No description available.

Restless legs syndrome (RLS) is a sensory-motor disorder characterized by abnormal circadian rhythm with an increase in the severity of sensory and motor symptoms at night. Even though many neurological diseases have shown a strong nexus between motor and cognitive symptoms, to date, cognitive functions especially cognitive control in RLS has been poorly understood. Given that cognitive control is a key to leading a self-serving and successful life, including many aspects of employment, social life, and attaining long-term goals, this thesis aimed to examine cognitive control and the underlying mechanisms in RLS. Thalamic gamma aminobutyric acid (GABA), which has been linked to RLS sensory-motor symptoms, also plays an important role in cognitive control. Therefore, the potential relationship between thalamic GABA level and cognitive control in RLS was examined (Study I). RLS patients displayed reduced working memory-based control performances as compared to healthy controls. Elevated thalamic GABA was found to attenuate the observed control deficits in RLS, even though changes in thalamic GABA levels might not be the ultimate causes of these deficits. According to the modulatory effect of thalamic GABA on thalamic activity and thalamo-cortical connectivity, relatively higher GABA levels may have helped RLS patients compensate for their pathological changes such as thalamic hyperactivity and hypoconnectivity, which may underpin the observed control deficits. The critical feature of RLS, abnormal circadian rhythm is thought to be related to nocturnal striatal dopamine deficiency. Concerning the dopaminergic modulation of cognitive control, the circadian variation of cognitive control processes has been investigated (Study II & III). RLS patients displayed reduced attentional control (Study II) and automatic response activation (Study III) at night, which resulted from decreased activation within the extra-striate visual cortex, the superior parietal cortex, and the premotor cortex. As there were no activity changes within the prefrontal cortex, it is likely that cortico-basal ganglia cognitive loops were less prone to RLS. Instead, striatal dopamine deficiency at night may have influenced the cortico-cortical functional connectivity and cortico-basal ganglia motor loops in RLS. These findings not only shed light on the underlying mechanisms of cognitive control, but also advance early clinical treatment possibilities for cognitive changes in RLS patients. Furthermore, recent insights into daytime-related cognition may help patients develop a suitable daytime schedule to minimize the detrimental effects induced by cognitive deficits.

Menschliche Systeme werden seit einiger Zeit modelliert und analysiert auf der Basis der Theorie komplexer Netzwerke. Dies erlaubt es quantitativ zu untersuchen, welche strukturellen und zeitlichen Merkmale eines Systems Ausbreitungsprozesse beeinflussen, z.B. von Informationen oder von Infektionskrankheiten. Im ersten Teil der Arbeit wird untersucht, wie eine modular-hierarchische Struktur von statischen Netzwerken eine schnelle Verbreitung von Signalen ermöglicht. Es werden neue Heuristiken entwickelt um die Random-Walk-Observablen “First Passage Time” und “Cover Time” auf lokal geclusterten Netzwerken zu ermitteln. Vergleiche mit der Approximation eines gemittelten Mediums zeigen, dass das Auftreten der beobachteten Minima der Observablen ein reiner Netzwerkeffekt ist. Es wird weiterhin dargelegt, dass nicht alle modular-hierarchischen Netzwerkmodelle dieses Phänomen aufweisen. Im zweiten Teil werden zeitlich veränderliche face-to-face Kontaktnetzwerke auf ihre Anfälligkeit für Infektionskrankheiten untersucht. Mehrere Studien belegen, dass Menschen vornehmlich Zeit in Isolation oder kleinen, stark verbundenen Gruppen verbringen, und dass ihre Kontaktaktivität einem zirkadianen Rhythmus folgt. Inwieweit diese beiden Merkmale die Ausbreitung von Krankheiten beeinflussen, ist noch unklar. Basierend auf einem neuen Modell wird erstmals gezeigt, dass zirkadian variierende Netzwerke Trajektorien folgen in einem Zustandsraum mit einer strukturellen und einer zeitlichen Dimension. Weiterhin wird dargelegt, dass mit zunehmender Annäherung der zeitlichen Dimension von System und Krankheit die systemische Infektionsanfälligkeit sinkt. Dies steht in direktem Widerspruch zu Ergebnissen anderer Studien, die eine zunehmende Anfälligkeit vorhersagen, eine Diskrepanz, die auf die Ungültigkeit einer weit verbreiteten Approximation zurückzuführen ist. Die hier vorgestellten Ergebnisse implizieren, dass auf dem Gebiet die Entwicklung neuer theoretischer Methoden notwendig ist. / Human systems have been modeled and analyzed on the basis of complex networks theory in recent time. This abstraction allows for thorough quantitative analyses to investigate which structural and temporal features of a system influence the evolution of spreading processes, such as the passage of information or of infectious diseases. The first part of this work investigates how the ubiquitous modular hierarchical structure of static real-world networks allows for fast delivery of messages. New heuristics are developed to evaluate random walk mean first passage times and cover times on locally clustered networks. A comparison to average medium approximations shows that the emergence of these minima are pure network phenomena. It is further found that not all modular hierarchical network models provide optimal message delivery structure. In the second part, temporally varying face-to-face contact networks are investigated for their susceptibility to infection. Several studies have shown that people tend to spend time in small, densely-connected groups or in isolation, and that their connection behavior follows a circadian rhythm. To what extent both of these features influence the spread of diseases is as yet unclear. Therefore, a new temporal network model is devised here. Based on this model, circadially varying networks can for the first time be interpreted as following trajectories through a newly defined systemic state space. It is further revealed that in many temporally varying networks the system becomes less susceptible to infection when the time-scale of the disease approaches the time-scale of the network variation. This is in direct conflict with findings of other studies that predict increasing susceptibility of temporal networks, a discrepancy which is attributed to the invalidity of a widely applied approximation. The results presented here imply that new theoretical advances are necessary to study the spread of diseases in temporally varying networks.