Equipped with its 302-cell nervous system, the nematode Caenorhabditis elegans adapts its locomotion in different environments, exhibiting so-called swimming in liquids and crawling on dense gels. Recent experiments have demonstrated that the worm displays the full range of intermediate behaviors when placed in intermediate environments. The continuous nature of this transition strongly suggests that these behaviors all stem from modulation of a single underlying mechanism. We present a model of C. elegans forward locomotion that includes a neuromuscular control system that relies on a sensory feedback mechanism to generate undulations and is integrated with a physical model of the body and environment. We find that the model reproduces the entire swim-crawl transition, as well as locomotion in complex and heterogeneous environments. This is achieved with no modulatory mechanism, except via the proprioceptive response to the physical environment. Manipulations of the model are used to dissect the proposed pattern generation mechanism and its modulation. The model suggests a possible role for GABAergic D-class neurons in forward locomotion and makes a number of experimental predictions, in particular with respect to non-linearities in the model and to symmetry breaking between the neuromuscular systems on the ventral and dorsal sides of the body.

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We measured the long term spontaneous electrical activity of neuronal networks with different sizes, grown on lithographically prepared substrates and recorded with multi-electrode-array technology. The time sequences of synchronized bursting events were used to characterize network dynamics. All networks exhibit scale-invariant Lévy distributions and long-range correlations. These observations suggest that different-size networks self-organize to adjust their activities over many time scales. As predictions of current models differ from our observations, this calls for revised models.

SUMMARY Little is known about how animals integrate multiple sensory inputs in natural environments to balance avoidance of danger with approach to things of value. Furthermore, the mechanistic link between internal physiological state and threat-reward decision making remains poorly understood. Here we confronted C. elegans worms with the decision whether to cross a hyperosmotic barrier presenting the threat of desiccation to reach a source of food odor. We identified a specific interneuron that controls this decision via top-down extrasynaptic aminergic potentiation of the primary osmosensory neurons to increase their sensitivity to the barrier. We also establish that food deprivation increases the worm’s willingness to cross the dangerous barrier by suppressing this pathway. These studies reveal a potentially general neural circuit architecture for internal state control of threat-reward decision making.

Transcription is a vital stage in the process of gene expression and a major contributor to fluctuations in gene expression levels for which it is typically modeled as a single-step process with Poisson statistics. However, recent single molecule experiments raise questions about the validity of such a simple single-step picture. We present a molecular multistep model of transcription elongation that demonstrates that transcription times are in general non-Poisson-distributed. In particular, we model transcriptional pauses due to backtracking of the RNA polymerase as a first passage process. By including such pauses, we obtain a broad, heavy-tailed distribution of transcription elongation times, which can be significantly longer than would be otherwise. When transcriptional pauses result in long transcription times, we demonstrate that this naturally leads to bursts of mRNA production and non-Poisson statistics of mRNA levels. These results suggest that transcriptional pauses may be a significant contributor to the variability in transcription rates with direct implications for noise in cellular processes as well as variability between cells.