Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment

Frontiers in Aging Neuroscience

Volumn 5, Issue DEC, 2013, Pages

  Garcés, Pilar ^a   Vicente, Raul ^b,c,d   Wibral, Michael ^b   Pineda Pardo, Jose ángel ^a   López, Maria Eugenia ^a   Aurtenetxe, Sara ^a   Marcos, Alberto ^e   de Andrés, Maria Emiliana ^f   Yus, Miguel ^e   Sancho, Miguel ^a   Maestú, Fernando ^a   Fernández, Alberto ^a  

^a UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

^b GOETHE UNIVERSITY   (Germany)

^c MAX PLANCK INSTITUTE FOR BRAIN RESEARCH   (Germany)

^d UNIVERSITY OF TARTU   (Estonia)

^e HOSPITAL CLÍNICO SAN CARLOS   (Spain)

^f Memory Decline Prevention Center Ayuntamiento de Madrid   (Spain)

Author keywords

Alpha peak; Hippocampal volume; Magnetoencephalography; Mild cognitive impairment; Slowing

Indexed keywords

AGE; AGED; ALPHA RHYTHM; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; DAILY LIFE ACTIVITY; FEMALE; FRONTAL OPERCULUM; GLOBUS PALLIDUS; HIPPOCAMPUS; HUMAN; MAGNETOENCEPHALOGRAPHY; MALE; MEMORY DISORDER; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; POWER SPECTRUM; SEX DIFFERENCE;

EID: 84895834265     PISSN: None     EISSN: 16634365     Source Type: Journal    
DOI: 10.3389/fnagi.2013.00100     Document Type: Article

References (45)

1. Babiloni, C., Carducci, F., Lizio, R., Vecchio, F., Baglieri, A., Bernardini, S., et al. (2013). Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease. Hum. Brain Mapp. 34, 1427-1446. doi: 10.1002/hbm.22005.
2. Babiloni, C., Frisoni, G. B., Pievani, M., Vecchio, F., Lizio, R., Buttiglione, M., et al. (2009). Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease. Neuroimage 44, 123-135. doi: 10.1016/j.neuroimage.2008.08.005.
3. Bate, C., and Williams, A. (2011). Amyloid-β-induced synapse damage is mediated via cross-linkage of cellular prion proteins. J. Biol. Chem. 286, 37955-37963. doi: 10.1074/jbc. M111.248724.
4. Berendse, H., Verbunt, J. P., Scheltens, P., van Dijk, B., and Jonkman, E. (2000). Magnetoencephalographic analysis of cortical activity in Alzheimer's disease: a pilot study. Clin. Neurophysiol. 111, 604-612. doi: 10.1016/S1388-2457(99)00309-0.
5. Bhattacharya, B. S., Coyle, D., and Maguire, L. P. (2011). A thalamo-cortico-thalamic neural mass model to study alpha rhythms in Alzheimer's disease. Neural Netw. 24, 631-645. doi: 10.1016/j.neunet.2011.02.009.
6. Bollimunta, A., Chen, Y., Schroeder, C. E., and Ding, M. (2008). Neuronal mechanisms of cortical alpha oscillations in awake-behaving macaques. J. Neurosci. 28, 9976-9988. doi: 10.1523/JNEUROSCI.2699-08.2008.
7. Bollimunta, A., Mo, J., Schroeder, C. E., and Ding, M. (2011). Neuronal mechanisms and attentional modulation of corticothalamic a oscillations. J. Neurosci. 31, 4935-4943. doi: 10.1523/JNEUROSCI.5580-10.2011.
8. Chiang, A. K. I., Rennie, C. J., Robinson, P. A., Roberts, J. A., Rigozzi, M. K., Whitehouse, R. W., et al. (2008). Automated characterization of multiple alpha peaks in multi-site electroencephalograms. J. Neurosci. Methods 168, 396-411. doi: 10.1016/j.jneumeth.2007.11.001.
9. Chiang, A. K. I., Rennie, C. J., Robinson, P. A., van Albada, S. J., and Kerr, C. C. (2011). Age trends and sex differences of alpha rhythms including split alpha peaks. Clin. Neurophysiol. 122, 1505-1517. doi: 10.1016/j.clinph.2011.01.040.
10. Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., et al. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968-980. doi: 10.1016/j.neuroimage.2006.01.021.
11. Dubois, B., Feldman, H. H., Jacova, C., Dekosky, S. T., Barberger-Gateau, P., Cummings, J., et al. (2007). Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 6, 734-746. doi: 10.1016/S1474-4422(07)70178-3.
12. Dustman, R. E., Shearer, D. E., and Emmerson, R. Y. (1993). EEG and event-related potentials in normal aging. Prog. Neurobiol. 41, 369-401. doi: 10.1016/0301-0082(93)90005-D.
13. Fernández, A., Arrazola, J., Maestú, F., Amo, C., Gil-Gregorio, P., Wienbruch, C., et al. (2003). Correlations of hippocampal atrophy and focal low-frequency magnetic activity in Alzheimer disease: volumetric MR imaging-magnetoencephalographic study. AJNR Am. J. Neuroradiol. 24, 481-487. Available online at: http://www.ncbi.nlm.nih.gov/pubmed/12637301.
14. Fernández, A., Hornero, R., Mayo, A., Poza, J., Gil-Gregorio, P., and Ortiz, T. (2006). MEG spectral profile in Alzheimer's disease and mild cognitive impairment. Clin. Neurophysiol. 117, 306-314. doi: 10.1016/j.clinph.2005.10.017.
15. Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., et al. (2002). Whole brain segmentation. Neuron 33, 341-355. doi: 10.1016/S0896-6273(02)00569-X.
16. Flint, A. C., and Connors, B. W. (1996). Two types of network oscillations in neocortex mediated by distinct glutamate receptor subtypes and neuronal populations. J Neurophysiol 75, 951-957.
17. Grundman, M., Petersen, R. C., Ferris, S. H., Thomas, R. G., Aisen, P. S., Bennett, D. A., et al. (2004). Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials. Arch. Neurol. 61, 59-66. doi: 10.1001/archneur.61.1.59.
18. Hindriks, R., and van Putten, M. J. A. M. (2013). Thalamo-cortical mechanisms underlying changes in amplitude and frequency of human alpha oscillations. Neuroimage 70, 150-163. doi: 10.1016/j.neuroimage.2012.12.018.
19. Huang, C., Wahlund, L.-O., Dierks, T., Julin, P., Winblad, B., and Jelic, V. (2000). Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study. Clin. Neurophysiol. 111, 1961-1967. doi: 10.1016/S1388-2457(00)00454-5.
20. Hughes, S. W., and Crunelli, V. (2005). Thalamic mechanisms of EEG alpha rhythms and their pathological implications. Neuroscientist 11, 357-372. doi: 10.1177/1073858405277450.
21. Jasper, H., and Penfield, W. (1949). Zur Deutung des normalen Elektrencephalogramms und selner Veriinderungen. Electroeorticograms in man: effect of voluntary movement upon the electrical activity of the preeentral gyrus *. Arch. Psychiatr. Z. Neurol. 174, 163-174. doi: 10.1007/BF01062488.
22. Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., and Smith, S. M. (2012). FSL. Neuroimage 62, 782-790. doi: 10.1016/j.neuroimage.2011.09.015.
23. Lodder, S. S., and van Putten, M. J. A M. (2011). Automated EEG analysis: characterizing the posterior dominant rhythm. J. Neurosci. Methods 200, 86-93. doi: 10.1016/j.jneumeth.2011.06.008.
24. Lorincz, M. L., Kékesi, K. A., Juhász, G., Crunelli, V., and Hughes, S. W. (2009). Temporal framing of thalamic relay-mode firing by phasic inhibition during the alpha rhythm. Neuron 63, 683-696. doi: 10.1016/j.neuron.2009.08.012.
25. Maris, E., and Oostenveld, R. (2007). Nonparametric statistical testing of EEG-and MEG-data. J. Neurosci. Methods 164, 177-190. doi: 10.1016/j.jneumeth.2007.03.024.
26. Moretti, D. V., Fracassi, C., Pievani, M., Geroldi, C., Binetti, G., Zanetti, O., et al. (2009a). Increase of theta/gamma ratio is associated with memory impairment. Clin. Neurophysiol. 120, 295-303. doi: 10.1016/j.clinph.2008.11.012.
27. Moretti, D. V., Pievani, M., Fracassi, C., Binetti, G., Rosini, S., Geroldi, C., et al. (2009b). Increase of theta/gamma and alpha3/alpha2 ratio is associated with amygdalo-hippocampal complex atrophy. J. Alzheimers Dis. 17, 349-357. doi: 10.3233/JAD-2009-1059.
28. Moretti, D. V., Frisoni, G. B., Fracassi, C., Pievani, M., Geroldi, C., Binetti, G., et al. (2011). MCI patients' EEGs show group differences between those who progress and those who do not progress to AD. Neurobiol. Aging 32, 563-571. doi: 10.1016/j.neurobiolaging.2009.04.003.
29. Moretti, D. V., Paternicò, D., Binetti, G., Zanetti, O., and Frisoni, G. B. (2012). EEG markers are associated to gray matter changes in thalamus and basal ganglia in subjects with mild cognitive impairment. Neuroimage 60, 489-496. doi: 10.1016/j.neuroimage.2011.11.086.
30. Nolte, G. (2003). The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors. Phys. Med. Biol. 48, 3637-3652. doi: 10.1088/0031-9155/48/22/002.
31. Nunez, P. L., Wingeier, B. M., and Silberstein, R. B. (2001). Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of local networks. Hum. Brain Mapp. 13, 125-164. doi: 10.1002/hbm.1030.
32. Oostenveld, R., Fries, P., Maris, E., and Schoffelen, J.-M. (2011). FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 156869. doi: 10.1155/2011/156869.
33. Osipova, D., Ahveninen, J., Jensen, O., Ylikoski, A., and Pekkonen, E. (2005). Altered generation of spontaneous oscillations in Alzheimer's disease. Neuroimage 27, 835-841. doi: 10.1016/j.neuroimage.2005.05.011.
34. Osipova, D., Rantanen, K., Ahveninen, J., Ylikoski, R., Häppölä, O., Strandberg, T., et al. (2006). Source estimation of spontaneous MEG oscillations in mild cognitive impairment. Neurosci. Lett. 405, 57-61. doi: 10.1016/j.neulet.2006.06.045.
35. Passero, S., Rocchi, R., Vatti, G., Burgalassi, L., and Battistini, N. (1995). Quantitative EEG mapping, regional cerebral blood flow, and neuropsychological function in Alzheimer's disease. Dement. Geriatr. Cogn. Disord. 6, 148-156. doi: 10.1159/000106938.
36. Petersén, I., and Eeg-Olofsson, O. (2008). The development of the electroencephalogram in normal children from the age of 1 through 15 years-non-paroxysmal activity. Neuropediatrics 2, 247-304. doi: 10.1055/s-0028-1091786.
37. Petersen, R. C. (2001). Current concepts in mild cognitive impairment. Arch. Neurol. 58, 1985-1992. doi: 10.1001/archneur.58.12.1985.
38. Petersen, R. C., and Negash, S. (2008). Mild cognitive impairment: an overview. CNS Spectr. 13, 45-53. Available online at: http://www.ncbi.nlm.nih.gov/pubmed/18204414.
39. Prestia, A., Caroli, A., van der Flier, W. M., Ossenkoppele, R., Van Berckel, B., Barkhof, F., et al. (2013). Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease. Neurology 80, 1048-1056. doi: 10.1212/WNL.0b013e3182872830.
40. Reddy, P. H., and Beal, M. F. (2008). Amyloid beta, mitochondrial dysfunction and synaptic damage: implications for cognitive decline in aging and Alzheimer's disease. Trends Mol. Med. 14, 45-53. doi: 10.1016/j.molmed.2007.12.002.
41. Rosen, W. G., Terry, R. D., Fuld, P. A., Katzman, R., and Peck, A. (1980). Pathological verification of ischemic score in differentiation of dementias. Ann. Neurol. 7, 486-488. doi: 10.1002/ana.410070516.
42. Samson-Dollfus, D., Delapierre, G., Do Marcolino, C., and Blondeau, C. (1997). Normal and pathological changes in alpha rhythms. Int. J. Psychophysiol. 26, 395-409. doi: 10.1016/S0167-8760(97)00778-2.
43. Taulu, S., and Simola, J. (2006). Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements. Phys. Med. Biol. 51, 1759-1768. doi: 10.1088/0031-9155/51/7/008.
44. Van Veen, B. D., van Drongelen, W., Yuchtman, M., and Suzuki, A. (1997). Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans. Biomed. Eng. 44, 867-880. doi: 10.1109/10.623056.
45. Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M., et al. (1982). Development and validation of a geriatric depression screening scale: a preliminary report. J. Psychiatr. Res. 17, 37-49. doi: 10.1016/0022-3956(82)90033-4.