Gene expression oscillators can structure biological events temporally and spatially. Different biological functions benefit from distinct oscillator properties. Thus, finite developmental processes rely on oscillators that start and stop at specific times, a poorly understood behavior. Here, we have characterized a massive gene expression oscillator comprising > 3,700 genes in Caenorhabditis elegans larvae. We report that oscillations initiate in embryos, arrest transiently after hatching and in response to perturbation, and cease in adults. Experimental observation of the transitions between oscillatory and non-oscillatory states at high temporal resolution reveals an oscillator operating near a Saddle Node on Invariant Cycle (SNIC) bifurcation. These findings constrain the architecture and mathematical models that can represent this oscillator. They also reveal that oscillator arrests occur reproducibly in a specific phase. Since we find oscillations to be coupled to developmental processes, including molting, this characteristic of SNIC bifurcations endows the oscillator with the potential to halt larval development at defined intervals, and thereby execute a developmental checkpoint function.
Gene expression oscillators drive various repetitive biological processes. The architecture and properties of an oscillatory system can be inferred from the way it transitions, or bifurcates, between active (oscillatory) and quiescent (stable) states. Here, we have characterized the behavior of a developmental gene expression oscillator in C. elegans during naturally occurring and induced bifurcations. We observe a rigid oscillator that appears to operate near a Saddle Node on Invariant Cycle (SNIC) rather than a supercritical Hopf bifurcation, which yields specific system features. Developmental progression and the oscillation period are coupled, and the stable state of the system resembles a specific phase of the oscillator. This phase coincides with the time of transitions between different developmental stages, which are sensitive to nutrition. Hence, we speculate that the system's bifurcation may constitute a checkpoint for progression of C. elegans larval development.Gene expression oscillations occur in many other biological systems as exemplified by the circadian rhythms in metabolism and behavior (1), vertebrate somitogenesis (2), and plant lateral root branching (3), and have thus been of a long-standing interest to both experimentalists and theoreticians. A recently discovered 'C. elegans oscillator' (4, 5), i.e., a system of genes expressed in an oscillatory manner in larvae, differs from other gene expression oscillators in its unique combination of features (4, 5): an oscillation of thousands of genes is detectable at the whole animal level and occurs with large amplitudes and widely dispersed expression peak times (i.e., peak phases). It also lacks temperature-compensation such that the oscillation period increases as ambient temperature decreases. Thus, a better understanding of this oscillator can provide insights into a striking phenomenon of dynamic gene expression and may help to reveal potential common principles and idiosyncrasies of gene expression oscillators.As the properties of an oscillatory system are constrained by its architecture (6, 7), examination of oscillator behavior can be used to infer architecture and function. Relevant characteristic behaviors include a system's response to perturbations and the way it transitions, or bifurcates, between stable (quiescent) and oscillatory (active) states. However, for many biological oscillators, including those controlling somitogenesis and circadian rhythms, it has been difficult to access bifurcations.Here, we have surveyed C. elegans oscillator activity at high temporal resolution from embryogenesis to adulthood to observe naturally occurring and induced state transitions of the oscillator during development. This has enabled us to characterize the oscillator at a level where we can identify bifurcation points, and to probe the coupling of the oscillations with development.
An individual's brain functional organization is unique and can reliably be observed using modalities such as functional magnetic resonance imaging (fMRI). Here we demonstrate that a quantification of the dynamics of functional connectivity (FC) as measured using electroencephalography (EEG) offers an alternative means of observing an individual's brain functional organization. Using data from both healthy individuals as well as from patients with Parkinson's disease (PD) (n = 103 healthy individuals, n = 57 PD patients), we show that “dynamic FC” (DFC) profiles can be used to identify individuals in a large group. Furthermore, we show that DFC profiles predict gender and exhibit characteristics shared both among individuals as well as between both hemispheres. Furthermore, DFC profile characteristics are frequency band specific, indicating that they reflect distinct processes in the brain. Our empirically derived method of DFC demonstrates the potential of studying the dynamics of the functional organization of the brain using EEG.
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