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Updated: Jul 12, 2026

C. elegans Tracking and Behavioral Measurement
Published on: November 17, 2012
Neuronal decoding of temperature signals in Caenorhabditis elegans
Abhilasha Batra1, Rati Sharma1
1Indian Institute of Science Education and Research (IISER), Department of Chemistry, Bhopal 462066, Madhya Pradesh, India.
Abstract:
Neural processing in animals facilitates sensory adaptation by eliciting appropriate responses to changing environmental stimuli. Although sensory adaptation is well recognized, the specific role of individual neurons in these adaptive mechanisms remains poorly understood from a theoretical standpoint. Specifically, it is unclear how single neurons influence the processing of sensory information and modulate their responses to environmental changes. In Caenorhabditis elegans, the primary AFD thermosensory neurons respond to external thermal stimuli incorporating experience-dependent temperature response thresholds. While extensive experimental studies have highlighted the functional features of the AFD neurons, mathematical understanding of their responses is still not well established. In this study, we develop a theoretical framework that captures how a single pair of AFD neurons encodes sensory information and regulates their responses to thermal warming signals, with a focus on how prior environmental experiences influence these responses. Through this framework we find that the interaction between two key entities, i.e., cGMP and calcium, plays a crucial role in processing sensory information and fine-tuning neuronal responses to thermal changes. In addition to reproducing experimentally known trends, our results show that growth conditions such as cultivation temperature of the worms significantly shape the neurons' functional properties, including their operating range, activation thresholds and response start time and duration. The findings in this work, therefore, enhance the overall understanding of how environmental experiences by single neuron shape sensory systems and provide a deeper connection between experimental data and quantitative models.

