Quantitative EEG analysis : Temporal variability and clinical applications
Abstract: The quantification of the EEG power (qEEG) in different frequency bands, and their spatial distribution improve the sensitivity of the technique, although questions have been raised about the reproducibility of the results. The aim of the present work was to study the reproducibility of some quantitative parameters in clinical routine EEG, and their clinical application in the study of patients with type I diabetes. Paper I is a study of the variability of EEG power spectrum, considering its time course in resting conditions, and the relationship between the spectral parameters and the length of the analysed segments. Recordings were performed in 57 normal subjects, with a protocol consisting of regular cycles with open eyes (5 s) followed by closed eyes (55 s) repeated during 15 min. The power spectrum showed a systematic decrease in alpha and beta power and increase in delta and theta power, both within the closed eyes periods and over the entire recordings. The coefficient of variation (CV) for the power of 4 s epochs was in the range 0.49-0.67 (delta), 0.53-0.58 (theta), 0.58-0.76 (alpha), 0.37-0.49 (beta) and 0.09-0.12 for die alpha peak frequency. CV decreased proportionally to the square root of the sample size. Increasing the recording length from 40 to 400 s increased CV by 36% (alpha), 41 % (beta), 29% (delta) and 35% (theta), while the standard error of the mean decreased by 55-60%. In conclusion, the EEG power estimates are heavily dependent on the length of the analyzed segments, and the way they are selected. This observation is particularly relevant for clinical and drug studies where short parts of the recordings are often used, which may lead to a bias in the estimation of the EEG parameters. The present data provide an estimate on the minimal length of EEG required for a given level of variability. In Paper II a clinical study applying the aforementioned protocol was performed on patients with type I diabetes. The aim of this study was to identify whether adolescents with type I diabetes receiving modem multiple insulin injection therapy (MIT) have abnormal EEGs, and to elucidate possible correlations with a history of severe hypoglycaemia, poor metabolic control and nerve conduction defects. Thirty-five patients (age 14-19 years) with disease duration 7.6±4.6 years, and 45 healthy control subjects were investigated. The EEGs of the patients showed an increased slow activity (delta and theta) and a reduction in alpha peak frequency, both of which were most pronounced in the frontal regions (p<0.001). They also showed a decrease in fast activity, most pronounced bilaterally in the posterior temporal regions (alpha p<0.001, beta p<0.01, gamma p<0.001). A history of severe hypoglycaemia was correlated with a global increase in theta activity (p<0.01-0.05). Poor metabolic control, measured as acute and long-term HbA1c levels, was correlated with an increase in delta power and a decrease in alpha peak frequency. The decrease in fast activity in the temporal regions was not correlated with any of the studied clinical parameters. It is concluded that recurrent severe hypoglycaemia and poor metabolic control are risk factors for EEG abnormalities in adolescents with type I diabetes receiving MIT treatment. In addition, we found pronounced abnormalities in the temporal regions that were not related to these risk factors.
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