Abstract

This study aims to assess the impact of unilateral increases in carotid stiffness on cortical functional connectivity measures in the resting state. Using a novel animal model of induced arterial stiffness combined with optical intrinsic signals and laser speckle imaging, resting state functional networks derived from hemodynamic signals are investigated for their modulation by isolated changes in stiffness of the right common carotid artery. By means of seed-based analysis, results showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Furthermore, a graph analysis indicated a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex lateral to the treated carotid, which however did not translate in differentiated metabolic activity.

© 2013 Optical Society of America

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2012 (5)

M. P. Pase, A. Herbert, N. A. Grima, A. Pipingas, M. F. O’Rourke, “Arterial stiffness as a cause of cognitive decline and dementia: a systematic review and meta-analysis,” Intern. Med. J. 42(7), 808–815 (2012).
[CrossRef]

V. Bolduc, E. Baraghis, N. Duquette, N. Thorin-Trescases, J. Lambert, F. Lesage, E. Thorin, “Catechin prevents severe dyslipidemia-associated changes in wall biomechanics of cerebral arteries in LDLr−/−:hApoB+/+ mice and improves cerebral blood flow,” Am. J. Physiol. Heart Circ. Physiol. 302(6), H1330–H1339 (2012).
[CrossRef]

H.-L. Cheng, C.-J. Lin, B.-W. Soong, P.-N. Wang, F.-C. Chang, Y.-T. Wu, K.-H. Chou, C.-P. Lin, P.-C. Tu, I.-H. Lee, “Impairments in cognitive function and brain connectivity in severe asymptomatic carotid stenosis,” Stroke 43(10), 2567–2573 (2012).
[CrossRef]

A. W. Bero, A. Q. Bauer, F. R. Stewart, B. R. White, J. R. Cirrito, M. E. Raichle, J. P. Culver, D. M. Holtzman, “Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain,” J. Neurosci. 32(13), 4334–4340 (2012).
[CrossRef]

S. Whitfield-Gabrieli, A. Nieto-Castanon, “Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks,” Brain Connect 2(3), 125–141 (2012).
[CrossRef]

2011 (8)

B. R. White, A. Q. Bauer, A. Z. Snyder, B. L. Schlaggar, J.-M. Lee, J. P. Culver, “Imaging of functional connectivity in the mouse brain,” PLoS ONE 6(1), e16322 (2011).
[CrossRef]

Y. Sun, L. Qin, Y. Zhou, Q. Xu, L. Qian, J. Tao, J. Xu, “Abnormal functional connectivity in patients with vascular cognitive impairment, no dementia: a resting-state functional magnetic resonance imaging study,” Behav. Brain Res. 223(2), 388–394 (2011).
[CrossRef]

A. G. van Norden, K. F. de Laat, R. A. Gons, I. W. van Uden, E. J. van Dijk, L. J. van Oudheusden, R. A. Esselink, B. R. Bloem, B. G. van Engelen, M. J. Zwarts, I. Tendolkar, M. G. Olde-Rikkert, M. J. van der Vlugt, M. P. Zwiers, D. G. Norris, F.-E. de Leeuw, “Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol,” BMC Neurol. 11(1), 29 (2011).
[CrossRef]

T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, “Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution,” J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011).
[CrossRef]

S. Dubeau, G. Ferland, P. Gaudreau, E. Beaumont, F. Lesage, “Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: A model of healthy aging,” Neuroimage 56(4), 1892–1901 (2011).
[CrossRef]

R. S. Marshall, R. M. Lazar, “Pumps, aqueducts, and drought management: vascular physiology in vascular cognitive impairment,” Stroke 42(1), 221–226 (2011).
[CrossRef]

F. M. Faraci, “Protecting against vascular disease in brain,” Am. J. Physiol. Heart Circ. Physiol. 300(5), H1566–H1582 (2011).
[CrossRef]

J. Sun, S. Tong, G.-Y. Yang, “Reorganization of Brain Networks in Aging and Age-related Diseases,” Aging Dis. 3, 181–193 (2011).

2010 (7)

C. Iadecola, “The overlap between neurodegenerative and vascular factors in the pathogenesis of dementia,” Acta Neuropathol. 120(3), 287–296 (2010).
[CrossRef]

R. O. Roberts, D. S. Knopman, Y. E. Geda, R. H. Cha, V. L. Roger, R. C. Petersen, “Coronary heart disease is associated with non-amnestic mild cognitive impairment,” Neurobiol. Aging 31(11), 1894–1902 (2010).
[CrossRef]

M. P. van den Heuvel, H. E. Hulshoff Pol, “Exploring the brain network: A review on resting-state fMRI functional connectivity,” Eur. Neuropsychopharmacol. 20(8), 519–534 (2010).
[CrossRef]

D. M. Cole, S. M. Smith, C. F. Beckmann, “Advances and pitfalls in the analysis and interpretation of resting-state FMRI data,” Front Syst Neurosci 4, 8 (2010).

N. Brieu, E. Beaumont, S. Dubeau, J. Cohen-Adad, F. Lesage, “Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle,” J. Neurosci. Methods 191(2), 151–157 (2010).
[CrossRef]

D. A. Boas, A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15(1), 011109 (2010).
[CrossRef]

J. Luckl, W. Baker, Z.-H. Sun, T. Durduran, A. G. Yodh, J. H. Greenberg, “The biological effect of contralateral forepaw stimulation in rat focal cerebral ischemia: a multispectral optical imaging study,” Front Neuroenergetics 2, 19 (2010).

2009 (2)

Y. He, Z. Chen, G. Gong, A. Evans, “Neuronal networks in Alzheimer’s disease,” Neuroscientist 15(4), 333–350 (2009).
[CrossRef]

O. Moldestad, P. Karlsen, S. Molden, J. F. Storm, “Tracheotomy improves experiment success rate in mice during urethane anesthesia and stereotaxic surgery,” J. Neurosci. Methods 176(2), 57–62 (2009).
[CrossRef]

2008 (1)

R. L. Buckner, J. R. Andrews-Hanna, D. L. Schacter, “The brain’s default network: anatomy, function, and relevance to disease,” Ann. N. Y. Acad. Sci. 1124(1), 1–38 (2008).
[CrossRef]

2007 (3)

M. D. Fox, M. E. Raichle, “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci. 8(9), 700–711 (2007).
[CrossRef]

S. Achard, E. Bullmore, “Efficiency and Cost of Economical Brain Functional Networks,” PLOS Comput. Biol. 3(2), e17 (2007).
[CrossRef]

J. Saramäki, M. Kivelä, J.-P. Onnela, K. Kaski, J. Kertész, “Generalizations of the clustering coefficient to weighted complex networks,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 75(2), 027105 (2007).
[CrossRef]

2006 (1)

D. S. Bassett, E. Bullmore, “Small-world brain networks,” Neuroscientist 12(6), 512–523 (2006).
[CrossRef]

2005 (1)

A. K. Dunn, A. Devor, A. M. Dale, D. A. Boas, “Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex,” Neuroimage 27(2), 279–290 (2005).
[CrossRef]

2004 (1)

M. D. Greicius, G. Srivastava, A. L. Reiss, V. Menon, “Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI,” Proc. Natl. Acad. Sci. U.S.A. 101(13), 4637–4642 (2004).
[CrossRef]

2003 (3)

M. D. Greicius, B. Krasnow, A. L. Reiss, V. Menon, “Functional connectivity in the resting brain: a network analysis of the default mode hypothesis,” Proc. Natl. Acad. Sci. U.S.A. 100(1), 253–258 (2003).
[CrossRef]

A. Singh-Manoux, A. R. Britton, M. Marmot, “Vascular disease and cognitive function: evidence from the Whitehall II Study,” J. Am. Geriatr. Soc. 51(10), 1445–1450 (2003).
[CrossRef]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, D. A. Boas, “Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation,” Opt. Lett. 28(1), 28–30 (2003).
[CrossRef]

2002 (1)

B. H. Anderton, “Ageing of the brain,” Mech. Ageing Dev. 123(7), 811–817 (2002).
[CrossRef]

2001 (6)

R. S. Marshall, R. M. Lazar, J. Pile-Spellman, W. L. Young, D. H. Duong, S. Joshi, N. Ostapkovich, “Recovery of brain function during induced cerebral hypoperfusion,” Brain 124(6), 1208–1217 (2001).
[CrossRef]

D. A. Gusnard, M. E. Raichle, “Searching for a baseline: functional imaging and the resting human brain,” Nat. Rev. Neurosci. 2(10), 685–694 (2001).
[CrossRef]

J. D. Briers, “Laser Doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22(4), R35–R66 (2001).
[CrossRef]

A. K. Dunn, H. Bolay, M. A. Moskowitz, D. A. Boas, “Dynamic Imaging of Cerebral Blood Flow Using Laser Speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[CrossRef]

M. Jones, J. Berwick, D. Johnston, J. Mayhew, “Concurrent optical imaging spectroscopy and laser-Doppler flowmetry: the relationship between blood flow, oxygenation, and volume in rodent barrel cortex,” Neuroimage 13(6), 1002–1015 (2001).
[CrossRef]

V. Latora, M. Marchiori, “Efficient Behavior of Small-World Networks,” Phys. Rev. Lett. 87(19), 198701 (2001).
[CrossRef]

2000 (2)

J. Mayhew, D. Johnston, J. Berwick, M. Jones, P. Coffey, Y. Zheng, “Spectroscopic Analysis of Neural Activity in Brain: Increased Oxygen Consumption Following Activation of Barrel Cortex,” Neuroimage 12(6), 664–675 (2000).
[CrossRef]

M. Kohl, U. Lindauer, G. Royl, M. Kuhl, L. Gold, A. Villringer, U. Dirnagl, “Physical model for the spectroscopic analysis of cortical intrinsic optical signals,” Phys. Med. Biol. 45(12), 3749–3764 (2000).
[CrossRef]

1998 (1)

P. Thevenaz, U. E. Ruttimann, M. Unser, “A pyramid approach to subpixel registration based on intensity,” IEEE Trans. Image Process. 7(1), 27–41 (1998).
[CrossRef]

1994 (2)

F. Pukelsheim, “The Three Sigma Rule,” Am. Stat. 48, 88 (1994).

M. M. Breteler, J. J. Claus, D. E. Grobbee, A. Hofman, “Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study,” BMJ 308(6944), 1604–1608 (1994).
[CrossRef]

1990 (1)

M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
[CrossRef]

1988 (1)

D. T. Delpy, M. Cope, P. van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33(12), 1433–1442 (1988).
[CrossRef]

Achard, S.

S. Achard, E. Bullmore, “Efficiency and Cost of Economical Brain Functional Networks,” PLOS Comput. Biol. 3(2), e17 (2007).
[CrossRef]

Andermann, M. L.

Anderton, B. H.

B. H. Anderton, “Ageing of the brain,” Mech. Ageing Dev. 123(7), 811–817 (2002).
[CrossRef]

Andrews-Hanna, J. R.

R. L. Buckner, J. R. Andrews-Hanna, D. L. Schacter, “The brain’s default network: anatomy, function, and relevance to disease,” Ann. N. Y. Acad. Sci. 1124(1), 1–38 (2008).
[CrossRef]

Aronson, M. K.

M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
[CrossRef]

Arridge, S.

D. T. Delpy, M. Cope, P. van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33(12), 1433–1442 (1988).
[CrossRef]

Baker, W.

J. Luckl, W. Baker, Z.-H. Sun, T. Durduran, A. G. Yodh, J. H. Greenberg, “The biological effect of contralateral forepaw stimulation in rat focal cerebral ischemia: a multispectral optical imaging study,” Front Neuroenergetics 2, 19 (2010).

Baraghis, E.

V. Bolduc, E. Baraghis, N. Duquette, N. Thorin-Trescases, J. Lambert, F. Lesage, E. Thorin, “Catechin prevents severe dyslipidemia-associated changes in wall biomechanics of cerebral arteries in LDLr−/−:hApoB+/+ mice and improves cerebral blood flow,” Am. J. Physiol. Heart Circ. Physiol. 302(6), H1330–H1339 (2012).
[CrossRef]

Bassett, D. S.

D. S. Bassett, E. Bullmore, “Small-world brain networks,” Neuroscientist 12(6), 512–523 (2006).
[CrossRef]

Bauer, A. Q.

A. W. Bero, A. Q. Bauer, F. R. Stewart, B. R. White, J. R. Cirrito, M. E. Raichle, J. P. Culver, D. M. Holtzman, “Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain,” J. Neurosci. 32(13), 4334–4340 (2012).
[CrossRef]

B. R. White, A. Q. Bauer, A. Z. Snyder, B. L. Schlaggar, J.-M. Lee, J. P. Culver, “Imaging of functional connectivity in the mouse brain,” PLoS ONE 6(1), e16322 (2011).
[CrossRef]

Beaumont, E.

S. Dubeau, G. Ferland, P. Gaudreau, E. Beaumont, F. Lesage, “Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: A model of healthy aging,” Neuroimage 56(4), 1892–1901 (2011).
[CrossRef]

N. Brieu, E. Beaumont, S. Dubeau, J. Cohen-Adad, F. Lesage, “Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle,” J. Neurosci. Methods 191(2), 151–157 (2010).
[CrossRef]

Beckmann, C. F.

D. M. Cole, S. M. Smith, C. F. Beckmann, “Advances and pitfalls in the analysis and interpretation of resting-state FMRI data,” Front Syst Neurosci 4, 8 (2010).

Bero, A. W.

A. W. Bero, A. Q. Bauer, F. R. Stewart, B. R. White, J. R. Cirrito, M. E. Raichle, J. P. Culver, D. M. Holtzman, “Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain,” J. Neurosci. 32(13), 4334–4340 (2012).
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M. Jones, J. Berwick, D. Johnston, J. Mayhew, “Concurrent optical imaging spectroscopy and laser-Doppler flowmetry: the relationship between blood flow, oxygenation, and volume in rodent barrel cortex,” Neuroimage 13(6), 1002–1015 (2001).
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J. Mayhew, D. Johnston, J. Berwick, M. Jones, P. Coffey, Y. Zheng, “Spectroscopic Analysis of Neural Activity in Brain: Increased Oxygen Consumption Following Activation of Barrel Cortex,” Neuroimage 12(6), 664–675 (2000).
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A. G. van Norden, K. F. de Laat, R. A. Gons, I. W. van Uden, E. J. van Dijk, L. J. van Oudheusden, R. A. Esselink, B. R. Bloem, B. G. van Engelen, M. J. Zwarts, I. Tendolkar, M. G. Olde-Rikkert, M. J. van der Vlugt, M. P. Zwiers, D. G. Norris, F.-E. de Leeuw, “Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol,” BMC Neurol. 11(1), 29 (2011).
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D. A. Boas, A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15(1), 011109 (2010).
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A. K. Dunn, A. Devor, A. M. Dale, D. A. Boas, “Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex,” Neuroimage 27(2), 279–290 (2005).
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A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, D. A. Boas, “Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation,” Opt. Lett. 28(1), 28–30 (2003).
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A. K. Dunn, H. Bolay, M. A. Moskowitz, D. A. Boas, “Dynamic Imaging of Cerebral Blood Flow Using Laser Speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
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Bolduc, V.

V. Bolduc, E. Baraghis, N. Duquette, N. Thorin-Trescases, J. Lambert, F. Lesage, E. Thorin, “Catechin prevents severe dyslipidemia-associated changes in wall biomechanics of cerebral arteries in LDLr−/−:hApoB+/+ mice and improves cerebral blood flow,” Am. J. Physiol. Heart Circ. Physiol. 302(6), H1330–H1339 (2012).
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T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, “Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution,” J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011).
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M. M. Breteler, J. J. Claus, D. E. Grobbee, A. Hofman, “Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study,” BMJ 308(6944), 1604–1608 (1994).
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N. Brieu, E. Beaumont, S. Dubeau, J. Cohen-Adad, F. Lesage, “Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle,” J. Neurosci. Methods 191(2), 151–157 (2010).
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A. Singh-Manoux, A. R. Britton, M. Marmot, “Vascular disease and cognitive function: evidence from the Whitehall II Study,” J. Am. Geriatr. Soc. 51(10), 1445–1450 (2003).
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T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, “Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution,” J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011).
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T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, “Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution,” J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011).
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R. O. Roberts, D. S. Knopman, Y. E. Geda, R. H. Cha, V. L. Roger, R. C. Petersen, “Coronary heart disease is associated with non-amnestic mild cognitive impairment,” Neurobiol. Aging 31(11), 1894–1902 (2010).
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H.-L. Cheng, C.-J. Lin, B.-W. Soong, P.-N. Wang, F.-C. Chang, Y.-T. Wu, K.-H. Chou, C.-P. Lin, P.-C. Tu, I.-H. Lee, “Impairments in cognitive function and brain connectivity in severe asymptomatic carotid stenosis,” Stroke 43(10), 2567–2573 (2012).
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Y. He, Z. Chen, G. Gong, A. Evans, “Neuronal networks in Alzheimer’s disease,” Neuroscientist 15(4), 333–350 (2009).
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H.-L. Cheng, C.-J. Lin, B.-W. Soong, P.-N. Wang, F.-C. Chang, Y.-T. Wu, K.-H. Chou, C.-P. Lin, P.-C. Tu, I.-H. Lee, “Impairments in cognitive function and brain connectivity in severe asymptomatic carotid stenosis,” Stroke 43(10), 2567–2573 (2012).
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H.-L. Cheng, C.-J. Lin, B.-W. Soong, P.-N. Wang, F.-C. Chang, Y.-T. Wu, K.-H. Chou, C.-P. Lin, P.-C. Tu, I.-H. Lee, “Impairments in cognitive function and brain connectivity in severe asymptomatic carotid stenosis,” Stroke 43(10), 2567–2573 (2012).
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A. W. Bero, A. Q. Bauer, F. R. Stewart, B. R. White, J. R. Cirrito, M. E. Raichle, J. P. Culver, D. M. Holtzman, “Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain,” J. Neurosci. 32(13), 4334–4340 (2012).
[CrossRef]

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M. M. Breteler, J. J. Claus, D. E. Grobbee, A. Hofman, “Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study,” BMJ 308(6944), 1604–1608 (1994).
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J. Mayhew, D. Johnston, J. Berwick, M. Jones, P. Coffey, Y. Zheng, “Spectroscopic Analysis of Neural Activity in Brain: Increased Oxygen Consumption Following Activation of Barrel Cortex,” Neuroimage 12(6), 664–675 (2000).
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N. Brieu, E. Beaumont, S. Dubeau, J. Cohen-Adad, F. Lesage, “Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle,” J. Neurosci. Methods 191(2), 151–157 (2010).
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D. M. Cole, S. M. Smith, C. F. Beckmann, “Advances and pitfalls in the analysis and interpretation of resting-state FMRI data,” Front Syst Neurosci 4, 8 (2010).

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D. T. Delpy, M. Cope, P. van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33(12), 1433–1442 (1988).
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M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
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A. W. Bero, A. Q. Bauer, F. R. Stewart, B. R. White, J. R. Cirrito, M. E. Raichle, J. P. Culver, D. M. Holtzman, “Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain,” J. Neurosci. 32(13), 4334–4340 (2012).
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A. K. Dunn, A. Devor, A. M. Dale, D. A. Boas, “Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex,” Neuroimage 27(2), 279–290 (2005).
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A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, D. A. Boas, “Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation,” Opt. Lett. 28(1), 28–30 (2003).
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A. G. van Norden, K. F. de Laat, R. A. Gons, I. W. van Uden, E. J. van Dijk, L. J. van Oudheusden, R. A. Esselink, B. R. Bloem, B. G. van Engelen, M. J. Zwarts, I. Tendolkar, M. G. Olde-Rikkert, M. J. van der Vlugt, M. P. Zwiers, D. G. Norris, F.-E. de Leeuw, “Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol,” BMC Neurol. 11(1), 29 (2011).
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A. G. van Norden, K. F. de Laat, R. A. Gons, I. W. van Uden, E. J. van Dijk, L. J. van Oudheusden, R. A. Esselink, B. R. Bloem, B. G. van Engelen, M. J. Zwarts, I. Tendolkar, M. G. Olde-Rikkert, M. J. van der Vlugt, M. P. Zwiers, D. G. Norris, F.-E. de Leeuw, “Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol,” BMC Neurol. 11(1), 29 (2011).
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D. T. Delpy, M. Cope, P. van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33(12), 1433–1442 (1988).
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A. K. Dunn, A. Devor, A. M. Dale, D. A. Boas, “Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex,” Neuroimage 27(2), 279–290 (2005).
[CrossRef]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, D. A. Boas, “Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation,” Opt. Lett. 28(1), 28–30 (2003).
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M. Kohl, U. Lindauer, G. Royl, M. Kuhl, L. Gold, A. Villringer, U. Dirnagl, “Physical model for the spectroscopic analysis of cortical intrinsic optical signals,” Phys. Med. Biol. 45(12), 3749–3764 (2000).
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S. Dubeau, G. Ferland, P. Gaudreau, E. Beaumont, F. Lesage, “Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: A model of healthy aging,” Neuroimage 56(4), 1892–1901 (2011).
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N. Brieu, E. Beaumont, S. Dubeau, J. Cohen-Adad, F. Lesage, “Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle,” J. Neurosci. Methods 191(2), 151–157 (2010).
[CrossRef]

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D. A. Boas, A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15(1), 011109 (2010).
[CrossRef]

A. K. Dunn, A. Devor, A. M. Dale, D. A. Boas, “Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex,” Neuroimage 27(2), 279–290 (2005).
[CrossRef]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, D. A. Boas, “Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation,” Opt. Lett. 28(1), 28–30 (2003).
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A. K. Dunn, H. Bolay, M. A. Moskowitz, D. A. Boas, “Dynamic Imaging of Cerebral Blood Flow Using Laser Speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[CrossRef]

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R. S. Marshall, R. M. Lazar, J. Pile-Spellman, W. L. Young, D. H. Duong, S. Joshi, N. Ostapkovich, “Recovery of brain function during induced cerebral hypoperfusion,” Brain 124(6), 1208–1217 (2001).
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Duquette, N.

V. Bolduc, E. Baraghis, N. Duquette, N. Thorin-Trescases, J. Lambert, F. Lesage, E. Thorin, “Catechin prevents severe dyslipidemia-associated changes in wall biomechanics of cerebral arteries in LDLr−/−:hApoB+/+ mice and improves cerebral blood flow,” Am. J. Physiol. Heart Circ. Physiol. 302(6), H1330–H1339 (2012).
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J. Luckl, W. Baker, Z.-H. Sun, T. Durduran, A. G. Yodh, J. H. Greenberg, “The biological effect of contralateral forepaw stimulation in rat focal cerebral ischemia: a multispectral optical imaging study,” Front Neuroenergetics 2, 19 (2010).

Esselink, R. A.

A. G. van Norden, K. F. de Laat, R. A. Gons, I. W. van Uden, E. J. van Dijk, L. J. van Oudheusden, R. A. Esselink, B. R. Bloem, B. G. van Engelen, M. J. Zwarts, I. Tendolkar, M. G. Olde-Rikkert, M. J. van der Vlugt, M. P. Zwiers, D. G. Norris, F.-E. de Leeuw, “Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol,” BMC Neurol. 11(1), 29 (2011).
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Y. He, Z. Chen, G. Gong, A. Evans, “Neuronal networks in Alzheimer’s disease,” Neuroscientist 15(4), 333–350 (2009).
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F. M. Faraci, “Protecting against vascular disease in brain,” Am. J. Physiol. Heart Circ. Physiol. 300(5), H1566–H1582 (2011).
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S. Dubeau, G. Ferland, P. Gaudreau, E. Beaumont, F. Lesage, “Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: A model of healthy aging,” Neuroimage 56(4), 1892–1901 (2011).
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M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
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M. D. Fox, M. E. Raichle, “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci. 8(9), 700–711 (2007).
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M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
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S. Dubeau, G. Ferland, P. Gaudreau, E. Beaumont, F. Lesage, “Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: A model of healthy aging,” Neuroimage 56(4), 1892–1901 (2011).
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R. O. Roberts, D. S. Knopman, Y. E. Geda, R. H. Cha, V. L. Roger, R. C. Petersen, “Coronary heart disease is associated with non-amnestic mild cognitive impairment,” Neurobiol. Aging 31(11), 1894–1902 (2010).
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Gili, T.

T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, “Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution,” J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011).
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T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, “Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution,” J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011).
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N. Sadekova, D. Vallerand, E. Guevara, F. Lesage, H. Girouard, “Carotid calcification in mice: a new model to study the effects of arterial stiffness on the brain,” J Am Heart Assoc. Manuscript ID JAHA/2013/000224–T2 (posted May 17 2013, in press).

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M. Kohl, U. Lindauer, G. Royl, M. Kuhl, L. Gold, A. Villringer, U. Dirnagl, “Physical model for the spectroscopic analysis of cortical intrinsic optical signals,” Phys. Med. Biol. 45(12), 3749–3764 (2000).
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Y. He, Z. Chen, G. Gong, A. Evans, “Neuronal networks in Alzheimer’s disease,” Neuroscientist 15(4), 333–350 (2009).
[CrossRef]

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A. G. van Norden, K. F. de Laat, R. A. Gons, I. W. van Uden, E. J. van Dijk, L. J. van Oudheusden, R. A. Esselink, B. R. Bloem, B. G. van Engelen, M. J. Zwarts, I. Tendolkar, M. G. Olde-Rikkert, M. J. van der Vlugt, M. P. Zwiers, D. G. Norris, F.-E. de Leeuw, “Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol,” BMC Neurol. 11(1), 29 (2011).
[CrossRef]

Greenberg, J. H.

J. Luckl, W. Baker, Z.-H. Sun, T. Durduran, A. G. Yodh, J. H. Greenberg, “The biological effect of contralateral forepaw stimulation in rat focal cerebral ischemia: a multispectral optical imaging study,” Front Neuroenergetics 2, 19 (2010).

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M. D. Greicius, G. Srivastava, A. L. Reiss, V. Menon, “Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI,” Proc. Natl. Acad. Sci. U.S.A. 101(13), 4637–4642 (2004).
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M. D. Greicius, B. Krasnow, A. L. Reiss, V. Menon, “Functional connectivity in the resting brain: a network analysis of the default mode hypothesis,” Proc. Natl. Acad. Sci. U.S.A. 100(1), 253–258 (2003).
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M. P. Pase, A. Herbert, N. A. Grima, A. Pipingas, M. F. O’Rourke, “Arterial stiffness as a cause of cognitive decline and dementia: a systematic review and meta-analysis,” Intern. Med. J. 42(7), 808–815 (2012).
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M. M. Breteler, J. J. Claus, D. E. Grobbee, A. Hofman, “Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study,” BMJ 308(6944), 1604–1608 (1994).
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N. Sadekova, D. Vallerand, E. Guevara, F. Lesage, H. Girouard, “Carotid calcification in mice: a new model to study the effects of arterial stiffness on the brain,” J Am Heart Assoc. Manuscript ID JAHA/2013/000224–T2 (posted May 17 2013, in press).

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M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
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Y. He, Z. Chen, G. Gong, A. Evans, “Neuronal networks in Alzheimer’s disease,” Neuroscientist 15(4), 333–350 (2009).
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M. P. Pase, A. Herbert, N. A. Grima, A. Pipingas, M. F. O’Rourke, “Arterial stiffness as a cause of cognitive decline and dementia: a systematic review and meta-analysis,” Intern. Med. J. 42(7), 808–815 (2012).
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Hofman, A.

M. M. Breteler, J. J. Claus, D. E. Grobbee, A. Hofman, “Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study,” BMJ 308(6944), 1604–1608 (1994).
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Holtzman, D. M.

A. W. Bero, A. Q. Bauer, F. R. Stewart, B. R. White, J. R. Cirrito, M. E. Raichle, J. P. Culver, D. M. Holtzman, “Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain,” J. Neurosci. 32(13), 4334–4340 (2012).
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M. Jones, J. Berwick, D. Johnston, J. Mayhew, “Concurrent optical imaging spectroscopy and laser-Doppler flowmetry: the relationship between blood flow, oxygenation, and volume in rodent barrel cortex,” Neuroimage 13(6), 1002–1015 (2001).
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J. Mayhew, D. Johnston, J. Berwick, M. Jones, P. Coffey, Y. Zheng, “Spectroscopic Analysis of Neural Activity in Brain: Increased Oxygen Consumption Following Activation of Barrel Cortex,” Neuroimage 12(6), 664–675 (2000).
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M. Jones, J. Berwick, D. Johnston, J. Mayhew, “Concurrent optical imaging spectroscopy and laser-Doppler flowmetry: the relationship between blood flow, oxygenation, and volume in rodent barrel cortex,” Neuroimage 13(6), 1002–1015 (2001).
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J. Mayhew, D. Johnston, J. Berwick, M. Jones, P. Coffey, Y. Zheng, “Spectroscopic Analysis of Neural Activity in Brain: Increased Oxygen Consumption Following Activation of Barrel Cortex,” Neuroimage 12(6), 664–675 (2000).
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R. S. Marshall, R. M. Lazar, J. Pile-Spellman, W. L. Young, D. H. Duong, S. Joshi, N. Ostapkovich, “Recovery of brain function during induced cerebral hypoperfusion,” Brain 124(6), 1208–1217 (2001).
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M. K. Aronson, W. L. Ooi, H. Morgenstern, A. Hafner, D. Masur, H. Crystal, W. H. Frishman, D. Fisher, R. Katzman, “Women, myocardial infarction, and dementia in the very old,” Neurology 40(7), 1102–1106 (1990).
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J. Saramäki, M. Kivelä, J.-P. Onnela, K. Kaski, J. Kertész, “Generalizations of the clustering coefficient to weighted complex networks,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 75(2), 027105 (2007).
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J. Saramäki, M. Kivelä, J.-P. Onnela, K. Kaski, J. Kertész, “Generalizations of the clustering coefficient to weighted complex networks,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 75(2), 027105 (2007).
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R. O. Roberts, D. S. Knopman, Y. E. Geda, R. H. Cha, V. L. Roger, R. C. Petersen, “Coronary heart disease is associated with non-amnestic mild cognitive impairment,” Neurobiol. Aging 31(11), 1894–1902 (2010).
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M. Kohl, U. Lindauer, G. Royl, M. Kuhl, L. Gold, A. Villringer, U. Dirnagl, “Physical model for the spectroscopic analysis of cortical intrinsic optical signals,” Phys. Med. Biol. 45(12), 3749–3764 (2000).
[CrossRef]

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Figures (6)

Fig. 1
Fig. 1

(a) Overview of the intrinsic signal optical imaging system. LEDs and laser diode are time-multiplexed and synchronized to the acquisition system so that each recorded image corresponds to either a single LED wavelength (525, 590, 625 nm) or to the laser illumination (785 nm). (b) Functional regions on the mouse cortex and seed placement and size, manually constructed from the work of Bero et al. [42]. Abbreviations: F, frontal; M, motor; C, cingulate; S, somatosensory; R, retrosplenial; V, visual.

Fig. 2
Fig. 2

Average seed-based correlation maps. Images were manually aligned through an affine registration using ImageJ’s plugin TurboReg [51]. HbO2 contrast is shown. The scale for all correlation maps is −1≤r≤1. Maps are shown overlaid on the anatomical image of one of the mice for reference (λ = 525 nm). White circles denote seed position and size. Abbreviations: F: frontal cortex, M: motor cortex, C: cingulate cortex, S: somatosensory cortex R: retrosplenial cortex, V: visual cortex, (L) left seed, (R) right seed.

Fig. 3
Fig. 3

Regional bilateral functional correlation, comparison performed between control NaCl and treatment group CaCl2; analysis done for every seed time-trace and its contralateral part. Contrasts shown: (a) HbO2, (b) HbR (c) CBF and (d) CMRO2. Standard error bars shown (F: frontal cortex, M: motor cortex, C: cingulate cortex, S: somatosensory cortex R: retrosplenial cortex, V: visual cortex).

Fig. 4
Fig. 4

Functional connectivity diagrams for NaCl (top row) and CaCl2 (bottom row) subjects. Edge thicknesses depend on the seed-to-seed average correlation coefficients, only edges with |r|>0.3 are shown. Node sizes are proportional to betweenness centrality CBn(G) of each seed. Positive correlations are depicted in warm colors. Negative correlations are depicted in cool colors.

Fig. 5
Fig. 5

Representative fc maps for all contrasts for a given seed (ML) (a)HbO2 (b)HbR (c) CBF (d) CMRO2.

Fig. 6
Fig. 6

Regional bilateral functional connectivity, comparison performed between control NaCl and treatment group CaCl2; analysis done for every seed time-trace and its contralateral part. Data points that were more than 3 standard deviations away from the mean were considered outliers and consequently removed. Contrasts shown: (a) HbO2, (b) HbR (c) CBF and (d) CMRO2. Standard error bars shown (σ/√N), with N = 19. (F: frontal cortex, M: motor cortex, C: cingulate cortex, S: somatosensory cortex R: retrosplenial cortex, V: visual cortex).

Tables (1)

Tables Icon

Table 1 Summary of significant results from second-level analysis using graph theoretical measures a

Equations (3)

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Δ O D ( λ , t ) = i ε i ( λ ) C i ( t ) D ( λ ) .
C = σ I , 2 Δ C C 0 Δ v v 0 Δ C B F C B F 0 ,
Δ C M R O 2 Δ C M R O 2 , 0 = ( 1 + Δ C B F C B F 0 ) ( 1 + γ R Δ H b R H b R 0 ) ( 1 + γ T Δ H b T H b T 0 ) 1 ,

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