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. We measured brain activity during three graded tasks (hand movement, index finger movement, and no-movement), in 12 subjects, using high-density NIRS and functional magnetic resonance imaging (fMRI), acquired in different sessions. The reconstruction performance of our algorithm, and the current gold-standard method for DOT image reconstruction, were evaluated using the blood-oxygenation-level-dependent (BOLD) signals of the fMRI as a reference. In comparison with the BOLD signals, our method achieved a median localization error of 6 and 8mm, and a spatial-pattern similarity of 0.6 and 0.4 for the hand and finger tasks, respectively. It also did not reconstruct any activity in the no-movement task. Compared with the current gold-standard method, the new method showed fewer false positives, which resulted in improved spatial-pattern similarity, although the localization errors of the main activity clusters were comparable.

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). In the inverse problem of DOT, we introduce smooth regularization to the hemodynamic change in the scalp and sparse regularization to that in the cortex based on the nature of the hemodynamic responses. These appropriate regularization models, with the spatial information of optical paths of many measurement channels, allow three-dimensional reconstruction of both hemodynamic changes. We validate our proposed method through two-layer phantom experiments and MRI-based head-model simulations. In both experiments, the proposed method simultaneously estimates the superficial smooth activity in the scalp area and the deep localized activity in the cortical area.

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. First, the exponentially decaying sensitivity causes a systematic depth-localization error. Second, the nature of diffusive light makes the image blurred. In this paper, we propose a three-dimensional reconstruction method that overcomes these two problems by introducing sensitivity-normalized regularization and sparsity into the hierarchical Bayesian method. Phantom experiments were performed to validate the proposed method under three conditions of probe interval: 26 mm, 18.4 mm, and 13 mm. We found that two absorbers with distances shorter than the probe interval could be discriminated under the high-density conditions of 18.4-mm and 13-mm intervals. This discrimination ability was possible even if the depths of the two absorbers were different from each other. These results show the high spatial resolution of the proposed method in both depth and horizontal directions.

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. The skin blood flow changes during locomotor tasks on a treadmill. The activated spatial distribution of one of the components separated by ICA reveals an overall increase in fNIRS channels. To evaluate the uniformity of the activated spatial distribution, we define a new statistical value-the coefficient of spatial uniformity (CSU). The CSU value is a highly discriminating value (e.g., 2.82) compared with values of other components (e.g., 1.41, 1.10, 0.96, 0.61, and 0.58). In addition, the independent component signal corresponding to the activated spatial distribution is similar to changes in skin blood flow measured with the laser Doppler tissue blood flow meter. The coefficient of correlation indicates strong correlation. Localized activation areas around the premotor and medial somatosensory cortices are shown more clearly by eliminating the extracted component.

[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. This suggests that NIRS would serve as an objective indicator to evaluate the frontal lobe function in DAI patients.

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. We next examined cortical activation during mock apple peeling by simultaneous measurement using multichannel NIRS and functional magnetic resonance imaging (fMRI) in four subjects. We detected activations extending over the motor, premotor and supplementary motor areas, but not in the prefrontal cortex. Thus, we finally focused on the prefrontal cortex and examined its activation during apple peeling in 12 subjects using a multichannel NIRS. We subsequently found that regional concentrations of oxygenated hemoglobin significantly increased in the measured region, which encompassed portions of the dorsolateral, ventrolateral and frontopolar areas of the prefrontal cortex. The current study demonstrated that apple peeling as practiced in daily life recruited the prefrontal cortex but that such activation might not be detected for less laborious mock apple peeling that can be performed in an fMRI environment. We suggest the importance of cortical study of an everyday task as it is but not as a simplified form; we also suggest the validity of NIRS for this purpose. Studies on everyday tasks may serve as stepping stone toward understanding human activities in terms of cortical activations.