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Frontiers in Neuroenergetics ·

Volume 2 - 2010 | https://doi.org/10.3389/fnene.2010.00023

Linear Superposition of Sensory-Evoked and Ongoing Cortical Hemodynamics

  • Mohamad Saka1
  • Jason Berwick1
  • Myles Jones1*corresponding author
  1. 1 The Centre for Signal Processing in NeuroImaging and Systems Neuroscience, Department of Psychology, University of Sheffield Sheffield, South Yorkshire, UK
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Abstract

Modern non-invasive brain imaging techniques utilize changes in cerebral blood flow, volume and oxygenation that accompany brain activation. However, stimulus-evoked hemodynamic responses display considerable inter-trial variability even when identical stimuli are presented and the sources of this variability are poorly understood. One of the sources of this response variation could be ongoing spontaneous hemodynamic fluctuations. To investigate this issue, 2-dimensional optical imaging spectroscopy was used to measure cortical hemodynamics in response to sensory stimuli in anesthetized rodents. Pre-stimulus cortical hemodynamics displayed spontaneous periodic fluctuations and as such, data from individual stimulus presentation trials were assigned to one of four groups depending on the phase angle of pre-stimulus hemodynamic fluctuations and averaged. This analysis revealed that sensory evoked cortical hemodynamics displayed distinctive response characteristics and magnitudes depending on the phase angle of ongoing fluctuations at stimulus onset. To investigate the origin of this phenomenon, “null-trials” were collected without stimulus presentation. Subtraction of phase averaged “null trials” from their phase averaged stimulus-evoked counterparts resulted in four similar time series that resembled the mean stimulus-evoked response. These analyses suggest that linear superposition of evoked and ongoing cortical hemodynamic changes may be a property of the structure of inter-trial variability.

Keywords

References

  1. Aguirre G. K., Zarahn E., D'Esposito M. (1998). The variability of human, BOLD hemodynamic responses. Neuroimage 8, 360 – 369. doi:10.1006/nimg.1998.0369
  2. Arieli A., Sterkin A., Grinvald A., Aertsen A. (1996). Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science 273, 1868 – 1871. doi:10.1126/science.273.5283.1868
  3. Berwick J., Johnston D., Jones M., Martindale J., Martin C., Kennerley A. J., Redgrave P., Mayhew J. E. (2008). Fine detail of neurovascular coupling revealed by spatiotemporal analysis of the hemodynamic response to single whisker stimulation in rat barrel cortex. J. Neurophysiol. 99, 787 – 798. doi:10.1152/jn.00658.2007
  4. Berwick J., Johnston D., Jones M., Martindale J., Redgrave P., McLoughlin N., Schiessl I., Mayhew J. E. (2005). Neurovascular coupling investigated with two-dimensional optical imaging spectroscopy in rat whisker barrel cortex. Eur. J. Neurosci. 22, 1655 – 1666. doi:10.1111/j.1460-9568.2005.04347.x
  5. Biswal B., Yetkin F. Z., Haughton V. M., Hyde J. S. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34, 537 – 541. doi:10.1002/mrm.1910340409
  6. Cannestra A. F., Pouratian N., Shomer M. H., Toga A. W. (1998). Refractory periods observed by intrinsic signal and fluorescent dye imaging. J. Neurophysiol. 80, 1522 – 1532.
  7. Damber J. E., Lindahl O., Selstam G., Tenland T. (1983). Rhythmical oscillations in rat testicular microcirculation as recorded by laser Doppler flowmetry. Acta Physiol. Scand. 118, 117 – 123. doi:10.1111/j.1748-1716.1983.tb07251.x
  8. Devor A., Dunn A. K., Andermann M. L., Ulbert I., Boas D. A., Dale A. M. (2003). Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex. Neuron 39, 353 – 359. doi:10.1016/S0896-6273(03)00403-3
  9. Devor A., Hillman E. M., Tian P., Waeber C., Teng I. C., Ruvinskaya L., Shalinsky M. H., Zhu H., Haslinger R. H., Narayanan S. N., Ulbert I., Dunn A. K., Lo E. H., Rosen B. R., Dale A. M., Kleinfeld D., Boas D. A. (2008). Stimulus-induced changes in blood flow and 2-deoxyglucose uptake dissociate in ipsilateral somatosensory cortex. J. Neurosci. 28, 14347 – 14357. doi:10.1523/JNEUROSCI.4307-08.2008
  10. Elwell C. E., Owen-Reece H., Wyatt J. S., Cope M., Reynolds E. O., Delpy D. T. (1996). Influence of respiration and changes in expiratory pressure on cerebral haemoglobin concentration measured by near infrared spectroscopy. J. Cereb. Blood Flow Metab. 16, 353 – 357. doi:10.1097/00004647-199603000-00022
  11. Elwell C. E., Springett R., Hillman E., Delpy D. T. (1999). Oscillations in cerebral haemodynamics. Implications for functional activation studies. Adv. Exp. Med. Biol. 471, 57 – 65.
  12. Fox M. D., Corbetta M., Snyder A. Z., Vincent J. L., Raichle M. E. (2006a). Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc. Natl. Acad. Sci. U.S.A. 103, 10046 – 10051. doi:10.1073/pnas.0604187103
  13. Fox M. D., Snyder A. Z., Zacks J. M., Raichle M. E. (2006b). Coherent spontaneous activity accounts for trial-to-trial variability in human evoked brain responses. Nat. Neurosci. 9, 23 – 25. doi:10.1038/nn1616
  14. Fox M. D., Snyder A. Z., Vincent J. L., Corbetta M., Van Essen D. C., Raichle M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U.S.A. 102, 9673 – 9678. doi:10.1073/pnas.0504136102
  15. Friston K. J., Mechelli A., Turner R., Price C. J. (2000). Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics. Neuroimage 12, 466 – 477. doi:10.1006/nimg.2000.0630
  16. Golanov E. V., Reis D. J. (1996). Cerebral cortical neurons with activity linked to central neurogenic spontaneous and evoked elevations in cerebral blood flow. Neurosci. Lett. 209, 101 – 104. doi:10.1016/0304-3940(96)12611-2
  17. Golanov E. V., Yamamoto S., Reis D. J. (1994). Spontaneous waves of cerebral blood flow associated with a pattern of electrocortical activity. Am. J. Physiol. 266, R204 – R214.
  18. Greicius M. D., Krasnow B., Reiss A. L., Menon V. (2003). Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl. Acad. Sci. U.S.A. 100, 253 – 258. doi:10.1073/pnas.0135058100
  19. Hampson M., Peterson B. S., Skudlarski P., Gatenby J. C., Gore J. C. (2002). Detection of functional connectivity using temporal correlations in MR images. Hum. Brain Mapp. 15, 247 – 262. doi:10.1002/hbm.10022
  20. Haslinger R., Ulbert I., Moore C. I., Brown E. N., Devor A. (2006). Analysis of LFP phase predicts sensory response of barrel cortex. J. Neurophysiol. 96, 1658 – 1663. doi:10.1152/jn.01288.2005
  21. Jones M., Berwick J., Hewson-Stoate N., Gias C., Mayhew J. (2005). The effect of hypercapnia on the neural and hemodynamic responses to somatosensory stimulation. Neuroimage 27, 609 – 623. doi:10.1016/j.neuroimage.2005.04.036
  22. Jones M., Berwick J., Johnston D., Mayhew J. (2001). Concurrent optical imaging spectroscopy and laser-Doppler flowmetry: the relationship between blood flow, oxygenation, and volume in rodent barrel cortex. Neuroimage 13, 1002 – 1015. doi:10.1006/nimg.2001.0808
  23. Jones M., Berwick J., Mayhew J. (2002). Changes in blood flow, oxygenation, and volume following extended stimulation of rodent barrel cortex. Neuroimage 15, 474 – 487. doi:10.1006/nimg.2001.1000
  24. Jones M., Devonshire I. M., Berwick J., Martin C., Redgrave P., Mayhew J. (2008). Altered neurovascular coupling during information-processing states. Eur. J. Neurosci. 27, 2758 – 2772. doi:10.1111/j.1460-9568.2008.06212.x
  25. Jones M., Hewson-Stoate N., Martindale J., Redgrave P., Mayhew J. (2004). Nonlinear coupling of neural activity and CBF in rodent barrel cortex. Neuroimage 22, 956 – 965. doi:10.1016/j.neuroimage.2004.02.007
  26. Kennerley A. J., Berwick J., Martindale J., Johnston D., Papadakis N., Mayhew J. E. (2005). Concurrent fMRI and optical measures for the investigation of the hemodynamic response function. Magn. Reson. Med. 54, 354 – 365. doi:10.1002/mrm.20511
  27. Kwong K. K., Belliveau J. W., Chesler D. A., Goldberg I. E., Weisskoff R. M., Poncelet B. P., Kennedy D. N., Hoppel B. E., Cohen M. S., Turner R., Cheng H-M., Brady T. J., Rosen B. R. (1992). Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Natl. Acad. Sci. U.S.A. 89, 5675 – 5679. doi:10.1073/pnas.89.12.5675
  28. Le Van Quyen M., Bragin A. (2007). Analysis of dynamic brain oscillations: methodological advances. Trends Neurosci. 30, 365 – 373. doi:10.1016/j.tins.2007.05.006
  29. Le Van Quyen M., Foucher J., Lachaux J., Rodriguez E., Lutz A., Martinerie J., Varela F. J. (2001). Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony. J. Neurosci. Methods 111, 83 – 98. doi:10.1016/S0165-0270(01)00372-7
  30. Logothetis N. K., Pauls J., Augath M., Trinath T., Oeltermann A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150 – 157. doi:10.1038/35084005
  31. Lowe M. J., Mock B. J., Sorenson J. A. (1998). Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 7, 119 – 132. doi:10.1006/nimg.1997.0315
  32. Majeed W., Magnuson M., Keilholz S. D. (2009). Spatiotemporal dynamics of low frequency fluctuations in BOLD fMRI of the rat. J. Magn. Reson. Imaging 30, 384 – 393. doi:10.1002/jmri.21848
  33. Malonek D., Dirnagl U., Lindauer U., Yamada K., Kanno I., Grinvald A. (1997). Vascular imprints of neuronal activity: relationships between the dynamics of cortical blood flow, oxygenation, and volume changes following sensory stimulation. Proc. Natl. Acad. Sci. U.S.A. 94, 14826 – 14831. doi:10.1073/pnas.94.26.14826
  34. Martindale J., Mayhew J., Berwick J., Jones M., Martin C., Johnston D., Redgrave P., Zheng Y. (2003). The hemodynamic impulse response to a single neural event. J. Cereb. Blood Flow Metab. 23, 546 – 555. doi:10.1097/01.WCB.0000058871.46954.2B
  35. Mayhew J., Hu D., Zheng Y., Askew S., Hou Y., Berwick J., Coffey P. J., Brown N. (1998). An evaluation of linear model analysis techniques for processing images of microcirculation activity. Neuroimage 7, 49 – 71. doi:10.1006/nimg.1997.0311
  36. Mayhew J., Johnston D., Berwick J., Jones M., Coffey P., Zheng Y. (2000). Spectroscopic analysis of neural activity in brain: increased oxygen consumption following activation of barrel cortex. Neuroimage 12, 664 – 675. doi:10.1006/nimg.2000.0656
  37. Mayhew J., Zheng Y., Hou Y., Vuksanovic B., Berwick J., Askew S., Coffey P. (1999). Spectroscopic analysis of changes in remitted illumination: the response to increased neural activity in brain. Neuroimage 10, 304 – 326. doi:10.1006/nimg.1999.0460
  38. Mayhew J. E., Askew S., Zheng Y., Porrill J., Westby G. W., Redgrave P., Rector D. M., Harper R. M. (1996). Cerebral vasomotion: a 0.1-Hz oscillation in reflected light imaging of neural activity. Neuroimage 4, 183 – 193. doi:10.1006/nimg.1996.0069
  39. Mitra P. P., Ogawa S., Hu X., Ugurbil K. (1997). The nature of spatiotemporal changes in cerebral hemodynamics as manifested in functional magnetic resonance imaging. Magn. Reson. Med. 37, 511 – 518. doi:10.1002/mrm.1910370407
  40. Molgedey L., Schuster H. G. (1994). Separation of a mixture of independent signals using time delayed correlations. Phys. Rev. Lett. 72, 3634 – 3637. doi:10.1103/PhysRevLett.72.3634
  41. Morita Y., Hardebo J. E., Bouskela E. (1995). Influence of cerebrovascular sympathetic, parasympathetic, and sensory nerves on autoregulation and spontaneous vasomotion. Acta Physiol. Scand. 154, 121 – 130. doi:10.1111/j.1748-1716.1995.tb09894.x
  42. Obrig H., Neufang M., Wenzel R., Kohl M., Steinbrink J., Einhaupl K., Villringer A. (2000). Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults. Neuroimage 12, 623 – 639. doi:10.1006/nimg.2000.0657
  43. Ogawa S., Tank D. W., Menon R., Ellermann J. M., Kim S. G., Merkle H., Ugurbil K. (1992). Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc. Natl. Acad. Sci. U.S.A. 89, 5951 – 5955. doi:10.1073/pnas.89.13.5951
  44. Pikovsky A., Rosenblum M., Kurths J. (2001). Synchronization - A Universal Concept in Nonlinear Sciences. Cambridge, UK: Cambridge.
  45. Sauseng P., Klimesch W., Gruber W. R., Hanslmayr S., Freunberger R., Doppelmayr M. (2007). Are event-related potential components generated by phase resetting of brain oscillations? A critical discussion. Neuroscience 146, 1435 – 1444. doi:10.1016/j.neuroscience.2007.03.014
  46. Sheth S., Nemoto M., Guiou M., Walker M., Pouratian N., Toga A. W. (2003). Evaluation of coupling between optical intrinsic signals and neuronal activity in rat somatosensory cortex. Neuroimage 19, 884 – 894. doi:10.1016/S1053-8119(03)00086-7
  47. Shmuel A., Leopold D. A. (2008). Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest. Hum. Brain Mapp. 29, 751 – 761. doi:10.1002/hbm.20580
  48. Spitzer M. W., Calford M. B., Clarey J. C., Pettigrew J. D., Roe A. W. (2001). Spontaneous and stimulus-evoked intrinsic optical signals in primary auditory cortex of the cat. J. Neurophysiol. 85, 1283 – 1298.
  49. van de Ven V. G., Formisano E., Prvulovic D., Roeder C. H., Linden D. E. (2004). Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest. Hum. Brain Mapp. 22, 165 – 178. doi:10.1002/hbm.20022
  50. Vincent J. L., Patel G. H., Fox M. D., Snyder A. Z., Baker J. T., Van Essen D. C., Zempel J. M., Snyder L. H., Corbetta M., Raichle M. E. (2007). Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447, 83 – 86. doi:10.1038/nature05758
  51. Zhang R., Zuckerman J. H., Giller C. A., Levine B. D. (1998a). Transfer function analysis of dynamic cerebral autoregulation in humans. Am. J. Physiol. 274, H233 – H241.
  52. Zhang R., Zuckerman J. H., Levine B. D. (1998b). Deterioration of cerebral autoregulation during orthostatic stress: insights from the frequency domain. J. Appl. Physiol. 85, 1113 – 1122.
  53. Zheng Y., Johnston D., Berwick J., Mayhew J. (2001). Signal source separation in the analysis of neural activity in brain. Neuroimage 13, 447 – 458. doi:10.1006/nimg.2000.0705

Citation

Saka, M., et al. (2010). Linear Superposition of Sensory-Evoked and Ongoing Cortical Hemodynamics. Frontiers in Neuroenergetics, Volume 2. https://doi.org/
Received
Accepted
Published
Volume
2 - 2010

Copyright

Copyright © 2010 Saka, Berwick and Jones.

License: http://www.frontiersin.org/licenseagreement

*Correspondence: Myles Jones

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