Abstract

Autism spectrum disorder (ASD) is a neuro-developmental disorder, which has been associated with atypical neural synchronization. In this study, functional near infrared spectroscopy (fNIRS) was used to study the differences in functional connectivity in bilateral inferior frontal cortices (IFC) and bilateral temporal cortices (TC) between ASD and typically developing (TD) children between 8 and 11 years of age. As the first report of fNIRS study on the resting state functional connectivity (RSFC) in children with ASD, ten children with ASD and ten TD children were recruited in this study for 8 minute resting state measurement. Compared to TD children, children with ASD showed reduced interhemispheric connectivity in TC. Children with ASD also showed significantly lower local connectivity in bilateral temporal cortices. In contrast to TD children, children with ASD did not show typical patterns of symmetry in functional connectivity in temporal cortex. These results support the feasibility of using the fNIRS method to assess atypical functional connectivity of cortical responses of ASD and its potential application in diagnosis.

© 2014 Optical Society of America

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    [CrossRef] [PubMed]

2014 (2)

R. E. Vanderwert and C. A. Nelson, “The use of near-infrared spectroscopy in the study of typical and atypical development,” Neuroimage85(Pt 1), 264–271 (2014).
[CrossRef] [PubMed]

D. A. Boas, C. E. Elwell, M. Ferrari, and G. Taga, “Twenty years of functional near-infrared spectroscopy: introduction for the special issue,” Neuroimage85(Pt 1), 1–5 (2014).
[CrossRef] [PubMed]

2013 (1)

Z. Guo, F. Cai, and S. He, “Optimization for Brain Activity Monitoring with Near Infrared Light in a Four-Layered Model of the Human Head,” Prog. Electromagnetics Res.140, 277–295 (2013).
[CrossRef]

2012 (1)

B. R. White, S. M. Liao, S. L. Ferradal, T. E. Inder, and J. P. Culver, “Bedside optical imaging of occipital resting-state functional connectivity in neonates,” Neuroimage59(3), 2529–2538 (2012).
[CrossRef] [PubMed]

2011 (4)

J. S. Anderson, T. J. Druzgal, A. Froehlich, M. B. DuBray, N. Lange, A. L. Alexander, T. Abildskov, J. A. Nielsen, A. N. Cariello, J. R. Cooperrider, E. D. Bigler, and J. E. Lainhart, “Decreased interhemispheric functional connectivity in autism,” Cereb. Cortex21(5), 1134–1146 (2011).
[CrossRef] [PubMed]

I. Dinstein, K. Pierce, L. Eyler, S. Solso, R. Malach, M. Behrmann, and E. Courchesne, “Disrupted neural synchronization in toddlers with autism,” Neuron70(6), 1218–1225 (2011).
[CrossRef] [PubMed]

U. Chaudhary, M. Hall, A. Gutierrez, D. Messinger, G. Rey, and A. Godavarty, “Joint attention studies in normal and autistic children using NIRS,” Proc. SPIE7883, 788348 (2011).
[CrossRef]

Y. Kita, A. Gunji, Y. Inoue, T. Goto, K. Sakihara, M. Kaga, M. Inagaki, and T. Hosokawa, “Self-face recognition in children with autism spectrum disorders: a near-infrared spectroscopy study,” Brain Dev.33(6), 494–503 (2011).
[CrossRef] [PubMed]

2010 (6)

Y.-J. Zhang, C.-M. Lu, B. B. Biswal, Y.-F. Zang, D.-L. Peng, and C.-Z. Zhu, “Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy,”J. Biomed. Opt.15, 047003 (2010).

S.-J. Weng, J. L. Wiggins, S. J. Peltier, M. Carrasco, S. Risi, C. Lord, and C. S. Monk, “Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders,” Brain Res.1313, 202–214 (2010).
[CrossRef] [PubMed]

M. Assaf, K. Jagannathan, V. D. Calhoun, L. Miller, M. C. Stevens, R. Sahl, J. G. O’Boyle, R. T. Schultz, and G. D. Pearlson, “Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients,” Neuroimage53(1), 247–256 (2010).
[CrossRef] [PubMed]

R. C. Mesquita, M. A. Franceschini, and D. A. Boas, “Resting state functional connectivity of the whole head with near-infrared spectroscopy,” Biomed. Opt. Express1(1), 324–336 (2010).
[CrossRef] [PubMed]

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. Methods186(2), 242–249 (2010).
[CrossRef] [PubMed]

M. E. Raichle, “Two views of brain function,” Trends Cogn. Sci. (Regul. Ed.)14(4), 180–190 (2010).
[CrossRef] [PubMed]

2009 (5)

Y. Kawakubo, H. Kuwabara, K.-i. Watanabe, M. Minowa, T. Someya, I. Minowa, T. Kono, H. Nishida, T. Sugiyama, N. Kato, and K. Kasai, “Impaired prefrontal hemodynamic maturation in autism and unaffected siblings,” PLoS ONE4(9), e6881 (2009).
[CrossRef] [PubMed]

L. Koessler, L. Maillard, A. Benhadid, J. P. Vignal, J. Felblinger, H. Vespignani, and M. Braun, “Automated cortical projection of EEG sensors: Anatomical correlation via the international 10-10 system,” Neuroimage46(1), 64–72 (2009).
[CrossRef] [PubMed]

M. D. Fox, D. Zhang, A. Z. Snyder, and M. E. Raichle, “The global signal and observed anticorrelated resting state brain networks,” J. Neurophysiol.101(6), 3270–3283 (2009).
[CrossRef] [PubMed]

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,” Neuroimage47(1), 148–156 (2009).
[CrossRef] [PubMed]

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?” Neuroimage44(3), 893–905 (2009).
[CrossRef] [PubMed]

2008 (2)

D. P. Kennedy and E. Courchesne, “The intrinsic functional organization of the brain is altered in autism,” Neuroimage39(4), 1877–1885 (2008).
[CrossRef] [PubMed]

H. Koshino, R. K. Kana, T. A. Keller, V. L. Cherkassky, N. J. Minshew, and M. A. Just, “fMRI investigation of working memory for faces in autism: visual coding and underconnectivity with frontal areas,” Cereb. Cortex18(2), 289–300 (2008).
[CrossRef] [PubMed]

2007 (3)

R. K. Kana, T. A. Keller, N. J. Minshew, and M. A. Just, “Inhibitory control in high-functioning autism: decreased activation and underconnectivity in inhibition networks,” Biol. Psychiatry62(3), 198–206 (2007).
[CrossRef] [PubMed]

M. Murias, S. J. Webb, J. Greenson, and G. Dawson, “Resting state cortical connectivity reflected in EEG coherence in individuals with autism,” Biol. Psychiatry62(3), 270–273 (2007).
[CrossRef] [PubMed]

G. Hickok and D. Poeppel, “The cortical organization of speech processing,” Nat. Rev. Neurosci.8(5), 393–402 (2007).
[CrossRef] [PubMed]

2006 (3)

V. L. Cherkassky, R. K. Kana, T. A. Keller, and M. A. Just, “Functional connectivity in a baseline resting-state network in autism,” Neuroreport17(16), 1687–1690 (2006).
[CrossRef] [PubMed]

M. Dapretto, M. S. Davies, J. H. Pfeifer, A. A. Scott, M. Sigman, S. Y. Bookheimer, and M. Iacoboni, “Understanding emotions in others: mirror neuron dysfunction in children with autism spectrum disorders,” Nat. Neurosci.9(1), 28–30 (2006).
[CrossRef] [PubMed]

P. J. Uhlhaas and W. Singer, “Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology,” Neuron52(1), 155–168 (2006).
[CrossRef] [PubMed]

2005 (1)

A. Devor, I. Ulbert, A. K. Dunn, S. N. Narayanan, S. R. Jones, M. L. Andermann, D. A. Boas, and A. M. Dale, “Coupling of the cortical hemodynamic response to cortical and thalamic neuronal activity,” Proc. Natl. Acad. Sci. U.S.A.102(10), 3822–3827 (2005).
[CrossRef] [PubMed]

2004 (6)

P. M. Macey, K. E. Macey, R. Kumar, and R. M. Harper, “A method for removal of global effects from fMRI time series,” Neuroimage22(1), 360–366 (2004).
[CrossRef] [PubMed]

N. Boddaert, N. Chabane, H. Gervais, C. D. Good, M. Bourgeois, M. H. Plumet, C. Barthélémy, M. C. Mouren, E. Artiges, Y. Samson, F. Brunelle, R. S. Frackowiak, and M. Zilbovicius, “Superior temporal sulcus anatomical abnormalities in childhood autism: a voxel-based morphometry MRI study,” Neuroimage23(1), 364–369 (2004).
[CrossRef] [PubMed]

G. M. McAlonan, V. Cheung, C. Cheung, J. Suckling, G. Y. Lam, K. S. Tai, L. Yip, D. G. Murphy, and S. E. Chua, “Mapping the brain in autism. A voxel-based MRI study of volumetric differences and intercorrelations in autism,” Brain128(2), 268–276 (2004).
[CrossRef] [PubMed]

M. A. Just, V. L. Cherkassky, T. A. Keller, and N. J. Minshew, “Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity,” Brain127(8), 1811–1821 (2004).
[CrossRef] [PubMed]

G. Rizzolatti and L. Craighero, “The mirror-neuron system,” Annu. Rev. Neurosci.27(1), 169–192 (2004).
[CrossRef] [PubMed]

M. R. Herbert, D. A. Ziegler, N. Makris, P. A. Filipek, T. L. Kemper, J. J. Normandin, H. A. Sanders, D. N. Kennedy, and V. S. Caviness., “Localization of white matter volume increase in autism and developmental language disorder,” Ann. Neurol.55(4), 530–540 (2004).
[CrossRef] [PubMed]

2003 (2)

U. Frith and C. D. Frith, “Development and neurophysiology of mentalizing,” Philos. Trans. R. Soc. Lond. B Biol. Sci.358(1431), 459–473 (2003).
[CrossRef] [PubMed]

E. Courchesne, R. Carper, and N. Akshoomoff, “Evidence of brain overgrowth in the first year of life in autism,” JAMA290(3), 337–344 (2003).
[CrossRef] [PubMed]

2002 (1)

F. Castelli, C. Frith, F. Happé, and U. Frith, “Autism, Asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes,” Brain125(8), 1839–1849 (2002).
[CrossRef] [PubMed]

2000 (1)

R. A. Carper and E. Courchesne, “Inverse correlation between frontal lobe and cerebellum sizes in children with autism,” Brain123(4), 836–844 (2000).
[CrossRef] [PubMed]

1999 (1)

S. Baron-Cohen, H. A. Ring, S. Wheelwright, E. T. Bullmore, M. J. Brammer, A. Simmons, and S. C. Williams, “Social intelligence in the normal and autistic brain: an fMRI study,” Eur. J. Neurosci.11(6), 1891–1898 (1999).
[CrossRef] [PubMed]

1997 (2)

A. Villringer and B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci.20(10), 435–442 (1997).
[CrossRef] [PubMed]

M. Tamura, Y. Hoshi, and F. Okada, “Localized near-infrared spectroscopy and functional optical imaging of brain activity,” Philos. Trans. R. Soc. Lond. B Biol. Sci.352(1354), 737–742 (1997).
[CrossRef] [PubMed]

1995 (1)

B. Biswal, F. Z. 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]

1993 (1)

A. Villringer, J. Planck, C. Hock, L. Schleinkofer, and U. Dirnagl, “Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults,” Neurosci. Lett.154(1-2), 101–104 (1993).
[CrossRef] [PubMed]

1990 (1)

L. Brothers, “The social brain: a project for integrating primate behavior and neurophysiology in a new domain,” Concepts Neurosci.1, 27–51 (1990).

1986 (1)

G. Dawson, C. Finley, S. Phillips, and L. Galpert, “Hemispheric specialization and the language abilities of autistic children,” Child Dev.57(6), 1440–1453 (1986).
[CrossRef] [PubMed]

1979 (1)

M. R. Prior and J. L. Bradshaw, “Hemisphere functioning in autistic children,” Cortex15(1), 73–81 (1979).
[CrossRef] [PubMed]

1977 (1)

F. F. Jöbsis, “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science198(4323), 1264–1267 (1977).
[CrossRef] [PubMed]

Abildskov, T.

J. S. Anderson, T. J. Druzgal, A. Froehlich, M. B. DuBray, N. Lange, A. L. Alexander, T. Abildskov, J. A. Nielsen, A. N. Cariello, J. R. Cooperrider, E. D. Bigler, and J. E. Lainhart, “Decreased interhemispheric functional connectivity in autism,” Cereb. Cortex21(5), 1134–1146 (2011).
[CrossRef] [PubMed]

Akshoomoff, N.

E. Courchesne, R. Carper, and N. Akshoomoff, “Evidence of brain overgrowth in the first year of life in autism,” JAMA290(3), 337–344 (2003).
[CrossRef] [PubMed]

Alexander, A. L.

J. S. Anderson, T. J. Druzgal, A. Froehlich, M. B. DuBray, N. Lange, A. L. Alexander, T. Abildskov, J. A. Nielsen, A. N. Cariello, J. R. Cooperrider, E. D. Bigler, and J. E. Lainhart, “Decreased interhemispheric functional connectivity in autism,” Cereb. Cortex21(5), 1134–1146 (2011).
[CrossRef] [PubMed]

Andermann, M. L.

A. Devor, I. Ulbert, A. K. Dunn, S. N. Narayanan, S. R. Jones, M. L. Andermann, D. A. Boas, and A. M. Dale, “Coupling of the cortical hemodynamic response to cortical and thalamic neuronal activity,” Proc. Natl. Acad. Sci. U.S.A.102(10), 3822–3827 (2005).
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M. R. Herbert, D. A. Ziegler, N. Makris, P. A. Filipek, T. L. Kemper, J. J. Normandin, H. A. Sanders, D. N. Kennedy, and V. S. Caviness., “Localization of white matter volume increase in autism and developmental language disorder,” Ann. Neurol.55(4), 530–540 (2004).
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M. D. Fox, D. Zhang, A. Z. Snyder, and M. E. Raichle, “The global signal and observed anticorrelated resting state brain networks,” J. Neurophysiol.101(6), 3270–3283 (2009).
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Neuron (2)

P. J. Uhlhaas and W. Singer, “Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology,” Neuron52(1), 155–168 (2006).
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Figures (4)

Fig. 1
Fig. 1

The position of the optical probes (7 sources: red circles, 8 detectors: blue circles) in the left hemisphere. A black line connecting a source and a detector presents a data channel, which has a number alongside. 22 channels were used to cover inferior frontal cortex (IFC) and temporal cortex (TC). There were 7 channels (left hemisphere: from Channel 1 to Channel 7, right hemisphere: from Channel 23 to Channel 29) covering IFC and 15 channels (left hemisphere: from Channel 8 to Channel 22, right hemisphere: from Channel 30 to Channel 44) covering TC. IFC was boxed with the blue line and TC with the red line in Figs. 1(a)1(c). Channels 4, 9, 14 (26, 31, 36 in symmetry in the right hemisphere) were located in the F7, FT7 and T7 in the international 10-10 system, respectively. The settings of the optical probes in the right hemisphere were identical to those of the probes in the left hemisphere through the anatomical symmetry. Channels’ numbers were marked on the left hemisphere (Fig. 1(b)) and right hemisphere (Fig. 1(c)) of the brain. We used an image of standard brain to visualize where the channels were mostly likely located in the cortex.

Fig. 2
Fig. 2

Interhemispheric correlation in ROIs of children with autism spectrum disorder (ASD, red, n = 10) and typically developing (TD) children (blue, n = 10). Error bars are standard error of mean across participants. Children with ASD showed significantly reduced interhemispheric correlation in overall (including all the channels, p = 0.018) and temporal cortex (TC, p = 0.002) than TDs in terms of HbO.

Fig. 3
Fig. 3

Inter-region correlation (HbO) between four ROIs and six seeds of children with ASD (red line, n = 10) and TDs (blue line, n = 10). Four ROIs are left interior frontal cortex (a), right inferior frontal cortex (b), left temporal cortex (c), and right temporal cortex (d). Six seeds are left inferior frontal gyrus (Channel 4), left superior temporal gyrus (Channel 9), left middle temporal gyrus (Chanel 14), right inferior frontal gyrus (Channel 26), right superior temporal gyrus (Channel 31), and right middle temporal gyrus (Channel 36). Error bars are standard error of mean across participants. Significant group difference was marked with red asterisks: * means 0.01<p<0.05, ** means p<0.01. The ASDs showed significantly weaker inter-region correlation between right TC and left STG, and weaker local correlation in right TC than controls (d).

Fig. 4
Fig. 4

HbO correlation maps for a typically developing (TD) child and an autism spectrum disorder (ASD) child. The selected seeds (Channel 4, Channel 9, Channel 14 in the left hemisphere and Channel 26, Channel 31, Channel 36 in the right hemisphere) were marked on the maps. (a) HbO correlation maps for a TD child (interhemispheric correlation value is 0.530). (b) HbO correlation maps for an ASD child (interhemispheric correlation value is 0.036). Color bar represents the strength of the correlation with the seed.

Tables (1)

Tables Icon

Table 1 Means and standard errors of means across all participants for maximum correlation of HbO and Hb, between 4 ROIs and 6 seeds.

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