Abstract

Optical Coherence Tomography (OCT) angiography was applied to image functional hyperemia in different vascular compartments in the rat somatosensory cortex. Dynamic backscattering changes, indicative of changes in dynamic red blood cell (dRBC) content, were used to monitor the hemodynamic response. Three-dimensional movies depicting the microvascular response to neuronal activation were created for the first time. An increase in the attenuation coefficient during activation was identified, and a simple normalization procedure was proposed to correct for it. This procedure was applied to determine compartment-resolved backscattering changes caused by dRBC content changes during functional activation. Increases in dRBC content were observed in all vascular compartments (arterial, arteriolar, capillary, and venular), with the largest responses found in the arterial and arteriolar compartments. dRBC content increased with dilation in arteries but with barely detectable dilation in veins. dRBC content increased in capillaries without significant “all or none” capillary recruitment.

© 2013 OSA

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  41. A. R. Pries, T. W. Secomb, and P. Gaehtgens, “Biophysical aspects of blood flow in the microvasculature,” Cardiovasc. Res.32(4), 654–667 (1996).
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2013

C. Martin, Y. Zheng, N. R. Sibson, J. E. Mayhew, and J. Berwick, “Complex spatiotemporal haemodynamic response following sensory stimulation in the awake rat,” Neuroimage66, 1–8 (2013).
[PubMed]

2012

A. K. Dunn, “Laser speckle contrast imaging of cerebral blood flow,” Ann. Biomed. Eng.40(2), 367–377 (2012).
[CrossRef] [PubMed]

A. Y. Shih, J. D. Driscoll, P. J. Drew, N. Nishimura, C. B. Schaffer, and D. Kleinfeld, “Two-photon microscopy as a tool to study blood flow and neurovascular coupling in the rodent brain,” J. Cereb. Blood Flow Metab.32(7), 1277–1309 (2012).
[CrossRef] [PubMed]

V. J. Srinivasan, H. Radhakrishnan, E. H. Lo, E. T. Mandeville, J. Y. Jiang, S. Barry, and A. E. Cable, “OCT methods for capillary velocimetry,” Biomed. Opt. Express3(3), 612–629 (2012).
[CrossRef] [PubMed]

2011

P. J. Drew, A. Y. Shih, and D. Kleinfeld, “Fluctuating and sensory-induced vasodynamics in rodent cortex extend arteriole capacity,” Proc. Natl. Acad. Sci. U.S.A.108(20), 8473–8478 (2011).
[CrossRef] [PubMed]

S. Yousefi, Z. Zhi, and R. K. Wang, “Eigendecomposition-based clutter filtering technique for optical micro-angiography,” IEEE Trans. Biomed. Eng.58(8), 2316–2323 (2011).
[CrossRef] [PubMed]

V. J. Srinivasan, D. N. Atochin, H. Radhakrishnan, J. Y. Jiang, S. Ruvinskaya, W. Wu, S. Barry, A. E. Cable, C. Ayata, P. L. Huang, and D. A. Boas, “Optical coherence tomography for the quantitative study of cerebrovascular physiology,” J. Cereb. Blood Flow Metab.31(6), 1339–1345 (2011).
[CrossRef] [PubMed]

P. Cimalla, J. Walther, M. Mittasch, and E. Koch, “Shear flow-induced optical inhomogeneity of blood assessed in vivo and in vitro by spectral domain optical coherence tomography in the 1.3 μm wavelength range,” J. Biomed. Opt.16(11), 116020 (2011).
[CrossRef] [PubMed]

Y. Mutalifu, L. Holm, C. Ince, E. Theodorsson, and F. Sjöberg, “Multiple different laminar velocity profiles in separate veins in the microvascular network of brain cortex in rats,” Int. J. Clin. Exp. Med.4(1), 10–16 (2011).
[PubMed]

E. Macé, G. Montaldo, I. Cohen, M. Baulac, M. Fink, and M. Tanter, “Functional ultrasound imaging of the brain,” Nat. Methods8(8), 662–664 (2011).
[CrossRef] [PubMed]

2010

2009

V. J. Srinivasan, S. Sakadzić, I. Gorczynska, S. Ruvinskaya, W. Wu, J. G. Fujimoto, and D. A. Boas, “Depth-resolved microscopy of cortical hemodynamics with optical coherence tomography,” Opt. Lett.34(20), 3086–3088 (2009).
[CrossRef] [PubMed]

E. M. Hillman and S. A. Burgess, “Sub-millimeter resolution 3D optical imaging of living tissue using laminar optical tomography,” Laser Photon Rev3(1-2), 159–179 (2009).
[CrossRef] [PubMed]

B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med.15(10), 1219–1223 (2009).
[CrossRef] [PubMed]

D. J. Faber and T. G. van Leeuwen, “Are quantitative attenuation measurements of blood by optical coherence tomography feasible?” Opt. Lett.34(9), 1435–1437 (2009).
[CrossRef] [PubMed]

2008

B. Stefanovic, E. Hutchinson, V. Yakovleva, V. Schram, J. T. Russell, L. Belluscio, A. P. Koretsky, and A. C. Silva, “Functional reactivity of cerebral capillaries,” J. Cereb. Blood Flow Metab.28(5), 961–972 (2008).
[CrossRef] [PubMed]

A. Mariampillai, B. A. Standish, E. H. Moriyama, M. Khurana, N. R. Munce, M. K. K. Leung, J. Y. Jiang, A. E. Cable, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Speckle variance detection of microvasculature using swept-source optical coherence tomography,” Opt. Lett.33(13), 1530–1532 (2008).
[CrossRef] [PubMed]

Y. K. Tao, A. M. Davis, and J. A. Izatt, “Single-pass volumetric bidirectional blood flow imaging spectral domain optical coherence tomography using a modified Hilbert transform,” Opt. Express16(16), 12350–12361 (2008).
[CrossRef] [PubMed]

R. Samatham, S. L. Jacques, and P. Campagnola, “Optical properties of mutant versus wild-type mouse skin measured by reflectance-mode confocal scanning laser microscopy (rCSLM),” J. Biomed. Opt.13(4), 041309 (2008).
[CrossRef] [PubMed]

2007

J. Fingler, D. Schwartz, C. Yang, and S. E. Fraser, “Mobility and transverse flow visualization using phase variance contrast with spectral domain optical coherence tomography,” Opt. Express15(20), 12636–12653 (2007).
[CrossRef] [PubMed]

R. K. Wang, S. L. Jacques, Z. Ma, S. Hurst, S. R. Hanson, and A. Gruber, “Three dimensional optical angiography,” Opt. Express15(7), 4083–4097 (2007).
[CrossRef] [PubMed]

E. M. Hillman, A. Devor, M. B. Bouchard, A. K. Dunn, G. W. Krauss, J. Skoch, B. J. Bacskai, A. M. Dale, and D. A. Boas, “Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation,” Neuroimage35(1), 89–104 (2007).
[CrossRef] [PubMed]

A. Devor, P. Tian, N. Nishimura, I. C. Teng, E. M. Hillman, S. N. Narayanan, I. Ulbert, D. A. Boas, D. Kleinfeld, and A. M. Dale, “Suppressed neuronal activity and concurrent arteriolar vasoconstriction may explain negative blood oxygenation level-dependent signal,” J. Neurosci.27(16), 4452–4459 (2007).
[CrossRef] [PubMed]

2006

H. Ren, T. Sun, D. J. MacDonald, M. J. Cobb, and X. Li, “Real-time in vivo blood-flow imaging by moving-scatterer-sensitive spectral-domain optical Doppler tomography,” Opt. Lett.31(7), 927–929 (2006).
[CrossRef] [PubMed]

M. E. Raichle and M. A. Mintun, “Brain work and brain imaging,” Annu. Rev. Neurosci.29(1), 449–476 (2006).
[CrossRef] [PubMed]

R. C. Koehler, D. Gebremedhin, and D. R. Harder, “Role of astrocytes in cerebrovascular regulation,” J. Appl. Physiol.100(1), 307–317 (2006).
[CrossRef] [PubMed]

2005

I. Vanzetta, R. Hildesheim, and A. Grinvald, “Compartment-resolved imaging of activity-dependent dynamics of cortical blood volume and oximetry,” J. Neurosci.25(9), 2233–2244 (2005).
[CrossRef] [PubMed]

2004

C. Iadecola, “Neurovascular regulation in the normal brain and in Alzheimer’s disease,” Nat. Rev. Neurosci.5(5), 347–360 (2004).
[CrossRef] [PubMed]

E. Hamel, “Cholinergic modulation of the cortical microvascular bed,” Prog. Brain Res.145, 171–178 (2004).
[CrossRef] [PubMed]

B. Cauli, X. K. Tong, A. Rancillac, N. Serluca, B. Lambolez, J. Rossier, and E. Hamel, “Cortical GABA interneurons in neurovascular coupling: relays for subcortical vasoactive pathways,” J. Neurosci.24(41), 8940–8949 (2004).
[CrossRef] [PubMed]

2003

J. P. Culver, T. Durduran, C. Cheung, A. G. Yodh, D. Furuya, and J. H. Greenberg, “Diffuse optical measurement of hemoglobin and cerebral blood flow in rat brain during hypercapnia, hypoxia and cardiac arrest,” Adv. Exp. Med. Biol.510, 293–297 (2003).
[CrossRef] [PubMed]

2001

N. K. Logothetis, J. Pauls, M. Augath, T. Trinath, and A. Oeltermann, “Neurophysiological investigation of the basis of the fMRI signal,” Nature412(6843), 150–157 (2001).
[CrossRef] [PubMed]

1999

J. B. Mandeville, J. J. Marota, C. Ayata, M. A. Moskowitz, R. M. Weisskoff, and B. R. Rosen, “MRI measurement of the temporal evolution of relative CMRO2 during rat forepaw stimulation,” Magn. Reson. Med.42(5), 944–951 (1999).
[CrossRef] [PubMed]

1996

A. R. Pries, T. W. Secomb, and P. Gaehtgens, “Biophysical aspects of blood flow in the microvasculature,” Cardiovasc. Res.32(4), 654–667 (1996).
[PubMed]

1994

A. Villringer, A. Them, U. Lindauer, K. Einhäupl, and U. Dirnagl, “Capillary perfusion of the rat brain cortex. An in vivo confocal microscopy study,” Circ. Res.75(1), 55–62 (1994).
[CrossRef] [PubMed]

1992

K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppel, M. S. Cohen, R. Turner, H.-M. Cheng, T. J. Brady, and B. R. Rosen, “Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation,” Proc. Natl. Acad. Sci. U.S.A.89(12), 5675–5679 (1992).
[CrossRef] [PubMed]

S. Ogawa, D. W. Tank, R. Menon, J. M. Ellermann, S.-G. Kim, H. Merkle, and K. Ugurbil, “Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging,” Proc. Natl. Acad. Sci. U.S.A.89(13), 5951–5955 (1992).
[CrossRef] [PubMed]

A. R. Pries, D. Neuhaus, and P. Gaehtgens, “Blood viscosity in tube flow: dependence on diameter and hematocrit,” Am. J. Physiol.263(6 Pt 2), H1770–H1778 (1992).
[PubMed]

1991

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science254(5035), 1178–1181 (1991).
[CrossRef] [PubMed]

R. A. Stepnoski, A. LaPorta, F. Raccuia-Behling, G. E. Blonder, R. E. Slusher, and D. Kleinfeld, “Noninvasive detection of changes in membrane potential in cultured neurons by light scattering,” Proc. Natl. Acad. Sci. U.S.A.88(21), 9382–9386 (1991).
[CrossRef] [PubMed]

1986

A. Grinvald, E. Lieke, R. D. Frostig, C. D. Gilbert, and T. N. Wiesel, “Functional architecture of cortex revealed by optical imaging of intrinsic signals,” Nature324(6095), 361–364 (1986).
[CrossRef] [PubMed]

1931

R. Fahraeus and T. Lindqvist, “The viscosity of the blood in narrow capillary tubes,” Am. J. Physiol.96, 562–568 (1931).

Atochin, D. N.

V. J. Srinivasan, D. N. Atochin, H. Radhakrishnan, J. Y. Jiang, S. Ruvinskaya, W. Wu, S. Barry, A. E. Cable, C. Ayata, P. L. Huang, and D. A. Boas, “Optical coherence tomography for the quantitative study of cerebrovascular physiology,” J. Cereb. Blood Flow Metab.31(6), 1339–1345 (2011).
[CrossRef] [PubMed]

Augath, M.

N. K. Logothetis, J. Pauls, M. Augath, T. Trinath, and A. Oeltermann, “Neurophysiological investigation of the basis of the fMRI signal,” Nature412(6843), 150–157 (2001).
[CrossRef] [PubMed]

Ayata, C.

V. J. Srinivasan, D. N. Atochin, H. Radhakrishnan, J. Y. Jiang, S. Ruvinskaya, W. Wu, S. Barry, A. E. Cable, C. Ayata, P. L. Huang, and D. A. Boas, “Optical coherence tomography for the quantitative study of cerebrovascular physiology,” J. Cereb. Blood Flow Metab.31(6), 1339–1345 (2011).
[CrossRef] [PubMed]

J. B. Mandeville, J. J. Marota, C. Ayata, M. A. Moskowitz, R. M. Weisskoff, and B. R. Rosen, “MRI measurement of the temporal evolution of relative CMRO2 during rat forepaw stimulation,” Magn. Reson. Med.42(5), 944–951 (1999).
[CrossRef] [PubMed]

Bacskai, B. J.

E. M. Hillman, A. Devor, M. B. Bouchard, A. K. Dunn, G. W. Krauss, J. Skoch, B. J. Bacskai, A. M. Dale, and D. A. Boas, “Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation,” Neuroimage35(1), 89–104 (2007).
[CrossRef] [PubMed]

Barry, S.

Bartlett, L. A.

B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med.15(10), 1219–1223 (2009).
[CrossRef] [PubMed]

Baulac, M.

E. Macé, G. Montaldo, I. Cohen, M. Baulac, M. Fink, and M. Tanter, “Functional ultrasound imaging of the brain,” Nat. Methods8(8), 662–664 (2011).
[CrossRef] [PubMed]

Belliveau, J. W.

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K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppel, M. S. Cohen, R. Turner, H.-M. Cheng, T. J. Brady, and B. R. Rosen, “Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation,” Proc. Natl. Acad. Sci. U.S.A.89(12), 5675–5679 (1992).
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A. Y. Shih, J. D. Driscoll, P. J. Drew, N. Nishimura, C. B. Schaffer, and D. Kleinfeld, “Two-photon microscopy as a tool to study blood flow and neurovascular coupling in the rodent brain,” J. Cereb. Blood Flow Metab.32(7), 1277–1309 (2012).
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A. Villringer, A. Them, U. Lindauer, K. Einhäupl, and U. Dirnagl, “Capillary perfusion of the rat brain cortex. An in vivo confocal microscopy study,” Circ. Res.75(1), 55–62 (1994).
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E. Macé, G. Montaldo, I. Cohen, M. Baulac, M. Fink, and M. Tanter, “Functional ultrasound imaging of the brain,” Nat. Methods8(8), 662–664 (2011).
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M. A. Franceschini, H. Radhakrishnan, K. Thakur, W. Wu, S. Ruvinskaya, S. Carp, and D. A. Boas, “The effect of different anesthetics on neurovascular coupling,” Neuroimage51(4), 1367–1377 (2010).
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J. P. Culver, T. Durduran, C. Cheung, A. G. Yodh, D. Furuya, and J. H. Greenberg, “Diffuse optical measurement of hemoglobin and cerebral blood flow in rat brain during hypercapnia, hypoxia and cardiac arrest,” Adv. Exp. Med. Biol.510, 293–297 (2003).
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Greenberg, J. H.

J. P. Culver, T. Durduran, C. Cheung, A. G. Yodh, D. Furuya, and J. H. Greenberg, “Diffuse optical measurement of hemoglobin and cerebral blood flow in rat brain during hypercapnia, hypoxia and cardiac arrest,” Adv. Exp. Med. Biol.510, 293–297 (2003).
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D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science254(5035), 1178–1181 (1991).
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I. Vanzetta, R. Hildesheim, and A. Grinvald, “Compartment-resolved imaging of activity-dependent dynamics of cortical blood volume and oximetry,” J. Neurosci.25(9), 2233–2244 (2005).
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A. Grinvald, E. Lieke, R. D. Frostig, C. D. Gilbert, and T. N. Wiesel, “Functional architecture of cortex revealed by optical imaging of intrinsic signals,” Nature324(6095), 361–364 (1986).
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Hanson, S. R.

Harder, D. R.

R. C. Koehler, D. Gebremedhin, and D. R. Harder, “Role of astrocytes in cerebrovascular regulation,” J. Appl. Physiol.100(1), 307–317 (2006).
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D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science254(5035), 1178–1181 (1991).
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I. Vanzetta, R. Hildesheim, and A. Grinvald, “Compartment-resolved imaging of activity-dependent dynamics of cortical blood volume and oximetry,” J. Neurosci.25(9), 2233–2244 (2005).
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E. M. Hillman and S. A. Burgess, “Sub-millimeter resolution 3D optical imaging of living tissue using laminar optical tomography,” Laser Photon Rev3(1-2), 159–179 (2009).
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E. M. Hillman, A. Devor, M. B. Bouchard, A. K. Dunn, G. W. Krauss, J. Skoch, B. J. Bacskai, A. M. Dale, and D. A. Boas, “Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation,” Neuroimage35(1), 89–104 (2007).
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A. Devor, P. Tian, N. Nishimura, I. C. Teng, E. M. Hillman, S. N. Narayanan, I. Ulbert, D. A. Boas, D. Kleinfeld, and A. M. Dale, “Suppressed neuronal activity and concurrent arteriolar vasoconstriction may explain negative blood oxygenation level-dependent signal,” J. Neurosci.27(16), 4452–4459 (2007).
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Y. Mutalifu, L. Holm, C. Ince, E. Theodorsson, and F. Sjöberg, “Multiple different laminar velocity profiles in separate veins in the microvascular network of brain cortex in rats,” Int. J. Clin. Exp. Med.4(1), 10–16 (2011).
[PubMed]

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K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppel, M. S. Cohen, R. Turner, H.-M. Cheng, T. J. Brady, and B. R. Rosen, “Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation,” Proc. Natl. Acad. Sci. U.S.A.89(12), 5675–5679 (1992).
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D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science254(5035), 1178–1181 (1991).
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V. J. Srinivasan, D. N. Atochin, H. Radhakrishnan, J. Y. Jiang, S. Ruvinskaya, W. Wu, S. Barry, A. E. Cable, C. Ayata, P. L. Huang, and D. A. Boas, “Optical coherence tomography for the quantitative study of cerebrovascular physiology,” J. Cereb. Blood Flow Metab.31(6), 1339–1345 (2011).
[CrossRef] [PubMed]

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Hutchinson, E.

B. Stefanovic, E. Hutchinson, V. Yakovleva, V. Schram, J. T. Russell, L. Belluscio, A. P. Koretsky, and A. C. Silva, “Functional reactivity of cerebral capillaries,” J. Cereb. Blood Flow Metab.28(5), 961–972 (2008).
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Y. Mutalifu, L. Holm, C. Ince, E. Theodorsson, and F. Sjöberg, “Multiple different laminar velocity profiles in separate veins in the microvascular network of brain cortex in rats,” Int. J. Clin. Exp. Med.4(1), 10–16 (2011).
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Jacques, S. L.

R. Samatham, S. L. Jacques, and P. Campagnola, “Optical properties of mutant versus wild-type mouse skin measured by reflectance-mode confocal scanning laser microscopy (rCSLM),” J. Biomed. Opt.13(4), 041309 (2008).
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R. K. Wang, S. L. Jacques, Z. Ma, S. Hurst, S. R. Hanson, and A. Gruber, “Three dimensional optical angiography,” Opt. Express15(7), 4083–4097 (2007).
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Jain, R. K.

B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med.15(10), 1219–1223 (2009).
[CrossRef] [PubMed]

Jiang, J. Y.

Kennedy, D. N.

K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppel, M. S. Cohen, R. Turner, H.-M. Cheng, T. J. Brady, and B. R. Rosen, “Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation,” Proc. Natl. Acad. Sci. U.S.A.89(12), 5675–5679 (1992).
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Kim, S.-G.

S. Ogawa, D. W. Tank, R. Menon, J. M. Ellermann, S.-G. Kim, H. Merkle, and K. Ugurbil, “Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging,” Proc. Natl. Acad. Sci. U.S.A.89(13), 5951–5955 (1992).
[CrossRef] [PubMed]

Kleinfeld, D.

A. Y. Shih, J. D. Driscoll, P. J. Drew, N. Nishimura, C. B. Schaffer, and D. Kleinfeld, “Two-photon microscopy as a tool to study blood flow and neurovascular coupling in the rodent brain,” J. Cereb. Blood Flow Metab.32(7), 1277–1309 (2012).
[CrossRef] [PubMed]

P. J. Drew, A. Y. Shih, and D. Kleinfeld, “Fluctuating and sensory-induced vasodynamics in rodent cortex extend arteriole capacity,” Proc. Natl. Acad. Sci. U.S.A.108(20), 8473–8478 (2011).
[CrossRef] [PubMed]

A. Devor, P. Tian, N. Nishimura, I. C. Teng, E. M. Hillman, S. N. Narayanan, I. Ulbert, D. A. Boas, D. Kleinfeld, and A. M. Dale, “Suppressed neuronal activity and concurrent arteriolar vasoconstriction may explain negative blood oxygenation level-dependent signal,” J. Neurosci.27(16), 4452–4459 (2007).
[CrossRef] [PubMed]

R. A. Stepnoski, A. LaPorta, F. Raccuia-Behling, G. E. Blonder, R. E. Slusher, and D. Kleinfeld, “Noninvasive detection of changes in membrane potential in cultured neurons by light scattering,” Proc. Natl. Acad. Sci. U.S.A.88(21), 9382–9386 (1991).
[CrossRef] [PubMed]

Koch, E.

P. Cimalla, J. Walther, M. Mittasch, and E. Koch, “Shear flow-induced optical inhomogeneity of blood assessed in vivo and in vitro by spectral domain optical coherence tomography in the 1.3 μm wavelength range,” J. Biomed. Opt.16(11), 116020 (2011).
[CrossRef] [PubMed]

Koehler, R. C.

R. C. Koehler, D. Gebremedhin, and D. R. Harder, “Role of astrocytes in cerebrovascular regulation,” J. Appl. Physiol.100(1), 307–317 (2006).
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A. Villringer, A. Them, U. Lindauer, K. Einhäupl, and U. Dirnagl, “Capillary perfusion of the rat brain cortex. An in vivo confocal microscopy study,” Circ. Res.75(1), 55–62 (1994).
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Supplementary Material (2)

» Media 1: AVI (1846 KB)     
» Media 2: AVI (3119 KB)     

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Figures (8)

Fig. 1
Fig. 1

OCT angiography location was chosen based on optical intrinsic signal imaging (OISI). (A) Peak fractional reflectance change (∆R/R) map for OISI imaging at 570 nm, for a two second stimulus. The map is heavily weighed to the pial arteries, where the blood volume changes and relative reflectance changes are highest. (B) Time courses for fractional reflectance changes at locations labeled 1-4 (left). When normalized curves are plotted, differences in the response widths are evident (right). (C) Spatial map of the response width, showing better response localization than (A). (D) Single image at 570 nm, with OCT maximum intensity projection (MIP) angiogram overlay. (E) OCT MIP angiogram showing volumetric region measured during activation.

Fig. 2
Fig. 2

A correction procedure was applied to determine depth-specific dynamic backscattering changes. (A) The OCT angiogram, representing the dynamic signal Id, with relative changes in a region of interest (white rectangle) plotted during stimulation (average of 12 trials). (B) Raw OCT intensity image, with relative changes of static signal in the same region of interest plotted during stimulation. The static signal decrease is due to a µt increase (Eq. (5)), which likewise affects the dynamic signal (Eq. (6)). (C) As a solution to this confound, relative changes in normalized signal (magenta) are determined from the ratio of dynamic to static signal within the same region of interest. (D) Plot of the average fractional change in normalized signal (magenta squares) indicates a maximum at a cortical depth of between 500 and 700 microns. The average fractional change in static signal exhibits a linear dependence vs. depth (blue triangles), supporting the assumption of an increase in the attenuation coefficient. To achieve a larger depth of focus and investigate laminar differences, a 7.2 micron transverse resolution was used for this figure.

Fig. 3
Fig. 3

OCT angiography scanning protocols. (A) Three-dimensional scanning protocol used to determine compartment-resolved steady-state changes during a long stimulus (>10 s). (B) Four-dimensional asynchronous scanning protocol used to determine time-courses of compartment-resolved changes during a short (2 s) stimulus.

Fig. 4
Fig. 4

Separation of static and dynamic signal can be interpreted as a high-pass filtering procedure. A change in the dynamic spectrum width (related to velocity) or area (related to red blood cell number or orientation) may affect the measured dynamic signal in Eq. (10) and Eq. (11).

Fig. 5
Fig. 5

Three-dimensional volumetric imaging during continuous 3 Hz stimulation shows salient arterial dilation, subtle venous dilation, and apparent lack of capillary recruitment. Comparison of baseline (A) and activation (B) MIP angiograms shows that only one vessel branch which was not perfused at baseline becomes perfused during activation (green circle). Moreover, as depicted in the OCT angiograms, arteries clearly dilate (red arrows), while venous changes are more subtle (blue arrows). A change in the “striped” scattering pattern caused by RBC orientation in the surface vein is evident during activation (white lines, dotted represents baseline). This is due to higher flow in venules draining the activated region, and the presence of non-mixing flow streams. (C) Comparison of vessel diameters at baseline and during activation shows that while both arteries and veins dilate, arterial dilation is considerably greater than venous dilation.

Fig. 6
Fig. 6

Frames from a four-dimensional (4-D) movie of the hemodynamic response to functional activation, obtained from resampling a series of 3-D data sets obtained by the protocol shown in Fig. 4B. A maximum intensity projection over each resampled three-dimensional data set was performed to generate en face images at each time point relative to the stimulus. The stimulus is from 0 to 2 seconds. At 2.7 seconds, clear arterial dilation relative to baseline is observed (Media 1).

Fig. 7
Fig. 7

Compartment resolved changes in dRBC content were investigated with a 4-D scanning protocol at baseline (23-25 s after stimulus onset) and during maximal activation (2-4 s after stimulus onset). (A-B) The highly scattering stripe corresponding to non-mixing flow streams moves during activation (dotted white line in B corresponds to baseline). (C-D) In agreement with Fig. 5, arteries dilate, while veins barely dilate, and capillary recruitment is absent save one exception (green circle). (E) Relative diameter changes in arteries, but not veins, are statistically significant (N = 3) (Media 2).

Fig. 8
Fig. 8

Compartment-resolved changes in the normalized dynamic signal, reflecting dRBC content changes, were investigated. We selected individual regions of interest in the OCT angiograms, and investigated relative signal changes in these regions. (A-B) Large increases in the dynamic backscattering signal in both the arterial and arteriolar compartments were observed. (C-D) Modest increases in the dynamic backscattering signal in both the venular and capillary compartments were observed, with delayed returns to baseline. The average of all ROIs is shown as a solid black curve.

Equations (11)

Equations on this page are rendered with MathJax. Learn more.

R(x,y,z,τ,Τ)=R s (x,y,z,τ,Τ)+R d (x,y,z,τ,Τ)
I s (x,y,z,Τ)=R s (x,y,z,0,Τ)
I d (x,y,z,Τ)=R d (x,y,z,0,Τ)
μ t s a
I s (x,y,z,T)=B s (x,y,z)h spectrometer (z)h confocal (z)exp[-2μ t (x,y,T)z]
I d (x,y,z,T)=B d (x,y,z)h spectrometer (z)h confocal (z)exp[-2μ t (x,y,T)z]
I norm (x,y,z,T)= I d (x,y,z,T) I s (x,y,z,T) = B d (x,y,z,T) B s (x,y,z)
ΔI norm (x,y,z,T) I norm (x,y,z,0) = I norm (x,y,z,T)-I norm (x,y,z,0) I norm (x,y,z,0)
ΔI norm (x,y,z,T) I norm (x,y,z,0) = B d (x,y,z,T)-B d (x,y,z,0) B d (x,y,z,0)
ΔA(x,z,t)=ΔA[x,z, (t 2n +t 2n-1 ) 2 ]= |A(x,z,t 2n )-A(x,z,t 2n-1 )| 2
I d [x,y,z,T]= I d [x,v y ×mod(t-t 0,vol ,t vol ),z,mod(t-t 0,stim ,t rep )]=ΔA(x,z,t) 2

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