Twenty years of functional near-infrared spectroscopy: introduction for the special issue

Boas, David A.; Elwell, Clare E.; Ferrari, Marco; Taga, Gentaro

doi:10.1016/j.neuroimage.2013.11.033

Cited by 457 publications

(351 citation statements)

References 68 publications

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“…In fact, the validity of Eqs (5), (6), (10) and (11), is not dependent on the considered geometry. In particular, making use of analytical solutions of the DE in layered geometries [46][47][48][49][50] , numerical evaluations of the relative 〈 z max |t〉 DE and 〈 z max |ρ〉 DE can be obtained with Eqs (5) and (10).…”

Section: Discussionmentioning

confidence: 96%

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Vaessen

Saj̈

Lövblad

et al. 2016

Cortex

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We propose a comprehensive statistical approach describing the penetration depth of light in random media. The presented theory exploits the concept of probability density function f(z|ρ, t) for the maximum depth reached by the photons that are eventually re-emitted from the surface of the medium at distance ρ and time t. Analytical formulas for f, for the mean maximum depth 〈z max 〉 and for the mean average depth z reached by the detected photons at the surface of a diffusive slab are derived within the framework of the diffusion approximation to the radiative transfer equation, both in the time domain and the continuous wave domain. Validation of the theory by means of comparisons with Monte Carlo simulations is also presented. The results are of interest for many research fields such as biomedical optics, advanced microscopy and disordered photonics.

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Section: Discussionmentioning

confidence: 96%

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Vaessen

Saj̈

Lövblad

et al. 2016

Cortex

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“…The animal was placed prone on the bed of the CT scanner on top of a heated blanket used to maintain rectal temperature between 38 and 39 °C throughout the experiment. To place the optical probes directly on the brain, a rectangular piece of scalp tissue (~10 cm 2 ) located laterally to the midline on the right hemisphere was first excised. A caustic pencil was used to cauterize the incised scalp tissue to prevent bleeding.…”

Section: Methodsmentioning

confidence: 99%

“…Near-infrared spectroscopy (NIRS) methods based on the quantification of light absorption at specific wavelengths have been developed for measuring key physiological parameters, such as tissue perfusion, blood volume and oxygenation [1][2][3]. For example, blood flow can be measured by manipulating arterial oxygenation saturation or injecting a light-absorbing contrast agent [4][5][6]; however, these techniques only enable single time-point measurements.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the best flow model to characterize diffuse correlation spectroscopy data acquired directly on the brain

Verdecchia¹,

Diop²,

Morrison³

et al. 2015

Biomed. Opt. Express

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Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique capable of monitoring tissue perfusion. The normalized temporal intensity autocorrelation function generated by DCS is typically characterized by assuming that the movement of erythrocytes can be modeled as a Brownian diffusion-like process instead of by the expected random flow model. Recently, a hybrid model, referred to as the hydrodynamic diffusion model, was proposed, which combines the random and Brownian flow models. The purpose of this study was to investigate the best model to describe autocorrelation functions acquired directly on the brain in order to avoid confounding effects of extracerebral tissues. Data were acquired from 11 pigs during normocapnia and hypocapnia, and flow changes were verified by computed tomography perfusion (CTP). The hydrodynamic diffusion model was found to provide the best fit to the autocorrelation functions; however, no significant difference for relative flow changes measured by the Brownian and hydrodynamic diffusion models was observed.

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“…Non-invasive brain-computer interface (BCI) methods measure brain activities either by detecting the electrophysiological signals [1][2][3] or by determining the hemodynamic responses [4][5][6][7][8][9][10]. The electrophysiological phenomena are generated due to neuronal firing as a result of brain tasks [1].…”

Section: Introductionmentioning

confidence: 99%

Passive BCI based on drowsiness detection: an fNIRS study

Khan

Hong

2015

Biomed. Opt. Express

184

136

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Abstract:We use functional near-infrared spectroscopy (fNIRS) to discriminate the alert and drowsy states for a passive brain-computer interface (BCI). The passive brain signals for the drowsy state are acquired from the prefrontal and dorsolateral prefrontal cortex. The experiment is performed on 13 healthy subjects using a driving simulator, and their brain activity is recorded using a continuous-wave fNIRS system. Linear discriminant analysis (LDA) is employed for training and testing, using the data from the prefrontal, left-and right-dorsolateral prefrontal regions. For classification, eight features are tested: mean oxyhemoglobin, mean deoxyhemoglobin, skewness, kurtosis, signal slope, number of peaks, sum of peaks, and signal peak, in 0~5, 0~10, and 0~15 second time windows, respectively. The results show that the best performance for classification is achieved using mean oxyhemoglobin, the signal peak, and the sum of peaks as features. The average accuracies in the right dorsolateral prefrontal cortex (83.1, 83.4 and 84.9% in the 0~5, 0~10 and 0~15 second time windows, respectively) show that the proposed method has an effective utility for detection of drowsiness for a passive BCI.

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Twenty years of functional near-infrared spectroscopy: introduction for the special issue

Cited by 457 publications

References 68 publications

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Assessment of the best flow model to characterize diffuse correlation spectroscopy data acquired directly on the brain

Passive BCI based on drowsiness detection: an fNIRS study

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