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C. elegans episodic swimming is driven by multifractal kinetics.

ABSTRACT: Fractal scaling is a common property of temporal change in various modes of animal behavior. The molecular mechanisms of fractal scaling in animal behaviors remain largely unexplored. The nematode C. elegans alternates between swimming and resting states in a liquid solution. Here, we report that C. elegans episodic swimming is characterized by scale-free kinetics with long-range temporal correlation and local temporal clusterization, namely consistent with multifractal kinetics. Residence times in actively-moving and inactive states were distributed in a power law-based scale-free manner. Multifractal analysis showed that temporal correlation and temporal clusterization were distinct between the actively-moving state and the inactive state. These results indicate that C. elegans episodic swimming is driven by transition between two behavioral states, in which each of two transition kinetics follows distinct multifractal kinetics. We found that a conserved behavioral modulator, cyclic GMP dependent kinase (PKG) may regulate the multifractal kinetics underlying an animal behavior. Our combinatorial analysis approach involving molecular genetics and kinetics provides a platform for the molecular dissection of the fractal nature of physiological and behavioral phenomena.

SUBMITTER: Ikeda Y

PROVIDER: S-EPMC7478975 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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C. elegans episodic swimming is driven by multifractal kinetics.

Ikeda Yusaku Y Jurica Peter P Kimura Hiroshi H Takagi Hiroaki H Struzik Zbigniew R ZR Kiyono Ken K Arata Yukinobu Y Sako Yasushi Y

Scientific reports 20200908 1

Fractal scaling is a common property of temporal change in various modes of animal behavior. The molecular mechanisms of fractal scaling in animal behaviors remain largely unexplored. The nematode C. elegans alternates between swimming and resting states in a liquid solution. Here, we report that C. elegans episodic swimming is characterized by scale-free kinetics with long-range temporal correlation and local temporal clusterization, namely consistent with multifractal kinetics. Residence times ...[more]

PMID: 32901071

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Project description:Physiological processes-such as, the brain's resting-state electrical activity or hemodynamic fluctuations-exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF). The first approach (moment-wise scaling range adaptivity) allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD) is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS), electroencephalography (EEG), and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD). The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the ? and ? bands, suggesting an independent generator for the multifractal ? rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal fMRI-BOLD imaging data for the topology of multifractal metrics free of the masking effect of the underlying random noise.

Project description:Animals optimize survival and reproduction in part through control of behavioral states, which depend on an organism's internal and external environments. In the nematode Caenorhabditis elegans a variety of behavioral states have been described, including roaming, dwelling, quiescence, and episodic swimming. These states have been considered in isolation under varied experimental conditions, making it difficult to establish a unified picture of how they are regulated. Using long-term imaging, we examined C. elegans episodic behavioral states under varied mechanical and nutritional environments. We found that animals alternate between high-activity (active) and low-activity (sedentary) episodes in any mechanical environment, while the incidence of episodes and their behavioral composition depend on food levels. During active episodes, worms primarily roam, as characterized by continuous whole body movement. During sedentary episodes, animals exhibit dwelling (slower movements confined to the anterior half of the body) and quiescence (a complete lack of movement). Roaming, dwelling, and quiescent states are manifest not only through locomotory characteristics but also in pharyngeal pumping (feeding) and in egg-laying behaviors. Next, we analyzed the genetic basis of behavioral states. We found that modulation of behavioral states depends on neuropeptides and insulin-like signaling in the nervous system. Sensory neurons and the Foraging homolog EGL-4 regulate behavior through control of active/sedentary episodes. Optogenetic stimulation of dopaminergic and serotonergic neurons induced dwelling, implicating dopamine as a dwell-promoting neurotransmitter. Our findings provide a more unified description of behavioral states and suggest that perception of nutrition is a conserved mechanism for regulating animal behavior.NEW & NOTEWORTHY One strategy by which animals adapt to their internal states and external environments is by adopting behavioral states. The roundworm Caenorhabditis elegans is an attractive model for investigating how behavioral states are genetically and neuronally controlled. Here we describe the hierarchical organization of behavioral states characterized by locomotory activity, feeding, and egg-laying. We show that decisions to engage in these behaviors are controlled by the nervous system through insulin-like signaling and the perception of food.

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C. elegans episodic swimming is driven by multifractal kinetics.

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C. elegans episodic swimming is driven by multifractal kinetics.

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