck Amyot; Trelawny Zimmermann; Jason Riley; Jana M Kainerstorfer; Victor Chernomordik; Eric Mooshagian; Laleh Najafizadeh; Frank Krueger; Amir H Gandjbakhche; Eric M Wassermann Journal: Neuroimage Date: 2012-01-28 Impact factor: 6.556
Authors: Franck Amyot; David B Arciniegas; Michael P Brazaitis; Kenneth C Curley; Ramon Diaz-Arrastia; Amir Gandjbakhche; Peter Herscovitch; Sidney R Hinds; Geoffrey T Manley; Anthony Pacifico; Alexander Razumovsky; Jason Riley; Wanda Salzer; Robert Shih; James G Smirniotopoulos; Derek Stocker Journal: J Neurotrauma Date: 2015-09-30 Impact factor: 5.269
Authors: Ning Liu; Charis Mok; Emily E Witt; Anjali H Pradhan; Jingyuan E Chen; Allan L Reiss Journal: Front Hum Neurosci Date: 2016-03-08 Impact factor: 3.169