Abstract

Visual stimulation is one of the most commonly used paradigms for cerebral cortex function investigation. Experiments typically involve presenting to a volunteer a black-and-white checkerboard with contrast-reversing at a frequency of 4 to 16 Hz. The aim of the present study was to investigate the influence of the flickering frequency on the amplitude of changes in the concentration of oxygenated and deoxygenated hemoglobin. The hemoglobin concentrations were assessed with the use of a high resolution diffuse optical tomography method. Spatial distributions of changes in hemoglobin concentrations overlaying the visual cortex are shown for various stimuli frequencies. Moreover, the hemoglobin concentration changes obtained for different source-detector separations (from 1.5 to 5.4 cm) are presented. Our results demonstrate that the flickering frequency had a statistically significant effect on the induced oxyhemoglobin changes (p < 0,001). The amplitude of oxy hemoglobin concentration changes at a frequency of 8 Hz was higher in comparison with that measured at 4 Hz :[median(25th-75thpercentiles) 1.24 (0.94–1.71) vs. 0.92(0.73–1.28)µM, p < 0.001]; 12 Hz:[1.24 (0.94–1.71) vs. 1.04 (0.78–1.32) µM, p < 0.001]; and 16 Hz:[1.24 (0.94–1.71) vs. 1.15(0.87–1.48) µM, p < 0.001]. No significant differences were observed between the size of an area of activation for various frequencies. The demonstrated superiority of 8 Hz over other frequencies can advance understanding of visual stimulations and help guide future fNIRS protocols.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2019 (1)

V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fNIRS) for assessing cerebral cortex function during human behavior in natural/social situations: a concise review,” Organizational Research Methods 22(1), 46–68 (2019).
[Crossref]

2018 (2)

R. T. Aitchison, L. Ward, G. J. Kennedy, X. Shu, D. C. Mansfield, and U. Shahani, “Measuring visual cortical oxygenation in diabetes using functional near-infrared spectroscopy,” Acta Diabetol 55(11), 1181–1189 (2018).
[Crossref]

L. M. Ward, R. T. Aitchison, G. Hill, J. Imrie, A. J. Simmers, G. Morrison, D. Mansfield, G. J. Kennedy, and U. Shahani, “Effects of Glaucoma and Snoring on Cerebral Oxygenation in the Visual Cortex: a Study Using functional Near Infrared Spectroscopy (fNIRS),” Spectroscopy (fNIRS) 2, 017–025 (2018).

2017 (1)

A. Eisen-Enosh, N. Farah, Z. Burgansky-Eliash, U. Polat, and Y. Mandel, “Evaluation of critical flicker-fusion frequency measurement methods for the investigation of visual temporal resolution,” Sci. Rep. 7(1), 15621 (2017).
[Crossref]

2014 (4)

C.-H. Chen, M.-S. Ho, K.-K. Shyu, K.-C. Hsu, K.-W. Wang, and P.-L. Lee, “A noninvasive brain computer interface using visually-induced near-infrared spectroscopy responses,” Neurosci. Lett. 580, 22–26 (2014).
[Crossref]

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fNIRS system for brain imaging in freely moving subjects,” NeuroImage 85, 64–71 (2014).
[Crossref]

F. Scholkmann, S. Kleiser, A. J. Metz, R. Zimmermann, J. M. Pavia, U. Wolf, and M. Wolf, “A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology,” NeuroImage 85, 6–27 (2014).
[Crossref]

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref]

2013 (1)

L. Thaler, A. C. Schütz, M. A. Goodale, and K. R. Gegenfurtner, “What is the best fixation target? The effect of target shape on stability of fixational eye movements,” Vision Res. 76, 31–42 (2013).
[Crossref]

2012 (4)

C. Habermehl, S. Holtze, J. Steinbrink, S. P. Koch, H. Obrig, J. Mehnert, and C. H. Schmitz, “Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography,” NeuroImage 59(4), 3201–3211 (2012).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

S. M. Liao, S. L. Ferradal, B. R. White, N. M. Gregg, T. E. Inder, and J. P. Culver, “High-density diffuse optical tomography of term infant visual cortex in the nursery,” J. Biomed. Opt. 17(8), 081414 (2012).
[Crossref]

S. Wijeakumar, U. Shahani, W. A. Simpson, and D. L. McCulloch, “Localization of hemodynamic responses to simple visual stimulation: an fNIRS study,” Invest. Ophthalmol. Visual Sci. 53(4), 2266–2273 (2012).
[Crossref]

2011 (2)

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” NeuroImage 54(4), 2808–2821 (2011).
[Crossref]

A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
[Crossref]

2010 (2)

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front. Neuroenerg. 2, 14 (2010).
[Crossref]

S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front. Neuroenerg. 2, 12 (2010).
[Crossref]

2009 (2)

2008 (2)

R. S. Marshall, J. J. Ferrera, A. Barnes, X. Zhang, K. A. O’Brien, M. Chmayssani, J. Hirsch, and R. M. Lazar, “Brain activity associated with stimulation therapy of the visual borderzone in hemianopic stroke patients,” Neurorehabilitation and Neural Repair 22(2), 136–144 (2008).
[Crossref]

U. E. Emir, Z. Bayraktaroglu, C. Ozturk, A. Ademoglu, and T. Demiralp, “Changes in BOLD transients with visual stimuli across 1–44 Hz,” Neurosci. Lett. 436(2), 185–188 (2008).
[Crossref]

2007 (6)

M. Kacprzak, A. Liebert, P. L. Sawosz, N. S. Zolek, and R. Maniewski, “Time-resolved optical imager for assessment of cerebral oxygenation,” J. Biomed. Opt. 12(3), 034019 (2007).
[Crossref]

R. Srinivasan, E. Fornari, M. G. Knyazeva, R. Meuli, and P. Maeder, “fMRI responses in medial frontal cortex that depend on the temporal frequency of visual input,” Exp. Brain Res. 180(4), 677–691 (2007).
[Crossref]

V. Y. Toronov, X. Zhang, and A. G. Webb, “A spatial and temporal comparison of hemodynamic signals measured using optical and functional magnetic resonance imaging during activation in the human primary visual cortex,” NeuroImage 34(3), 1136–1148 (2007).
[Crossref]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. 104(29), 12169–12174 (2007).
[Crossref]

H. Shankar and K. Pesudovs, “Critical flicker fusion test of potential vision,” J. Cataract Refractive Surg. 33(2), 232–239 (2007).
[Crossref]

B. A. Wandell, S. O. Dumoulin, and A. A. Brewer, “Visual field maps in human cortex,” Neuron 56(2), 366–383 (2007).
[Crossref]

2004 (2)

T. Kusaka, K. Kawada, K. Okubo, K. Nagano, M. Namba, H. Okada, T. Imai, K. Isobe, and S. Itoh, “Noninvasive optical imaging in the visual cortex in young infants,” Hum. Brain Mapp. 22(2), 122–132 (2004).
[Crossref]

L. M. Parkes, P. Fries, C. M. Kerskens, and D. G. Norris, “Reduced BOLD response to periodic visual stimulation,” NeuroImage 21(1), 236–243 (2004).
[Crossref]

2003 (3)

M. Singh, S. Kim, and T. S. Kim, “Correlation between BOLD-fMRI and EEG signal changes in response to visual stimulus frequency in humans,” Magn. Reson. Med. 49(1), 108–114 (2003).
[Crossref]

Y. Hoshi, “Functional near-infrared optical imaging: Utility and limitations in human brain mapping,” Psychophysiology 40(4), 511–520 (2003).
[Crossref]

H. Obrig and A. Villringer, “Beyond the visible—imaging the human brain with light,” J. Cereb. Blood Flow Metab. 23(1), 1–18 (2003).
[Crossref]

2002 (2)

G. Kircheis, M. Wettstein, L. Timmermann, A. Schnitzler, and D. Häussinger, “Critical flicker frequency for quantification of low-grade hepatic encephalopathy,” Hepatology 35(2), 357–366 (2002).
[Crossref]

M. Wolf, U. Wolf, V. Toronov, A. Michalos, L. A. Paunescu, J. H. Choi, and E. Gratton, “Different time evolution of oxyhemoglobin and deoxyhemoglobin concentration changes in the visual and motor cortices during functional stimulation: a near-infrared spectroscopy study,” NeuroImage 16(3), 704–712 (2002).
[Crossref]

2001 (8)

C. S. Herrmann, “Human EEG responses to 1–100 Hz flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena,” Exp. Brain Res. 137(3-4), 346–353 (2001).
[Crossref]

E. F. Wells, G. M. Bernstein, B. W. Scott, P. J. Bennett, and J. R. Mendelson, “Critical flicker frequency responses in visual cortex,” Exp. Brain Res. 139(1), 106–110 (2001).
[Crossref]

R. Hagenbeek, S. Rombouts, and F. Barkhof, “Interindividual differences in stimulus response curve in the striate cortex as a function of flicker frequency: an FMRI study,” NeuroImage 13(6), 981 (2001).
[Crossref]

C. Kaufmann, G. K. Elbel, C. Gössl, B. Pütz, and D. P. Auer, “Frequency dependence and gender effects in visual cortical regions involved in temporal frequency dependent pattern processing,” Hum. Brain Mapp. 14(1), 28–38 (2001).
[Crossref]

B. Ozus, H.-L. Liu, L. Chen, M. B. Iyer, P. T. Fox, and J.-H. Gao, “Rate dependence of human visual cortical response due to brief stimulation: an event-related fMRI study,” Magn. Reson. Imaging 19(1), 21–25 (2001).
[Crossref]

P. Zaramella, F. Freato, A. Amigoni, S. Salvadori, P. Marangoni, A. Suppjei, B. Schiavo, and L. Chiandetti, “Brain auditory activation measured by near-infrared spectroscopy (NIRS) in neonates,” Pediatr. Res. 49(2), 213–219 (2001).
[Crossref]

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” NeuroImage 13(1), 76–90 (2001).
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P. Wobst, R. Wenzel, M. Kohl, H. Obrig, and A. Villringer, “Linear aspects of changes in deoxygenated hemoglobin concentration and cytochrome oxidase oxidation during brain activation,” NeuroImage 13(3), 520–530 (2001).
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2000 (2)

K. Takahashi, S. Ogata, R. Yamamoto, S. Shiotsuka, A. Maki, Y. Yamashita, T. Yamamoto, H. Koizumi, H. Hirasawa, and M. Igawa, “Activation of visual cortex imaged by 24 channel near-infrared spectroscopy,” J. Biomed. Opt. 5(1), 93–97 (2000).
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I. Shevelev, V. Kamenkovich, E. Bark, V. Verkhlutov, G. Sharaev, and E. Mikhailova, “Visual illusions and travelling alpha waves produced by flicker at alpha frequency,” International Journal of Psychophysiology 39(1), 9–20 (2000).
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1999 (2)

B. A. Wandell, “Computational neuroimaging of human visual cortex,” Annu. Rev. Neurosci. 22(1), 145–173 (1999).
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R. D. Hoge, J. Atkinson, B. Gill, G. R. Crelier, S. Marrett, and G. B. Pike, “Stimulus-dependent BOLD and perfusion dynamics in human V1,” NeuroImage 9(6), 573–585 (1999).
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1997 (2)

M. J. Mentis, G. E. Alexander, C. L. Grady, B. Horwitz, J. Krasuski, P. Pietrini, T. Strassburger, H. Hampel, M. B. Schapiro, and S. I. Rapoport, “Frequency variation of a pattern-flash visual stimulus during PET differentially activates brain from striate through frontal cortex,” NeuroImage 5(2), 116–128 (1997).
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K. K. Yoshiyama and C. A. Johnson, “Which method of flicker perimetry is most effective for detection of glaucomatous visual field loss,” Invest. Ophthalmol. Visual Sci. 38(11), 2270–2277 (1997).

1996 (1)

S. Wu, S. A. Burns, A. Reeves, and A. E. Elsner, “Flicker brightness enhancement and visual nonlinearity,” Vision Res. 36(11), 1573–1583 (1996).
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1995 (2)

J. Meek, C. Elwell, M. Khan, J. Romaya, J. Wyatt, D. T. Delpy, and S. Zeki, “Regional changes in cerebral haemodynamics as a result of a visual stimulus measured by near infrared spectroscopy,” Proc. R. Soc. London, Ser. B 261(1362), 351–356 (1995).
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A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, L. Tyszczuk, M. Cope, and D. Delpy, “Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy,” Phys. Med. Biol. 40(2), 295–304 (1995).
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1987 (1)

P. T. Fox, F. M. Miezin, J. M. Allman, D. C. Van Essen, and M. E. Raichle, “Retinotopic organization of human visual cortex mapped with positron-emission tomography,” J. Neurosci. 7(3), 913–922 (1987).
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1985 (1)

P. T. Fox and M. E. Raichle, “Stimulus rate determines regional brain blood flow in striate cortex,” Ann. Neurol. 17, 303–305 (1985).
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1984 (1)

P. T. Fox and M. E. Raichle, “Stimulus rate dependence of regional cerebral blood flow in human striate cortex, demonstrated by positron emission tomography,” J. Neurophysiol. 51(5), 1109–1120 (1984).
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1981 (1)

C. W. Tyler, “Specific deficits of flicker sensitivity in glaucoma and ocular hypertension,” Invest. Ophthalmol. Visual Sci. 20(2), 204–212 (1981).

1960 (1)

M. Alpern, D. B. Flitman, and R. H. Joseph, “Centrally fixed flicker thresholds in amblyopia,” Am. J. Ophthalmol. 49(5), 1194–1202 (1960).
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1956 (1)

W. G. Walter, “Colour illusions and aberrations during stimulation by flickering light,” Nature 177(4511), 710 (1956).
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1933 (1)

S. Hecht and C. D. Verrijp, “The influence of intensity, color and retinal location on the fusion frequency of intermittent illumination,” Proc. Natl. Acad. Sci. U. S. A. 19(5), 522–535 (1933).
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A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
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U. E. Emir, Z. Bayraktaroglu, C. Ozturk, A. Ademoglu, and T. Demiralp, “Changes in BOLD transients with visual stimuli across 1–44 Hz,” Neurosci. Lett. 436(2), 185–188 (2008).
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Aichelburg, C.

P. Pinti, I. Tachtsidis, A. Hamilton, J. Hirsch, C. Aichelburg, S. Gilbert, and P. W. Burgess, “The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience,” Annals of the New York Academy of Sciences (2018).

Aitchison, R. T.

R. T. Aitchison, L. Ward, G. J. Kennedy, X. Shu, D. C. Mansfield, and U. Shahani, “Measuring visual cortical oxygenation in diabetes using functional near-infrared spectroscopy,” Acta Diabetol 55(11), 1181–1189 (2018).
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L. M. Ward, R. T. Aitchison, G. Hill, J. Imrie, A. J. Simmers, G. Morrison, D. Mansfield, G. J. Kennedy, and U. Shahani, “Effects of Glaucoma and Snoring on Cerebral Oxygenation in the Visual Cortex: a Study Using functional Near Infrared Spectroscopy (fNIRS),” Spectroscopy (fNIRS) 2, 017–025 (2018).

Alexander, G. E.

M. J. Mentis, G. E. Alexander, C. L. Grady, B. Horwitz, J. Krasuski, P. Pietrini, T. Strassburger, H. Hampel, M. B. Schapiro, and S. I. Rapoport, “Frequency variation of a pattern-flash visual stimulus during PET differentially activates brain from striate through frontal cortex,” NeuroImage 5(2), 116–128 (1997).
[Crossref]

Allman, J. M.

P. T. Fox, F. M. Miezin, J. M. Allman, D. C. Van Essen, and M. E. Raichle, “Retinotopic organization of human visual cortex mapped with positron-emission tomography,” J. Neurosci. 7(3), 913–922 (1987).
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Alm, A.

L. A. Levin, S. F. Nilsson, J. Ver Hoeve, S. Wu, P. L. Kaufman, and A. Alm, Adler's Physiology of the Eye E-Book: Expert Consult-Online and Print (Elsevier Health Sciences, 2011).

Alpern, M.

M. Alpern, D. B. Flitman, and R. H. Joseph, “Centrally fixed flicker thresholds in amblyopia,” Am. J. Ophthalmol. 49(5), 1194–1202 (1960).
[Crossref]

Amigoni, A.

P. Zaramella, F. Freato, A. Amigoni, S. Salvadori, P. Marangoni, A. Suppjei, B. Schiavo, and L. Chiandetti, “Brain auditory activation measured by near-infrared spectroscopy (NIRS) in neonates,” Pediatr. Res. 49(2), 213–219 (2001).
[Crossref]

Atkinson, J.

R. D. Hoge, J. Atkinson, B. Gill, G. R. Crelier, S. Marrett, and G. B. Pike, “Stimulus-dependent BOLD and perfusion dynamics in human V1,” NeuroImage 9(6), 573–585 (1999).
[Crossref]

Auer, D. P.

C. Kaufmann, G. K. Elbel, C. Gössl, B. Pütz, and D. P. Auer, “Frequency dependence and gender effects in visual cortical regions involved in temporal frequency dependent pattern processing,” Hum. Brain Mapp. 14(1), 28–38 (2001).
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Ayaz, H.

Y. Liu, E. A. Piazza, E. Simony, P. A. Shewokis, B. Onaral, U. Hasson, and H. Ayaz, “Measuring speaker–listener neural coupling with functional near infrared spectroscopy,” Sci. Rep.7(1), 43293 (2017).
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Bark, E.

I. Shevelev, V. Kamenkovich, E. Bark, V. Verkhlutov, G. Sharaev, and E. Mikhailova, “Visual illusions and travelling alpha waves produced by flicker at alpha frequency,” International Journal of Psychophysiology 39(1), 9–20 (2000).
[Crossref]

Barkhof, F.

R. Hagenbeek, S. Rombouts, and F. Barkhof, “Interindividual differences in stimulus response curve in the striate cortex as a function of flicker frequency: an FMRI study,” NeuroImage 13(6), 981 (2001).
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Barnes, A.

R. S. Marshall, J. J. Ferrera, A. Barnes, X. Zhang, K. A. O’Brien, M. Chmayssani, J. Hirsch, and R. M. Lazar, “Brain activity associated with stimulation therapy of the visual borderzone in hemianopic stroke patients,” Neurorehabilitation and Neural Repair 22(2), 136–144 (2008).
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Bayraktaroglu, Z.

A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
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U. E. Emir, Z. Bayraktaroglu, C. Ozturk, A. Ademoglu, and T. Demiralp, “Changes in BOLD transients with visual stimuli across 1–44 Hz,” Neurosci. Lett. 436(2), 185–188 (2008).
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Bayram, A.

A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
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Bejm, K.

S. Wojtkiewicz, P. Sawosz, M. Kacprzak, A. Gerega, K. Bejm, R. Maniewski, and A. Liebert, “Towards Optical Tomography of an Adult Human Head,” in Optical Tomography and Spectroscopy, (Optical Society of America, 2016), OM4C. 2.

Bennett, P. J.

E. F. Wells, G. M. Bernstein, B. W. Scott, P. J. Bennett, and J. R. Mendelson, “Critical flicker frequency responses in visual cortex,” Exp. Brain Res. 139(1), 106–110 (2001).
[Crossref]

Berger, A. J.

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front. Neuroenerg. 2, 14 (2010).
[Crossref]

Bernstein, G. M.

E. F. Wells, G. M. Bernstein, B. W. Scott, P. J. Bennett, and J. R. Mendelson, “Critical flicker frequency responses in visual cortex,” Exp. Brain Res. 139(1), 106–110 (2001).
[Crossref]

Bilgic, B.

A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
[Crossref]

Boas, D. A.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” NeuroImage 13(1), 76–90 (2001).
[Crossref]

Bray, S.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” NeuroImage 54(4), 2808–2821 (2011).
[Crossref]

Brewer, A. A.

B. A. Wandell, S. O. Dumoulin, and A. A. Brewer, “Visual field maps in human cortex,” Neuron 56(2), 366–383 (2007).
[Crossref]

Bryant, D. M.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” NeuroImage 54(4), 2808–2821 (2011).
[Crossref]

Burgansky-Eliash, Z.

A. Eisen-Enosh, N. Farah, Z. Burgansky-Eliash, U. Polat, and Y. Mandel, “Evaluation of critical flicker-fusion frequency measurement methods for the investigation of visual temporal resolution,” Sci. Rep. 7(1), 15621 (2017).
[Crossref]

Burgess, P. W.

P. Pinti, I. Tachtsidis, A. Hamilton, J. Hirsch, C. Aichelburg, S. Gilbert, and P. W. Burgess, “The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience,” Annals of the New York Academy of Sciences (2018).

Burns, S. A.

S. Wu, S. A. Burns, A. Reeves, and A. E. Elsner, “Flicker brightness enhancement and visual nonlinearity,” Vision Res. 36(11), 1573–1583 (1996).
[Crossref]

Chen, C.

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
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Chen, C.-H.

C.-H. Chen, M.-S. Ho, K.-K. Shyu, K.-C. Hsu, K.-W. Wang, and P.-L. Lee, “A noninvasive brain computer interface using visually-induced near-infrared spectroscopy responses,” Neurosci. Lett. 580, 22–26 (2014).
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Chen, L.

B. Ozus, H.-L. Liu, L. Chen, M. B. Iyer, P. T. Fox, and J.-H. Gao, “Rate dependence of human visual cortical response due to brief stimulation: an event-related fMRI study,” Magn. Reson. Imaging 19(1), 21–25 (2001).
[Crossref]

Cheng, X.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” NeuroImage 13(1), 76–90 (2001).
[Crossref]

Chiandetti, L.

P. Zaramella, F. Freato, A. Amigoni, S. Salvadori, P. Marangoni, A. Suppjei, B. Schiavo, and L. Chiandetti, “Brain auditory activation measured by near-infrared spectroscopy (NIRS) in neonates,” Pediatr. Res. 49(2), 213–219 (2001).
[Crossref]

Chmayssani, M.

R. S. Marshall, J. J. Ferrera, A. Barnes, X. Zhang, K. A. O’Brien, M. Chmayssani, J. Hirsch, and R. M. Lazar, “Brain activity associated with stimulation therapy of the visual borderzone in hemianopic stroke patients,” Neurorehabilitation and Neural Repair 22(2), 136–144 (2008).
[Crossref]

Choi, J. H.

M. Wolf, U. Wolf, V. Toronov, A. Michalos, L. A. Paunescu, J. H. Choi, and E. Gratton, “Different time evolution of oxyhemoglobin and deoxyhemoglobin concentration changes in the visual and motor cortices during functional stimulation: a near-infrared spectroscopy study,” NeuroImage 16(3), 704–712 (2002).
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Clemence, M.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, L. Tyszczuk, M. Cope, and D. Delpy, “Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy,” Phys. Med. Biol. 40(2), 295–304 (1995).
[Crossref]

Cope, M.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, L. Tyszczuk, M. Cope, and D. Delpy, “Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy,” Phys. Med. Biol. 40(2), 295–304 (1995).
[Crossref]

Crelier, G. R.

R. D. Hoge, J. Atkinson, B. Gill, G. R. Crelier, S. Marrett, and G. B. Pike, “Stimulus-dependent BOLD and perfusion dynamics in human V1,” NeuroImage 9(6), 573–585 (1999).
[Crossref]

Cui, X.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” NeuroImage 54(4), 2808–2821 (2011).
[Crossref]

Culver, J. P.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

S. M. Liao, S. L. Ferradal, B. R. White, N. M. Gregg, T. E. Inder, and J. P. Culver, “High-density diffuse optical tomography of term infant visual cortex in the nursery,” J. Biomed. Opt. 17(8), 081414 (2012).
[Crossref]

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front. Neuroenerg. 2, 14 (2010).
[Crossref]

H. Dehghani, B. R. White, B. W. Zeff, A. Tizzard, and J. P. Culver, “Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography,” Appl. Opt. 48(10), D137–D143 (2009).
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B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. 104(29), 12169–12174 (2007).
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Dehghani, H.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

H. Dehghani, B. R. White, B. W. Zeff, A. Tizzard, and J. P. Culver, “Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography,” Appl. Opt. 48(10), D137–D143 (2009).
[Crossref]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. 104(29), 12169–12174 (2007).
[Crossref]

Delpy, D.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, L. Tyszczuk, M. Cope, and D. Delpy, “Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy,” Phys. Med. Biol. 40(2), 295–304 (1995).
[Crossref]

Delpy, D. T.

J. Meek, C. Elwell, M. Khan, J. Romaya, J. Wyatt, D. T. Delpy, and S. Zeki, “Regional changes in cerebral haemodynamics as a result of a visual stimulus measured by near infrared spectroscopy,” Proc. R. Soc. London, Ser. B 261(1362), 351–356 (1995).
[Crossref]

Demiralp, T.

U. E. Emir, Z. Bayraktaroglu, C. Ozturk, A. Ademoglu, and T. Demiralp, “Changes in BOLD transients with visual stimuli across 1–44 Hz,” Neurosci. Lett. 436(2), 185–188 (2008).
[Crossref]

Dumoulin, S. O.

B. A. Wandell, S. O. Dumoulin, and A. A. Brewer, “Visual field maps in human cortex,” Neuron 56(2), 366–383 (2007).
[Crossref]

Duncan, A.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, L. Tyszczuk, M. Cope, and D. Delpy, “Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy,” Phys. Med. Biol. 40(2), 295–304 (1995).
[Crossref]

Duru, A. D.

A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
[Crossref]

Eggebrecht, A. T.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

Eisen-Enosh, A.

A. Eisen-Enosh, N. Farah, Z. Burgansky-Eliash, U. Polat, and Y. Mandel, “Evaluation of critical flicker-fusion frequency measurement methods for the investigation of visual temporal resolution,” Sci. Rep. 7(1), 15621 (2017).
[Crossref]

Elbel, G. K.

C. Kaufmann, G. K. Elbel, C. Gössl, B. Pütz, and D. P. Auer, “Frequency dependence and gender effects in visual cortical regions involved in temporal frequency dependent pattern processing,” Hum. Brain Mapp. 14(1), 28–38 (2001).
[Crossref]

Elsner, A. E.

S. Wu, S. A. Burns, A. Reeves, and A. E. Elsner, “Flicker brightness enhancement and visual nonlinearity,” Vision Res. 36(11), 1573–1583 (1996).
[Crossref]

Elwell, C.

J. Meek, C. Elwell, M. Khan, J. Romaya, J. Wyatt, D. T. Delpy, and S. Zeki, “Regional changes in cerebral haemodynamics as a result of a visual stimulus measured by near infrared spectroscopy,” Proc. R. Soc. London, Ser. B 261(1362), 351–356 (1995).
[Crossref]

Elwell, C. E.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, L. Tyszczuk, M. Cope, and D. Delpy, “Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy,” Phys. Med. Biol. 40(2), 295–304 (1995).
[Crossref]

Emir, U. E.

U. E. Emir, Z. Bayraktaroglu, C. Ozturk, A. Ademoglu, and T. Demiralp, “Changes in BOLD transients with visual stimuli across 1–44 Hz,” Neurosci. Lett. 436(2), 185–188 (2008).
[Crossref]

Erdogan, B.

A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, and C. Öztürk, “Simultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses,” Clin EEG Neurosci 42(2), 98–106 (2011).
[Crossref]

Farah, N.

A. Eisen-Enosh, N. Farah, Z. Burgansky-Eliash, U. Polat, and Y. Mandel, “Evaluation of critical flicker-fusion frequency measurement methods for the investigation of visual temporal resolution,” Sci. Rep. 7(1), 15621 (2017).
[Crossref]

Ferradal, S. L.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

S. M. Liao, S. L. Ferradal, B. R. White, N. M. Gregg, T. E. Inder, and J. P. Culver, “High-density diffuse optical tomography of term infant visual cortex in the nursery,” J. Biomed. Opt. 17(8), 081414 (2012).
[Crossref]

Ferrari, M.

V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fNIRS) for assessing cerebral cortex function during human behavior in natural/social situations: a concise review,” Organizational Research Methods 22(1), 46–68 (2019).
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S. Wijeakumar, U. Shahani, W. A. Simpson, and D. L. McCulloch, “Localization of hemodynamic responses to simple visual stimulation: an fNIRS study,” Invest. Ophthalmol. Visual Sci. 53(4), 2266–2273 (2012).
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Figures (12)

Fig. 1.
Fig. 1. Geometry of the pad (A) and its location on the head surface (B).
Fig. 2.
Fig. 2. The frequency spectra corresponding to measurements of checkerboard flickering frequency. The frequency spectra were shifted by 0.05 vertically in order to achieve the better visibility.
Fig. 3.
Fig. 3. Experimental design showing the measurement protocol (A), the patterns of visual stimulus (B) and the measurement stand (C).
Fig. 4.
Fig. 4. The frequency spectra of signals of light intensity (detector output) for selected source-detector pair at the source-detector distance of 3.4 cm for 850 nm. The first peak marked with arrow is related to stimulation frequency (1/45 seconds) and its surrounded by noise. The second peak marked with arrow corresponds to heart rate. The orange lines show the frequency response of the highpass and lowpass filter.
Fig. 5.
Fig. 5. Schematic of the data analysis algorithm. A. Preparing the set of sources (x,y) and detectors (x,y) coordinates and indication of the set of source- detector couples at selected source-detector separation (in this example 3.4 cm). The midpoints between source and detector position were marked with blue stars. B. Calculation of hemoglobin concentration changes for a selected source-detector pair. C. Block averaged changes in concentration of oxy- and deoxyhemoglobin. D. Calculation of the median value of the last 7.5 seconds of 15-seconds long stimulation period (marked with orange dashed lines). E. Assignment of the values of amplitudes of the oxyhemoglobin concentration changes to the positions of midpoints between source and detector positions. F. Visualization of spatial distributions of the oxyhemoglobin concentration changes with the use of interpolation - triangulation-based cubic technique. G. Calculation of the maximum amplitude of hemoglobin changes for each hemisphere. The maximum is marked with black star. H. The blue dashed line indicates the threshold representing 75% of the amplitude of hemoglobin change for each hemisphere. The image shows activation map (F) in cross section. I. Visualization of spatial distributions of the oxyhemoglobin concentration changes, where the area of the stimulation is marked with a red line.
Fig. 6.
Fig. 6. The signals obtained for Subject 1 during visual stimulation for flickering frequency 8 Hz at the source-detector distance of 1.5 cm (A), 3.4 cm (B), 4.5 cm (C) and 5.4 cm (D). Grey highlighted rectangles indicate the stimulation periods. The colors correspond to oxyhemoglobin (red) and deoxyhemoglobin (blue) concentrations. In the right column the signals averaged for the five cycles of measurement were presented.
Fig. 7.
Fig. 7. The frequency spectra of ΔCHbO2 signals for selected source-detector pairs at the source-detector distances of 1.5 cm, 3.4 cm, 4.5 cm and 5.4 cm (respective time traces are shown in the Fig. 6.) The first strong peak is related to visual stimulation frequency (1/45 sec = 0.0223 Hz). The time period of 45 seconds is related to duration one block of rest and stimulation.
Fig. 8.
Fig. 8. Averaged amplitudes of changes in concentrations of oxy- and deoxy-hemoglobin from area of stimulation as a function of source detector separation for one subject at the checkerboard reversing frequency of 8 Hz. A central red line in each box corresponds to the median, lower and upper boundary of the box correspond to 25th (q1) and 75th (q3) percentiles respectively and the whiskers represent interquartile range.
Fig. 9.
Fig. 9. Spatial distributions of averaged changes in concentrations of oxy- and deoxy-hemoglobin related to visual stimulation for different frequencies of checkerboard contrast-reversing (from 4 Hz to 16Hz). Red lines mark areas of high stimulation amplitude.
Fig. 10.
Fig. 10. Comparison of averaged amplitudes of oxy- (positive changes)— and deoxy hemoglobin (negative changes) concentration changes as a function of checkerboard flickering frequency. The symbols of different colors correspond to the averaged changes in hemoglobin concentrations obtained for eight subjects calculated from the area of stimulation. The dashed lines have been added in order to facilitate trend focusing. Note that the lines connecting data points are a guide to the eye only.
Fig. 11.
Fig. 11. Averaged amplitudes of oxy- (positive changes) and deoxyhemoglobin changes (negative changes) as a function of flickering frequency. A central red line in each box corresponds to the median, lower and upper boundary of the box correspond to 25th (q1) and 75th (q3) percentiles respectively and the whiskers represent interquartile range.
Fig. 12.
Fig. 12. Size of the stimulation area as a function of checkerboard flickering frequency. The central red line in each box corresponds to the median, lower and upper boundary of the box correspond to 25th (q1) and 75th (q3) percentiles respectively and the whiskers represent interquartile range.