Skip to main content
Log in

Spatio-temporal analysis of stimuli-modulated spontaneous low frequency oscillations

  • Articles
  • Neurobiology
  • Published:
Chinese Science Bulletin

Abstract

In this paper, the spatio-temporal architecture of the stimulation-modulated spontaneous low frequency oscillation (LFO) in the SD rat’s somatosensory cortex is studied by optical imaging (OI) technology. After the electrical stimulation, it is observed that the phases of the LFO signals are changed, the amplitudes are increased, and most importantly, the signals in the bilateral somatosensory cortex tend to be synchronized. Based on these phenomena, the origin of the LFO signals is discussed. It is argued that the arteriole vasomotion may be the major contribution to the LFO signals under green illumination (546±10 nm). The phase relationship among the LFO signals of arteries, veins and cortex has also been studied. It is found that there are phase differences between the LFO signal of veins and that of cortex under red illumination (605±10 nm), the signal of cortex leads that of veins by 0.6–1.0 s, while under green illumination, no obvious differences are observed and the reason may be that the mechanism of the LFO signals of cortexes and vessels are different.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Grinvald A, Frostig R D, Lieke E, et al. Optical imaging of neuronal activity. Physiol Rev, 1988, 68: 1285–1365

    Google Scholar 

  2. Frostig R D, Lieke E E, Ts’o D, et al. Cortical functional architecture and local coupling between neuronal activity and the microcirculation revealed by in vivo high-resolution optical imaging of intrinsic signals. Proc Natl Acad Sci USA, 1990, 87: 6082–6086

    Article  Google Scholar 

  3. Greicius M D, Srivastava G, Reiss A L, et al. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proc Natl Acad Sci USA, 2004, 101:4637–4642

    Article  Google Scholar 

  4. Li Y Z, Wang L Q, Wang M S. EEG-correlated fMRI of P3b component in P300 waves. Chin Sci Bull, 2005, 50(21): 2448–2456

    Article  Google Scholar 

  5. Wise R G, Ide K, Poulin M J, et al. Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal. NeuroImage, 2004, 21: 1652–1664

    Article  Google Scholar 

  6. Laufs H, Krakow K, Sterzer P, et al. Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. Proc Natl Acad Sci USA, 2003, 100: 11053–11058

    Article  Google Scholar 

  7. Biswal B B, Hudetz A G. Synchronous oscillations in cerebrocortical capillary red blood cell velocity after nitric oxide synthase inhibition. Microvasc Res, 1995, 52: 1–12

    Article  Google Scholar 

  8. Obrig H, Neufang M, Wenzel R, et al. Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults. NeuroImage, 2000, 12: 623–639

    Article  Google Scholar 

  9. Mayhew J, Askew S, Zheng Y, et al. Cerebral vasomotion: A 0.1-Hz oscillation in reflected light imaging of neural activity. NeuroImage, 1996, 4: 183–193

    Article  Google Scholar 

  10. Elwell C E, Springett R, Hillman E, et al. Oscillations in cerebral haemodynamics, implications for functional activation studies. Adv Exp Med Biol, 1999, 471: 57–65

    Google Scholar 

  11. Mayhew J, Hu D W, Zheng Y, et al. An evaluation of linear model analysis techniques for processing images of microcirculation activity. NeuroImage, 1998, 7: 49–71

    Article  Google Scholar 

  12. Spitzer M W, Calford M B, Clarey J C, et al. Spontaneous and stimulus-evoked intrinsic optical signals in primary auditory cortex of the cat. J Neurophysiol, 2001, 85: 1283–1298

    Google Scholar 

  13. Hu H H, Kuo T B, Wong W J, et al. Transfer function analysis of cerebral hemodynamics in patients with carotid stenosis. J Cereb Blood Flow Metab, 1999, 19: 460–465

    Article  Google Scholar 

  14. Diehl R R, Linden D, Lucke D, et al. Phase relationship between cerebral blood flow velocity and blood pressure. Stroke, 1995, 26: 1801–1804

    Google Scholar 

  15. Biswal B B, Yetkin F Z, Haughton V M, et al. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med, 1995, 34: 537–541

    Article  Google Scholar 

  16. Coyle S, Ward T, Markham C. Physiological noise in near-infrared spectroscopy: Implications for optical brain computer interfacing. IEEE Proc EMBS, 2004, 2: 4540–4543

    Google Scholar 

  17. Kiviniemi V. Spontaneous blood oxygen fluctuation in awake and sedated brain cortex-a BOLD fMRI study. Doctor Dissertation. Finland: University of Oulu, 2004

    Google Scholar 

  18. Fagrell B, Intaglietta M, Ostergren J. Relative hematocrit in human skin capillaries and its relation to capillary blood flow velocity. Microvasc Res, 1980, 20: 327–335

    Article  Google Scholar 

  19. Golanov E V, Reis D J. Vasodilation evoked from medulla and cerebellum is coupled to bursts of cortical EEG activity in rats. Am J Physiol, 1995, 268: R454–R467

    Google Scholar 

  20. Golanov E V, Reis D J. Cerebral cortical neurons with activity linked to central neurogenic spontaneous and evoked elevations in cerebral blood flow. Neurosci Lett, 1996, 209: 101–104

    Article  Google Scholar 

  21. Cooley R L, Montano N, Cogliati C, et al. Evidence for a central origin of the low-frequency oscillation in RR-interval variability. Circulation, 1998, 98: 556–561

    Google Scholar 

  22. Tomita M, Gotoh F, Sato T, et al. 4–6 cycle per minute fluctuation in cerebral blood volume of feline cortical tissue in situ. J Cereb Blood Flow Metab, 1981, 1: 443–444

    Google Scholar 

  23. Colantuoni A, Bertuglia S, Intaglietta M. Microvascular vasomotion: Origin of laser Doppler flux motion. Int J Microcirc, 1994, 14: 151–158

    Google Scholar 

  24. Liu T T, Behzadi Y, Restom K, et al. Caffeine alters the temporal dynamics of the visual BOLD response. NeuroImage, 2004, 23: 1402–1413

    Article  Google Scholar 

  25. Zilles K, Wree A. Cortex: Areal and laminar structure. The Rat Nervous System, vol 1: Forebrain and Midbrain. Sydney: Academic Press, 1985. 375–415

    Google Scholar 

  26. Chen X, Shou T D. Accurate establishment of the retinotopic topography of area 17 in cats by intrinsic signal optical imaging. Acta Physiol Sin (in Chinese), 2003, 55: 541–546

    Google Scholar 

  27. Pouratian N, Cannestra A F, Martin N A, et al. Intraoperative optical intrinsic signal imaging: A clinical tool for functional brain mapping. Neurosurg Focus, 2002, 13: 1–9

    Google Scholar 

  28. Sato K, Nariai T, Tanaka Y, et al. Functional representation of the finger and face in the human somatosensory cortex: Intraoperative intrinsic optical imaging. NeuroImage, 2005, 25: 1292–1301

    Article  Google Scholar 

  29. Li P C, Ni S L, Zhang L, et al. Imaging cerebral blood flow through the intact rat skull with temporal laser speckle imaging. Opt Lett, 2006, 31: 1824–1826

    Article  Google Scholar 

  30. Li P C, Chen S B, Luo W H, et al. Correlation between in vivo intrinsic optical signals and cerebral vessel response during cortical spreading depression in rat. Prog Nat Sci (in Chinese), 2003, 13: 1320–1324

    Google Scholar 

  31. Yang Y P, Jin J Z, Zhou Y F, etc. Temporal properties of pattern adaptation of relay cells in the lateral geniculate nucleus of cats. Chin Sci Bull, 2001, 46(17): 1463–1466

    Article  Google Scholar 

  32. Morita Y, Hardebo J E, Bouskela E. Influence of cerebrovascular sympathetic, parasympathetic and sensory nerves on autoregulation and spontaneous vasomotion. Acta Physiol Scand, 1995, 154: 121–130

    Article  Google Scholar 

  33. Nilsson H, Aalkjaer C. Vasomotion: mechanisms and physiological importance. Mol Interv, 2003, 3: 79–89

    Article  Google Scholar 

  34. Cox S B, Woolsey T A, Rovainen C M. Localized dynamic changes in cortical blood flow with whisker stimulation corresponds to matched vascular and neuronal architecture of rat barrels. J Cereb Blood Flow Metab, 1993, 13: 899–913

    Google Scholar 

  35. Colantuoni A, Bertuglia S, Intaglietta M. Quantitation of rhythmic diameter changes in arterial microcirculation. Am J Physiol-Heart Circ Physiol, 1984, 246: H508–H517

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hu DeWen.

Additional information

Supported by the National Basic Research Program of China (Grant No. 2003CB716104), the National Natural Science Foundation of China (Grant Nos. 30370416, 60575044 and 60675005), the National Distinguished Young Scholars Fund of China (Grant No. 60225015) and the Teaching and Research Award Program for Outstanding Young Teachers

About this article

Cite this article

Li, M., Liu, Y., Hu, D. et al. Spatio-temporal analysis of stimuli-modulated spontaneous low frequency oscillations. CHINESE SCI BULL 52, 1475–1483 (2007). https://doi.org/10.1007/s11434-007-0219-8

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11434-007-0219-8

Keywords

Navigation