Waldemar Szelenberger

Topographic analysis of coherence and propagation of EEG activity during sleep and wakefulness

Overnight sleep EEG recorded from 21 derivations was studied in 8 healthy subjects. The vector autoregressive model was fitted to all 21 channels simultaneously. Ordinary, multiple and partial coherences and directed transfer functions were estimated for sleep stages and wakefulness. Ordinary coherences give rather trivial information that coherence decreases with distance. Partial coherences revealed specific structure that was well repeatable for the subjects studied. Differences in coherence patterns between sleep stages were found by means of statistical tests. An increase of coherence was found for sleep stages 2, 3 and 4. Directed transfer function made possible the identification of the main centers from which EEG activity is spreading during sleep and wakefulness. During sleep the influence of subcortical structures was manifested by propagation of activity from the fronto-central region. The range of this interaction was highest in sleep stages 3 and 4. An EEG analysis, based on the approach of treating time series as a realization of one process and on the simultaneous (not pair-wise) evaluation of signals offers new possibilities in the investigation of synchronization and functional relations in the brain.

High resolution study of sleep spindles

OBJECTIVE Universal high-resolution time-frequency parameterization of sleep EEG structures. METHODS A new algorithm called Matching Pursuit was used for the decomposition of sleep EEG into waveforms chosen from a large and redundant set of functions. As a result all signal structures were parameterized in terms of their frequency, time occurrence, time span and energy. Slow wave activity and sleep spindles were identified according to neurophysiological criteria and various distributions describing their time evolution, topographical and frequency characteristics were constructed. RESULTS Two types of sleep spindles of different topological and spectral properties were identified. High time-frequency resolution made possible separation of superimposed spindles. Cross-correlation between high- and low-frequency components of superimposed spindles revealed a fixed time-delay between them, the high-frequency component preceding the low-frequency one. CONCLUSION The results of our study suggest that processes of generation of both types of sleep spindles are weakly coupled.

A simple system for detection of EEG artifacts in polysomnographic recordings

We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of experts decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

Cognitive functions in abstinent alcohol-dependent patients

The objective of this cross-sectional study was to compare cognitive functioning of abstaining alcohol-dependent (AD) male patients and healthy controls as well as to investigate whether their cognitive performance varied by abstinence length. Forty-two maintaining abstinent (AD) patients and 34 healthy controls were examined. Tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were used to assess cognitive functions. Differences in cognitive performance were found between AD patients and healthy controls. Nonverbal tasks in cognitive domains such as attention, visual memory and working memory were impaired in AD patients who presented deficits in visual episodic memory, had slower reaction time and reduced working memory span. Patients who were abstinent for less than one year made more errors in both attentional set shifting and working memory tests than healthy controls and patients with longer durations of abstinence. Impairments identified in multiple cognitive domains in abstinent alcohol-dependent subjects suggest functional deficits in extensive brain networks connecting interrelated brain structures. Attentional control and spatial working memory were less impaired in those AD patients who maintained abstinence for at least one year.

Sleepwalking and night terrors: Psychopathological and psychophysiological correlates

Sleepwalking and night terrors are considered to be manifestations of the same nosologic continuum. It has been proposed that a sudden arousal from non-rapid eye movement (NREM) sleep is the cause of these disorders. Benign forms of NREM arousal parasomnias occur frequently in childhood and attenuate in teen years; however, they can persist into or begin in adulthood. The available literature documents high levels of psychopathology in adult patients. Sleepwalking and night terrors are most likely to manifest during the first episode of slow wave sleep, but may also appear any time during NREM sleep. The hypersynchronous delta activity, previously considered to be a hallmark of somnambulism, has proven to be unspecific. Post-arousal EEG activity reveals altered consciousness during sleepwalking and sleep terror episodes. Pathophysiology of NREM arousal parasomnias consists of predisposing factors, which may be a genetically determined tendency for deep sleep, facilitating factors which deepen sleep and increase slow wave sleep, and triggering factors which increase sleep fragmentation, such as stress, environmental or endogenous stimuli, and stimulants. Recently published data on low delta power in the first sleep cycle and slow decline of delta power in successive sleep cycles suggest a chronic inability to sustain slow wave sleep.

Micro- and macrostructure of sleep EEG

Electroencephalogram (EEG) provides important and unique information about the sleeping brain. Polysomnography was the major method of sleep analysis and the main diagnostic tool in sleep medicine. The standard interpretation of polysomnographic recordings describes their macrostructure in terms of sleep stages, delineated according to R&K scoring criteria. Several descriptors of sleep microstructure rely on the quantification of sleep spindles and slow wave activities, detection of arousals, etc. However, these descriptors are usually assessed by means of substantially different signal processing (or visual) methods. This hinders possibilities of combining their results into a coherent description of the sleep process. This study proposes a solution to these problems in terms of a framework based upon adaptive time-frequency approximations - a recent, advanced method of signal processing. The proposed approach provides compatibility with the visual EEG analysis and standard definitions of EEG structures and describes both the macro- and microstructure of sleep EEG. Adaptive time-frequency approximations of signals calculated by means of the matching pursuit (MP) algorithm allow for the discrimination between series of unrelated structures and oscillatory activity. The detection, parametrization, and description of all these features of sleep are based upon the same unifying approach

Adaptive time–frequency parametrization in pharmaco EEG

Adaptive time-frequency approximations offer description of the local structures of a signal in terms of their time and frequency coordinates, widths and amplitudes. These parameters can then be used to select and study electroencephalogram (EEG) structures like sleep spindles or slow wave activity (SWA) with high resolution. Such a detailed description of relevant structures improves on the sensitivity of the traditionally used spectral power estimates and opens new possibilities of investigation. These advantages are illustrated using a double-blind test of the influence of zolpidem and midazolam on sleep EEG, and the results are compared with the traditional approach. The observed decrease of frequency of the SWA under the influence of sleep-inducing drugs gives an example of an effect elusive to classical methodology.

Age-dependent symptomatology of depression in hospitalized patients and its implications for DSM-5

BACKGROUND We investigated effects of current age and age at onset on symptomatology of depression with reference to proposed revisions in DSM-5. METHODS The study entailed medical records of 326 inpatients diagnosed with major depressive disorder, including 520 depressive episodes, with 113 first episodes lifetime. Subjects were divided into three groups: young-adults, middle-aged adults and older adults. RESULTS In young-adults, active suicidal ideation, lifetime suicidal attempts, irritability, anhedonia and persistent depressive symptoms between the episodes were more frequent than in the other groups. Among older adults, depression was associated with insomnia, hypochondriasis, somatization, decreased appetite, weight loss, memory impairment and decreased activity. The older age was not associated with higher number of previous episodes of depression, bigger severity or duration of a single episode or a different degree of remission. Early-onset depression was associated with more suicidal attempts. LIMITATIONS The study was retrospective and the sample may be treated only as representative for hospitalized depressed patients. CONCLUSIONS Age and age at onset are important factors influencing the course and symptomatology of a depressive episode. Depressive episodes with anxiety and with suicide risk severity are important specifiers that vary with the age at onset and/or age of the patient and should be considered for inclusion in the DSM-5 revision.

Characterization of insomnia in patients with essential hypertension.

Introduction. Insomnia may increase risk of cardiovascular events. There is little data available reporting the prevalence and clinical relevance of insomnia in patients with essential hypertension. Therefore, the aim of the study was to investigate the relationship between insomnia and different clinical and biochemical parameters in essential hypertension patients. Methods. Four hundred and thirty‐two patients (mean age: 47±13 years; 253 male, 179 female) with essential hypertension were screened for insomnia using the Athens Insomnia Scale (AIS). Several variables including age, sex, known duration of hypertension, body mass index, creatinine, left ventricular mass index, coexisting disorders, smoking status and alcohol use were analysed. Twenty‐four‐hour ambulatory blood pressure measurements (ABPM) were performed. Results. Among patients included in the study, 207 subjects (mean age: 49±13 years; 47.9%) had an AIS score of 15 or higher and were identified as insomniacs. Insomnia was more frequent in women than in men (60.9% vs 38.7%, p<0.001) and was reported more frequently in patients with coronary artery disease. Subjects with insomnia were older and had longer duration of hypertension. There were no differences between insomniacs and non‐insomniacs in ABPM parameters. A relationship was found between the number of antihypertensive drugs and insomnia frequency. There were correlations between AIS score and age (r = 0.21; p<0.001) and duration of hypertension (r = 0.22; p<0.001). In the sub‐group of untreated essential hypertension patients, there were negative correlations between AIS score and night fall in systolic and diastolic blood pressure. Conclusion. Our results showed that insomnia is common in patients with essential hypertension and indicate an association between insomnia and gender, known duration of hypertension and number of antihypertensive drugs taken. Untreated essential hypertension insomniacs were characterized by less pronounced nocturnal fall in both systolic and diastolic blood pressure compared with non‐insomniacs.

High resolution parametric description of slow wave sleep

We propose a new framework for quantitative analysis of sleep EEG, compatible with the traditional analysis, based upon adaptive time-frequency approximation of signals. Using a high resolution description of EEG rhythms and transients in terms of their time occurrence and width, frequency and amplitude, we present a detailed detection and parameterization of delta waves, including also the time occupied by each delta wave-a parameter inaccessible directly by previously applied signal processing methods. To validate the proposed parameterization, we construct a simple detector of sleep stages 3 and 4, based explicitly upon the classical criteria related to delta waves. To properly compare its performance to the inter-expert agreements and other expert systems, we sort out and discuss the methodology of reporting concordance in this context. Since the proposed parameterization proves to be compatible with the visual analysis of EEG, we can derive new variables for quantitative analysis of EEG patterns recognized for decades. As examples, we present a continuous description of delta waves and sleep spindles in the overnight sleep, and compare results to the traditional FFT-based estimates.