Multi-subject and multi-task experimental validation of the hierarchical Bayesian diffuse optical tomography algorithm.

Diffuse optical tomography (DOT) is an emerging technology for improving the spatial resolution and spatial specificity of conventional multi-channel near-infrared spectroscopy (NIRS) by the use of high-density measurements and an image reconstruction algorithm. We recently proposed a hierarchical Bayesian DOT algorithm that allows for accurate simultaneous reconstruction of scalp and cortical hemodynamic changes, and verified its performance with a phantom experiment, a computer simulation, and experimental data from one human subject. We extend our previous human case study to a multi-subject, multi-task study, to demonstrate the validity of the algorithm on a wider population and varied task conditions.

Extended hierarchical Bayesian diffuse optical tomography for removing scalp artifact.

Functional near-infrared spectroscopy (fNIRS) can non-invasively measure hemodynamic responses in the cerebral cortex with a portable apparatus. However, the observation signal in fNIRS measurements is contaminated by the artifact signal from the hemodynamic response in the scalp. In this paper, we propose a method to separate the signals from the cortex and the scalp by estimating both hemodynamic changes by diffuse optical tomography (DOT).

Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography.

High-density diffuse optical tomography (HD-DOT) is an emerging technique for visualizing the internal state of biological tissues. The large number of overlapping measurement channels due to the use of high-density probe arrays permits the reconstruction of the internal optical properties, even with a reflectance-only measurement. However, accurate three-dimensional reconstruction is still a challenging problem.

Removal of the skin blood flow artifact in functional near-infrared spectroscopic imaging data through independent component analysis.

We investigate whether the functional near-infrared spectroscopic (fNIRS) signal includes a signal from the changing skin blood flow. During a locomotor task on a treadmill, changes in the hemodynamic response in the front-parietal area of healthy human subjects are simultaneously recorded using an fNIRS imaging system and a laser Doppler tissue blood flow meter. Independent component analysis (ICA) for fNIRS signals is performed.

[Examination of NIRS for evaluation of frontal lobe function in diffuse axonal injury (DAI) patients].

The purpose of this study is to compare diffuse axonal injury (DAI) patients with healthy controls by using near infrared spectroscopy (NIRS). The Wisconsin Card Sorting Test Keio Version (KWCST), a standard task paradigm to detect human frontal lobe dysfunction was set as a method. The result of the examination showed that compared with DAI patients, wider increase of total hemoglobin was admitted in the frontal part of the brain of healthy people during the KWCST.

Multimodal assessment of cortical activation during apple peeling by NIRS and fMRI.

An intriguing application of neuroimaging is directly measuring actual human brain activities during daily living. To this end, we investigated cortical activation patterns during apple peeling. We first conducted a pilot study to assess the activation pattern of the whole lateral cortical surface during apple peeling by multichannel near-infrared spectroscopy (NIRS) and detected substantial activation in the prefrontal region in addition to expected activations extending over the motor, premotor and supplementary motor areas.