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1

Waking EEG in primary insomnia

100%
Wolynczyk-Gmaj D., Szelenberger W.
Acta Neurobiologiae Experimentalis
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2011
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tom 71
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nr 3
Quantitative analysis of the waking EEG has been proposed as an objective method for measuring neurobehavioral impairment in primary insomnia. Thirty six patients with DSM-IV primary insomnia diagnosis (mean age 36 years) and 29 controls, matched for age and education, participated in the study. Waking EEG from 21 scalp electrodes was subjected to spectral analyses using a fast Fourier transform algorithm. Significantly lower values of power in the theta range and higher values of beta power were found in insomniacs as compared to control subjects. This theta power decrease in patients suffering from insomnia was not uniform throughout the brain, but it was pronounced in prefrontal derivations. Lower values of theta power correlated negatively and higher values of beta power correlated postively with Hyperarousal Scale score. Results of the research presented here support the notion of twenty-four hour hyperarousal in primary insomnia. Attenuated theta and enhanced beta power can be electrophysiological correlates of dysfunctional arousal in insomnia. Less waking theta power in insomniacs suggests a decrease in homeostatic sleep propensity.
2

EEG source activity during processing of neutral stimuli in subjects with anxiety disorders

51%
Gmaj B., Januszko P., Kaminski J., Drozdowicz E., Kopera M., Wolynczyk-Gmaj D., Szelenberger W., Wojnar M.
Acta Neurobiologiae Experimentalis
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2016
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tom 76
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nr 1
Anxiety disorders are a social problem due to their prevalence and consequences. It is crucial to explore the influence of anxiety on cognitive processes. In this study we recorded EEG activity from 73 subjects (35 patients, 38 controls, matched for age and education) during performance of the Continuous Attention Task. We used low resolution electromagnetic tomography (LORETA) for evaluation of mechanisms of impaired cognitive performance in anxiety disorders. Analysis showed that patients with anxiety disorders committed more errors than the controls, had a short latency of P300 and higher amplitude of ERPs at all steps of stimulus processing. Furthermore, we showed that there was a relationship between the scores of Hamilton Anxiety Scale and Beck Depression Inventory, and amplitudes and latencies of ERPs. The results of LORETA analysis showed that enhanced neural responses were found within circuits mediating visual information processing, sustained attention and anxiety. Also, we found higher current density within areas playing an important role in the brain fear network – anterior cingulate and anterior part of insula. Electrophysiological neuroimaging showed greater recruitment of cognitive resources in anxiety disorders, evidenced by higher current density and activation of greater number of brain areas. Despite the strategy employed to compensate for cognitive problems, the anxiety patients did not achieve the same performance as controls. Present study demonstrates that anxiety disorders influence processing of neutral stimuli and this influence is observable at both behavioral and electrophysiological level. The data suggests instability of neural systems responsible for information selection, working memory, engagement and focusing of attention.
3

Narcolepsy type 1 and hypersomnia associated with a psychiatric disorder show different slow wave activity dynamics

51%
Walacik-Ufnal E., Piotrowska A. J., Wolynczyk-Gmaj D., Januszko P., Gmaj B., Ufnal M., Kabat M., Wojnar M.
Acta Neurobiologiae Experimentalis
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2017
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tom 77
|
nr 2
The aim of the study was to compare electrophysiological parameters of night sleep in narcolepsy type 1 and hypersomnia associated with a psychiatric disorder. Forty-four patients: 15 with narcolepsy type 1, 14 with hypersomnia associated with a psychiatric disorder and 15 age- and sex-matched controls participated in the study. The study subjects filled in the Athens Insomnia Scale (AIS) and the Beck Depression Inventory (BDI). The severity of daytime sleepiness was quantified subjectively using the Epworth Sleepiness Scale (ESS) and the Stanford Sleepiness Scale (SSS), and objectively using the Multiple Sleep Latency Test (MSLT). All subjects underwent polysomnography (PSG) on the two consecutive nights. The data from the second night was analysed. The slow wave activity (SWA, 1–4 Hz) was calculated for the three consecutive sleep cycles, and topographic delta power maps were plotted. In contrast to narcoleptics, psychiatric hypersomniacs had undisturbed nocturnal sleep, high sleep efficiency, normal non-rapid eye movement (NREM) and rapid eye movement (REM) sleep proportions, normal REM latency and sleep latencies on MSLT and PSG. The subjective and objective sleepiness was significantly higher in narcolepsy group than in psychiatric hypersomnia group. In all the study groups SWA was the most prominent in frontal areas, while the greatest between-group differences were found in the central areas. There were significant differences between the groups in SWA in the second NREM episode. The highest SWA was observed in the hypersomnia group, while the lowest in the narcolepsy group. Psychiatric hypersomniacs and controls did not differ in the SWA exponential decline over consecutive NREM episodes, whereas narcoleptics exhibited a steeper dissipation of sleep pressure from the first to the second NREM episode. In conclusion, narcolepsy type1 and hypersomnia associated with psychiatric disorder differ in the SWA dynamics. Narcoleptics presented with the altered dynamics of sleep homeostasis, whereas psychiatric hypersomniacs showed normal nocturnal sleep and normal sleep homeostasis.
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