Multivariate assessment of linear and non-linear causal coupling pathways within the central-autonomic-network in patients suffering from schizophrenia

Im Bereich der Zeitreihenanalyse richtet sich das Interesse zunehmend darauf, wie Einblicke in die Interaktions- und Regulationsprozesse von pathophysiologischen- und physiologischen Zuständen erlangt werden können. Neuste Fortschritte in der nichtlinearen Dynamik, der Informationstheorie und der Netzwerktheorie liefern dabei fundiertes Wissen über Kopplungswege innerhalb (patho)physiologischer (Sub)Systeme. Kopplungsanalysen zielen darauf ab, ein besseres Verständnis dafür zu erlangen, wie die verschiedenen integrierten regulatorischen (Sub)Systeme mit ihren komplexen Strukturen und Regulationsmechanismen das globale Verhalten und die unterschiedlichen physiologischen Funktionen auf der Ebene des Organismus beschreiben. Insbesondere die Erfassung und Quantifizierung der Kopplungsstärke und -richtung sind wesentliche Aspekte für ein detaillierteres Verständnis physiologischer Regulationsprozesse. Ziel dieser Arbeit war die Charakterisierung kurzfristiger unmittelbarer zentral-autonomer Kopplungspfade (top-to-bottom und bottom to top) durch die Kopplungsanalysen der Herzfrequenz, des systolischen Blutdrucks, der Atmung und zentraler Aktivität (EEG) bei schizophrenen Patienten und Gesunden. Dafür wurden in dieser Arbeit neue multivariate kausale und nicht-kausale, lineare und nicht-lineare Kopplungsanalyseverfahren (HRJSD, mHRJSD, NSTPDC) entwickelt, die in der Lage sind, die Kopplungsstärke und -richtung, sowie deterministische regulatorische Kopplungsmuster innerhalb des zentralen-autonomen Netzwerks zu quantifizieren und zu klassifizieren. Diese Kopplungsanalyseverfahren haben ihre eigenen Besonderheiten, die sie einzigartig machen, auch im Vergleich zu etablierten Kopplungsverfahren. Sie erweitern das Spektrum neuartiger Kopplungsansätze für die Biosignalanalyse und tragen auf ihre Weise zur Gewinnung detaillierter Informationen und damit zu einer verbesserten Diagnostik/Therapie bei. Die Hauptergebnisse dieser Arbeit zeigen signifikant schwächere nichtlineare zentral-kardiovaskuläre und zentral-kardiorespiratorische Kopplungswege und einen signifikant stärkeren linearen zentralen Informationsfluss in Richtung des Herzkreislaufsystems auf, sowie einen signifikant stärkeren linearen respiratorischen Informationsfluss in Richtung des zentralen Nervensystems in der Schizophrenie im Vergleich zu Gesunden. Die detaillierten Erkenntnisse darüber, wie die verschiedenen zentral-autonomen Netzwerke mit paranoider Schizophrenie assoziiert sind, können zu einem besseren Verständnis darüber führen, wie zentrale Aktivierung und autonome Reaktionen und/oder Aktivierung in physiologischen Netzwerken unter pathophysiologischen Bedingungen zusammenhängen.In the field of time series analysis, increasing interest focuses on insights gained how the coupling pathways of regulatory mechanisms work in healthy and ill states. Recent advances in non-linear dynamics, information theory and network theory lead to a new sophisticated body of knowledge about coupling pathways within (patho)physiological (sub)systems. Coupling analyses aim to provide a better understanding of how the different integrated physiological (sub)systems, with their complex structures and regulatory mechanisms, describe the global behaviour and distinct physiological functions at the organism level. In particular, the detection and quantification of the coupling strength and direction are important aspects for a more detailed understanding of physiological regulatory processes. This thesis aimed to characterize short-term instantaneous central-autonomic-network coupling pathways (top-to-bottom and bottom to top) by analysing the coupling of heart rate, systolic blood pressure, respiration and central activity (EEG) in schizophrenic patients and healthy participants. Therefore, new multivariate causal and non-causal linear and non-linear coupling approaches (HRJSD, mHRJSD, NSTPDC) that are able to determine the coupling strength and direction were developed. Whereby, the HRJSD and mHRJSD approaches allow the quantification and classification of deterministic regulatory coupling patterns within and between the cardiovascular- the cardiorespiratory system and the central-autonomic-network were developed. These coupling approaches have their own unique features, even as compared to well-established coupling approaches. They expand the spectrum of novel coupling approaches for biosignal analysis and thus contribute in their own way to detailed information obtained, and thereby contribute to improved diagnostics/therapy. The main findings of this thesis revealed significantly weaker non-linear central-cardiovascular and central-cardiorespiratory coupling pathways, and significantly stronger linear central information flow in the direction of the cardiac- and vascular system, and a significantly stronger linear respiratory information transfer towards the central nervous system in schizophrenia in comparison to healthy participants. This thesis provides an enhanced understanding of the interrelationship of central and autonomic regulatory mechanisms in schizophrenia. The detailed findings on how variously-pronounced, central-autonomic-network pathways are associated with paranoid schizophrenia may enable a better understanding on how central activation and autonomic responses and/or activation are connected in physiology networks under pathophysiological conditions

Aerospace Medicine and Biology, a continuing bibliography with indexes

This bibliography lists 365 reports, articles and other documents introduced into the NASA scientific and technical information system in October 1984

A Study on Clinical Profile of Non Traumatic Coma Patients and Correlation of their Prognosis based on Electroencephalogram

BACKGROUND: Coma is an eye closed state of unresponsiveness with severely impaired arousal & cognition. EEG plays a role in establishing the prognosis of the disease states that are capable of causing neuronal death which is frequently underused in acute setting. AIMS AND OBJECTIVES: To assess the clinical profile of non traumatic coma patients and their EEG patterns & correlate it with outcome of the patient. MATERIALS AND METHODOLOGY: Detailed clinical examination & EEG was taken to 50 patients who satisfy our inclusion & exclusion criteria at admission in TMCH casualty. Results analyzed and statistical analysis done by SPSS software. RESULTS: Most common etiology of coma in our study is CVA (38%) followed by metabolic coma. Mortality rate is high in coma secondary to CVA (40.9%) and HIE (23%) where as less in metabolic coma. Alpha coma is the most common EEG pattern (72%) encountered in our study. Other coma like theta and delta are also seen but not specific to particular etiology. CONCLUSION: Apart from late hospitalization, initial poor GCS, presence of neuro-ophthalmological signs; poor outcome can be also predicted by theta and delta coma which has statistically significant high mortality(53.6%). Yet it is solely difficult to prognosticate the patient based on EEG alone, it can be used as a adjunct in many conditions

Physiological and psychological responses of patients with chronic fatigue syndrome to regular physical activity

Physiological and psychological responses of patients with chronic fatigue syndrome to regular physical activit

Advances in Clinical Neurophysiology

Including some of the newest advances in the field of neurophysiology, this book can be considered as one of the treasures that interested scientists would like to collect. It discusses many disciplines of clinical neurophysiology that are, currently, crucial in the practice as they explain methods and findings of techniques that help to improve diagnosis and to ensure better treatment. While trying to rely on evidence-based facts, this book presents some new ideas to be applied and tested in the clinical practice. Advances in Clinical Neurophysiology is important not only for the neurophysiologists but also for clinicians interested or working in wide range of specialties such as neurology, neurosurgery, intensive care units, pediatrics and so on. Generally, this book is written and designed to all those involved in, interpreting or requesting neurophysiologic tests

Physiological time-series investigations of cardiovascular regulation in healthy young adults during physical exercise.

Physiological parameters may be recorded non-invasively to gain information on cardiovascular function which can then characterise populations with various pathologies. Physical exercise produces specific autonomic nervous system (ANS) changes. There has been no comprehensive profiling of cardiovascular function during exercise or simultaneous characterisation of the influence of exercise on cardiac ventricular function and electrical activity. This work aims to address that, using a combination of physiological parameters. Between-lead agreement for ambulatory electrocardiographic (EGG) depolarisation-repolarisation (QT) interval was quantified during rest and exercise. In contrast to cardiac interval (RR) data, between-lead bias and limits of agreement for QT interval data should be quantified when reporting results from an ambulatory EGG system and between-gender QT differences should also be accounted for. EGG electrode location appears to significantly affect QT-RR hysteresis, the shortening of the post-exercise QT interval relative to that at similar heart rates during exercise or pre-exercise rest, further emphasising the need for standardisation of EGG electrode placement. Sample entropy (SampEn) measures data complexity. Few studies have compared SampEn of RR data (SampEn-RR) during exercise, whilst none have examined SampEn for the corresponding QT interval (SampEn-QT). Fractal analysis assesses data correlation and scaling structures. Detrended fluctuation analysis (DFA) provides a scaling exponent (a) which describes these properties. This has not been quantified for RR interval data during post-exercise recovery and has not been reported for QT interval data. Differences in a magnitudes for RR and QT data suggest that these quantities have different fractal properties. Exercise perturbs the resting QT-RR relationship via hysteresis. The QT variability index (QTVI) quantifies the relative autonomic influence on the atrial and ventricular myocardium during rest and exercise. QTVI is a consistent measure of cardiac ventricular function and as such appears to be a more useful index than other parameters based on RR or QT interval alone