title: Does EEG (visual and quantitative) reflect mental impairment in subcortical vascular dementia?
abstract: The aim of this study was to determine if the results of visual and quantitative EEG (QEEG) parameters reveal a correlation with mental impairment in subcortical vascular dementia (SVD), one of the most frequent causes of cognitive impairment in the elderly. In SVD, like in Alzheimer's disease disturbances were found in cholinergic transmission. The cholinergic deficit as manifested in changes of synaptic potentials is reflected in EEG signals.
  
  
  METHODS
  31 patients with probable SVD (according to NINCDS-AIREN and T. Erkinjuntii's criteria) and mean age 72.3 yrs;(M--43%, F--57%) and 14 healthy control subjects with mean age of 72.3 yrs (M-57%, F-43%). According to the Mini Mental Scale Examination (MMSE) the SVD group was divided into two subgroups with mild and moderate dementia, their EEGs being recorded with a Medelec and Neuroscan 4.2 system. Visual EEG findings were classified with the use of eight-degree scale of pathological changes by the presence of slow waves. Then QEEGs were made. The following parameters were calculated: alpha/slow wave power ratios, the mean wave frequency in all and in some selected derivations.
  
  
  RESULTS
  A significant difference was found between QEEGs in SVD subgroups with mild and moderate dementia (p<0.05), but there was no significant difference between visual EEGs. A significant correlation between QEEG parameters such as alpha/slow wave ratio or mean wave frequency and mental impairment (according to MMSE results) was found (p<0.001), but there was no significant correlation between degree of EEG abnormalities in visual analysis and MMSE results.
  
  
  CONCLUSIONS
  Only QEEGs are correlated with mental impairment in SVD. Visual EEG technique as a less precise tool does not reflect the mental impairment in SVD due to cholinergic deficit.
authors.affiliation: Department of Neurology, Medical University of Warsaw, Poland. mgawel@amwaw.edu.pl
authors.forename: M
authors.initials: M
authors.lastname: Gawel
authors.forename: E
authors.initials: E
authors.lastname: Zalewska
authors.forename: E
authors.initials: E
authors.lastname: Szmidt-Sałkowska
authors.forename: J
authors.initials: J
authors.lastname: Kowalski
mesh_terms: D000109:Acetylcholine / Q000172:deficiency; D000368:Aged; D000369:Aged, 80 and over; D020532:Basal Nucleus of Meynert / Q000378:metabolism / Q000473:pathology / Q000503:physiopathology; D003072:Cognition Disorders / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology; D015140:Dementia, Vascular / Q000175:diagnosis* / Q000503:physiopathology* / Q000523:psychology; D004185:Disability Evaluation; D018450:Disease Progression; D004569:Electroencephalography / Q000379:methods* / Q000592:standards; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000378:metabolism / Q000473:pathology; D019965:Neurocognitive Disorders / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology*; D009483:Neuropsychological Tests; D010775:Photic Stimulation; D011237:Predictive Value of Tests; D009435:Synaptic Transmission / Q000502:physiology; D013687:Telencephalon / Q000098:blood supply / Q000473:pathology / Q000503:physiopathology
chemical_list: D000109:Acetylcholine