A Novel Measure Inspired by Lyapunov Exponents for the Characterization of Dynamics in State-Transition Networks.

The combination of network sciences, nonlinear dynamics and time series analysis provides novel insights and analogies between the different approaches to complex systems. By combining the considerations behind the Lyapunov exponent of dynamical systems and the average entropy of transition probabilities for Markov chains, we introduce a network measure for characterizing the dynamics on state-transition networks with special focus on differentiating between chaotic and cyclic modes. One important property of this Lyapunov measure consists of its non-monotonous dependence on the cylicity of the dynamics.

Infraslow oscillations in human sleep spindle activity.

Background: It has previously been reported that EEG sigma (10-15 Hz) activity during sleep exhibits infraslow oscillations (ISO) with a period of 50 s. However, a detailed analysis of the ISO of individually identified sleep spindles is not available.

New Method: We investigated basic properties of ISO during baseline sleep of 34 healthy young human participants using new and established methods.

Association of symptoms of insomnia and sleep parameters among kidney transplant recipients.

Objective: Insomnia complaints are frequent among kidney transplant (kTx) recipients and are associated with fatigue, depression, lower quality of life and increased morbidity. However, it is not known if subjective insomnia symptoms are associated with objective parameters of sleep architecture. Thus, we analyze the association between sleep macrostructure and EEG activity versus insomnia symptoms among kTx recipients.

Stochastic graph Voronoi tessellation reveals community structure.

Given a network, the statistical ensemble of its graph-Voronoi diagrams with randomly chosen cell centers exhibits properties convertible into information on the network's large scale structures. We define a node-pair level measure called Voronoi cohesion which describes the probability for sharing the same Voronoi cell, when randomly choosing g centers in the network. This measure provides information based on the global context (the network in its entirety), a type of information that is not carried by other similarity measures.

Slow wave sleep and accelerated forgetting.

We investigated whether the benefit of slow wave sleep (SWS) for memory consolidation typically observed in healthy individuals is disrupted in people with accelerated long-term forgetting (ALF) due to epilepsy. SWS is thought to play an active role in declarative memory in healthy individuals and, furthermore, electrographic epileptiform activity is often more prevalent during SWS than during wakefulness or other sleep stages. We studied the relationship between SWS and the benefit of sleep for memory retention using a word-pair associates task.

Sleep deficits but no metabolic deficits in premanifest Huntington's disease.

Objective: Huntington disease (HD) is a fatal autosomal dominant, neurodegenerative condition characterized by progressively worsening motor and nonmotor problems including cognitive and neuropsychiatric disturbances, along with sleep abnormalities and weight loss. However, it is not known whether sleep disturbances and metabolic abnormalities underlying the weight loss are present at a premanifest stage.

Methods: We performed a comprehensive sleep and metabolic study in 38 premanifest gene carrier individuals and 36 age- and sex-matched controls.

Circadian regulation of slow waves in human sleep: Topographical aspects.

Slow waves (SWs, 0.5-4Hz) in field potentials during sleep reflect synchronized alternations between bursts of action potentials and periods of membrane hyperpolarization of cortical neurons. SWs decline during sleep and this is thought to be related to a reduction of synaptic strength in cortical networks and to be central to sleep's role in maintaining brain function.

Reduced fronto-cortical brain connectivity during NREM sleep in Asperger syndrome: an EEG spectral and phase coherence study.

Objective: To investigate whether sleep macrostructure and EEG power spectral density and coherence during NREM sleep are different in Asperger syndrome (AS) compared to typically developing children and adolescents.

Methods: Standard all night EEG sleep parameters were obtained from 18 un-medicated subjects with AS and 14 controls (age range: 7.5-21.