The DOI matches its Crossref record; 108 of the 108 references it cites were found in a registry or an index.
Sources of cortical rhythms in adults during physiological aging: A multicentric EEG study
Open accessAbstract
This electroencephalographic (EEG) study tested whether cortical EEG rhythms (especially delta and alpha) show a progressive increasing or decreasing trend across physiological aging. To this aim, we analyzed the type of correlation (linear and nonlinear) between cortical EEG rhythms and age. Resting eyes‐closed EEG data were recorded in 108 young (Nyoung; age range: 18–50 years, mean age 27.3 ± 7.3 SD) and 107 elderly (Nold; age range: 51–85 years, mean age 67.3 ± 9.2 SD) subjects. The EEG rhythms of interest were delta (2–4 Hz), theta (4–8 Hz), alpha 1 (8–10.5 Hz), alpha 2 (10.5–13 Hz), beta 1 (13–20 Hz), and beta 2 (20–30 Hz). EEG cortical sources were estimated by low‐resolution brain electromagnetic tomography (LORETA). Statistical results showed that delta sources in the occipital area had significantly less magnitude in Nold compared to Nyoung subjects. Similarly, alpha 1 and alpha 2 sources in the parietal, occipital, temporal, and limbic areas had significantly less magnitude in Nold compared to Nyoung subjects. These nine EEG sources were given as input for evaluating the type (linear, exponential, logarithmic, and power) of correlation with age. When subjects were considered as a single group there was a significant linear correlation of age with the magnitude of delta sources in the occipital area and of alpha 1 sources in occipital and limbic areas. The same was true for alpha 2 sources in the parietal, occipital, temporal, and limbic areas. In general, the EEG sources showing significant linear correlation with age also supported a nonlinear correlation with age. These results suggest that the occipital delta and posterior cortical alpha rhythms decrease in magnitude during physiological aging with both linear and nonlinear trends. In conclusion, this new methodological approach holds promise for the prediction of dementia in mild cognitive impairment by regional source rather than surface EEG data and by both linear and nonlinear predictors. Hum Brain Mapp, 2005. © 2005 Wiley‐Liss, Inc.
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Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Hirono, N., Mori, E., Ikejiri, Y., Imamura, T., Shimomura, T., Hashimoto, M., Yamashita, H., & Ikeda, M. (1997) · Brain and nerve · Cited by 21,012
Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589
Older Adults' Reasons for Using Technology while Aging in Place
Peek, S. T. M., Luijkx, K. G., Rijnaard, M. D., Nieboer, M. E., van der Voort, C. S., Aarts, S., van Hoof, J., Vrijhoef, H. J. M., & Wouters, E. J. M. (2016) · Gerontology · doi:10.1159/000430949 · Cited by 19,690
Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly
Kangas, M., Korpelainen, R., Vikman, I., Nyberg, L., & Jämsä, T. (2015) · Gerontology · doi:10.1159/000362720 · Cited by 18,909
Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living
Lawton, M. P., & Brody, E. M. (1969) · The Gerontologist · doi:10.1093/geront/9.3_part_1.179 · Cited by 18,540
Development and validation of a geriatric depression screening scale: a preliminary report
Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M., & Leirer, V. O. (1982) · Journal of Psychiatric Research · doi:10.1016/0022-3956(82)90033-4 · Cited by 15,025
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980
Cited by
BABILONI, C., FRISONI, G., PIEVANI, M., VECCHIO, F., LIZIO, R., BUTTIGLIONE, M., GEROLDI, C., FRACASSI, C., EUSEBI, F., & FERRI, R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.08.005 · Cited by 171
Self-citationBabiloni, C., Pievani, M., Vecchio, F., Geroldi, C., Eusebi, F., Fracassi, C., Fletcher, E., De Carli, C., Boccardi, M., Rossini, P. M., et al. (2009) · Human Brain Mapping · doi:10.1002/hbm.20612 · Cited by 75
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Metadata
- Authors
- Babiloni, C., Binetti, G., Cassarino, A., Dal Forno, G., Del Percio, C., Ferreri, F., Ferri, R., Frisoni, G., Galderisi, S., Hirata, K., Lanuzza, B., Miniussi, C., Mucci, A., Nobili, F., Rodriguez, G., Luca Romani, G., & Rossini, P. M.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2005-08-17
- Volume
- 27
- Issue
- 2
- Pages
- 162-172
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2077695508
- Cited by
- 314
- References
- 108
- FWCI
- 2.96
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Babiloni, C., Binetti, G., Cassarino, A., Dal Forno, G., Del Percio, C., Ferreri, F., Ferri, R., Frisoni, G., Galderisi, S., Hirata, K., Lanuzza, B., Miniussi, C., Mucci, A., Nobili, F., Rodriguez, G., Luca Romani, G., & Rossini, P. M. (2006). Sources of cortical rhythms in adults during physiological aging: A multicentric EEG study. Human Brain Mapping. https://doi.org/10.1002/hbm.20175
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