Inwon Jung1, Kyungjin You1, Hyunchool Shin1, Chinsu Koh2, Hyungcheul Shin2, Jaewoo Shin2
(1. Dept. of Electronic Engineering, Soongsil University, Seoul 156-743, Korea; 2. Dept. of Physiology, College of Medicine, Hallym University, Chuncheon 200-702, Korea)
Abstract：We characterize the hemodynamic response changes in the main olfactory bulb (MOB) of anesthetized rats with near-infrared spectroscopy (NIRS) during the presentation of three different odorants: (i) plain air as a reference (Blank), (ii) 2-heptanone (HEP), and (iii) isopropylbenzene (Ib). Odorants generate different changes in the concentrations of oxy-hemoglobin. Our results suggest that NIRS technology might be useful in discriminating various odorants in a non-invasive manner using animals with a superb olfactory system.
Key words：brain-machine interface (BMI); functional near-infrared spectroscopy (fNIRS); main olfactory bulb (MOB); oxyhemoglobin (HbO2); Beer-Lambert law; maximum likelihood estimation (MLE)
CLD number： TN219 Document code： A
Article ID： 1674-8042(2013)01-0089-05 doi： 10.3969/j.issn.1674-8042.2013.01.019
References
[1] Jobsis F. Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters, Science, 1977, 198(4323): 1264-1267.
[2] Lee H J, Shin H C, et al, Odor-dependent hemodynamic responses measured with NIRS in the main olfactory bulb of anesthetized rats. Experimental Neurobiology, 2011, 20: 189-196.
[3] Crespi F, Bandera A, Donini M, et al. Non-invasive in vivo infrared laser spectroscopy to analyse endogenous oxy-haemoglobin, deoxy-haemoglobin, and blood volume in the rat CNS. Journal of Neuroscience Methods, 2005, 145(1/2): 11-22.
[4] Duncan A, Meek J H, Clemence M, et al. Optical pathlength measurements on adult head, calf and forearm and the new born infant using phase resolved optical spectroscopy. Phyics in Medicine and Biology, 1995, 40(5): 295-304.
[5] ZHANG Quan, Strangman G E, Ganis G. Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: How well and when does it work? NeuroImage, 2009, 45(3): 788-794.
[6] Shin H C, Aggarwal V, Acharya S, et al. Neural decoding of finger movements using Skellam-based maximum-likelihood decoding. IEEE Transactions on Biomedical Engineering, 2010, 57(3): 754-760.
[7] Jazayeri M, Movshon J A, Optimal representation of sensory information by neural populations. Nature Neuroscience, 2006, 9(5): 690-696.
[8] You K J, Ham H G, Lee H J, et al, Odor discrimination using neural decoding of the main olfactory bulb in rats. IEEE Transactions on Biomedical Engineering, 2011, 58(5): 1208-1215.
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