Abstract

Multiscale entropy (MSE) analysis is a novel entropy-based analysis method for quantifying the complexity of dynamic neural signals and physiological systems across multiple temporal scales. This approach may assist in elucidating the pathophysiologic mechanisms of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). Using resting-state fNIRS imaging, we recorded spontaneous brain activity from 31 healthy controls (HC), 27 patients with aMCI, and 24 patients with AD. The quantitative analysis of MSE revealed that reduced brain signal complexity in AD patients in several networks, namely, the default, frontoparietal, ventral and dorsal attention networks. For the default and ventral attention networks, the MSE values also showed significant positive correlations with cognitive performances. These findings demonstrated that the MSE-based analysis method could serve as a novel tool for fNIRS study in characterizing and understanding the complexity of abnormal cortical signals in AD cohorts.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2016 (3)

P. Scheltens, K. Blennow, M. M. Breteler, B. de Strooper, G. B. Frisoni, S. Salloway, and W. M. Van der Flier, “Alzheimer’s disease,” Lancet 388(10043), 505–517 (2016).
[Crossref] [PubMed]

M. A. Kamran, M. M. Mannan, and M. Y. Jeong, “Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review,” Front. Hum. Neurosci. 10, 261 (2016).
[Crossref] [PubMed]

H. Li, J. Jia, and Z. Yang, “Mini-Mental State Examination in Elderly Chinese: A Population-Based Normative Study,” J. Alzheimers Dis. 53(2), 487–496 (2016).
[Crossref] [PubMed]

2015 (5)

Z. Zhang, H. Zheng, K. Liang, H. Wang, S. Kong, J. Hu, F. Wu, and G. Sun, “Functional degeneration in dorsal and ventral attention systems in amnestic mild cognitive impairment and Alzheimer’s disease: an fMRI study,” Neurosci. Lett. 585, 160–165 (2015).
[Crossref] [PubMed]

P. H. Tsai, S. C. Chang, F. C. Liu, J. Tsao, Y. H. Wang, and M. T. Lo, “A Novel Application of Multiscale Entropy in Electroencephalography to Predict the Efficacy of Acetylcholinesterase Inhibitor in Alzheimer’s Disease,” Comput. Math. Methods Med. 2015, 953868 (2015).
[Crossref] [PubMed]

Z. Li, H. Liu, X. Liao, J. Xu, W. Liu, F. Tian, Y. He, and H. Niu, “Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy,” Biomed. Opt. Express 6(7), 2337–2352 (2015).
[Crossref] [PubMed]

H. J. Li, X. H. Hou, H. H. Liu, C. L. Yue, Y. He, and X. N. Zuo, “Toward systems neuroscience in mild cognitive impairment and Alzheimer’s disease: a meta-analysis of 75 fMRI studies,” Hum. Brain Mapp. 36(3), 1217–1232 (2015).
[Crossref] [PubMed]

J. Xu, X. Liu, J. Zhang, Z. Li, X. Wang, F. Fang, and H. Niu, “FC-NIRS: a functional connectivity analysis tool for near-infrared spectroscopy data,” BioMed Res. Int. 2015, 248724 (2015).
[Crossref] [PubMed]

2014 (3)

I. M. McDonough and K. Nashiro, “Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project,” Front. Hum. Neurosci. 8, 409 (2014).
[Crossref] [PubMed]

K. M. Langa and D. A. Levine, “The diagnosis and management of mild cognitive impairment: a clinical review,” JAMA 312(23), 2551–2561 (2014).
[Crossref] [PubMed]

H. Niu and Y. He, “Resting-state functional brain connectivity: lessons from functional near-infrared spectroscopy,” The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry 20(2), 173–188 (2014).
[Crossref] [PubMed]

2013 (7)

H. Niu, Z. Li, X. Liao, J. Wang, T. Zhao, N. Shu, X. Zhao, and Y. He, “Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study,” PLoS One 8(9), e72425 (2013).
[Crossref] [PubMed]

C. Y. Liu, A. P. Krishnan, L. Yan, R. X. Smith, E. Kilroy, J. R. Alger, J. M. Ringman, and D. J. Wang, “Complexity and synchronicity of resting state blood oxygenation level-dependent (BOLD) functional MRI in normal aging and cognitive decline,” J. Magn. Reson. Imaging 38(1), 36–45 (2013).
[Crossref] [PubMed]

B. Manor and L. A. Lipsitz, “Physiologic complexity and aging: implications for physical function and rehabilitation,” Prog. Neuropsychopharmacol. Biol. Psychiatry 45, 287–293 (2013).
[Crossref] [PubMed]

A. C. Yang, S. J. Wang, K. L. Lai, C. F. Tsai, C. H. Yang, J. P. Hwang, M. T. Lo, N. E. Huang, C. K. Peng, and J. L. Fuh, “Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer’s disease,” Prog. Neuropsychopharmacol. Biol. Psychiatry 47, 52–61 (2013).
[Crossref] [PubMed]

A. C. Yang, C. C. Huang, H. L. Yeh, M. E. Liu, C. J. Hong, P. C. Tu, J. F. Chen, N. E. Huang, C. K. Peng, C. P. Lin, and S. J. Tsai, “Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis,” Neurobiol. Aging 34(2), 428–438 (2013).
[Crossref] [PubMed]

T. P. Zanto and A. Gazzaley, “Fronto-parietal network: flexible hub of cognitive control,” Trends Cogn. Sci. (Regul. Ed.) 17(12), 602–603 (2013).
[Crossref] [PubMed]

M. W. Cole, J. R. Reynolds, J. D. Power, G. Repovs, A. Anticevic, and T. S. Braver, “Multi-task connectivity reveals flexible hubs for adaptive task control,” Nat. Neurosci. 16(9), 1348–1355 (2013).
[Crossref] [PubMed]

2012 (2)

X. Cui, D. M. Bryant, and A. L. Reiss, “NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation,” Neuroimage 59(3), 2430–2437 (2012).
[Crossref] [PubMed]

R. Li, X. Wu, A. S. Fleisher, E. M. Reiman, K. Chen, and L. Yao, “Attention-related networks in Alzheimer’s disease: a resting functional MRI study,” Hum. Brain Mapp. 33(5), 1076–1088 (2012).
[Crossref] [PubMed]

2011 (4)

J. Lu, D. Li, F. Li, A. Zhou, F. Wang, X. Zuo, X. F. Jia, H. Song, and J. Jia, “Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: a population-based study,” J. Geriatr. Psychiatry Neurol. 24(4), 184–190 (2011).
[Crossref] [PubMed]

A. C. Yang, S. J. Tsai, C. H. Yang, C. H. Kuo, T. J. Chen, and C. J. Hong, “Reduced physiologic complexity is associated with poor sleep in patients with major depression and primary insomnia,” J. Affect. Disord. 131(1-3), 179–185 (2011).
[Crossref] [PubMed]

D. Kapogiannis and M. P. Mattson, “Disrupted energy metabolism and neuronal circuit dysfunction in cognitive impairment and Alzheimer’s disease,” Lancet Neurol. 10(2), 187–198 (2011).
[Crossref] [PubMed]

B. T. Yeo, F. M. Krienen, J. Sepulcre, M. R. Sabuncu, D. Lashkari, M. Hollinshead, J. L. Roffman, J. W. Smoller, L. Zöllei, J. R. Polimeni, B. Fischl, H. Liu, and R. L. Buckner, “The organization of the human cerebral cortex estimated by intrinsic functional connectivity,” J. Neurophysiol. 106(3), 1125–1165 (2011).
[Crossref] [PubMed]

2010 (3)

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]

T. Mizuno, T. Takahashi, R. Y. Cho, M. Kikuchi, T. Murata, K. Takahashi, and Y. Wada, “Assessment of EEG dynamical complexity in Alzheimer’s disease using multiscale entropy,” Clin. Neurophysiol. 121(9), 1438–1446 (2010).
[Crossref] [PubMed]

T. Takahashi, R. Y. Cho, T. Mizuno, M. Kikuchi, T. Murata, K. Takahashi, and Y. Wada, “Antipsychotics reverse abnormal EEG complexity in drug-naive schizophrenia: a multiscale entropy analysis,” Neuroimage 51(1), 173–182 (2010).
[Crossref] [PubMed]

2009 (4)

P. R. Norris, J. A. Canter, J. M. Jenkins, J. H. Moore, A. E. Williams, and J. A. Morris., “Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients,” Ann. Surg. 250(4), 524–530 (2009).
[PubMed]

D. Cheng, S. J. Tsai, C. J. Hong, and A. C. Yang, “Reduced physiological complexity in robust elderly adults with the APOE epsilon4 allele,” PLoS One 4(11), e7733 (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,” Neuroimage 47(1), 148–156 (2009).
[Crossref] [PubMed]

B. C. Dickerson and R. A. Sperling, “Large-scale functional brain network abnormalities in Alzheimer’s disease: insights from functional neuroimaging,” Behav. Neurol. 21(1), 63–75 (2009).
[Crossref] [PubMed]

2007 (1)

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]

2006 (1)

J. Escudero, D. Abásolo, R. Hornero, P. Espino, and M. López, “Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy,” Physiol. Meas. 27(11), 1091–1106 (2006).
[Crossref] [PubMed]

2005 (2)

M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of biological signals,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(2 Pt 1), 021906 (2005).
[Crossref] [PubMed]

R. L. Buckner, A. Z. Snyder, B. J. Shannon, G. LaRossa, R. Sachs, A. F. Fotenos, Y. I. Sheline, W. E. Klunk, C. A. Mathis, J. C. Morris, and M. A. Mintun, “Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory,” The Journal. of neurosci : the official journal of the Society for Neuroscience 25(34), 7709–7717 (2005).
[Crossref] [PubMed]

2004 (3)

J. Jeong, “EEG dynamics in patients with Alzheimer’s disease,” Clin. Neurophysiol. 115(7), 1490–1505 (2004).
[Crossref] [PubMed]

R. C. Petersen, “Mild cognitive impairment as a diagnostic entity,” J. Intern. Med. 256(3), 183–194 (2004).
[Crossref] [PubMed]

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]

2003 (2)

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]

X. Delbeuck, M. Van der Linden, and F. Collette, “Alzheimer’s disease as a disconnection syndrome?” Neuropsychol. Rev. 13(2), 79–92 (2003).
[Crossref] [PubMed]

2002 (3)

M. Corbetta and G. L. Shulman, “Control of goal-directed and stimulus-driven attention in the brain,” Nat. Rev. Neurosci. 3(3), 201–215 (2002).
[Crossref] [PubMed]

M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of complex physiologic time series,” Phys. Rev. Lett. 89(6), 068102 (2002).
[Crossref] [PubMed]

D. R. Chialvo, “Physiology: unhealthy surprises,” Nature 419(6904), 263 (2002).
[Crossref] [PubMed]

1999 (1)

B. Jelles, J. H. van Birgelen, J. P. Slaets, R. E. Hekster, E. J. Jonkman, and C. J. Stam, “Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls,” Clin. Neurophysiol. 110(7), 1159–1167 (1999).
[Crossref] [PubMed]

1998 (1)

G. Tononi, G. M. Edelman, and O. Sporns, “Complexity and coherency: integrating information in the brain,” Trends Cogn. Sci. (Regul. Ed.) 2(12), 474–484 (1998).
[Crossref] [PubMed]

1995 (2)

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]

K. J. Friston, G. Tononi, O. Sporns, and G. Edelman, “Characterising the complexity of neuronal interactions,” Hum. Brain Mapp. 3(4), 302–314 (1995).
[Crossref]

1994 (1)

G. Tononi, O. Sporns, and G. M. Edelman, “A measure for brain complexity: relating functional segregation and integration in the nervous system,” Proc. Natl. Acad. Sci. U.S.A. 91(11), 5033–5037 (1994).
[Crossref] [PubMed]

1984 (1)

G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, and E. M. Stadlan, “Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease,” Neurology 34(7), 939–944 (1984).
[Crossref] [PubMed]

Abásolo, D.

J. Escudero, D. Abásolo, R. Hornero, P. Espino, and M. López, “Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy,” Physiol. Meas. 27(11), 1091–1106 (2006).
[Crossref] [PubMed]

Alger, J. R.

C. Y. Liu, A. P. Krishnan, L. Yan, R. X. Smith, E. Kilroy, J. R. Alger, J. M. Ringman, and D. J. Wang, “Complexity and synchronicity of resting state blood oxygenation level-dependent (BOLD) functional MRI in normal aging and cognitive decline,” J. Magn. Reson. Imaging 38(1), 36–45 (2013).
[Crossref] [PubMed]

Amita, T.

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]

Anticevic, A.

M. W. Cole, J. R. Reynolds, J. D. Power, G. Repovs, A. Anticevic, and T. S. Braver, “Multi-task connectivity reveals flexible hubs for adaptive task control,” Nat. Neurosci. 16(9), 1348–1355 (2013).
[Crossref] [PubMed]

Biswal, B.

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]

Blennow, K.

P. Scheltens, K. Blennow, M. M. Breteler, B. de Strooper, G. B. Frisoni, S. Salloway, and W. M. Van der Flier, “Alzheimer’s disease,” Lancet 388(10043), 505–517 (2016).
[Crossref] [PubMed]

Braver, T. S.

M. W. Cole, J. R. Reynolds, J. D. Power, G. Repovs, A. Anticevic, and T. S. Braver, “Multi-task connectivity reveals flexible hubs for adaptive task control,” Nat. Neurosci. 16(9), 1348–1355 (2013).
[Crossref] [PubMed]

Breteler, M. M.

P. Scheltens, K. Blennow, M. M. Breteler, B. de Strooper, G. B. Frisoni, S. Salloway, and W. M. Van der Flier, “Alzheimer’s disease,” Lancet 388(10043), 505–517 (2016).
[Crossref] [PubMed]

Bryant, D. M.

X. Cui, D. M. Bryant, and A. L. Reiss, “NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation,” Neuroimage 59(3), 2430–2437 (2012).
[Crossref] [PubMed]

Buckner, R. L.

B. T. Yeo, F. M. Krienen, J. Sepulcre, M. R. Sabuncu, D. Lashkari, M. Hollinshead, J. L. Roffman, J. W. Smoller, L. Zöllei, J. R. Polimeni, B. Fischl, H. Liu, and R. L. Buckner, “The organization of the human cerebral cortex estimated by intrinsic functional connectivity,” J. Neurophysiol. 106(3), 1125–1165 (2011).
[Crossref] [PubMed]

R. L. Buckner, A. Z. Snyder, B. J. Shannon, G. LaRossa, R. Sachs, A. F. Fotenos, Y. I. Sheline, W. E. Klunk, C. A. Mathis, J. C. Morris, and M. A. Mintun, “Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory,” The Journal. of neurosci : the official journal of the Society for Neuroscience 25(34), 7709–7717 (2005).
[Crossref] [PubMed]

Canter, J. A.

P. R. Norris, J. A. Canter, J. M. Jenkins, J. H. Moore, A. E. Williams, and J. A. Morris., “Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients,” Ann. Surg. 250(4), 524–530 (2009).
[PubMed]

Chang, S. C.

P. H. Tsai, S. C. Chang, F. C. Liu, J. Tsao, Y. H. Wang, and M. T. Lo, “A Novel Application of Multiscale Entropy in Electroencephalography to Predict the Efficacy of Acetylcholinesterase Inhibitor in Alzheimer’s Disease,” Comput. Math. Methods Med. 2015, 953868 (2015).
[Crossref] [PubMed]

Chen, J. F.

A. C. Yang, C. C. Huang, H. L. Yeh, M. E. Liu, C. J. Hong, P. C. Tu, J. F. Chen, N. E. Huang, C. K. Peng, C. P. Lin, and S. J. Tsai, “Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis,” Neurobiol. Aging 34(2), 428–438 (2013).
[Crossref] [PubMed]

Chen, K.

R. Li, X. Wu, A. S. Fleisher, E. M. Reiman, K. Chen, and L. Yao, “Attention-related networks in Alzheimer’s disease: a resting functional MRI study,” Hum. Brain Mapp. 33(5), 1076–1088 (2012).
[Crossref] [PubMed]

Chen, T. J.

A. C. Yang, S. J. Tsai, C. H. Yang, C. H. Kuo, T. J. Chen, and C. J. Hong, “Reduced physiologic complexity is associated with poor sleep in patients with major depression and primary insomnia,” J. Affect. Disord. 131(1-3), 179–185 (2011).
[Crossref] [PubMed]

Cheng, D.

D. Cheng, S. J. Tsai, C. J. Hong, and A. C. Yang, “Reduced physiological complexity in robust elderly adults with the APOE epsilon4 allele,” PLoS One 4(11), e7733 (2009).
[Crossref] [PubMed]

Chialvo, D. R.

D. R. Chialvo, “Physiology: unhealthy surprises,” Nature 419(6904), 263 (2002).
[Crossref] [PubMed]

Cho, R. Y.

T. Mizuno, T. Takahashi, R. Y. Cho, M. Kikuchi, T. Murata, K. Takahashi, and Y. Wada, “Assessment of EEG dynamical complexity in Alzheimer’s disease using multiscale entropy,” Clin. Neurophysiol. 121(9), 1438–1446 (2010).
[Crossref] [PubMed]

T. Takahashi, R. Y. Cho, T. Mizuno, M. Kikuchi, T. Murata, K. Takahashi, and Y. Wada, “Antipsychotics reverse abnormal EEG complexity in drug-naive schizophrenia: a multiscale entropy analysis,” Neuroimage 51(1), 173–182 (2010).
[Crossref] [PubMed]

Cohen, A. L.

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]

Cole, M. W.

M. W. Cole, J. R. Reynolds, J. D. Power, G. Repovs, A. Anticevic, and T. S. Braver, “Multi-task connectivity reveals flexible hubs for adaptive task control,” Nat. Neurosci. 16(9), 1348–1355 (2013).
[Crossref] [PubMed]

Collette, F.

X. Delbeuck, M. Van der Linden, and F. Collette, “Alzheimer’s disease as a disconnection syndrome?” Neuropsychol. Rev. 13(2), 79–92 (2003).
[Crossref] [PubMed]

Corbetta, M.

M. Corbetta and G. L. Shulman, “Control of goal-directed and stimulus-driven attention in the brain,” Nat. Rev. Neurosci. 3(3), 201–215 (2002).
[Crossref] [PubMed]

Costa, M.

M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of biological signals,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(2 Pt 1), 021906 (2005).
[Crossref] [PubMed]

M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of complex physiologic time series,” Phys. Rev. Lett. 89(6), 068102 (2002).
[Crossref] [PubMed]

Cui, X.

X. Cui, D. M. Bryant, and A. L. Reiss, “NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation,” Neuroimage 59(3), 2430–2437 (2012).
[Crossref] [PubMed]

Culver, J. P.

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]

de Strooper, B.

P. Scheltens, K. Blennow, M. M. Breteler, B. de Strooper, G. B. Frisoni, S. Salloway, and W. M. Van der Flier, “Alzheimer’s disease,” Lancet 388(10043), 505–517 (2016).
[Crossref] [PubMed]

Delbeuck, X.

X. Delbeuck, M. Van der Linden, and F. Collette, “Alzheimer’s disease as a disconnection syndrome?” Neuropsychol. Rev. 13(2), 79–92 (2003).
[Crossref] [PubMed]

Dickerson, B. C.

B. C. Dickerson and R. A. Sperling, “Large-scale functional brain network abnormalities in Alzheimer’s disease: insights from functional neuroimaging,” Behav. Neurol. 21(1), 63–75 (2009).
[Crossref] [PubMed]

Drachman, D.

G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, and E. M. Stadlan, “Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease,” Neurology 34(7), 939–944 (1984).
[Crossref] [PubMed]

Edelman, G.

K. J. Friston, G. Tononi, O. Sporns, and G. Edelman, “Characterising the complexity of neuronal interactions,” Hum. Brain Mapp. 3(4), 302–314 (1995).
[Crossref]

Edelman, G. M.

G. Tononi, G. M. Edelman, and O. Sporns, “Complexity and coherency: integrating information in the brain,” Trends Cogn. Sci. (Regul. Ed.) 2(12), 474–484 (1998).
[Crossref] [PubMed]

G. Tononi, O. Sporns, and G. M. Edelman, “A measure for brain complexity: relating functional segregation and integration in the nervous system,” Proc. Natl. Acad. Sci. U.S.A. 91(11), 5033–5037 (1994).
[Crossref] [PubMed]

Escudero, J.

J. Escudero, D. Abásolo, R. Hornero, P. Espino, and M. López, “Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy,” Physiol. Meas. 27(11), 1091–1106 (2006).
[Crossref] [PubMed]

Espino, P.

J. Escudero, D. Abásolo, R. Hornero, P. Espino, and M. López, “Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy,” Physiol. Meas. 27(11), 1091–1106 (2006).
[Crossref] [PubMed]

Fang, F.

J. Xu, X. Liu, J. Zhang, Z. Li, X. Wang, F. Fang, and H. Niu, “FC-NIRS: a functional connectivity analysis tool for near-infrared spectroscopy data,” BioMed Res. Int. 2015, 248724 (2015).
[Crossref] [PubMed]

Fischl, B.

B. T. Yeo, F. M. Krienen, J. Sepulcre, M. R. Sabuncu, D. Lashkari, M. Hollinshead, J. L. Roffman, J. W. Smoller, L. Zöllei, J. R. Polimeni, B. Fischl, H. Liu, and R. L. Buckner, “The organization of the human cerebral cortex estimated by intrinsic functional connectivity,” J. Neurophysiol. 106(3), 1125–1165 (2011).
[Crossref] [PubMed]

Fleisher, A. S.

R. Li, X. Wu, A. S. Fleisher, E. M. Reiman, K. Chen, and L. Yao, “Attention-related networks in Alzheimer’s disease: a resting functional MRI study,” Hum. Brain Mapp. 33(5), 1076–1088 (2012).
[Crossref] [PubMed]

Folstein, M.

G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, and E. M. Stadlan, “Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease,” Neurology 34(7), 939–944 (1984).
[Crossref] [PubMed]

Fotenos, A. F.

R. L. Buckner, A. Z. Snyder, B. J. Shannon, G. LaRossa, R. Sachs, A. F. Fotenos, Y. I. Sheline, W. E. Klunk, C. A. Mathis, J. C. Morris, and M. A. Mintun, “Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory,” The Journal. of neurosci : the official journal of the Society for Neuroscience 25(34), 7709–7717 (2005).
[Crossref] [PubMed]

Frisoni, G. B.

P. Scheltens, K. Blennow, M. M. Breteler, B. de Strooper, G. B. Frisoni, S. Salloway, and W. M. Van der Flier, “Alzheimer’s disease,” Lancet 388(10043), 505–517 (2016).
[Crossref] [PubMed]

Friston, K. J.

K. J. Friston, G. Tononi, O. Sporns, and G. Edelman, “Characterising the complexity of neuronal interactions,” Hum. Brain Mapp. 3(4), 302–314 (1995).
[Crossref]

Fuh, J. L.

A. C. Yang, S. J. Wang, K. L. Lai, C. F. Tsai, C. H. Yang, J. P. Hwang, M. T. Lo, N. E. Huang, C. K. Peng, and J. L. Fuh, “Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer’s disease,” Prog. Neuropsychopharmacol. Biol. Psychiatry 47, 52–61 (2013).
[Crossref] [PubMed]

Gazzaley, A.

T. P. Zanto and A. Gazzaley, “Fronto-parietal network: flexible hub of cognitive control,” Trends Cogn. Sci. (Regul. Ed.) 17(12), 602–603 (2013).
[Crossref] [PubMed]

Goldberger, A. L.

M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of biological signals,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(2 Pt 1), 021906 (2005).
[Crossref] [PubMed]

M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of complex physiologic time series,” Phys. Rev. Lett. 89(6), 068102 (2002).
[Crossref] [PubMed]

Greicius, M. D.

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]

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]

Haughton, V. M.

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]

He, Y.

H. J. Li, X. H. Hou, H. H. Liu, C. L. Yue, Y. He, and X. N. Zuo, “Toward systems neuroscience in mild cognitive impairment and Alzheimer’s disease: a meta-analysis of 75 fMRI studies,” Hum. Brain Mapp. 36(3), 1217–1232 (2015).
[Crossref] [PubMed]

Z. Li, H. Liu, X. Liao, J. Xu, W. Liu, F. Tian, Y. He, and H. Niu, “Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy,” Biomed. Opt. Express 6(7), 2337–2352 (2015).
[Crossref] [PubMed]

H. Niu and Y. He, “Resting-state functional brain connectivity: lessons from functional near-infrared spectroscopy,” The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry 20(2), 173–188 (2014).
[Crossref] [PubMed]

H. Niu, Z. Li, X. Liao, J. Wang, T. Zhao, N. Shu, X. Zhao, and Y. He, “Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study,” PLoS One 8(9), e72425 (2013).
[Crossref] [PubMed]

Hekster, R. E.

B. Jelles, J. H. van Birgelen, J. P. Slaets, R. E. Hekster, E. J. Jonkman, and C. J. Stam, “Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls,” Clin. Neurophysiol. 110(7), 1159–1167 (1999).
[Crossref] [PubMed]

Hollinshead, M.

B. T. Yeo, F. M. Krienen, J. Sepulcre, M. R. Sabuncu, D. Lashkari, M. Hollinshead, J. L. Roffman, J. W. Smoller, L. Zöllei, J. R. Polimeni, B. Fischl, H. Liu, and R. L. Buckner, “The organization of the human cerebral cortex estimated by intrinsic functional connectivity,” J. Neurophysiol. 106(3), 1125–1165 (2011).
[Crossref] [PubMed]

Hong, C. J.

A. C. Yang, C. C. Huang, H. L. Yeh, M. E. Liu, C. J. Hong, P. C. Tu, J. F. Chen, N. E. Huang, C. K. Peng, C. P. Lin, and S. J. Tsai, “Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis,” Neurobiol. Aging 34(2), 428–438 (2013).
[Crossref] [PubMed]

A. C. Yang, S. J. Tsai, C. H. Yang, C. H. Kuo, T. J. Chen, and C. J. Hong, “Reduced physiologic complexity is associated with poor sleep in patients with major depression and primary insomnia,” J. Affect. Disord. 131(1-3), 179–185 (2011).
[Crossref] [PubMed]

D. Cheng, S. J. Tsai, C. J. Hong, and A. C. Yang, “Reduced physiological complexity in robust elderly adults with the APOE epsilon4 allele,” PLoS One 4(11), e7733 (2009).
[Crossref] [PubMed]

Hornero, R.

J. Escudero, D. Abásolo, R. Hornero, P. Espino, and M. López, “Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy,” Physiol. Meas. 27(11), 1091–1106 (2006).
[Crossref] [PubMed]

Hou, X. H.

H. J. Li, X. H. Hou, H. H. Liu, C. L. Yue, Y. He, and X. N. Zuo, “Toward systems neuroscience in mild cognitive impairment and Alzheimer’s disease: a meta-analysis of 75 fMRI studies,” Hum. Brain Mapp. 36(3), 1217–1232 (2015).
[Crossref] [PubMed]

Hu, J.

Z. Zhang, H. Zheng, K. Liang, H. Wang, S. Kong, J. Hu, F. Wu, and G. Sun, “Functional degeneration in dorsal and ventral attention systems in amnestic mild cognitive impairment and Alzheimer’s disease: an fMRI study,” Neurosci. Lett. 585, 160–165 (2015).
[Crossref] [PubMed]

Huang, C. C.

A. C. Yang, C. C. Huang, H. L. Yeh, M. E. Liu, C. J. Hong, P. C. Tu, J. F. Chen, N. E. Huang, C. K. Peng, C. P. Lin, and S. J. Tsai, “Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis,” Neurobiol. Aging 34(2), 428–438 (2013).
[Crossref] [PubMed]

Huang, N. E.

A. C. Yang, C. C. Huang, H. L. Yeh, M. E. Liu, C. J. Hong, P. C. Tu, J. F. Chen, N. E. Huang, C. K. Peng, C. P. Lin, and S. J. Tsai, “Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis,” Neurobiol. Aging 34(2), 428–438 (2013).
[Crossref] [PubMed]

A. C. Yang, S. J. Wang, K. L. Lai, C. F. Tsai, C. H. Yang, J. P. Hwang, M. T. Lo, N. E. Huang, C. K. Peng, and J. L. Fuh, “Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer’s disease,” Prog. Neuropsychopharmacol. Biol. Psychiatry 47, 52–61 (2013).
[Crossref] [PubMed]

Hwang, J. P.

A. C. Yang, S. J. Wang, K. L. Lai, C. F. Tsai, C. H. Yang, J. P. Hwang, M. T. Lo, N. E. Huang, C. K. Peng, and J. L. Fuh, “Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer’s disease,” Prog. Neuropsychopharmacol. Biol. Psychiatry 47, 52–61 (2013).
[Crossref] [PubMed]

Hyde, J. S.

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]

Ishikawa, A.

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]

Jelles, B.

B. Jelles, J. H. van Birgelen, J. P. Slaets, R. E. Hekster, E. J. Jonkman, and C. J. Stam, “Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls,” Clin. Neurophysiol. 110(7), 1159–1167 (1999).
[Crossref] [PubMed]

Jenkins, J. M.

P. R. Norris, J. A. Canter, J. M. Jenkins, J. H. Moore, A. E. Williams, and J. A. Morris., “Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients,” Ann. Surg. 250(4), 524–530 (2009).
[PubMed]

Jeong, J.

J. Jeong, “EEG dynamics in patients with Alzheimer’s disease,” Clin. Neurophysiol. 115(7), 1490–1505 (2004).
[Crossref] [PubMed]

Jeong, M. Y.

M. A. Kamran, M. M. Mannan, and M. Y. Jeong, “Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review,” Front. Hum. Neurosci. 10, 261 (2016).
[Crossref] [PubMed]

Jia, J.

H. Li, J. Jia, and Z. Yang, “Mini-Mental State Examination in Elderly Chinese: A Population-Based Normative Study,” J. Alzheimers Dis. 53(2), 487–496 (2016).
[Crossref] [PubMed]

J. Lu, D. Li, F. Li, A. Zhou, F. Wang, X. Zuo, X. F. Jia, H. Song, and J. Jia, “Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: a population-based study,” J. Geriatr. Psychiatry Neurol. 24(4), 184–190 (2011).
[Crossref] [PubMed]

Jia, X. F.

J. Lu, D. Li, F. Li, A. Zhou, F. Wang, X. Zuo, X. F. Jia, H. Song, and J. Jia, “Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: a population-based study,” J. Geriatr. Psychiatry Neurol. 24(4), 184–190 (2011).
[Crossref] [PubMed]

Jonkman, E. J.

B. Jelles, J. H. van Birgelen, J. P. Slaets, R. E. Hekster, E. J. Jonkman, and C. J. Stam, “Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls,” Clin. Neurophysiol. 110(7), 1159–1167 (1999).
[Crossref] [PubMed]

Kamran, M. A.

M. A. Kamran, M. M. Mannan, and M. Y. Jeong, “Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review,” Front. Hum. Neurosci. 10, 261 (2016).
[Crossref] [PubMed]

Kapogiannis, D.

D. Kapogiannis and M. P. Mattson, “Disrupted energy metabolism and neuronal circuit dysfunction in cognitive impairment and Alzheimer’s disease,” Lancet Neurol. 10(2), 187–198 (2011).
[Crossref] [PubMed]

Katzman, R.

G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, and E. M. Stadlan, “Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease,” Neurology 34(7), 939–944 (1984).
[Crossref] [PubMed]

Kikuchi, M.

T. Mizuno, T. Takahashi, R. Y. Cho, M. Kikuchi, T. Murata, K. Takahashi, and Y. Wada, “Assessment of EEG dynamical complexity in Alzheimer’s disease using multiscale entropy,” Clin. Neurophysiol. 121(9), 1438–1446 (2010).
[Crossref] [PubMed]

T. Takahashi, R. Y. Cho, T. Mizuno, M. Kikuchi, T. Murata, K. Takahashi, and Y. Wada, “Antipsychotics reverse abnormal EEG complexity in drug-naive schizophrenia: a multiscale entropy analysis,” Neuroimage 51(1), 173–182 (2010).
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Kilroy, E.

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R. L. Buckner, A. Z. Snyder, B. J. Shannon, G. LaRossa, R. Sachs, A. F. Fotenos, Y. I. Sheline, W. E. Klunk, C. A. Mathis, J. C. Morris, and M. A. Mintun, “Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory,” The Journal. of neurosci : the official journal of the Society for Neuroscience 25(34), 7709–7717 (2005).
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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).
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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).
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C. Y. Liu, A. P. Krishnan, L. Yan, R. X. Smith, E. Kilroy, J. R. Alger, J. M. Ringman, and D. J. Wang, “Complexity and synchronicity of resting state blood oxygenation level-dependent (BOLD) functional MRI in normal aging and cognitive decline,” J. Magn. Reson. Imaging 38(1), 36–45 (2013).
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B. T. Yeo, F. M. Krienen, J. Sepulcre, M. R. Sabuncu, D. Lashkari, M. Hollinshead, J. L. Roffman, J. W. Smoller, L. Zöllei, J. R. Polimeni, B. Fischl, H. Liu, and R. L. Buckner, “The organization of the human cerebral cortex estimated by intrinsic functional connectivity,” J. Neurophysiol. 106(3), 1125–1165 (2011).
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Figures (5)

Fig. 1
Fig. 1 Schematic diagram of experimental data acquisition. (A) Photo obtained during data collection. (B) The arrangement of the whole-head 46 measurement channels on a plane graph. (C) The arrangement of the whole-head 46 measurement channels on a functional network brain template [21].
Fig. 2
Fig. 2 The MSE and the distribution of MSE. (A) Sample entropy for participants in the HC, aMCI and AD groups, estimated for a specific brain region (i.e., channel No 37) and the whole brain, at different temporal scales. (B) The MSE distribution histogram of three groups of participants.
Fig. 3
Fig. 3 Group difference analysis. (A) The spatial maps of MSE in HC, aMCI and AD groups, respectively. Interpolation algorithm was adopted to obtain smooth spatial maps. (B) Group differences in MSE values among HC, aMCI and AD groups. One asterisk represents significant group differences with a two sample t-test at p < 0.05 (Bonferroni corrected). The error bars indicate standard deviations.
Fig. 4
Fig. 4 Group differences in MSE values among HC, aMCI and AD in 6 functional networks. One, two and three asterisks represent significant group differences with a two sample t-test at p < 0.1, 0.05 and 0.01 (Bonferroni corrected). The error bars indicate standard deviations.
Fig. 5
Fig. 5 Correlation analysis between brain signal complexity and clinical variables. The scatter plots between clinical variable scores and MSE values in the combined AD and aMCI groups. The dashed lines in the correlation maps are regression lines with 95% prediction error bounds.

Tables (1)

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Table 1 Demographics and clinical characters of the participants

Equations (3)

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y j t = 1 t i = ( j 1 ) t + 1 j t x i , 1 j N t .
S E ( m , r ) = ln C m + 1 ( r ) C m ( r ) ,
C m ( r ) = number of pairs( i , j ) with | v i m v j m | < r × S T D ( y ) number of all probable pairs .

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