During navigation, animals process temporal sequences of sensory inputs to evaluate the surrounding environment. Thermotaxis of Caenorhabditis elegans is a favorable sensory behavior to elucidate how navigating animals process sensory signals from the environment. Sensation and storage of temperature information by a bilaterally symmetric pair of thermosensory neurons, AFD, is essential for the animals to migrate toward the memorized temperature on a thermal gradient. However, the encoding mechanisms of the spatial environment with the temporal AFD activity during navigation remain to be elucidated. Here, we show how the AFD neuron encodes sequences of sensory inputs to perceive spatial thermal environment. We used simultaneous calcium imaging and tracking system for a freely moving animal and characterized the response property of AFD to the thermal stimulus during thermotaxis. We show that AFD neurons respond to shallow temperature increases with intermittent calcium pulses and detect temperature differences with a critical time window of 20 s, which is similar to the timescale of behavioral elements of C. elegans, such as turning. Convolution of a thermal stimulus and the identified response property successfully reconstructs AFD activity. Conversely, deconvolution of the identified response kernel and AFD activity reconstructs the shallow thermal gradient with migration trajectory, indicating that AFD activity and the migration trajectory are sufficient as the encoded signals for thermal environment. Our study demonstrates bidirectional transformation between environmental thermal information and encoded neural activity.Key words: C. elegans; imaging; reconstruction; response function; thermosensory neuron; tracking IntroductionEvaluation of the surrounding environment is a vital ability for living organisms. When animals migrate through their environment, sensory systems convert external information into neural activities as temporally encoded signals. Depending on the encoded signals, animals organize sequences of movement with proper timing to migrate to preferred environments. Elucidating the neuronal mechanisms by which temporal activities of sensory neurons generated a response to environmental input is crucial for understanding the neural code to express and convey the Received July 28, 2015; revised Dec. 12, 2015; accepted Dec. 31, 2015. Author contributions: Y.T., H.N., S.I., and I. Significance StatementDeciphering how information is encoded in the nervous system is an important challenge for understanding the principles of information processing in neural circuits. During navigation behavior, animals transform spatial information to temporal patterns of neural activity. To elucidate how a sensory system achieves this transformation, we focused on a thermosensory neuron in Caenorhabditis elegans called AFD, which plays a major role in a sensory behavior. Using tracking and calcium imaging system for freely moving animals, we identified the response property of the AFD. The identified response pr...

We propose a new computation-based approach for elucidating how signaling molecules are decoded in cell migration. In this approach, we performed FRET time-lapse imaging of Rac1 and Cdc42, members of Rho GTPases which are responsible for cell motility, and quantitatively identified the response functions that describe the conversion from the molecular activities to the morphological changes. Based on the identified response functions, we clarified the profiles of how the morphology spatiotemporally changes in response to local and transient activation of Rac1 and Cdc42, and found that Rac1 and Cdc42 activation triggers laterally propagating membrane protrusion. The response functions were also endowed with property of differentiator, which is beneficial for maintaining sensitivity under adaptation to the mean level of input. Using the response function, we could predict the morphological change from molecular activity, and its predictive performance provides a new quantitative measure of how much the Rho GTPases participate in the cell migration. Interestingly, we discovered distinct predictive performance of Rac1 and Cdc42 depending on the migration modes, indicating that Rac1 and Cdc42 contribute to persistent and random migration, respectively. Thus, our proposed predictive approach enabled us to uncover the hidden information processing rules of Rho GTPases in the cell migration.

We consider the vertebrate somite segmentation clock as an example of a rhythmic phenomenon that occurs in development. Using mouse genetics and mathematical analyses, we found that the period of the clock in each presomitic cell is sensitive to Notch activity. It may be a system for each cell to adapt to its local environment.

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems.