A quantitative comparison of NIRS and fMRI across multiple cognitive tasks

Abstract

Near infrared spectroscopy (NIRS) is an increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging (fMRI), such as measurement of concentration changes in both oxygenated and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. In the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correlated with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMRI for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp.

Introduction

Cognitive tasks engender local changes in blood flow, volume, and oxygenation in the brain. Functional magnetic resonance imaging (fMRI) and near infrared spectroscopy (NIRS) take advantage of these biophysical phenomena by measuring these hemodynamic correlates of neural activity. fMRI measures the blood oxygen level-dependent (BOLD) response that results from local concentration changes in paramagnetic deoxy-hemoglobin (deoxy-Hb) (Ogawa et al., 1990) and has rapidly become the gold standard for in vivo imaging of human brain activity, due in large part to the relatively high spatial resolution afforded by this technique. However, fMRI also presents several challenges such as high sensitivity to participant motion, a loud, restrictive environment, low temporal resolution, and relatively high cost. Some of these challenges are overcome with optical imaging: NIRS measures changes in oxygenated and deoxygenated hemoglobin (oxy- and deoxy-Hb) from the cortical surface and is less invasive and expensive than fMRI.

NIRS of the human brain is a relatively flexible technology and to date has been successfully applied in several domains. NIRS measures changes in both oxy- and deoxy-Hb and has been used to provide insight into the physiological mechanisms of the BOLD response (Toronov et al., 2003, Hoge et al., 2005, Kleinschmidt et al., 1996, Schroeter et al., 2006, Emir et al., 2008, Malonek et al., 1997, Huppert et al., 2006b, Huppert et al., 2007, Huppert et al., 2009). NIRS can be very portable (Atsumori et al., 2009) and has been proposed as a useful technology for non-invasive brain–computer interfaces (Power et al., 2010, Coyle et al., 2004, Coyle et al., 2007, Sitaram et al., 2007, Utsugi et al., 2008). NIRS has been used to study brain activity in both active tasks and resting states (Boecker et al., 2007, Herrmann et al., 2005, White et al., 2009, Honda et al., 2010, Zhang et al., 2010, Lu et al., 2010) and may be particularly useful with experimental paradigms that are not well suited to the MRI scanner, such as face-to-face communication (Suda et al., 2010) or driving (Tomioka et al., 2009).

While NIRS presents several advantages, there are also several disadvantages to this technology. Compared to fMRI, the signal-to-noise ratio (SNR) is low and the spatial resolution of NIRS is poor. The trajectory of the photon path from emitter to detector is assumed to be a ‘banana’ shape between the two probes (van der Zee et al., 1990, Okada et al., 1997), but positioning the probes above target brain regions of interest can be challenging (Kleinschmidt et al., 1996). It is also unclear how deeply into the brain NIRS measures in practice.

NIRS signals can be conceptually compared to the BOLD response measured with fMRI using the balloon model (Buxton et al., 1998, Obata et al., 2004), which relates changes in BOLD to changes in deoxy-Hb and regional cerebral blood volume (rCBV). In practice, several studies have used simultaneous measurement of NIRS and fMRI to better understand the generation of the BOLD response. See Steinbrink et al. (2006) for a review of combined fMRI/NIRS studies. In one of the earliest simultaneous experiments, Kleinschmidt et al. (1996) recorded both fMRI and NIRS signals over ipsi- and contralateral motor cortex during a finger tapping task and confirmed that an increase in BOLD in motor cortex contralateral to the moving hand was correlated with a decrease in deoxy-Hb concentration. Strangman et al. (2002) performed a similar motor paradigm and found that oxy-Hb correlated most robustly with the BOLD response. This may be partly attributable to a higher SNR in oxy-Hb. Several other studies have found good correlation between NIRS and fMRI signals (Mehagnoul-Schipper et al., 2002, Kennan et al., 2002, Okamoto et al., 2004, Hoge et al., 2005, Toronov et al., 2001a, Toronov et al., 2001b, Huppert et al., 2006b) in both simultaneous and sequential acquisitions on a range of tasks including motor, language, and visual tasks.

It is of great practical interest for cognitive neuroscience researchers considering NIRS as an experimental tool to gain a better understanding of how NIRS compares with fMRI in terms of SNR, spatial resolution, and temporal correspondence. The majority of combined fMRI/NIRS studies to date have been performed using motor (Okamoto et al., 2004, Kleinschmidt et al., 1996, Mehagnoul-Schipper et al., 2002, Toronov et al., 2001a, Toronov et al., 2003, Strangman et al., 2002, Boas et al., 2003, Hoge et al., 2005, Huppert et al., 2006a, Huppert et al., 2006b, Huppert et al., 2008) or visual (Toronov et al., 2007, Zhang et al., 2005a, Zhang et al., 2006, Abdelnour et al., 2009) tasks, and it remains unclear whether one would draw similar conclusions using cognitive tasks with more subtle effects. In this study we address this question by scanning participants simultaneously with NIRS and fMRI on a battery of cognitive tasks. We analyze the data from two perspectives, first investigating the temporal correlation between NIRS and fMRI signals in proximal regions of interest (ROIs) and second, exploring the spatial distribution of fMRI voxels that best correlate with the NIRS signal.

The data presented here are uniquely comprehensive among combined NIRS/fMRI studies to date in that we have included measurements from multiple brain regions, across multiple cognitive domains, and in a relatively large number of participants. The breadth of this data set allows us to make detailed comparisons of NIRS and BOLD signals in terms of SNR and temporal and spatial correspondence. We hypothesized that we would find strong correlations between the NIRS signals and proximal fMRI voxels, but that this correlation might be stronger in tasks with higher SNR, and weaker when the photons travel a larger distance from the scalp to the brain's surface. In the spatial domain, we explored several possible ROI shapes, to empirically confirm the effective measurement area of NIRS channels.