Scalp electric potentials (electroencephalogram; EEG) are contingent to the impressed current density unleashed by cortical pyramidal neurons undergoing post-synaptic processes. EEG neuroimaging consists of estimating the cortical current density from scalp recordings. We report a solution to this inverse problem that attains exact localization: exact low-resolution brain electromagnetic tomography (eLORETA). This non-invasive method yields high time-resolution intracranial signals that can be used for assessing functional dynamic connectivity in the brain, quantified by coherence and phase synchronization. However, these measures are non-physiologically high because of volume conduction and low spatial resolution. We present a new method to solve this problem by decomposing them into instantaneous and lagged components, with the lagged part having almost pure physiological origin.

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Huntington's disease (HD) is a devastating neurodegenerative disorder with prominent motor and cognitive decline. Previous studies with small sample sizes and methodological limitations have described abnormal electroencephalograms (EEG) in this cohort. The aim of the present study was to investigate objectively and quantitatively the neurophysiological basis of the disease in HD patients as compared to normal controls, utilizing EEG mapping. In 55 HD patients and 55 healthy controls, a 3-min vigilance-controlled EEG (V-EEG) was recorded during midmorning hours. Evaluation of 36 EEG variables was carried out by spectral analysis and visualized by EEG mapping techniques. To elucidate drug interference, the analysis was performed for the total group, unmedicated patients only and between treated and untreated patients. Statistical overall analysis by the omnibus significance test demonstrated significant (p < 0.01 and p < 0.05) EEG differences between HD patients and controls. Subsequent univariate analysis revealed a general decrease in total power and absolute alpha and beta power, an increase in delta/theta power, and a slowing of the centroids of delta/theta, beta and total power. The slowing of the EEG in HD reflects a disturbed brain function in the sense of a vigilance decrement, electrophysiologically characterized by inhibited cortical areas (increased delta/theta power) and a lack of normal routine and excitatory activity (decreased alpha and beta power). The results are similar to those found in other dementing disorders. Medication did not affect the overall interpretation of the quantitative EEG analysis, but certain differences might be due to drug interaction, predominantly with antipsychotics. Spearman rank correlations revealed significant correlations between EEG mapping and cognitive and motor impairment in HD patients.

Previous studies have shown abnormal electroencephalography (EEG) in Huntington's disease (HD). The aim of the present investigation was to compare quantitatively analyzed EEGs of HD patients and controls by means of low-resolution brain electromagnetic tomography (LORETA). Further aims were to delineate the sensitivity and utility of EEG LORETA in the progression of HD, and to correlate parameters of cognitive and motor impairment with neurophysiological variables. In 55 HD patients and 55 controls a 3-min vigilance-controlled EEG (V-EEG) was recorded during midmorning hours. Power spectra and intracortical tomography were computed by LORETA in seven frequency bands and compared between groups. Spearman rank correlations were based on V-EEG and psychometric data. Statistical overall analysis by means of the omnibus significance test demonstrated significant (p < 0.01) differences between HD patients and controls. LORETA theta, alpha and beta power were decreased from early to late stages of the disease. Only advanced disease stages showed a significant increase in delta power, mainly in the right orbitofrontal cortex. Correlation analyses revealed that a decrease of alpha and theta power correlated significantly with increasing cognitive and motor decline. LORETA proved to be a sensitive instrument for detecting progressive electrophysiological changes in HD. Reduced alpha power seems to be a trait marker of HD, whereas increased prefrontal delta power seems to reflect worsening of the disease. Motor function and cognitive function deteriorate together with a decrease in alpha and theta power. This data set, so far the largest in HD research, helps to elucidate remaining uncertainties about electrophysiological abnormalities in HD.