Abstract

Functional magnetic resonance (fMRI) imaging is the current gold-standard in neuroimaging. fMRI exploits local changes in blood oxygenation to map neuronal activity over the entire brain. However, its spatial resolution is currently limited to a few hundreds of microns. Here we use extended-focus optical coherence microscopy (xfOCM) to quantitatively measure changes in blood flow velocity during functional hyperaemia at high spatio-temporal resolution in the somatosensory cortex of mice. As optical coherence microscopy acquires hundreds of depth slices simultaneously, blood flow velocity measurements can be performed over several vessels in parallel. We present the proof-of-principle of an optimised statistical parametric mapping framework to analyse quantitative blood flow timetraces acquired with xfOCM using the general linear model. We demonstrate the feasibility of generating maps of cortical hemodynamic reactivity at the capillary level with optical coherence microscopy. To validate our method, we exploited 3 stimulation paradigms, covering different temporal dynamics and stimulated limbs, and demonstrated its repeatability over 2 trials, separated by a week.

© 2016 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Cerebral capillary velocimetry based on temporal OCT speckle contrast

Woo June Choi, Yuandong Li, Wan Qin, and Ruikang K. Wang
Biomed. Opt. Express 7(12) 4859-4873 (2016)

Quantitative cerebral blood flow imaging with extended-focus optical coherence microscopy

Arno Bouwens, Tristan Bolmont, Daniel Szlag, Corinne Berclaz, and Theo Lasser
Opt. Lett. 39(1) 37-40 (2014)

Measurement of the absolute velocity of blood flow in early-stage chick embryos using spectral domain optical coherence tomography

Z.-H. Ma, Y.-S. Ma, Y.-Q. Zhao, J. Liu, J.-H. Liu, J.-T. Lv, and Y. Wang
Appl. Opt. 56(31) 8832-8837 (2017)

References

  • View by:
  • |
  • |
  • |

  1. K. Friston, “Chapter 2 - Statistical parametric mapping,” in Statistical Parametric Mapping, K. Friston, J. Ashburner, S. Kiebel, T. Nichols, and W. Penny, eds. (Academic Press, London, 2007), pp. 10–31.
    [Crossref]
  2. L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
    [Crossref] [PubMed]
  3. A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
    [Crossref]
  4. 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, 1339–1345 (2011).
    [Crossref] [PubMed]
  5. V. J. Srinivasan and H. Radhakrishnan, “Optical Coherence Tomography angiography reveals laminar microvascular hemodynamics in the rat somatosensory cortex during activation,” Neuroimage 102, Part 2, 393–406 (2014).
    [Crossref] [PubMed]
  6. J. Lee, J. Y. Jiang, W. Wu, F. Lesage, and D. A. Boas, “Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux,” Biomed. Opt. Express 5, 1160 (2014).
    [Crossref] [PubMed]
  7. J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
    [Crossref] [PubMed]
  8. R. A. Leitgeb, M. Villiger, A. H. Bachmann, L. Steinmann, and T. Lasser, “Extended focus depth for Fourier domain optical coherence microscopy,” Opt. Lett. 31, 2450 (2006).
    [Crossref] [PubMed]
  9. A. Bouwens, D. Szlag, M. Szkulmowski, T. Bolmont, M. Wojtkowski, and T. Lasser, “Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography,” Opt. Express 21, 17711–17729 (2013).
    [Crossref] [PubMed]
  10. A. Bouwens, T. Bolmont, D. Szlag, C. Berclaz, and T. Lasser, “Quantitative cerebral blood flow imaging with extended-focus optical coherence microscopy,” Opt. Lett. 39, 37–40 (2014).
    [Crossref]
  11. T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
    [Crossref] [PubMed]
  12. J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
    [Crossref]
  13. V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
    [Crossref] [PubMed]
  14. C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
    [Crossref]
  15. J. R. Bumstead, A. Q. Bauer, P. W. Wright, and J. P. Culver, “Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability,” J. Cereb. Blood Flow Metab. (2016).
    [Crossref] [PubMed]
  16. C. Iadecola, “Neurovascular regulation in the normal brain and in Alzheimer’s disease,” Nat. Rev. Neurosci. 5, 347–360 (2004).
    [Crossref] [PubMed]
  17. D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
    [Crossref] [PubMed]
  18. F. Schlegel, A. Schroeter, and M. Rudin, “The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data,” Neuroimage 116, 40–49 (2015).
    [Crossref] [PubMed]
  19. 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, 1277–1309 (2012).
    [Crossref] [PubMed]
  20. 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,” Neuroimage 51, 1367–1377 (2010).
    [Crossref] [PubMed]
  21. Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
    [Crossref] [PubMed]

2015 (1)

F. Schlegel, A. Schroeter, and M. Rudin, “The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data,” Neuroimage 116, 40–49 (2015).
[Crossref] [PubMed]

2014 (5)

C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
[Crossref]

A. Bouwens, T. Bolmont, D. Szlag, C. Berclaz, and T. Lasser, “Quantitative cerebral blood flow imaging with extended-focus optical coherence microscopy,” Opt. Lett. 39, 37–40 (2014).
[Crossref]

V. J. Srinivasan and H. Radhakrishnan, “Optical Coherence Tomography angiography reveals laminar microvascular hemodynamics in the rat somatosensory cortex during activation,” Neuroimage 102, Part 2, 393–406 (2014).
[Crossref] [PubMed]

J. Lee, J. Y. Jiang, W. Wu, F. Lesage, and D. A. Boas, “Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux,” Biomed. Opt. Express 5, 1160 (2014).
[Crossref] [PubMed]

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

2013 (3)

J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
[Crossref] [PubMed]

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

A. Bouwens, D. Szlag, M. Szkulmowski, T. Bolmont, M. Wojtkowski, and T. Lasser, “Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography,” Opt. Express 21, 17711–17729 (2013).
[Crossref] [PubMed]

2012 (3)

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

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, 1277–1309 (2012).
[Crossref] [PubMed]

2011 (1)

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, 1339–1345 (2011).
[Crossref] [PubMed]

2010 (2)

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

2006 (1)

2004 (1)

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

2003 (1)

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

1998 (1)

D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
[Crossref] [PubMed]

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, 1339–1345 (2011).
[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, 1339–1345 (2011).
[Crossref] [PubMed]

Bachmann, A. H.

Barry, S.

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, 1339–1345 (2011).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

Bauer, A. Q.

J. R. Bumstead, A. Q. Bauer, P. W. Wright, and J. P. Culver, “Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability,” J. Cereb. Blood Flow Metab. (2016).
[Crossref] [PubMed]

Berclaz, C.

A. Bouwens, T. Bolmont, D. Szlag, C. Berclaz, and T. Lasser, “Quantitative cerebral blood flow imaging with extended-focus optical coherence microscopy,” Opt. Lett. 39, 37–40 (2014).
[Crossref]

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

Boas, D. A.

J. Lee, J. Y. Jiang, W. Wu, F. Lesage, and D. A. Boas, “Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux,” Biomed. Opt. Express 5, 1160 (2014).
[Crossref] [PubMed]

J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
[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, 1339–1345 (2011).
[Crossref] [PubMed]

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

Bolmont, T.

Bouwens, A.

Bumstead, J. R.

J. R. Bumstead, A. Q. Bauer, P. W. Wright, and J. P. Culver, “Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability,” J. Cereb. Blood Flow Metab. (2016).
[Crossref] [PubMed]

Cable, A. E.

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, 1339–1345 (2011).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

Calhoun, M. E.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Carp, S.

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

Chartash, D.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Culver, J. P.

J. R. Bumstead, A. Q. Bauer, P. W. Wright, and J. P. Culver, “Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability,” J. Cereb. Blood Flow Metab. (2016).
[Crossref] [PubMed]

Denk, W.

D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
[Crossref] [PubMed]

Dimitrov, M.

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

Dorr, A.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Drew, P. J.

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, 1277–1309 (2012).
[Crossref] [PubMed]

Drexler, W.

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

Driscoll, J. 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, 1277–1309 (2012).
[Crossref] [PubMed]

Du, C.

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
[Crossref]

Eicke, D.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Fercher, A. F.

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

Fraering, P. C.

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

Franceschini, M. A.

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

Friston, K.

K. Friston, “Chapter 2 - Statistical parametric mapping,” in Statistical Parametric Mapping, K. Friston, J. Ashburner, S. Kiebel, T. Nichols, and W. Penny, eds. (Academic Press, London, 2007), pp. 10–31.
[Crossref]

Grathwohl, S. A.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Hefendehl, J. K.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Helmchen, F.

D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
[Crossref] [PubMed]

Hitzenberger, C. K.

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

Huang, P. L.

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, 1339–1345 (2011).
[Crossref] [PubMed]

Iadecola, C.

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

Janik, R.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Jiang, J. Y.

Jucker, M.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

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, 1277–1309 (2012).
[Crossref] [PubMed]

D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
[Crossref] [PubMed]

Koretsky, A. P.

C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
[Crossref]

Lasser, T.

A. Bouwens, T. Bolmont, D. Szlag, C. Berclaz, and T. Lasser, “Quantitative cerebral blood flow imaging with extended-focus optical coherence microscopy,” Opt. Lett. 39, 37–40 (2014).
[Crossref]

A. Bouwens, D. Szlag, M. Szkulmowski, T. Bolmont, M. Wojtkowski, and T. Lasser, “Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography,” Opt. Express 21, 17711–17729 (2013).
[Crossref] [PubMed]

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

R. A. Leitgeb, M. Villiger, A. H. Bachmann, L. Steinmann, and T. Lasser, “Extended focus depth for Fourier domain optical coherence microscopy,” Opt. Lett. 31, 2450 (2006).
[Crossref] [PubMed]

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

Lee, J.

J. Lee, J. Y. Jiang, W. Wu, F. Lesage, and D. A. Boas, “Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux,” Biomed. Opt. Express 5, 1160 (2014).
[Crossref] [PubMed]

J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
[Crossref] [PubMed]

Leitgeb, R. A.

Lesage, F.

J. Lee, J. Y. Jiang, W. Wu, F. Lesage, and D. A. Boas, “Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux,” Biomed. Opt. Express 5, 1160 (2014).
[Crossref] [PubMed]

J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
[Crossref] [PubMed]

Liebig, C.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Lindvere, L.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Milford, D.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Mitra, P. P.

D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
[Crossref] [PubMed]

Nishimura, N.

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, 1277–1309 (2012).
[Crossref] [PubMed]

Pache, C.

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

Pan, Y.

C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
[Crossref]

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

Park, K.

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

Radhakrishnan, H.

V. J. Srinivasan and H. Radhakrishnan, “Optical Coherence Tomography angiography reveals laminar microvascular hemodynamics in the rat somatosensory cortex during activation,” Neuroimage 102, Part 2, 393–406 (2014).
[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, 1339–1345 (2011).
[Crossref] [PubMed]

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

Rudin, M.

F. Schlegel, A. Schroeter, and M. Rudin, “The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data,” Neuroimage 116, 40–49 (2015).
[Crossref] [PubMed]

Ruvinskaya, S.

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, 1339–1345 (2011).
[Crossref] [PubMed]

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

Sahota, B.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Schaffer, C. B.

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, 1277–1309 (2012).
[Crossref] [PubMed]

Schlegel, F.

F. Schlegel, A. Schroeter, and M. Rudin, “The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data,” Neuroimage 116, 40–49 (2015).
[Crossref] [PubMed]

Schroeter, A.

F. Schlegel, A. Schroeter, and M. Rudin, “The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data,” Neuroimage 116, 40–49 (2015).
[Crossref] [PubMed]

Shih, A. Y.

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, 1277–1309 (2012).
[Crossref] [PubMed]

Sled, J. G.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Srinivasan, V. J.

V. J. Srinivasan and H. Radhakrishnan, “Optical Coherence Tomography angiography reveals laminar microvascular hemodynamics in the rat somatosensory cortex during activation,” Neuroimage 102, Part 2, 393–406 (2014).
[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, 1339–1345 (2011).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

Stefanovic, B.

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

Steinmann, L.

Szkulmowski, M.

Szlag, D.

Thakur, K.

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

Villiger, M.

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

R. A. Leitgeb, M. Villiger, A. H. Bachmann, L. Steinmann, and T. Lasser, “Extended focus depth for Fourier domain optical coherence microscopy,” Opt. Lett. 31, 2450 (2006).
[Crossref] [PubMed]

Volkow, N.

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

Volkow, N. D.

C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
[Crossref]

Wegenast-Braun, B. M.

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

Wojtkowski, M.

Wright, P. W.

J. R. Bumstead, A. Q. Bauer, P. W. Wright, and J. P. Culver, “Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability,” J. Cereb. Blood Flow Metab. (2016).
[Crossref] [PubMed]

Wu, W.

J. Lee, J. Y. Jiang, W. Wu, F. Lesage, and D. A. Boas, “Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux,” Biomed. Opt. Express 5, 1160 (2014).
[Crossref] [PubMed]

J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
[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, 1339–1345 (2011).
[Crossref] [PubMed]

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

V. J. Srinivasan, J. Y. Jiang, M. A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A. E. Cable, and D. A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43–45 (2010).
[Crossref] [PubMed]

Yaseen, M. A.

You, J.

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

Biomed. Opt. Express (1)

J. Cereb. Blood Flow Metab. (3)

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, 1339–1345 (2011).
[Crossref] [PubMed]

J. Lee, W. Wu, F. Lesage, and D. A. Boas, “Multiple-capillary measurement of RBC speed, flux, and density with optical coherence tomography,” J. Cereb. Blood Flow Metab. 33, 1707–1710 (2013).
[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, 1277–1309 (2012).
[Crossref] [PubMed]

J. Neurosci. (1)

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

J. Neurosci. Methods (1)

J. K. Hefendehl, D. Milford, D. Eicke, B. M. Wegenast-Braun, M. E. Calhoun, S. A. Grathwohl, M. Jucker, and C. Liebig, “Repeatable target localization for long-term in vivo imaging of mice with 2-photon microscopy,” J. Neurosci. Methods 205, 357–363 (2012).
[Crossref]

Nat. Rev. Neurosci. (1)

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

Neuroimage (5)

L. Lindvere, R. Janik, A. Dorr, D. Chartash, B. Sahota, J. G. Sled, and B. Stefanovic, “Cerebral microvascular network geometry changes in response to functional stimulation,” Neuroimage 71, 248–259 (2013).
[Crossref] [PubMed]

V. J. Srinivasan and H. Radhakrishnan, “Optical Coherence Tomography angiography reveals laminar microvascular hemodynamics in the rat somatosensory cortex during activation,” Neuroimage 102, Part 2, 393–406 (2014).
[Crossref] [PubMed]

F. Schlegel, A. Schroeter, and M. Rudin, “The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data,” Neuroimage 116, 40–49 (2015).
[Crossref] [PubMed]

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,” Neuroimage 51, 1367–1377 (2010).
[Crossref] [PubMed]

Y. Pan, J. You, N. Volkow, K. Park, and C. Du, “Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo,” Neuroimage 103, 492–501 (2014).
[Crossref] [PubMed]

Opt. Express (1)

Opt. Lett. (3)

Proc. Natl. Acad. Sci. U.S.A. (2)

C. Du, N. D. Volkow, A. P. Koretsky, and Y. Pan, “Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex,” Proc. Natl. Acad. Sci. U.S.A. 111, 1–10 (2014).
[Crossref]

D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex,” Proc. Natl. Acad. Sci. U.S.A. 95, 15741–15746 (1998).
[Crossref] [PubMed]

Rep. Prog. Phys. (1)

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography - development, principles, applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

Other (2)

J. R. Bumstead, A. Q. Bauer, P. W. Wright, and J. P. Culver, “Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability,” J. Cereb. Blood Flow Metab. (2016).
[Crossref] [PubMed]

K. Friston, “Chapter 2 - Statistical parametric mapping,” in Statistical Parametric Mapping, K. Friston, J. Ashburner, S. Kiebel, T. Nichols, and W. Penny, eds. (Academic Press, London, 2007), pp. 10–31.
[Crossref]

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (5)

Fig. 1
Fig. 1 The xfOCM set-up was augmented with an OIS imaging module and an LED ring to localise the area of maximal response to stimulation (a). Two individual computers controlled the xfOCM and the OIS detection respectively and were both connected to a Pulse Stimulator to deliver the electrical pulses to the limb of interest. OCM angiograms, as shown in (d), were obtained by acquiring 3 passes along the slow axis at each lateral position (b). In contrast, total flow velocity images, as depicted in tile (e), were obtained by oversampling 32 times along the fast axis (c). During the functional imaging, the total blood flow velocity protocol was applied at selected lateral positions (highlighted by the red arrow in (c) and by yellow dashed line in the following figures) instead of all over the lateral field of view to increase the temporal resolution of the acquisitions. The differences between total flow and axial flow images are portrayed in tiles (e) & (f) respectively, where the orientation of the vessel leads to discontinuities and speed reversal in the axial but not in the total flow image. Moreover, the range of velocities between both tiles is also different, as in (e) the magnitude of the total velocity vector is shown whereas only the magnitude of its projection along the optical axis is shown in (f). Scalebars: 200 µm.
Fig. 2
Fig. 2 SPM-OCM protocol: An angiogram (a) is first acquired on the area of response previously localised using OIS imaging. At a selected lateral position (highlighted by the yellow dashed line in a), an acquisition of total blood flow during the electrical stimulation is performed (b). Subsequently, an angiogram is acquired at the same location for segmentation purposes (c). The vessels in the selected angiogram are segmented manually via a MATLAB interface (d) and the total blood flow timetraces of each individual segmented vessel are isolated and smoothed temporally. Finally, a GLM analysis, using a design matrix (example for the short stimulation paradigm shown in (f)), is performed on each timetrace and leads to a p-value map, displaying the vessel’s reactivity (e). The design matrix used in the GLM analyses comprised the velocity response regressor h, its derivative dh/dt, a baseline flow value CBFv0 and a drift component (f). An illustration of the results obtained by the GLM analysis is displayed in tile (g), showing that the p-value obtained by the regression is sensitive to the noise in the data, pointed by the arrows. Scalebars: 100 µm.
Fig. 3
Fig. 3 Assessment of the variability of the evoked response within different vascular compartments using the short protocol on animal 1. OISI imaging is first used to localise the area of maximal response to the electrical stimulation, here with a 5× objective (a). An angiogram is then obtained in OCM over a selected region (square in tile (a)) to reveal the vasculature (b). The total velocity timetraces which lead to a statistically significant result after GLM analysis are displayed in tile (c), demonstrating the inherent heterogeneity of the hemodynamic reactivity of vessels (the arrows indicate both fast and slow total blood flow responses). The statistical maps of the different lateral positions highlighted in (b) are shown in tiles (d) to (h), where the p-value is color coded. The regressor used to model the velocity response for the GLM analysis of this dataset is shown in tile (i). The significant timetraces were grouped according to their respective vascular compartment (arteries and arterioles, capillaries and venules and veins) and both their average relative changes and average blood velocity are plotted in tile (j). The shaded areas in (j) represent the standard error around the mean (in bold). Each individual relative change curve are plotted in light grey in the relative changed panel. Scalebars: 100 µm.
Fig. 4
Fig. 4 Assessment of the viability of SPM-OCM for longitudinal studies obtained by applying the long protocol on animal 2. The depth-coded angiograms for both trials are shown in tile (a) and (e) respectively, showing that the region interrogated in each trials was identical. The statistical maps characterizing the hemodynamic reactivity of the vessels are shown for the lateral positions highlighted with yellow dashed lines in the angiograms ((a) & (e)) in tiles (b) to (h). The average of all of the timetraces for both trials are shown in tile (i), whereas a selection of the statistically significant timetraces for each trials are shown in tiles (j) and (k). Interestingly, the higher flow traces are accompanied by a low frequency fluctuation, typically observed in cortical arteries (pointed by the arrows in (j) & (k)). Scalebars: 100 µm.
Fig. 5
Fig. 5 Illustration of the use of different stimulation protocols using SPM-OCM: Results for both short and long protocols on the animal 3. The top half of the figure displays the results from the short electrical stimulation applied to the hindpaw (Pr1). OIS imaging was first used to localize the area of maximal response to the stimulus with a 5× objective (a). An angiogram was then acquired using xfOCM over the area localized by OISI (b). Statistically relevent total velocity timetraces are plotted in tile (c), revealing again the intrinsic heterogeneity of the stimuli evoked velocity response. The statistical maps of the lateral positions highlighted in tile (b) are displayed in tiles (d), (e), (f) and (g). Similarly to animal 1, the vascular compartment of each timetrace was identified and the mean changes relative to the baseline and mean velocity for each group is plotted in (h). The mean of the respective plots is shown in bold with the standard error. The individual relative change curves for each vessel are shown in light grey. The lower half of the figure presents the results obtained using the long protocol applied to the forepaw (Pr3). Once again, OISI was used to first localize the area of maximal response (h), which was then imaged using xfOCM angiography (i). The statistical maps obtained after SPM analysis of the total velocity timetraces are displayed in tiles (j) to (p), with their lateral positions highlighted in tile (i). Scalebars: 100 µm.

Tables (3)

Tables Icon

Table 1 Summary of the 3 stimulation protocols used for the proof-of-principle of SPM-OCM

Tables Icon

Table 2 Summary of the acquisition protocols used for the proof-of-principle of SPM-OCM

Tables Icon

Table 3 Summary of the different average total blood flow speeds acquired for all animals and protocols. The mean value is given with the respective standard error. A: Arteries and arterioles, C: capillaries, V: Venules and veins.

Equations (2)

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

y = X [ β 1 β 2 β n ] + ϵ
H R F = ( t T 0 ) n 1 e ( t + T 0 ) / λ ( n 1 ) ! λ n

Metrics