We report comparison and assessment of the clinical utility of different automated methods for the estimation of the alpha frequency in electroencephalograph (EEG) and compare them with visual evaluation. A total of 56 consecutive patients, aged 17 to 78 years, who had a routine EEG recording, were included, and they were grouped as patients with epilepsy (Ep) and without epilepsy (nEp). Five different methods were used for alpha frequency estimation: visually guided manual counting and visually guided Fourier transform, and 3 methods were fully automated: time domain estimation of alpha (automatic assessment of alpha waves in time domain [ATD]) and 2 fast Fourier transform (FFT)-based methods, a segmented (automatic assessment of EEG segments by FFT) and one full FFT (automatic assessment of whole EEG by one FFT of the full recording [AWF]). The AWF discriminated significantly between Ep and nEp. Visually guided manual counting showed an almost significant difference independently in the 2 occipital electrodes. The ATD underestimated high frequencies and returned a too low mean frequency. This study shows that AWF is the best suited method for automatic assessment of the alpha frequency.
GloorP. The work of Hans Berger. Electroencephalogr Clin Neurophysiol. 1969;27(7):649.
2.
BergerH. Über das Elektroenkephalogramm des Menschen. Arch Psychiatr Nervenkr. 1929;87:527-570.
3.
DeuschlGEisenA.Recommendations for the Practice of Clinical Neurophysiology: Guidelines of the International Federation of Clinical Neurophysiology. Amsterdam, Elsevier Science Health Science Division; 1999.
4.
AndersenPAnderssonSALomoT. Nature of thalamo-cortical relations during spontaneous barbiturate spindle activity. J Physiol. 1967;192(2):283-307.
5.
AndersenPAnderssonSA. Physiological Basis of the Alpha Rhythm. New York, NY: Appleton-Century-Crofts; 1968.
6.
Lopes da SilvaFStorm van LeeuwenW. The cortical source of the alpha rhythm. Neurosci Lett. 1977;35(6):237-241.
7.
NunezPLReidLBickfordRG. The relationship of head size to alpha frequency with implications to a brain wave model. Electroencephalogr Clin Neurophysiol1978;44(3):344-352.
8.
NunezPL. Generation of human EEG by a combination of long and short range neocortical interactions. Brain Topogr. 1989;1(3):199-215.
9.
NunezPL. Toward a quantitative description of large-scale neocortical dynamic function and EEG. Behav Brain Sci. 2000;23(3):371-398.
10.
NunezPLSrinivasanR. A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness. Clin Neurophysiol. 2006;117(11):2424-2435.
11.
KoprunerVPfurtschellerGAuerLM. Quantitative EEG in normals and in patients with cerebral ischemia. Prog Brain Res. 1984;62:29-50.
12.
Eeg-OlofssonO. The development of the electroencephalogram in normal adolescents from the age of 16 through 21 years. Neuropadiatrie.1971;3(1):11-45.
13.
NiedermeyerE. The normal EEG of the waking adult. In: NiedermeyerEda SilvaFHL, eds. Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. Philadelphia, PA: Lippincott Williams & Wilkins; 2005:167-192.
14.
RayWJColeHW. EEG activity during cognitive processing: influence of attentional factors. Int J Psychophysiol. 1985;3(1):43-48.
15.
ColeHWRayWJ. EEG correlates of emotional tasks related to attentional demands. Int J Psychophysiol. 1985;3(1):33-41.
16.
RayWJColeHW. EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes. Science. 1985;228(4700):750-752.
17.
CooperNRCroftRJDomineySJBurgessAPGruzelierJH. Paradox lost? Exploring the role of alpha oscillations during externally vs. internally directed attention and the implications for idling and inhibition hypotheses. Int J Psychophysiol. 2003;47(1):65-74.
18.
CanteroJLAtienzaMGómezCMSalasRM. Spectral structure and brain mapping of human alpha activities in different arousal states. Neuropsychobiology. 1999;39(2):110-116.
19.
BrazierMABFinesingerESchwabRS. Characteristics of the normal electroencephalogram. II. The effect of varying blood sugar levels on the occipital cortical potentials in adults during quiet breathing. J Clin Invest. 1944;23(3):313-317.
KlimeschW. EEG-alpha rhythms and memory processes. Intl J Psychophysiology. 1997;26(1-3):319-340.
22.
KlimeschWDoppelmayrMWimmerH. Alpha and beta band power changes in normal and dyslexic children. Clin Neurophysiol. 2001;112(7):1186-1195.
23.
HanslmayrSSausengPDoppelmayrMSchabusMKlimeschW. Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Appl Psychophys Biof. 2005;30(1):1-10.
24.
ThutGNietzelABrandtAPascual-LeoneA. Alpha-band electroencephalographic activity over occipital cortex indexes visuospatial attention bias and predicts visual target detection. J Neurosci. 2006;26(37):9494-9502.
25.
PetscheHKaplanSvon SteinAFilzO. The possible meaning of the upper and lower alpha frequency ranges for cognitive and creative tasks. Int J Psychophysiol. 1997;26(1-3):77-97.
LarssonPGKostovH. Lower frequency variability in the alpha activity in EEG among patients with epilepsy. Clin Neurophysiol. 2005;116(11):2701-2706.
28.
FrostJDJrHrachovyRAGlazeDGRettigGM. Alpha rhythm slowing during initiation of carbamazepine therapy: implications for future cognitive performance. J Clin Neurophysiol. 1995;12(1):57-63.
29.
ClemensBMenesAPirosP. Quantitative EEG effects of carbamazepine, oxcarbazepine, valproate, lamotrigine, and possible clinical relevance of the findings. Epilepsy Res. 2006;70(2-3):190-199.
30.
SalinskyMStorzbachDOkenBSpencerD. Topiramate effects on the EEG and alertness in healthy volunteers: a different profile of antiepileptic drug neurotoxicity. Epilepsy Behav. 2007;10(3):463-469.
31.
SalinskyMCOkenBSMoreheadL. Intraindividual analysis of antiepileptic drug effects on EEG background rhythms. Electroencephalogr Clin Neurophysiol. 1994;90(3):186-193.
32.
SalinskyMCBinderLMOkenBSStorzbachDAronCRDodrillCB. Effects of gabapentin and carbamazepine on the EEG and cognition in healthy volunteers. Epilepsia. 2002;43(5):482-490.
33.
HelkalaELHanninenTHallikainenM. Slow-wave activity in the spectral analysis of the electroencephalogram and volumes of hippocampus in subgroups of Alzheimer's disease patients. Behav Neurosci. 1996;110(6):1235-1243.
34.
PenttilaMPartanenJVSoininenHRiekkinenPJ. Quantitative analysis of occipital EEG in different stages of Alzheimer's disease. Electroencephalogr Clin Neurophysiol. 1985;60(1):1-6.
35.
SoininenHPartanenVJHelkalaELRiekkinenPJ. EEG findings in senile dementia and normal aging. Acta Neurol Scand. 1982;65(1):59-70.
36.
GeletyTJBurgessRJDrakeMEJrFordCEBrownME. Computerized spectral analysis of the interictal EEG in epilepsy. Clin Electroencphalogr. 1985;16(2):94-97.
37.
RasmussenDD. Physiological interactions of the basic rest-activity cycle of the brain: pulsatile luteinizing hormone secretion as a model. Psychoneuroendocrinology. 1986;11(4):389-405.
38.
BarnaLCKoivuluomaMMicheloyannisSZervakisMVärriA.Spectral features of the EEG are unlikely to differentiate between normal and epileptic children. Biopattern Brain. 2006:9.
