Abstract

Functional Near InfraRed Spectroscopy (fNIRS) connectivity analysis is often performed using the measured oxy-haemoglobin (HbO2) signal, while the deoxy-haemoglobin (HHb) is largely ignored. The in-common information of the connectivity networks of both HbO2 and HHb is not regularly reported, or worse, assumed to be similar. Here we describe a methodology that allows the estimation of the symmetry between the functional connectivity (FC) networks of HbO2 and HHb and propose a differential symmetry index (DSI) indicative of the in-common physiological information. Our hypothesis is that the symmetry between FC networks associated with HbO2 and HHb is above what should be expected from random networks. FC analysis was done in fNIRS data collected from six freely-moving healthy volunteers over 16 locations on the prefrontal cortex during a real-world task in an out-of-the-lab environment. In addition, systemic data including breathing rate (BR) and heart rate (HR) were also synchronously collected and used within the FC analysis. FC networks for HbO2 and HHb were established independently using a Bayesian networks analysis. The DSI between both haemoglobin (Hb) networks with and without systemic influence was calculated. The relationship between the symmetry of HbO2 and HHb networks, including the segregational and integrational characteristics of the networks (modularity and global efficiency respectively) were further described. Consideration of systemic information increases the path lengths of the connectivity networks by 3%. Sparse networks exhibited higher asymmetry than dense networks. Importantly, our experimental connectivity networks symmetry between HbO2 and HHb departs from random (t-test: t(509) = 26.39, p < 0.0001). The DSI distribution suggests a threshold of 0.2 to decide whether both HbO2 and HHb FC networks ought to be studied. For sparse FC networks, analysis of both haemoglobin species is strongly recommended. Our DSI can provide a quantifiable guideline for deciding whether to proceed with single or both Hb networks in FC analysis.

Highlights

  • Diffuse near-infrared light can be used to interrogate brain haemodynamics and oxygenation non-invasively [1,2]

  • To separate the mathematical effect of the Jaccard index (Ji) index from the pure physiological effect, we propose a differential symmetry index (DSI) which discounts baseline Ji values expected for random networks

  • We have tackled the problem of quantifying the in-common information expressed from HbO2 and HHb functional connectivity (FC) networks

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Summary

Introduction

Diffuse near-infrared light can be used to interrogate brain haemodynamics and oxygenation non-invasively [1,2]. By measuring the light attenuation changes of the reflected light from the head, functional near infrared spectroscopy (fNIRS) quantifies the relative changes in the brain tissue concentrations of oxygenated (∆[HbO2 ]) and deoxygenated (∆[HHb]) haemoglobin in response. Ignoring the transient inverse response phase, the neuronal activity is inferred from the concomitant increase in HbO2 and decrease in HHb [1,5], consistent with our current understanding of the neurovascular coupling [6,7]. Most approaches for the analysis of connectivity yield a graph’s binary adjacency matrix characterizing the connectivity network. These approaches have two inherent shortcomings: (i) the binarization depends on a threshold that severely affects the graph density with important implications for interpretation [8];

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