1 Introduction
5
find that, the greater the malignancy of the cells, the more they tend to exhibit glycolytic oscillations and the higher the frequency becomes.
In Chap. 16, Jacobsen and Aalkjaer provide a brief review of vasomotion. These
are oscillations that occur in the tone or diameter of arteries and lead to the phenomenon of flowmotion, where the flow of blood into tissue occurs in an oscillatory
manner. They discuss the mechanisms and how these can be studied. The authors
hypothesise that vasomotion is beneficial because it ensures more efficient delivery
of oxygen and removal of waste products, but point out that there is still a need for
confirmatory experimental evidence. Chapter 17, by Colantuoni and Lapi provides
another succinct review of research on vasomotion, but from an historical perspective,
focusing on the seminal contributions made by their own research group.
The next two chapters relate to oscillations observed in skin blood flow. Chapter 18
by Tankanag et al. describes an investigation of paced and depth-controlled respiration in which they measured the phase coherence between skin blood flow oscillations
at the pacing frequency in the left and right index fingers. They find that pacing the
respiration results in a significant increase in phase coherence compared to spontaneous respiration. They attribute these results to the effect of the autonomic nervous
system on vascular tone regulation under controlled breathing. In Chap. 19, Thanaj et
al. review non-linear complexity-based approaches to the analysis of microvascular
blood flow oscillations, with a particular focus on the extent to which they are able
to identify changes in microvascular function. They conclude that, although such
approaches have utility in understanding the fundamental mechanistic contributors
to microvascular (dys)function, it has yet to be demonstrated that they can usefully
discriminate between different (patho)physiological states in order to inform treatment regimens or to predict clinical outcomes.
Chapter 20, by Penzel et al., examines the changes in cardiovascular and electroencephalograph (EEG) oscillations that take place during sleep. The autonomous
nervous system is regulated in totally different ways during slow-wave (non-REM)
and REM sleep, so that analysis of instantaneous heart-rate variations allows for automatic scoring of sleep stages. The authors also find it possible, to some extent, to
track transitions from wakefulness to sleep solely by analysis of heart-rate variations.
ECG and heart rate analysis allow assessment of sleep disorders as well.
The final chapter in Part III, Chap. 21 by Vuksanovi´ c, reviews current knowledge
of the modular properties of brain networks, as derived from in vivo neuroimaging of
cortical morphology (e.g. thickness, surface area), and their relationship to function.
The focus is on the cross-level and cross-modal organisational units of the brain, and
the relationships to their modular topology. Recent approaches in network science
enable the formation of bridges across different scales and properties, and suggest
that cross-modal neuroimaging and analysis may provide a tool for understanding
brain disorders at the system level.
5
find that, the greater the malignancy of the cells, the more they tend to exhibit glycolytic oscillations and the higher the frequency becomes.
In Chap. 16, Jacobsen and Aalkjaer provide a brief review of vasomotion. These
are oscillations that occur in the tone or diameter of arteries and lead to the phenomenon of flowmotion, where the flow of blood into tissue occurs in an oscillatory
manner. They discuss the mechanisms and how these can be studied. The authors
hypothesise that vasomotion is beneficial because it ensures more efficient delivery
of oxygen and removal of waste products, but point out that there is still a need for
confirmatory experimental evidence. Chapter 17, by Colantuoni and Lapi provides
another succinct review of research on vasomotion, but from an historical perspective,
focusing on the seminal contributions made by their own research group.
The next two chapters relate to oscillations observed in skin blood flow. Chapter 18
by Tankanag et al. describes an investigation of paced and depth-controlled respiration in which they measured the phase coherence between skin blood flow oscillations
at the pacing frequency in the left and right index fingers. They find that pacing the
respiration results in a significant increase in phase coherence compared to spontaneous respiration. They attribute these results to the effect of the autonomic nervous
system on vascular tone regulation under controlled breathing. In Chap. 19, Thanaj et
al. review non-linear complexity-based approaches to the analysis of microvascular
blood flow oscillations, with a particular focus on the extent to which they are able
to identify changes in microvascular function. They conclude that, although such
approaches have utility in understanding the fundamental mechanistic contributors
to microvascular (dys)function, it has yet to be demonstrated that they can usefully
discriminate between different (patho)physiological states in order to inform treatment regimens or to predict clinical outcomes.
Chapter 20, by Penzel et al., examines the changes in cardiovascular and electroencephalograph (EEG) oscillations that take place during sleep. The autonomous
nervous system is regulated in totally different ways during slow-wave (non-REM)
and REM sleep, so that analysis of instantaneous heart-rate variations allows for automatic scoring of sleep stages. The authors also find it possible, to some extent, to
track transitions from wakefulness to sleep solely by analysis of heart-rate variations.
ECG and heart rate analysis allow assessment of sleep disorders as well.
The final chapter in Part III, Chap. 21 by Vuksanovi´ c, reviews current knowledge
of the modular properties of brain networks, as derived from in vivo neuroimaging of
cortical morphology (e.g. thickness, surface area), and their relationship to function.
The focus is on the cross-level and cross-modal organisational units of the brain, and
the relationships to their modular topology. Recent approaches in network science
enable the formation of bridges across different scales and properties, and suggest
that cross-modal neuroimaging and analysis may provide a tool for understanding
brain disorders at the system level.