Resting-state functional connectivity in the human brain revealed with diffuse optical tomography

Abstract

Mapping resting-state networks allows insight into the brain's functional architecture and physiology and has rapidly become important in contemporary neuroscience research. Diffuse optical tomography (DOT) is an emerging functional neuroimaging technique with the advantages, relative to functional magnetic resonance imaging (fMRI), of portability and the ability to simultaneously measure both oxy- and deoxyhemoglobin. Previous optical studies have evaluated the temporal features of spontaneous resting brain signals. Herein, we develop techniques for spatially mapping functional connectivity with DOT (fc-DOT). Simultaneous imaging over the motor and visual cortices yielded robust correlation maps reproducing the expected functional neural architecture. The localization of the maps was confirmed with task-response studies and with subject-matched fc-MRI. These fc-DOT methods provide a task-less approach to mapping brain function in populations that were previously difficult to research. Our advances may permit new studies of early childhood development and of unconscious patients. In addition, the comprehensive hemoglobin contrasts of fc-DOT enable innovative studies of the biophysical origin of the functional connectivity signal.

Introduction

Optical neuroimaging has never lacked clinical potential, due to its ability to longitudinally and non-invasively monitor brain function. However, progress towards the bedside practice of methods to map brain function, such as functional near infrared spectroscopy (fNIRS), has been hindered by conceptual and technical limitations. One obstacle is that task-based neuroimaging, which is standard in cognitive neuroscience research, is generally ill-suited to clinical populations since they may be unable to perform any task. Recently in functional magnetic resonance imaging (fMRI), it was discovered that even during the absence of overt tasks, fluctuations in brain activity are correlated across functionally-related cortical regions (Biswal et al., 1995). Thus, the spatial and temporal evaluation of spontaneous neuronal activity has allowed mapping of these resting-state networks (RSNs) (Fox and Raichle, 2007). Translating these advances to optical techniques would enable new clinical and developmental studies. Yet, mapping spontaneous activity with fNIRS measurements presents significant challenges due to the obscuring influences of superficial signals, systemic physiology, and auto-regulation. In this paper, we develop three-dimensional diffuse optical tomography (DOT) (Zeff and White, 2007, Yodh and Chance, 1995, Joseph and Huppert, 2006, Bluestone and Abdoulaev, 2001, Gibson and Austin, 2006) and linear regression techniques that, combined with correlation analysis, allow us to isolate functional maps from resting-state measurements and demonstrate the feasibility of functional connectivity DOT (fc-DOT).

Low frequency fluctuations in cerebral hemodynamics have been detected by NIRS (Obrig and Neufang, 2000, Elwell and Springett, 1999). However, as the optical signal is a mixture of hemodynamics within the scalp, skull, and brain, it is particularly susceptible to artifacts from systemic changes. Such fluctuations have been found to obscure functional responses in fNIRS studies (Jasdzewski and Strangman, 2003, Boden and Obrig, 2007). In addition, their frequency components overlap those of RSNs. As with fc-MRI, these systemic contributions must be removed to observe the underlying spatial maps of the brain networks. In part because fNIRS has traditionally had difficulty in separating different physiologic contributions, previous resting-state studies have focused on investigating the correlation between the measured signal and systemic physiological variables (Rowley and Payne, 2007, Reinhard and Wehrle-Wieland, 2006, Katura and Tanaka, 2006, Franceschini and Joseph, 2006). While such experiments have yielded interesting results, including some within the clinical setting (Schroeter et al., 2005), they have not moved beyond temporal analysis to the study of spatial correlations and neural connectivity. fNIRS also suffers from spatial limitations. Low spatial resolution (> 3 cm) may average out any underlying spatial correlation structure. In addition, an fNIRS study to detect RSNs requires a field-of-view greater than typically available in order to cover both correlated and uncorrelated (e.g., control) brain regions.

While there are multiple challenges, both physiological and methodological, to the development of fc-DOT systems, their successful creation would open up new approaches to the research of resting-state physiology. The discovery of functional connectivity (fc-MRI) has led to its use as an important tool throughout neuroimaging research (Fox and Raichle, 2007), including insights into childhood brain development (Fair and Dosenbach, 2007, Fransson and Skiold, 2007, Fair and Cohen, 2008). Recent fc-MRI studies have found RSNs that are altered in patients with depression (Greicius et al., 2007), Alzheimer's disease (Greicius et al., 2004), and Tourette syndrome (Church et al., 2009). However, important brain-injured populations, such as intensive care patients, cannot be easily transported to fixed scanner environments. The portability and wearability (Obrig and Villringer, 2003) of fc-DOT systems could allow significant applications in populations that are not amenable to traditional functional neuroimaging, such as hospitalized patients and young children.

In addition, DOT provides a more comprehensive assessment of hemodynamics and metabolism than the blood oxygenation level-dependent (BOLD) signal, due to BOLD's complicated connection to the underlying neurovascular coupling (Raichle and Mintun, 2006, Heeger and Ress, 2002). While relying on the neurovascular response in much the same manner as BOLD-fMRI, DOT can measure changes in oxy - (HbO₂), deoxy - (HbR), and total hemoglobin (HbT) (the BOLD contrast is mostly sensitive to HbR) at a much higher sampling rate (at least 10 Hz, compared to ∼ 0.5 Hz with fMRI) (Steinbrink et al., 2006). This enhanced view of brain activity is especially important when the neurovascular coupling is either unknown (as in infants) (Born and Leth, 1998, Morita and Kochiyama, 2000, Colonnese and Phillips, 2008) or altered (as with brain injury) (Fujiwara and Sakatani, 2004, Bonakdarpour and Parrish, 2007, Zou and Mulhern, 2005, Iadecola, 2004, D'Esposito and Deouell, 2003).

To address our goal of fc-DOT mapping, we developed a DOT system with extended field-of-view that provides unique simultaneous 3D imaging of distributed cortical regions covering both the visual and motor cortices with high resolution. These spatial techniques are complemented by linear regression methods that remove global superficial signals and correlation analyses to map spontaneous brain activity patterns. We judge the success of fc-DOT by our ability to obtain spatial correlations maps based on local physiology that match the fc-MRI literature and our own subject-matched fc-MRI experiments. Functional connectivity was first demonstrated by BOLD-fMRI detecting low-frequency variations in the motor cortex during the resting state (Biswal et al., 1995). fc-MRI's original validation was that the resulting spatial correlations corresponded with the brain's functional architecture as mapped by task-induced responses. Previous fc-MRI studies have also demonstrated that the motor and visual cortices constitute largely independent functional networks, each exhibiting high levels of inter-hemispheric correlation (De Luca et al., 2006, Damoiseaux and Rombouts, 2006). We, thus, expect resting-state analysis of seed regions found from a sensory task-response study to reveal that sensory network, while the other sensory network will provide a control that should be uncorrelated. These studies aim to establish the utility of DOT for functional connectivity analysis.