On the structure of EEG development.
ABSTRACT Two different descriptions of EEG maturation are compared: a broad-band spectral parameters (BBSPs) model and a recently developed xi-alpha (xi alpha) model. 'Developmental equations' were obtained for both parameter sets using 1 min, eyes closed EEG sample from 165 normal children (5-12 years old). At each age, the xi alpha parameter set described the average spectrum more closely than the BBSP developmental equations. Furthermore, a more detailed picture of changes of spectral shape with age is possible with the xi alpha model. A computer simulation illustrates the possible appearance of fixed frequency bands as a byproduct of inadequate statistical models.
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- "Before the advent of modern computerized technologies, early developmental studies used laborious visual analysis for both longitudinal (Lindsley, 1938; Smith, 1938a; Smith, 1938b) and cross-sectional (Eeg-Olofsson, 1971; Petersen & Eeg-Olofsson, 1971) studies of children, adolescents , and adults (for a comprehensive review of these classic studies see Petersen, Sellden, & Eeg-Olofsson, 1975). These studies and later replications using computer-aided quantitative methods (e.g., Alvarez Amador et al., 1989; John, Prichep, Fridman, & Easton, 1988; Matousek & Petersen, 1973b; Petersen et al., 1975) revealed maturational trends across childhood that continued into adolescence . Few studies have focused specifically on adolescent EEG maturation (Eeg-Olofsson, 1971; Gasser, Jennen-Steinmetz, et al., 1988; Gasser, Verleger, Bacher, & Sroka, 1988), although characteristic patterns of spontaneous EEG activity over adolescent development have been reported in numerous studies spanning larger age ranges (Dustman et al., 1999; Henry, 1944; Matousek & Petersen, 1973a; Matousek & Petersen, 1973b; Matsuura et al., 1985; Petersen & Eeg-Olofsson, 1971; Petersen et al., 1975; Whitford et al., 2007). "
ABSTRACT: While psychological research has long shown that adolescence is a period of major cognitive and affective transition, recent neurophysiological research has shown that adolescence is also accompanied by observable maturational changes in the brain, both in terms of structure and neurotransmitter function. Given this situation, we would expect that there should be observable and perhaps major changes in electrocortical activity and responses. In this review, we discuss developmental reductions in EEG power and alterations in the dominant band of EEG oscillation frequency, moderated by developmental factors such as growth-related changes in grey and white matter, and in the developmental history of cognitive and sociocultural stressors. Similarly, we summarize alterations in event-related potential components reflecting stimulus processing, response monitoring, and response anticipation. We review the literature on such changes in EEG and event-related potentials during the adolescent period and summarize some of the new developments in the field as well as interpretative difficulties.Brain and Cognition 11/2009; 72(1):86-100. DOI:10.1016/j.bandc.2009.10.003 · 2.68 Impact Factor
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ABSTRACT: A new method for quantifying irregularity of EEGs is proposed in this study. The entropy, an information measure, determines the uniformity of proportion distribution. The peakedness or flatness of the distribution of the EEG power spectrum, representing EEG rhythmicity, can be measured by the entropy, because the power spectrum consists of proportions of power at each frequency. The irregularity of the EEG was measured by the entropy of the power spectrum, called an irregularity index (II). The II was obtained from the power spectrum at F3, F4, C3, C4, P3, P4, O1 and O2 during rest and mental arithmetic in 10 normal subjects. Relative band powers of delta, theta, alpha and beta bands and alpha peak frequency were also obtained. EEGs during rest were significantly more irregular anteriorly than in the occipital areas. Alpha activity was also more irregular in the anterior region. A greater degree of EEG desynchronization during mental arithmetic was found over the left hemisphere and the right occipital area. The II was more sensitive to such desynchronization than alpha band power and alpha peak frequency. The differences in spectral structures between rest and mental arithmetic conditions, mainly over the left hemisphere, were also confirmed by the Kullback-Leibler information.Electroencephalography and Clinical Neurophysiology 10/1991; 79(3):204-10. DOI:10.1016/0013-4694(91)90138-T
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ABSTRACT: High resolution spectral methods are explored as an alternative to broad band spectral parameters (BBSP) in quantitative EEG analysis. In a previous paper (Valdes et al. 1990b) regression equations ("Developmental surfaces") were introduced to characterize the age-frequency distribution of the mean and standard deviation of the log spectral EEG power in a normative sample. These normative surfaces allow the calculation of z transformed spectra for all derivations of the 10/20 system and z maps for each frequency. Clinical material is presented that illustrates how these procedures may pinpoint frequencies of abnormal brain activity and their topographic distribution, avoiding the frequency and spatial "smearing" that may occur using BBSP. The increased diagnostic accuracy of high resolution spectral methods is demonstrated by means of receiver operator characteristic (ROC) curve analysis. Procedures are introduced to avoid type I error inflation due to the use of more variables in this type of procedure.Brain Topography 02/1994; 6(3):211-9. DOI:10.1007/BF01187711 · 2.52 Impact Factor