Neurophysiological imaging techniques in dementia

Research output: Contribution to journalArticlepeer-review

Abstract

Neurophysiological methods, such as electroencephalography (EEG) and event-related potentials, are useful tools in the investigation of brain cognitive function in normal and pathological conditions, with an excellent time resolution when compared to that of other functional imaging techniques. Advanced techniques using a high number of EEG channels also enable a good spatial resolution to be achieved. This, together with the possibility of integration with other anatomical and functional images, may increase the ability to localize brain functions. Spectral analysis of the resting EEG, which gives information on the integrity of the cortical and subcortical networks involved in the generation of cortical rhythms, has the limitation of low sensitivity and specificity for the type of cognitive impairment. In almost all types of dementia, decreased power of the high frequencies is indeed observed in mild stages, accompanied by increased power of the slow rhythms in the more advanced phases. The sensitivity for the detection of spectral abnormalities is improved by studying centroid modifications. More specific information on the type of dementia can be provided by coherence analysis of the resting EEG, a measure of functional cortico-cortical connections, which has different abnormal patterns in Alzheimer's disease, cerebrovascular dementia and dementia associated with multiple sclerosis. Another tool for improving the assessment of demented patients is the study of EEG activity related to particular tasks, such as event-related potentials and event-related desynchronization/synchronization of the EEG, which allow the study of brain activation during cognitive and motor tasks.

Original languageEnglish
JournalItalian Journal of Neurological Sciences
Volume20
Issue number5 SUPPL.
Publication statusPublished - 1999

ASJC Scopus subject areas

  • Dermatology
  • Clinical Neurology
  • Psychiatry and Mental health
  • Neuroscience(all)

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