Alzheimer’s disease (AD) is the most common neurodegenerative disease in elderly individuals. We conducted this study to examine whether alterations in the fractional amplitudes of low-frequency fluctuations (fALFF) in the AD spectrum were frequency-dependent and symptom-relevant. A total of 43 patients with subjective cognitive decline (SCD), 52 with amnestic mild cognitive impairment (aMCI), 44 with Alzheimer’s dementia (d-AD) and 55 well-matched controls participated in resting-state functional magnetic resonance imaging (rs-fMRI) scans. The amplitudes were measured using fALFF within the slow-4 (0.027–0.073 Hz) and slow-5 (0.01–0.027 Hz) bands. Repeated-measures analysis of variance was performed on fALFF within two bands and correlated with neuropsychological test scores. The significant main effects of frequency and group on fALFF differed widely across brain regions. There were more varied areas in the slow-5 band than the slow-4 band. The fALFF associated with primary disease effects was mainly distributed in the parietal lobe. Obvious frequency band and group interaction effects were observed in the left angular gyrus, left calcarine fissure and surrounding cortex, left superior cerebellum, left cuneus and right lingual gyrus. Neuropsychological tests scores were significantly correlated with the fALFF magnitude of the left cuneus and right lingual in the slow-5 band. Our results suggested that the AD continuum had abnormal amplitudes in intrinsic brain activity, and these abnormalities were frequency-dependent and mainly associated with the slow-5 band rather than the slow-4 band. This may guide the frequency choice of future rs-fMRI studies and provide new insights into the neuropathophysiology of AD.
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Backman, L., Almkvist, O., Nyberg, L., & Andersson, J. (2000). Functional changes in brain activity during priming in Alzheimer's disease. Journal of Cognitive Neuroscience, 12(1), 134–141. https://doi.org/10.1162/089892900561922.
Bansal, R., & Peterson, B. S. (2018). Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions. Magnetic Resonance Imaging, 49, 101–115. https://doi.org/10.1016/j.mri.2018.01.004.
Birn, R. M. (2012). The role of physiological noise in resting-state functional connectivity. Neuroimage, 62(2), 864–870. https://doi.org/10.1016/j.neuroimage.2012.01.016.
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. Magnetic Resonance in Medicine, 34(4), 537–541. https://doi.org/10.1002/mrm.1910340409.
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain's default network: Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38. https://doi.org/10.1196/annals.1440.011.
Buzsaki, G., & Draguhn, A. (2004). Neuronal oscillations in cortical networks. Science, 304(5679), 1926–1929. https://doi.org/10.1126/science.1099745.
Calhoun, V. D., Kiehl, K. A., & Pearlson, G. D. (2008). Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks. Human Brain Mapping, 29(7), 828–838. https://doi.org/10.1002/hbm.20581.
Calhoun, V. D., Sui, J., Kiehl, K., Turner, J., Allen, E., & Pearlson, G. (2011). Exploring the psychosis functional connectome: Aberrant intrinsic networks in schizophrenia and bipolar disorder. Frontiers in Psychiatry, 2, 75. https://doi.org/10.3389/fpsyt.2011.00075.
Chang, M., Edmiston, E. K., Womer, F. Y., Thou, Q., Wei, S. N., Jiang, M. W., et al. (2019). Spontaneous low-frequency fluctuations in the neural system for emotional perception in major psychiatric disorders: Amplitude similarities and differences across frequency bands. [article]. Journal of Psychiatry & Neuroscience, 44(2), 132–141. https://doi.org/10.1503/jpn.170226.
Cho, H., Seo, S. W., Kim, J. H., Suh, M. K., Lee, J. H., Choe, Y. S., Lee, K. H., Kim, J. S., Kim, G. H., Noh, Y., Ye, B. S., Kim, H. J., Yoon, C. W., Chin, J., & Na, D. L. (2013). Amyloid deposition in early onset versus late onset Alzheimer's disease. Journal of Alzheimer's Disease, 35(4), 813–821. https://doi.org/10.3233/JAD-121927.
Ding, B., Ling, H. W., Zhang, Y., Huang, J., Zhang, H., Wang, T., et al. (2014). Pattern of cerebral hyperperfusion in Alzheimer's disease and amnestic mild cognitive impairment using voxel-based analysis of 3D arterial spin-labeling imaging: Initial experience. Clinical Interventions in Aging, 9, 493–500. https://doi.org/10.2147/CIA.S58879.
Dozeman, E., van Schaik, D. J., van Marwijk, H. W., Stek, M. L., van der Horst, H. E., & Beekman, A. T. (2011). The center for epidemiological studies depression scale (CES-D) is an adequate screening instrument for depressive and anxiety disorders in a very old population living in residential homes. International Journal of Geriatric Psychiatry, 26(3), 239–246. https://doi.org/10.1002/gps.2519.
Forster, S., Yousefi, B. H., Wester, H. J., Klupp, E., Rominger, A., Forstl, H., et al. (2012). Quantitative longitudinal interrelationships between brain metabolism and amyloid deposition during a 2-year follow-up in patients with early Alzheimer's disease. European Journal of Nuclear Medicine and Molecular Imaging, 39(12), 1927–1936. https://doi.org/10.1007/s00259-012-2230-9.
Friston, K. J., Worsley, K. J., Frackowiak, R. S., Mazziotta, J. C., & Evans, A. C. (1994). Assessing the significance of focal activations using their spatial extent. Human Brain Mapping, 1(3), 210–220. https://doi.org/10.1002/hbm.460010306.
Gao, L., Bai, L., Zhang, Y., Dai, X. J., Netra, R., Min, Y., Zhou, F., Niu, C., Dun, W., Gong, H., & Zhang, M. (2015). Frequency-dependent changes of local resting oscillations in sleep-deprived brain. PLoS One, 10(3), e0120323. https://doi.org/10.1371/journal.pone.0120323.
Guo, Q. H., Sun, Y. T., Yu, P. M., Hong, Z., & Lv, C. Z. (2007). Norm of auditory verbal learning test in the normal aged in Chinese community. Chinese Journal of Clinical Psychology, 15(2):132–134
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23, 56–62. https://doi.org/10.1136/jnnp.23.1.56.
Han, Y., Wang, J., Zhao, Z., Min, B., Lu, J., Li, K., He, Y., & Jia, J. (2011). Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: A resting-state fMRI study. Neuroimage, 55(1), 287–295. https://doi.org/10.1016/j.neuroimage.2010.11.059.
He, Y., Wang, L., Zang, Y., Tian, L., Zhang, X., Li, K., & Jiang, T. (2007). Regional coherence changes in the early stages of Alzheimer's disease: A combined structural and resting-state functional MRI study. Neuroimage, 35(2), 488–500. https://doi.org/10.1016/j.neuroimage.2006.11.042.
Hong, J. Y., Kilpatrick, L. A., Labus, J., Gupta, A., Jiang, Z., Ashe-McNalley, C., Stains, J., Heendeniya, N., Ebrat, B., Smith, S., Tillisch, K., Naliboff, B., & Mayer, E. A. (2013). Patients with chronic visceral pain show sex-related alterations in intrinsic oscillations of the resting brain. The Journal of Neuroscience, 33(29), 11994–12002. https://doi.org/10.1523/jneurosci.5733-12.2013.
Hong, Y. J., Yoon, B., Shim, Y. S., Ahn, K. J., Yang, D. W., & Lee, J. H. (2015). Gray and white matter degenerations in subjective memory impairment: Comparisons with Normal controls and mild cognitive impairment. [article]. Journal of Korean Medical Science, 30(11), 1652–1658. https://doi.org/10.3346/jkms.2015.30.11.1652.
Hou, Y., Wu, X., Hallett, M., Chan, P., & Wu, T. (2014). Frequency-dependent neural activity in Parkinson's disease. Human Brain Mapping, 35(12), 5815–5833. https://doi.org/10.1002/hbm.22587.
Hutcheon, B., & Yarom, Y. (2000). Resonance, oscillation and the intrinsic frequency preferences of neurons. Trends in Neurosciences, 23(5), 216–222. https://doi.org/10.1016/s0166-2236(00)01547-2.
Jessen, F., Amariglio, R. E., van Boxtel, M., Breteler, M., Ceccaldi, M., Chetelat, G., et al. (2014). A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimers Dement, 10(6), 844–852. https://doi.org/10.1016/j.jalz.2014.01.001.
Kang, D. W., Choi, W. H., Jung, W. S., Um, Y. H., Lee, C. U., & Lim, H. K. (2017). Impact of amyloid burden on regional functional synchronization in the cognitively Normal older adults. Scientific Reports, 7(1), 14690. https://doi.org/10.1038/s41598-017-15001-8.
Knyazev, G. G. (2007). Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neuroscience and Biobehavioral Reviews, 31(3), 377–395. https://doi.org/10.1016/j.neubiorev.2006.10.004.
Li, C., Liu, C., Yin, X., Yang, J., Gui, L., Wei, L., & Wang, J. (2014). Frequency-dependent changes in the amplitude of low-frequency fluctuations in subcortical ischemic vascular disease (SIVD): A resting-state fMRI study. Behavioural Brain Research, 274, 205–210. https://doi.org/10.1016/j.bbr.2014.08.019.
Li, Y., Jing, B., Liu, H., Li, Y., Gao, X., Li, Y., Mu, B., Yu, H., Cheng, J., Barker, P. B., Wang, H., & Han, Y. (2017). Frequency-dependent changes in the amplitude of low-frequency fluctuations in mild cognitive impairment with mild depression. Journal of Alzheimer's Disease, 58(4), 1175–1187. https://doi.org/10.3233/JAD-161282.
Liang, P., Xiang, J., Liang, H., Qi, Z., Li, K., & Alzheimer's Disease NeuroImaging, I. (2014). Altered amplitude of low-frequency fluctuations in early and late mild cognitive impairment and Alzheimer's disease. Current Alzheimer Research, 11(4), 389–398. https://doi.org/10.2174/1567205011666140331225335.
Liu, X., Wang, S., Zhang, X., Wang, Z., Tian, X., & He, Y. (2014). Abnormal amplitude of low-frequency fluctuations of intrinsic brain activity in Alzheimer's disease. Journal of Alzheimer's Disease, 40(2), 387–397. https://doi.org/10.3233/jad-131322.
Llinas, R. R. (1988). The intrinsic electrophysiological properties of mammalian neurons: Insights into central nervous system function. Science, 242(4886), 1654–1664. https://doi.org/10.1126/science.3059497.
Lu, J., Li, D., Li, F., Zhou, A., Wang, F., Zuo, X., Jia, X. F., Song, H., & Jia, J. (2011). Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: A population-based study. Journal of Geriatric Psychiatry and Neurology, 24(4), 184–190. https://doi.org/10.1177/0891988711422528.
Ma, X., Li, Z., Jing, B., Liu, H., Li, D., Li, H., & the Alzheimer’s Disease Neuroimaging Initiative. (2016). Identify the atrophy of Alzheimer's Disease, mild cognitive impairment and Normal aging using morphometric MRI analysis. Frontiers in Aging Neuroscience, 8, 243. https://doi.org/10.3389/fnagi.2016.00243.
Mascali, D., DiNuzzo, M., Gili, T., Moraschi, M., Fratini, M., Maraviglia, B., Serra, L., Bozzali, M., & Giove, F. (2015). Intrinsic patterns of coupling between correlation and amplitude of low-frequency fMRI fluctuations are disrupted in degenerative dementia mainly due to functional disconnection. PLoS One, 10(4), e0120988. https://doi.org/10.1371/journal.pone.0120988.
McDade, E., & Bateman, R. J. (2017). Stop Alzheimer's before it starts. Nature, 547(7662), 153–155. https://doi.org/10.1038/547153a.
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Jr., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., Mohs, R. C., Morris, J. C., Rossor, M. N., Scheltens, P., Carrillo, M. C., Thies, B., Weintraub, S., & Phelps, C. H. (2011). The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement, 7(3), 263–269. https://doi.org/10.1016/j.jalz.2011.03.005.
Morris, J. C. (1993). The clinical dementia rating (CDR): Current version and scoring rules. Neurology, 43(11), 2412–2414. https://doi.org/10.1212/WNL.43.11.2412-a.
Pan, P., Zhu, L., Yu, T., Shi, H., Zhang, B., Qin, R., Zhu, X., Qian, L., Zhao, H., Zhou, H., & Xu, Y. (2017). Aberrant spontaneous low-frequency brain activity in amnestic mild cognitive impairment: A meta-analysis of resting-state fMRI studies. Ageing Research Reviews, 35, 12–21. https://doi.org/10.1016/j.arr.2016.12.001.
Penttonen, M., & Buzsaki, G. (2003). Natural logarithmic relationship between brain oscillators. [article]. Thalamus & Related Systems, 2(2), 145–152. https://doi.org/10.1016/s1472-9288(03)00007-4.
Peraza, L. R., Colloby, S. J., Deboys, L., O'Brien, J. T., Kaiser, M., & Taylor, J. P. (2016). Regional functional synchronizations in dementia with Lewy bodies and Alzheimer's disease. International Psychogeriatrics, 28(7), 1143–1151. https://doi.org/10.1017/S1041610216000429.
Power, J. D., Plitt, M., Laumann, T. O., & Martin, A. (2017). Sources and implications of whole-brain fMRI signals in humans. Neuroimage, 146, 609–625. https://doi.org/10.1016/j.neuroimage.2016.09.038.
Prvulovic, D., Hubl, D., Sack, A. T., Melillo, L., Maurer, K., Frolich, L., et al. (2002). Functional imaging of visuospatial processing in Alzheimer's disease. Neuroimage, 17(3), 1403–1414. https://doi.org/10.1006/nimg.2002.1271.
Rabin, L. A., Smart, C. M., & Amariglio, R. E. (2017). Subjective cognitive decline in preclinical Alzheimer's Disease. Annual Review of Clinical Psychology, 13, 369–396. https://doi.org/10.1146/annurev-clinpsy-032816-045136.
Riederer, I., Bohn, K. P., Preibisch, C., Wiedemann, E., Zimmer, C., Alexopoulos, P., & Förster, S. (2018). Alzheimer Disease and mild cognitive impairment: Integrated pulsed arterial spin-labeling MRI and (18)F-FDG PET. Radiology, 288(1), 198–206. https://doi.org/10.1148/radiol.2018170575.
Risacher, S. L., Kim, S., Shen, L., Nho, K., Foroud, T., Green, R. C., et al. (2013). The role of apolipoprotein E (APOE) genotype in early mild cognitive impairment (E-MCI). Frontiers in Aging Neuroscience, 5, 11. https://doi.org/10.3389/fnagi.2013.00011.
Scarmeas, N., Anderson, K. E., Hilton, J., Park, A., Habeck, C., Flynn, J., Tycko, B., & Stern, Y. (2004). APOE-dependent PET patterns of brain activation in Alzheimer disease. Neurology, 63(5), 913–915. https://doi.org/10.1212/01.WNL.0000137274.93125.46
Seo, E. H., Lee, D. Y., Lee, J. M., Park, J. S., Sohn, B. K., Choe, Y. M., Byun, M. S., Choi, H. J., & Woo, J. I. (2013). Influence of APOE genotype on whole-brain functional networks in cognitively normal elderly. PLoS One, 8(12), e83205. https://doi.org/10.1371/journal.pone.0083205.
Silverman, D. H., Small, G. W., Chang, C. Y., Lu, C. S., Kung De Aburto, M. A., Chen, W., et al. (2001). Positron emission tomography in evaluation of dementia: Regional brain metabolism and long-term outcome. JAMA, 286(17), 2120–2127. https://doi.org/10.1001/jama.286.17.2120.
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Jr., Kaye, J., Montine, T. J., Park, D. C., Reiman, E. M., Rowe, C. C., Siemers, E., Stern, Y., Yaffe, K., Carrillo, M. C., Thies, B., Morrison-Bogorad, M., Wagster, M. V., & Phelps, C. H. (2011). Toward defining the preclinical stages of Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement, 7(3), 280–292. https://doi.org/10.1016/j.jalz.2011.03.003.
Wang, Z., Jia, X., Liang, P., Qi, Z., Yang, Y., Zhou, W., & Li, K. (2012). Changes in thalamus connectivity in mild cognitive impairment: Evidence from resting state fMRI. European Journal of Radiology, 81(2), 277–285. https://doi.org/10.1016/j.ejrad.2010.12.044.
Wei, L., Duan, X., Zheng, C., Wang, S., Gao, Q., Zhang, Z., Lu, G., & Chen, H. (2014). Specific frequency bands of amplitude low-frequency oscillation encodes personality. Human Brain Mapping, 35(1), 331–339. https://doi.org/10.1002/hbm.22176.
Worsley, K. J., Marrett, S., Neelin, P., Vandal, A. C., Friston, K. J., & Evans, A. C. (1996). A unified statistical approach for determining significant signals in images of cerebral activation. Human Brain Mapping, 4(1), 58–73.
Xue, S. W., Li, D., Weng, X. C., Northoff, G., & Li, D. W. (2014). Different neural manifestations of two slow frequency bands in resting functional magnetic resonance imaging: A systemic survey at regional, interregional, and network levels. Brain Connectivity, 4(4), 242–255. https://doi.org/10.1089/brain.2013.0182.
Yan, T., Wang, W., Yang, L., Chen, K., Chen, R., & Han, Y. (2018). Rich club disturbances of the human connectome from subjective cognitive decline to Alzheimer's disease. Theranostics, 8(12), 3237–3255. https://doi.org/10.7150/thno.23772.
Yang, C., Sun, X., Tao, W., Li, X., Zhang, J., Jia, J., Chen, K., & Zhang, Z. (2016). Multistage grading of amnestic mild cognitive impairment: The associated brain gray matter volume and cognitive behavior characterization. Frontiers in Aging Neuroscience, 8, 332. https://doi.org/10.3389/fnagi.2016.00332.
Yang, L., Yan, Y., Wang, Y., Hu, X., Lu, J., Chan, P., Yan, T., & Han, Y. (2018). Gradual disturbances of the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF in Alzheimer Spectrum. Frontiers in Neuroscience, 12.:975 https://doi.org/10.3389/fnins.2018.00975.
Yue, Y., Jia, X., Hou, Z., Zang, Y., & Yuan, Y. (2015). Frequency-dependent amplitude alterations of resting-state spontaneous fluctuations in late-onset depression. BioMed Research International, 2015, 505479–505479. https://doi.org/10.1155/2015/505479.
Zang, Y. F., He, Y., Zhu, C. Z., Cao, Q. J., Sui, M. Q., Liang, M., et al. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. [article]. Brain & Development, 29(2), 83–91. https://doi.org/10.1016/j.braindev.2006.07.002.
Zhang, Z., Hong, X., & Hui, L. I. (1999). The minimental state examination in the Chinese residents population aged 55 years and over in the urban and rural areas of Beijing. Chinese Journal of Neurology, 32, 149–153.
Zhao, W. N., Wang, X. T., Yin, C. H., He, M. F., Li, S. Y., & Han, Y. (2019). Trajectories of the hippocampal subfields atrophy in the Alzheimer's Disease: A structural imaging study. Frontiers in Neuroinformatics, 13, 9. https://doi.org/10.3389/fninf.2019.00013.
Zou, Q. H., Zhu, C. Z., Yang, Y., Zuo, X. N., Long, X. Y., Cao, Q. J., Wang, Y. F., & Zang, Y. F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. Journal of Neuroscience Methods, 172(1), 137–141. https://doi.org/10.1016/j.jneumeth.2008.04.012.
Zuo, X. N., Di Martino, A., Kelly, C., Shehzad, Z. E., Gee, D. G., Klein, D. F., et al. (2010). The oscillating brain: Complex and reliable. Neuroimage, 49(2), 1432–1445. https://doi.org/10.1016/j.neuroimage.2009.09.037.
This article was supported by the National Key Research and Development Program of China (2016YFC1306300, 2016YFC0103000, 2017YFB1002504); the National Natural Science Foundation of China (Grants 61633018, 81430037,81471731, 31371007, 81671776, 61727807, 81522021, 81801052); Beijing Municipal Nature Science Foundation (7161009, 7132147); the Beijing Municipal Commission of Health and Family Planning (PXM2019_026283_000002); the Beijing Nova Program (Grant No. Z171100001117057, Z191100010618004); the Beijing Municipal Science & Technology Commission; and China Postdoctoral Science Foundation (2018 M641414).
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The research was authorized by the Medical Research Ethics Committee and the Institutional Review Board of Xuanwu Hospital, Beijing, China.
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Yang, L., Yan, Y., Li, Y. et al. Frequency-dependent changes in fractional amplitude of low-frequency oscillations in Alzheimer’s disease: a resting-state fMRI study. Brain Imaging and Behavior 14, 2187–2201 (2020). https://doi.org/10.1007/s11682-019-00169-6
- Alzheimer’s disease
- Subjective cognitive decline
- Resting-state functional MRI
- Frequency dependence