OSA's Digital Library

Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 1, Iss. 1 — Aug. 2, 2010
  • pp: 324–336

Resting state functional connectivity of the whole head with near-infrared spectroscopy

Rickson C. Mesquita, Maria A. Franceschini, and David A. Boas  »View Author Affiliations

Biomedical Optics Express, Vol. 1, Issue 1, pp. 324-336 (2010)

View Full Text Article

Enhanced HTML    Acrobat PDF (1841 KB) | SpotlightSpotlight on Optics

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Resting state connectivity aims to identify spontaneous cerebral hemodynamic fluctuations that reflect neuronal activity at rest. In this study, we investigated the spatial-temporal correlation of hemoglobin concentration signals over the whole head during the resting state. By choosing a source-detector pair as a seed, we calculated the correlation value between its time course and the time course of all other source-detector combinations, and projected them onto a topographic map. In all subjects, we found robust spatial interactions in agreement with previous fMRI and NIRS findings. Strong correlations between the two opposite hemispheres were seen for both sensorimotor and visual cortices. Correlations in the prefrontal cortex were more heterogeneous and dependent on the hemodynamic contrast. HbT provided robust, well defined maps, suggesting that this contrast may be used to better localize functional connectivity. The effects of global systemic physiology were also investigated, particularly low frequency blood pressure oscillations which give rise to broad regions of high correlation and mislead interpretation of the results. These results confirm the feasibility of using functional connectivity with optical methods during the resting state, and validate its use to investigate cortical interactions across the whole head.

© 2010 OSA

OCIS Codes
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(170.5380) Medical optics and biotechnology : Physiology
(170.2655) Medical optics and biotechnology : Functional monitoring and imaging

ToC Category:
Neuroscience and Brain Imaging

Original Manuscript: May 28, 2010
Revised Manuscript: June 24, 2010
Manuscript Accepted: July 27, 2010
Published: July 28, 2010

Virtual Issues
August 2, 2010 Spotlight on Optics

Rickson C. Mesquita, Maria A. Franceschini, and David A. Boas, "Resting state functional connectivity of the whole head with near-infrared spectroscopy," Biomed. Opt. Express 1, 324-336 (2010)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. M. D. Fox and M. E. Raichle, “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci. 8(9), 700–711 (2007). [CrossRef] [PubMed]
  2. R. L. Buckner and J. L. Vincent, “Unrest at rest: default activity and spontaneous network correlations,” Neuroimage 37(4), 1091–1096, discussion 1097–1099 (2007). [CrossRef] [PubMed]
  3. C. F. Beckmann, M. DeLuca, J. T. Devlin, and S. M. Smith, “Investigations into resting-state connectivity using independent component analysis,” Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457), 1001–1013 (2005). [CrossRef] [PubMed]
  4. K. Murphy, R. M. Birn, D. A. Handwerker, T. B. Jones, and P. A. Bandettini, “The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?” Neuroimage 44(3), 893–905 (2009). [CrossRef] [PubMed]
  5. B. Biswal, F. Zerrin Yetkin, V. M. Haughton, and J. S. Hyde, “Functional connectivity in the motor cortex of resting human brain using echo-planar MRI,” Magn. Reson. Med. 34(4), 537–541 (1995). [CrossRef] [PubMed]
  6. M. J. Lowe, B. J. Mock, and J. A. Sorenson, “Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations,” Neuroimage 7(2), 119–132 (1998). [CrossRef] [PubMed]
  7. A. Arieli, A. Sterkin, A. Grinvald, and A. Aertsen, “Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses,” Science 273(5283), 1868–1871 (1996). [CrossRef] [PubMed]
  8. H. Laufs, K. Krakow, P. Sterzer, E. Eger, A. Beyerle, A. Salek-Haddadi, and A. Kleinschmidt, “Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest,” Proc. Natl. Acad. Sci. U.S.A. 100(19), 11053–11058 (2003). [CrossRef] [PubMed]
  9. G. Buzsáki and A. Draguhn, “Neuronal oscillations in cortical networks,” Science 304(5679), 1926–1929 (2004). [CrossRef] [PubMed]
  10. J. Xiong, L. M. Parsons, J. H. Gao, and P. T. Fox, “Interregional connectivity to primary motor cortex revealed using MRI resting state images,” Hum. Brain Mapp. 8(2-3), 151–156 (1999). [CrossRef] [PubMed]
  11. M. E. Raichle, A. M. MacLeod, A. Z. Snyder, W. J. Powers, D. A. Gusnard, and G. L. Shulman, “Inaugural Article: A default mode of brain function,” Proc. Natl. Acad. Sci. U.S.A. 98(2), 676–682 (2001). [CrossRef] [PubMed]
  12. M. D. Greicius, B. Krasnow, A. L. Reiss, and 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] [PubMed]
  13. M. De Luca, C. F. Beckmann, N. De Stefano, P. M. Matthews, and S. M. Smith, “fMRI resting state networks define distinct modes of long-distance interactions in the human brain,” Neuroimage 29(4), 1359–1367 (2006). [CrossRef] [PubMed]
  14. J. S. Damoiseaux, S. A. Rombouts, F. Barkhof, P. Scheltens, C. J. Stam, S. M. Smith, and C. F. Beckmann, “Consistent resting-state networks across healthy subjects,” Proc. Natl. Acad. Sci. U.S.A. 103(37), 13848–13853 (2006). [CrossRef] [PubMed]
  15. H. Lu, Y. Zuo, H. Gu, J. A. Waltz, W. Zhan, C. A. Scholl, W. Rea, Y. Yang, and E. A. Stein, “Synchronized delta oscillations correlate with the resting-state functional MRI signal,” Proc. Natl. Acad. Sci. U.S.A. 104(46), 18265–18269 (2007). [CrossRef] [PubMed]
  16. J. L. Vincent, G. H. Patel, M. D. Fox, A. Z. Snyder, J. T. Baker, D. C. Van Essen, J. M. Zempel, L. H. Snyder, M. Corbetta, and M. E. Raichle, “Intrinsic functional architecture in the anaesthetized monkey brain,” Nature 447(7140), 83–86 (2007). [CrossRef] [PubMed]
  17. M. D. Greicius, G. Srivastava, A. L. Reiss, and 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] [PubMed]
  18. A. R. Carter, S. V. Astafiev, C. E. Lang, L. T. Connor, J. Rengachary, M. J. Strube, D. L. W. Pope, G. L. Shulman, and M. Corbetta, “Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke,” Ann. Neurol. 67(3), 365–375 (2010). [PubMed]
  19. A. G. Garrity, G. D. Pearlson, K. McKiernan, D. Lloyd, K. A. Kiehl, and V. D. Calhoun, “Aberrant “default mode” functional connectivity in schizophrenia,” Am. J. Psychiatry 164(3), 450–457 (2007). [CrossRef] [PubMed]
  20. M. J. Lowe, M. D. Phillips, J. T. Lurito, D. Mattson, M. Dzemidzic, and V. P. Mathews, “Multiple sclerosis: low-frequency temporal blood oxygen level-dependent fluctuations indicate reduced functional connectivity initial results,” Radiology 224(1), 184–192 (2002). [CrossRef] [PubMed]
  21. D. P. Kennedy, E. Redcay, and E. Courchesne, “Failing to deactivate: resting functional abnormalities in autism,” Proc. Natl. Acad. Sci. U.S.A. 103(21), 8275–8280 (2006). [CrossRef] [PubMed]
  22. M. A. Just, V. L. Cherkassky, T. A. Keller, R. K. Kana, and N. J. Minshew, “Functional and anatomical cortical underconnectivity in autism: evidence from an FMRI study of an executive function task and corpus callosum morphometry,” Cereb. Cortex 17(4), 951–961 (2006). [CrossRef] [PubMed]
  23. S. Lui, L. Ouyang, Q. Chen, X. Huang, H. Tang, H. Chen, D. Zhou, G. J. Kemp, and Q. Gong, “Differential interictal activity of the precuneus/posterior cingulate cortex revealed by resting state functional MRI at 3T in generalized vs. partial seizure,” J. Magn. Reson. Imaging 27(6), 1214–1220 (2008). [CrossRef] [PubMed]
  24. G. H. Glover, T. Q. Li, and D. Ress, “Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR,” Magn. Rees. Med. 44(1), 162–167 (2000). [CrossRef]
  25. T. E. Lund, K. H. Madsen, K. Sidaros, W. L. Luo, and T. E. Nichols, “Non-white noise in fMRI: does modelling have an impact?” Neuroimage 29(1), 54–66 (2006). [CrossRef] [PubMed]
  26. R. M. Birn, J. B. Diamond, M. A. Smith, and P. A. Bandettini, “Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI,” Neuroimage 31(4), 1536–1548 (2006). [CrossRef] [PubMed]
  27. C. E. Elwell, R. Springett, E. Hillman, and D. T. Delpy, “Oscillations in cerebral haemodynamics – implications for functional activation studies,” In: A. Eke, D. Delpy (eds.), Oxygen transport to tissue XXI. Kluwer Academic, Plenum Publishers, New York, 57–65 (1999).
  28. H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhäupl, and A. Villringer, “Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults,” Neuroimage 12(6), 623–639 (2000). [CrossRef] [PubMed]
  29. V. Toronov, M. A. Franceschini, M. Filiaci, S. Fantini, M. Wolf, A. Michalos, and E. Gratton, “Near-infrared study of fluctuations in cerebral hemodynamics during rest and motor stimulation: temporal analysis and spatial mapping,” Med. Phys. 27(4), 801–815 (2000). [CrossRef] [PubMed]
  30. B. R. White, A. Z. Snyder, A. L. Cohen, S. E. Petersen, M. E. Raichle, B. L. Schlaggar, and J. P. Culver, “Resting-state functional connectivity in the human brain revealed with diffuse optical tomography,” Neuroimage 47(1), 148–156 (2009). [CrossRef] [PubMed]
  31. S. Aydöre, M. K. Mihçak, K. Ciftçi, and A. Akin, “On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals,” IEEE Trans. Biomed. Eng. 57(3), 761–768 (2010). [PubMed]
  32. C. M. Lu, Y. J. Zhang, B. B. Biswal, Y. F. Zang, D. L. Peng, and C. Z. Zhu, “Use of fNIRS to assess resting state functional connectivity,” J. Neurosci. Methods 186(2), 242–249 (2010). [CrossRef] [PubMed]
  33. H. Zhang, Y. J. Zhang, C. M. Lu, S. Y. Ma, Y. F. Zang, and C. Z. Zhu, “Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements,” Neuroimage 51(3), 1150–1161 (2010). [CrossRef] [PubMed]
  34. M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006). [CrossRef] [PubMed]
  35. S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006). [CrossRef] [PubMed]
  36. Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005). [CrossRef] [PubMed]
  37. D. K. Joseph, T. J. Huppert, M. A. Franceschini, and D. A. Boas, “Diffuse optical tomography system to image brain activation with improved spatial resolution and validation with functional magnetic resonance imaging,” Appl. Opt. 45(31), 8142–8151 (2006). [CrossRef] [PubMed]
  38. R. L. Buckner, J. R. Andrews-Hanna, and 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] [PubMed]
  39. J. L. Vincent, A. Z. Snyder, M. D. Fox, B. J. Shannon, J. R. Andrews, M. E. Raichle, and R. L. Buckner, “Coherent spontaneous activity identifies a hippocampal-parietal memory network,” J. Neurophysiol. 96(6), 3517–3531 (2006). [CrossRef] [PubMed]
  40. V. Kiviniemi, J. H. Kantola, J. Jauhiainen, A. Hyvärinen, and O. Tervonen, “Independent component analysis of nondeterministic fMRI signal sources,” Neuroimage 19(2), 253–260 (2003). [CrossRef] [PubMed]
  41. G. Morren, M. Wolf, P. Lemmerling, U. Wolf, J. H. Choi, E. Gratton, L. Lathauwer, and S. Huffel, “Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis,” Med. Biol. Eng. Comput. 42(1), 92–99 (2004). [CrossRef] [PubMed]
  42. S. Kohno, I. Miyai, A. Seiyama, I. Oda, A. Ishikawa, S. Tsuneishi, T. Amita, and K. Shimizu, “Removal of the skin blood flow artifact in functional near-infrared spectroscopic imaging data through independent component analysis,” J. Biomed. Opt. 12(6), 062111 (2007). [CrossRef] [PubMed]
  43. J. Markham, B. R. White, B. W. Zeff, and J. P. Culver, “Blind identification of evoked human brain activity with independent component analysis of optical data,” Hum. Brain Mapp. 30(8), 2382–2392 (2009). [CrossRef] [PubMed]
  44. I. Tachtsidis, C. E. Elwell, T. S. Leung, C. W. Lee, M. Smith, and D. T. Delpy, “Investigation of cerebral haemodynamics by near-infrared spectroscopy in young healthy volunteers reveals posture-dependent spontaneous oscillations,” Physiol. Meas. 25(2), 437–445 (2004). [CrossRef] [PubMed]
  45. B. L. Edlow, M. N. Kim, T. Durduran, C. Zhou, M. E. Putt, A. G. Yodh, J. H. Greenberg, and J. A. Detre, “The effects of healthy aging on cerebral hemodynamic responses to posture change,” Physiol. Meas. 31(4), 477–495 (2010). [CrossRef] [PubMed]
  46. M. A. Pinsk and S. Kastner, “Neuroscience: unconscious networking,” Nature 447(7140), 46–47 (2007). [CrossRef] [PubMed]
  47. J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005). [CrossRef] [PubMed]
  48. S. A. Sheth, M. Nemoto, M. Guiou, M. Walker, N. Pouratian, N. Hageman, and A. W. Toga, “Columnar specificity of microvascular oxygenation and volume responses: implications for functional brain mapping,” J. Neurosci. 24(3), 634–641 (2004). [CrossRef] [PubMed]
  49. A. Custo, D. A. Boas, D. Tsuzuki, I. Dan, R. C. Mesquita, B. Fischl, W. E. L. Grimson, and W. Wells, “Anatomical atlas-guided diffuse optical tomography of brain activation,” Neuroimage 49(1), 561–567 (2010). [CrossRef] [PubMed]
  50. Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering for global interference cancellation and real-time recovery of evoked brain activity: a Monte Carlo simulation study,” J. Biomed. Opt. 12(4), 044014 (2007). [CrossRef] [PubMed]
  51. T. J. Huppert, S. G. Diamond, and D. A. Boas, “Direct estimation of evoked hemoglobin changes by multimodality fusion imaging,” J. Biomed. Opt. 13(5), 054031 (2008). [CrossRef] [PubMed]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


Fig. 1 Fig. 2 Fig. 3
Fig. 4

« Previous Article

OSA is a member of CrossRef.

CrossCheck Deposited