Skip to main content

Aging and Degenerative Disorders

  • Chapter
Clinical Electroencephalography

Abstract

Cerebral aging is associated with characteristic changes of main EEG patterns recorded during wakefulness and sleep. They include a slowing of posterior dominant rhythm, the reduction of beta activity, and the appearance of theta-delta activities particularly over left and temporal regions. With the exception of frontotemporal dementia, there is usually a good correlation between the degree of cognitive impairment in dementia syndromes and the EEG changes. In multi-infarct dementia, the presence of focal and/or epileptiform discharges depends on the location and size of infarcts. In Parkinson’s disease the EEG changes are usually nonspecific.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Babiloni C, Del Percio C, Buján A. EEG in dementing disorders. In: Schomer DL, Lopes da Silva F, editors. Niedermeyer’s electroencephalography: basic principles, clinical applications, and related fields. 7th ed. New York, NY: Oxford University Press; 2018. p. 413–32.

    Google Scholar 

  2. Hubbard O, Sunde D, Goldensohn ES. The EEG in centenarians. Electroencephalogr Clin Neurophysiol. 1976;40:407–17.

    Article  CAS  Google Scholar 

  3. Giaquinto S, Nolfe G. The EEG in the normal elderly: a contribution to the interpretation of aging and dementia. Electroencephalogr Clin Neurophysiol. 1986;63:540–6.

    Article  CAS  Google Scholar 

  4. Brenner RP, Ulrich RF, Reinolds CF. EEG spectral analysis in healthy, elderly men and women: sex differences. Electroencephalogr Clin Neurophysiol. 1995;94:1–5.

    Article  CAS  Google Scholar 

  5. Widdess-Walsh P, Sweeney BJ, Galvin R, McNamara B. Utilization and yield of EEG in the elderly population. J Clin Neurophysiol. 2005;22:253–5.

    Article  Google Scholar 

  6. Kipervasser S, Neufeld MY. Video-EEG monitoring of paroxysmal events in the elderly. Acta Neurol Scand. 2007;116:221–5.

    Article  CAS  Google Scholar 

  7. Bottaro FJ, Martinez OA, Fernandez Pardal MM, et al. Nonconvulsive status epilepticus in the elderly: a case-control study. Epilepsia. 2007;48:966–72.

    Article  CAS  Google Scholar 

  8. Huang C, Wahlund L, Dierks T, Julin P, Winblad B, Jelic V. Discrimination of Alzheimer’s disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study. Clin Neurophysiol. 2000;111:1961–7.

    Article  CAS  Google Scholar 

  9. Van der Hiele K, Vein AA, van der Welle A, et al. EEG and MRI correlates of mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging. 2007;28:1322–9.

    Article  Google Scholar 

  10. Van der Hiele K, Vein AA, Reijntjes RHAM, et al. EEG correlates in the spectrum of cognitive decline. Clin Neurophysiol. 2007;118:1931–9.

    Article  Google Scholar 

  11. Jelles B, Scheltens PH, van der Flier WM, et al. Global dynamical analysis of the EEG in Alzheimer’s disease: frequency-specific changes of functional interactions. Clin Neurophysiol. 2008;119:837–41.

    Article  CAS  Google Scholar 

  12. Horvath A, Szucs A, Csukly G, Sakovics A, Stefanics G, Kamondi A. EEG and ERP biomarkers of Alzheimer’s disease: a critical review. Front Biosci (Landmark Ed). 2018;23:183–220.

    Article  Google Scholar 

  13. Van der Hiele K, Bollen ELEM, Vein AA, et al. EEG markers of future cognitive performance in the elderly. J Clin Neurophysiol. 2008;25:83–9.

    Article  Google Scholar 

  14. Cromarty RA, Elder GJ, Graziadio S, et al. Neurophysiological biomarkers for Lewy body dementias. Clin Neurophysiol. 2016;127:349–59.

    Article  Google Scholar 

  15. Calzetti S, Bortone E, Negrotti A, Zinno L, Mancia D. Frontal intermittent rhythmic delta activity (FIRDA) in patients with dementia with Lewy bodies: a diagnostic tool? Neurol Sci. 2002;23(Suppl 2):S65–6.

    Article  Google Scholar 

  16. Yener GG, Leuchter AF, Jenden D, Read SL, Cummings JL, Miller BL. Quantitative EEG in frontotemporal dementia. Clin Electroencephalogr. 1996;27:61–8.

    Article  CAS  Google Scholar 

  17. Malek N, Baker MR, Mann C, Greene J. Electroencephalographic markers in dementia. Acta Neurol Scand. 2017;135:388–93.

    Article  CAS  Google Scholar 

  18. Erkinjuntti T, Larsen T, Sulkava R, Ketonen L, Laaksonen R, Palo J. EEG in the differential diagnosis between Alzheimer’s disease and vascular dementia. Acta Neurol Scand. 1988;77:36–43.

    Article  CAS  Google Scholar 

  19. Cozac VV, Gschwandtner U, Hatz F, Hardmeier M, Rüegg S, Fuhr P. Quantitative EEG and cognitive decline in Parkinson’s disease. Parkinsons Dis. 2016;2016:9060649.

    PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Cite this chapter

Brigo, F., Mecarelli, O. (2019). Aging and Degenerative Disorders. In: Mecarelli, O. (eds) Clinical Electroencephalography. Springer, Cham. https://doi.org/10.1007/978-3-030-04573-9_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-04573-9_41

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04572-2

  • Online ISBN: 978-3-030-04573-9

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics