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The Temporal Confounding Effects of Extra-cerebral Contamination Factors on the Hemodynamic Signal Measured by Functional Near-Infrared Spectroscopy

Mehrdad Zarei, Mohammad Ali Ansari, Kourosh Zare




Introduction: Functional near-infrared spectroscopy (fNIRS) has been broadly applied for optical brain imaging. This method is hemodynamic-based functional brain imaging relying on the measurement of the neurovascular coupling to detect changes in cerebral neuronal activities. The extra-cerebral hemodynamic changes are important contaminating factors in fNIRS measurements. This error signal can be misinterpreted as cerebral activities during fNIRS studies. Recently, it was assumed that temporal changes in deoxygenated hemoglobin concentration [HHb] was hardly affected by superficial blood flow, and it was proposed that the activation maps could be determined from [HHb] at large source-detector separation.

Methods: In the current study, we measured the temporal changes in [HHb] using a continues-wave fNIRS device at large source-detector separation, while superficial blood flow was stimulated by infrared lasers. A mesh-based Monte Carlo code was applied to estimate fNIRS sensitivity to superficial hemodynamic changes in a realistic 3D MRI-based brain phantom.

Results: First, we simulated photon migration in a four-layered human-head slab model to calculate PPLs and fNIRS sensitivity. Then, the localization of the infrared laser inside a realistic brain model was studied using the Monte Carlo method. Finally, the changes in [HHb] over the prefrontal cortex of six adult males were measured by fNIRS at a source-detector separation of 3 cm. The results demonstrated that the relation between fNIRS sensitivity and an increase in S-D separation was nonlinear and a correlation between shallow and deep signals was observed.

Conclusion: The presented results demonstrated that the temporal changes in the superficial blood flow could strongly affect HHb measurement at large source-detector separation. Hence, the cerebral activity map extracted from the [HHb] signal was mainly contaminated by superficial blood flow.


Functional near-infrared spectroscopy; Photobiomodulation; Neurovascular coupling; Superficial blood flow


Ansari MA, Zakeri M. Blind localization of heating in neural tissues induced by a train of infrared pulse laser. J Lasers Med Sci. 2019;10(4):264-67. doi:10.15171/jlms.2019.43.

Salonia R, Bell MJ, Kochanek PM, Berger RP. The utility of near-infrared spectroscopy indetecting intracranial hemorrhage in children. J Neurotrauma. 2012; 29(6):1047-53. doi: 10.1089/neu.2011.1890.

Kim MN, Durduran T, Frangos S, Edlow BL, Buckley EM, Moss HE, et al. Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults. Neurocrit Care. 2010;12(2):173-80. doi:10.1007/s12028-009-9305-x.

Liebert A, Wabnitz H, Steinbrink J, Obrig H, Möller M, Macdonald R, et al. Time-resolved multidistance near-infrared spectroscopy of the adult head: intracerebral and extracerebral absorption changes from moments of distribution of times of flight of photons. Appl Opt. 2004;43(15):3037-47. doi:10.1364/ao.43.003037.

Tachtsidis I, Scholkmann H. False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward. Neurophotonics. 2016;3(3): 031405. doi:10.1117/1.NPh.3.3.039801.

Kirilina E, Jelzow A, Heine A, Niessing M, Wabnitz H, Brühl R, et al. The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy. Neuroimage.2012;61(1):70-81. doi:10.1016/j.neuroimage.2012.02.074.

Yamada T, Umeyama S, Matsuda K. Separation of fNIRS signals into functional and systemic components based on differences in hemodynamic modalities. PloS One. 2012;7(11):e50271. doi:10.1371/journal.pone.0050271.

Scholkmann F, Kleiser S, Metz AJ, Zimmermann R, Mata Pavia J, Wolf U , et all. A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage. 2014;85(1): 6-27. doi:10.1016/j.neuroimage.2013.05.004.

Funane T, Atsumori H, Katura T, Obata AN, Sato H, Tanikawa Y, et al. Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis. Neuroimage. 2014;85(1):150-65. doi:10.1016/j.neuroimage.2013.02.026.

Haeussinger FB, Dresler T, Heinzel S, Schecklmann M, Fallgatter AJ, Ehlis AC. Reconstructing functional near-infrared spectroscopy (fNIRS) signals impaired by extra-cranial confounds: an easy-to-use filter method. Neuroimage. 2014;95:69-79. doi: 10.1016/j.neuroimage.2014.02.035.

Cooper RJ, Selb J, Gagnon L, Phillip D, Schytz HW, Iversen HK, et al. A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy. Front Neurosci. 2012;6:147. doi:10.3389/fnins.2012.00147.

Medvedev AV, Kainerstorfer J, Borisov SV, Barbour RL, VanMeter J. Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis. Brain Res. 2008;1236:145-58. doi: 10.1016/j.brainres.2008.07.122.

Gagnon L, Yücel MA, Boas DA, Cooper RJ. Further improvement in reducing superficial contamination in NIRS using double short separation measurements. Neuroimage. 2014;85(1):127-35. doi:10.1016/j.neuroimage.2013.01.073.

Gagnon L, Cooper RJ, Yücel MA, Perdue KL, Greve DN, Boas DA. Short separation channel location impacts the performance of short channel regression in NIRS. Neuroimage. 2012;59(3):2518-28. doi:10.1016/j.neuroimage.2011.08.095.

Drummond PD, Lazaroo D. The effect of facial blood flow on ratings of blushing and negative affect during an embarrassing task: Preliminary findings. J Anxiety Disord. 2012;26(2):305-10. doi:10.1016/j.janxdis.2011.12.012.

Gilbert SJ, Spengler S, Simons JS, Steele JD, Lawrie SM, Frith CD , et al. Functional specialization within rostral prefrontal cortex (area 10): a meta-analysis. J Cogn Neurosci. 2006;18(6):932-48. doi:10.1162/jocn.2006.18.6.932.

Koenraadt KL, Roelofsen EG, Duysens J, Keijsers NL. Cortical control of normal gait and precision stepping: an fNIRS study. Neuroimage. 2014;85(1):415-22. doi: 10.1016/j.neuroimage.2013.04.070.

Fang Q. Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates. Biomed Opt Express. 2010;1(1):165-75. doi:10.1364/BOE.1.000165.

Wang S, Shibahara N, Kuramashi D, Okawa S, Kakuta N, Okada E, et al. Effects of spatial variation of skull and cerebrospinal fluid layers on optical mapping of brain activities. Opt Rev. 2010;17(4):410-420. doi:10.1007/s10043-010-0076-6.

Okada E, Delpy DT. Near-infrared light propagation in an adult head model. I. Modeling of low-level scattering in the cerebrospinal fluid layer. Appl Opt. 2003;42(16):2906-14. doi:10.1364/ao.42.002906.

Farina A, Torricelli A, Bargigia I, Spinelli L, Cubeddu R, Foschum F, et al. In-vivo multilaboratory investigation of the optical properties of the human head. Biomed Opt Express. 2015;6(7):2609-23. doi:10.1364/BOE.6.002609.

Tedford CE, DeLapp S, Jacques S, Anders J. Quantitative analysis of transcranial and intraparenchymal light penetration in human cadaver brain tissue. Lasers Surg Med. 2015;47(4):312-22. doi:10.1002/lsm.22343.

Konstantinović LM, Jelić MB, Jeremić A, Stevanović VB, Milanović SD, Filipović SR. Transcranial application of near‐infrared low‐level laser can modulate cortical excitability. Lasers Surg Med. 2013;45(10):648-53. doi:10.1002/lsm.22190.

Rojas JC, Bruchey AK, Gonzalez-Lima F. Low-level light therapy improves cortical metabolic capacity and memory retention. J Alzheimer Dis. 2012;32(3):741-52. doi: 10.3233/JAD-2012-120817.

Tian F, Hase SN, Gonzalez‐Lima F, Liu H. Transcranial laser stimulation improves human cerebral oxygenation. Lasers Surg Med. 2016;48(4):343-9. doi:10.1002/lsm.22471.

Hwang J, Castelli DM, Gonzalez-Lima F. Cognitive enhancement by transcranial laser stimulation and acute aerobic exercise. Lasers Med Sci. 2016;31(6):1151-60. doi: 10.1007/s10103-016-1962-3.

Liljemalm R, Nyberg T, von Holst H. Heating during infrared neural stimulation. Lasers Surg Med. 2013;45(7):469-81. doi:10.1002/lsm.22158.

Wells J, Konrad P, Kao C, Jansen ED, Mahadevan-Jansen A. Pulsed laser versus electrical energy for peripheral nerve stimulation. J Neurosci Methods. 2007;163(2):326-37. doi:10.1016/j.jneumeth.2007.03.016.

Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, et al. Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging. 1998;17(3):463-8. doi:10.1109/42.712135.

Mahmoodkalayeh S, Ansari MA, Tuchin VV. Head model based on the shape of the subject’s head for optical brain imaging. Biomed Opt express. 2019;10(6):2795-2808. doi: 10.1364/BOE.10.002795.

Ansari MA, Massudi R, Hejazi M. Experimental and numerical study on simultaneous effects of scattering and absorption on fluorescence spectroscopy of a breast phantom. Opt Laser Technol. 2009;41(6):746-50. doi:10.1016/j.optlastec.2008.12.019.

Strangman GE, Zhang Q, Li Z. Scalp and skull influence on near infrared photon propagation in the Colin27 brain template. Neuroimage. 2014;85(1):136-49. doi: 10.1016/j.neuroimage.2013.04.090.

Hiraoka M, Firbank M, Essenpreis M, Cope M, Arridge SR, Van der Zee P,et al. A Monte Carlo investigation of optical pathlength in inhomogeneous tissue and its application to near-infrared spectroscopy. Phys Med Biol. 1993;38(12):1859-76. doi:10.1088/0031-9155/38/12/011.

Ansari MA, Erfanzadeh M, Mohajerani E. Mechanisms of laser-tissue interaction: II. Tissue thermal properties. J Lasers Med Sci. 2013;4(3): 99-106. doi:10.22037/jlms.v4i3.4681.

Ansari MA, Zarei M, Akhlagipour N, Niknam AR. Skull and cerebrospinal fluid effects on microwave radiation propagation in human brain. J Phys D Appl Phys. 2017;50(49):495401. doi:10.1088/1361-6463/aa944b.

Cui X, Bray S, Bryan DM, Glover GH, Reiss AL. A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. Neuroimage. 2011;54(4):2808-21. doi: 10.1016/j.neuroimage.2010.10.069.

Aletti F, Re R, Pace V, Contini D, Molteni E, Cerutti S, et al. Deep and surface hemodynamic signal from functional time resolved transcranial near infrared spectroscopy compared to skin flowmotion. Comput Biol Med. 2012;42(3):282-9. doi: 10.1016/j.compbiomed.2011.06.001.

Heinzel S, Haeussinger FB, Hahn T, Ehlis AC, Plichta MM, Fallgatter AJ. Variability of (functional) hemodynamics as measured with simultaneous fNIRS and fMRI during intertemporal choice. Neuroimage. 2013;71:125-34. doi:10.1016/j.neuroimage.2012.12.074.

Kohri S, Hoshi Y, Tamura M, Kato C, Kuge Y, Tamaki N. Quantitative evaluation of the relative contribution ratio of cerebral tissue to near-infrared signals in the adult human head: a preliminary study. Physiol Meas. 2002;23(2):301-12. doi:10.1088/0967-3334/23/2/306.

Yamada T, Umeyama S, Matsuda K. Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy. J Biomed Opt. 2009;14(6):064034. doi: 10.1117/1.3275469.

DOI: https://doi.org/10.22037/jlms.v10i4.20607