Simulation and in vivo investigation of light-emitting diode, near infrared Gaussian beam profiles

Abstract

Near infrared spectroscopy is an optical imaging technique which offers a non-invasive, portable, and low-cost method for continuously measuring the oxygenation of tissues. In particular, it can provide the brain activation through measuring the blood oxygenation and blood volume in the cortex. Understanding and then improving the spatial and depth sensitivity of near infrared spectroscopy measurements to brain tissue are essential for designing experiments as well as interpreting research findings. In this study, we investigate the effect of applying two common light beam profiles including Uniform and Gaussian on the penetration depth of an LED-based near infrared spectroscopy. In this regard, two Gaussian profiles were produced by adjusting plano-convex and bi-convex lenses and the Uniform profile was provided by applying a flat lens. Two experiments were conducted in this study. First, a simulation experiment was carried out based on scanning the intra space of a liquid phantom by using static and pulsating absorbers to compare the penetration depth of the configurations applied on the LED-based near infrared spectroscopy with that of a laser-based near infrared spectroscopy. Second, to show the feasibility of the best proposed configuration applied, an in vivo experiment of stress assessment has been performed and its results have been compared with that results obtained by laser one. The results showed that the LED-based near infrared spectroscopy equipped with bi-convex lens provides a penetration depth and hence quality measurements of near infrared spectroscopy and its extracted heart rate variability signals as well as laser-based near infrared spectroscopy especially in the application of stress assessment.

Tracking differential activation of primary and supplementary motor cortex across timing tasks: An fNIRS validation study

“…Moreover, other recording techniques are highly affected by movement while fNIRS is less so. As such, fNIRS has been used to delineate the neural mechanisms underlying a range of perceptual and cognitive processes (e.g., Borjkhani and Setarehdan, 2020;Bortfeld et al, 2009Bortfeld et al, , 2007Chen et al, 2011;Mirbagheri et al, 2019;Ebrahimzadeh et al, 2019;Jahani et al, 2015;Mirbagheri et al, 2020;Pollonini et al, 2014;Rahimpour et al, 2017Rahimpour et al, , 2018. Here we extend the findings of Jantzen and colleagues (Jantzen et al, 2004) to fNIRS, with the goal of establishing whether fNIRS is spatially and temporally sensitive enough to differentiate activation in the different cortex-specific regions of interest identified by Jantzen et al to be differentially engaged by synchronized and syncopated finger tapping.…”

Simultaneous EEG-fMRI: A novel approach to localize the Seizure Onset Zone

“…It has been wellestablished that neuroelectrical activity and the corresponding hemodynamic response of the physiological and pathological brain function do not overlap precisely. Thus, when investigating the correlation between the two, the literature generally accepts a concordance within 20 mm [38][39][40], making focal the BOLD change a regional marker of epileptogenic networks at macroscopic scale which proves its usefulness in the evaluation process prior to placing EEG electrodes or performing surgery. In this case study, we have applied complementary physiological information, to identify and introduce the most relevant components.…”

“…The channels are then Page: 133 www.raftpubs.com reviewed to identify and remove abnormal channels, i.e., those with a p-value greater 0.01. The power line interference, containing high frequency components, is removed using the Clean Line algorithm [36][37][38], which is vastly superior to a notch filter in terms of retaining the main content of the signal. It adaptively estimates and removes sinusoidal artifacts, while unlike the notch filter, does not create band-holes in the EEG power spectrum.…”

Quantitative Comparison of Analytical Solution and Finite Element Method for Investigation of Near-infrared Light Propagation in Brain Tissue Model

“…Another specific issue that arises is that how much the reflectance of the detector is sensitive to depth. The previous study indicates that depths sensitivity decreases exponentially, depending on the source-detector separation (Mirbagheri et al, 2020b;Strangman, Li, & Zhang, 2013).…”

“…Functional Near-Infrared spectroscopy is a method for investigating brain activity noninvasively (Berivanlou, Setarehdan, & Noubari, 2014;Ferrari & Quaresima, 2012;Hemmati, Setarehdan, & Noubari, 2012;Rahimpour, Pollonini, Comstock, Balasubramaniam, & Bortfeld, 2020;Scholkmann et al, 2014). This low-cost imaging method has a lot of applications in the field of neuroscience, including infant cerebral hemodynamic monitoring; classification of chronic diseases; stress level, and mental workload assessment; IQ estimation (Dadgostar, Setarehdan, Shahzadi, & Akin, 2018;Firooz & Setarehdan, 2019;Hakimi & Setarehdan, 2018;Jahani, Berivanlou, Rahimpour, & Setarehdan, 2015;Mirbagheri, Hakimi, Ebrahimzadeh, & Setarehdan, 2020b, 2020aRahimpour, Dadashi, Soltanian-Zadeh, & Setarehdan, 2017;Rahimpour, Noubari, & Kazemian, 2018). In this imaging method, a light source and detector are installed on the head; consequently, re-emission of light from human skin contains optical information from the human body (Scholkmann et al, 2014).…”