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Event-related current density in primary insomnia

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EN
Using Low Resolution Electromagnetic Tomography (LORETA), event-related current density was investigated in 14 patients with primary insomnia and 14 controls matched for age, gender and education level. All subjects were rated on the Athens Insomnia Scale, the Hyperarousal Scale, the Hamilton Depression Rating Scale and the Beck Depression Inventory. They also completed the Selective Reminding Test and the Continuous Attention Test. Only minor elevations on depression scales were found in patients. The Continuous Attention Test did not reveal any between group differences. However, insomniacs required more trials before all the Selective Reminding Test items were learned. Insomniacs showed less event-related current density in orbitofrontal, medial prefrontal and anterior cingulate cortex, i.e. brain regions of relevance for cognition and affect. Earliest group differences appeared in the P1 time range and then were observed at the N1, N2 and P3 stages of stimulus processing. These stimulus processing differences correlated most consistently with severity of insomnia. Neuropsychological impairment correlated most strongly with less current density in Brodmann area 10.
EN
Overnight sleep EEG recorded from 21 derivtions was studied for 7 subjects (4 normal and 3 depressive).The multichannel autoregressive model was fitted to all 21 channels simultaneously.Ordinary, multiple and partial coherencies and directed trransfer function were estimated for sleep stages and wakefulness.Ordinary coherencies give rather trivial information that coherence decreases with the distance.Partial coherencies reveales specific structure to a large repeatable for studied subjects.Study of directed transfer function made possible the identification of main centres from which EEG activity is spreading during sleep.An EEG analysis, based on treating signals as a realization of one process and on simultaneous (not pair-wise) evolution of time series, offers new possibilities in the investigation of synchronization and functonal relations in brains.
EN
To investigate how partial sleep loss affects temporal and spatial pattern of information flow, we analyzed sources of brain electrical activity during continuous attention test. Sixteen physicians recruited from the university hospitals participated in the study. Each participant served as his own control. All participants underwent two test sessions including the Stanford Sleepiness Scale (SSS), the Beck Depression Inventory (BDI), the Selective Reminding Test (SRT), and the Continuous Attention Test (CAT). The CAT items were used as stimuli in event-related potential (ERP) recordings. EEG was recorded from 21 electrodes, according to the international 10-20 system. The sources of bioelectrical activity were computed with low resolution electromagnetic tomography (LORETA). Estimated sleep time was significantly shorter on nights spent on duty than on nights of normal sleep at home. Sleep loss resulted in significant increase in SSS and BDI scoring, and impairment of immediate recall. Performance on the CAT remained relatively intact. Under the sleep loss condition compared to baseline, significant differences in brain activity occurred only for targets. Within the P1 time frame, sleep loss led to greater activation in the right Brodmann's area 9/10. For the N1 component, significant differences were localized on the lateral surface of the right frontal lobe, in Brodmann's areas 8 and 9. No significant effects of sleep deprivation on the P3 component were found. Our results are consistent with earlier data indicating that increased activation of the prefrontal cortex allows the maintainance of performance during periods of sleep loss.
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Analysis of complexity of EEG during sleep

71%
EN
New multichannel descriptors of EEG activity: complexity (Omega), total power (Sigma) and generalized frequency (Phi) were applied to whole night sleep analysis in 11 healthy subjects. The values of Omega and Phi decreased systematically from waking to slow wave sleep, and increased systematically in consecutive NREM-REM sleep cycles. The changes of Sigma were opposite to Omega and Phi. These descriptors may be an alternative approach to the EEG sleep analysis.
6
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Interhemispheric differences of sleep EEG complexity

71%
EN
Complexity of EEG (W), a global measure reflecting degree of spatial synchronization, was computed for whole night recordings of sleep EEG of 10 healthy volunteers, 9 males and 1 female (age 21-53) and 6 depressive patients, 5 males and 1 female (age 23-64). Sleep was scored visually in 20's epochs, W was calculated in 2.5 s segments and the median from 8 segments (20 s) was calculated. W was calculated for the whole field of 21 electrodes and for the left and right hemisphere separately (2 x 8 electrodes). Measure of global power (S) and generalized frequency (f) were also computed for the same data. In healthy subjects the complexity was higher over the right hemisphere during waking, and the difference shifted to higher complexity over the left hemisphere in slow wave sleep (F=5.15, df1=4, df2=6856, P<0.0005). The opposite trend was found in depressives (F=10.51, dfl=4, df2=3960, P<0.0001).
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