Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool for studying evoked hemodynamic changes within the brain. By this technique, changes in the optical absorption of light are recorded over time and are used to estimate the functionally evoked changes in cerebral oxyhemoglobin and deoxyhemoglobin concentrations that result from local cerebral vascular and oxygen metabolic effects during brain activity. Over the past three decades this technology has continued to grow, and today NIRS studies have found many niche applications in the fields of psychology, physiology, and cerebral pathology. The growing popularity of this technique is in part associated with a lower cost and increased portability of NIRS equipment when compared with other imaging modalities, such as functional magnetic resonance imaging and positron emission tomography. With this increasing number of applications, new techniques for the processing, analysis, and interpretation of NIRS data are continually being developed. We review some of the time-series and functional analysis techniques that are currently used in NIRS studies, we describe the practical implementation of various signal processing techniques for removing physiological, instrumental, and motion-artifact noise from optical data, and we discuss the unique aspects of NIRS analysis in comparison with other brain imaging modalities. These methods are described within the context of the MATLAB-based graphical user interface program, HomER, which we have developed and distributed to facilitate the processing of optical functional brain data.

Although the trigeminal nerve innervates the meninges and participates in the genesis of migraine headaches, triggering mechanisms remain controversial and poorly understood. Here we establish a link between migraine aura and headache by demonstrating that cortical spreading depression, implicated in migraine visual aura, activates trigeminovascular afferents and evokes a series of cortical meningeal and brainstem events consistent with the development of headache. Cortical spreading depression caused long-lasting blood-flow enhancement selectively within the middle meningeal artery dependent upon trigeminal and parasympathetic activation, and plasma protein leakage within the dura mater in part by a neurokinin-1-receptor mechanism. Our findings provide a neural mechanism by which extracerebral cephalic blood flow couples to brain events; this mechanism explains vasodilation during headache and links intense neurometabolic brain activity with the transmission of headache pain by the trigeminal nerve.

Abstract. First introduced in the 1980s, laser speckle contrast imaging is a powerful tool for full-field imaging of blood flow. Recently laser speckle contrast imaging has gained increased attention, in part due to its rapid adoption for blood flow studies in the brain. We review the underlying physics of speckle contrast imaging and discuss recent developments to improve the quantitative accuracy of blood flow measures. We also review applications of laser speckle contrast imaging in neuroscience, dermatology and ophthalmology.

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A method for dynamic, high-resolution cerebral blood flow (CBF) imaging is presented in this article. By illuminating the cortex with laser light and imaging the resulting speckle pattern, relative CBF images with tens of microns spatial and millisecond temporal resolution are obtained. The regional CBF changes measured with the speckle technique are validated through direct comparison with conventional laser-Doppler measurements. Using this method, dynamic images of the relative CBF changes during focal cerebral ischemia and cortical spreading depression were obtained along with electrophysiologic recordings. Upon middle cerebral artery (MCA) occlusion, the speckle technique yielded high-resolution images of the residual CBF gradient encompassing the ischemic core, penumbra, oligemic, and normally perfused tissues over a 6 x 4 mm cortical area. Successive speckle images demonstrated a further decrease in residual CBF indicating an expansion of the ischemic zone with finely delineated borders. Dynamic CBF images during cortical spreading depression revealed a 2 to 3 mm area of increased CBF (160% to 250%) that propagated with a velocity of 2 to 3 mm/min. This technique is easy to implement and can be used to monitor the spatial and temporal evolution of CBF changes with high resolution in studies of cerebral pathophysiology.

We report a parallel Monte Carlo algorithm accelerated by graphics processing units (GPU) for modeling time-resolved photon migration in arbitrary 3D turbid media. By taking advantage of the massively parallel threads and low-memory latency, this algorithm allows many photons to be simulated simultaneously in a GPU. To further improve the computational efficiency, we explored two parallel random number generators (RNG), including a floating-point-only RNG based on a chaotic lattice. An efficient scheme for boundary reflection was implemented, along with the functions for time-resolved imaging. For a homogeneous semi-infinite medium, good agreement was observed between the simulation output and the analytical solution from the diffusion theory. The code was implemented with CUDA programming language, and benchmarked under various parameters, such as thread number, selection of RNG and memory access pattern. With a low-cost graphics card, this algorithm has demonstrated an acceleration ratio above 300 when using 1792 parallel threads over conventional CPU computation. The acceleration ratio drops to 75 when using atomic operations. These results render the GPU-based Monte Carlo simulation a practical solution for data analysis in a wide range of diffuse optical imaging applications, such as human brain or small-animal imaging.

Near-infrared spectroscopy (NIRS) and diffuse optical imaging (DOI) are finding widespread application in the study of human brain activation, motivating further application-specific development of the technology. NIRS and DOI offer the potential to quantify changes in deoxyhemoglobin (HbR) and total hemoglobin (HbT) concentration, thus enabling distinction of oxygen consumption and blood flow changes during brain activation. While the techniques implemented presently provide important results for cognition and the neurosciences through their relative measures of HbR and HbT concentrations, there is much to be done to improve sensitivity, accuracy, and resolution. In this paper, we review the advances currently being made and issues to consider for improving optical image quality. These include the optimal selection of wavelengths to minimize random and systematic error propagation in the calculation of the hemoglobin concentrations, the filtering of systemic physiological signal clutter to improve sensitivity to the hemodynamic response to brain activation, the implementation of overlapping measurements to improve image spatial resolution and uniformity, and the utilization of spatial prior information from structural and functional MRI to reduce DOI partial volume error and improve image quantitative accuracy. D 2004 Elsevier Inc. All rights reserved.

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