[Spectral analysis of the electroencephalogram in subjects with mild cognitive impairment]. / Análisis espectral del electroencefalogramaen sujetos con deterioro cognitivo leve.

INTRODUCTION: Mild cognitive impairment (MCI) is defined as a state of the ageing brain midway between normal cognition and dementia. Special attention has been paid to the electrophysiological substrate underlying Alzheimer's disease and MCI in order to identify as early as possible which subjects with MCI progress towards Alzheimer, which could be crucial for starting rehabilitation or pharmacological therapies. AIM: To perform a spectral characterisation of the electroencephalogram in subjects with MCI. PATIENTS AND METHODS: An electroencephalogram was carried out on 41 subjects with MCI in order to analyse the spectral measurements; apolipoprotein E genotype was also performed. RESULTS: In all, 94.8% of the sample displayed a significant increase in energy, and in 66.6% of them this was observed in the theta and delta bands, or both. Significant differences were found in the spectral measurements between carriers and non-carriers of the apolipoprotein E epsilon4 allele in the theta and alpha bands; there was also a statistically significant association between the years of schooling and being a carrier of this allele or not. An increase in the theta-alpha bands was observed in the left temporal region in subjects with a below-average number of years of schooling and carriers of the epsilon4 allele. CONCLUSIONS: In subjects with MCI and carriers of the epsilon4 allele, the alpha and theta cortical rhythms can be affected by similar pathological mechanisms and may be expressed earlier in subjects who have a lower level of schooling.

[Spectral analysis of the electroencephalogram in children with systemic lupus erythematosus]. / Análisis espectral del electroencefalograma en niños con lupus eritematoso sistémico.

INTRODUCTION: Systemic lupus erythematosus (SLE) is an autoimmune disease that affects different systems and organs, including the central nervous system (CNS). It has been suggested that about 40% of the cases of neuropsychiatric lupus (NPSLE) develop before SLE is diagnosed or at the same time it is being carried out, and 63% appear during the first year following diagnosis. AIMS: The aim of this study was to check the hypothesis that the electroencephalogram (EEG) may be sensitive to the damage to the CNS in children with SLE in whom there is still no clinical evidence of NPSLE. PATIENTS AND METHODS: EEG recordings were performed in 30 children with a diagnosis of SLE with or without signs of a neuropsychiatric syndrome. The results of the EEG were evaluated visually and analysed quantitatively. RESULTS: The visual inspection of the EEG showed the presence of alterations in 44.5% of the children with SLE and in 76.9% of those with NPSLE. There were significant differences in Student's t test (p = 0.0055) between the two groups for the analysis of the broadband spectral measurements. The narrow band analysis revealed a significant increase in the theta and delta frequencies in children with SLE as compared to standard values, whereas in children with NPSLE significant differences were found in the fast bands in frontal regions. CONCLUSIONS: Spectral analysis of the narrow band could help to confirm diagnoses of NPSLE, while anomalies in the slow bands could be an early marker of damage to the CNS although there are still no symptoms of the disease.

On the structure of EEG development.

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.

Multivariate Box-Cox transformations with applications to neurometric data.

The Box-Cox power transform methodology for achieving Gaussianity is developed for a variety of models useful in neurometric statistical analysis. Algorithms are proposed for estimating the optimal transformations in the univariate and multivariate cases. Their use is briefly illustrated with neurometric data.

A parametric model for multichannel EEG spectra.

The EEG is modelled as the superposition of two component processes: the xi and the alpha processes. In the frequency domain, the xi process is always present and appears as a spectral peak with maximum amplitude at very low frequencies, while the alpha process is characterized by a spectral peak with its maximum located in the traditional alpha band (7-13 Hz), and is not necessarily always present. The multivariate properties of EEG spectra are adequately modelled with frequency independent coherence matrices for each process. Multichannel EEG studies reveal interesting properties: (1) the generalized coherence for alpha is much larger than for xi, indicating increased functional coupling for the alpha process; (2) the alpha coherence matrix has reduced dimensionality, possibly related to a small number of generators; (3) xi coherences are zero phase with magnitudes that decrease exponentially with interelectrode distance; and (4) alpha coherences have significant nonzero phase shifts.