Reiss AP et al. (2021) J Neurogenet "Gaining an understanding of behavioral genetics through studies of foraging in Drosophila and learning in C. elegans."

Rankin CH, Reiss AP

[J Neurogenet, 2021]

The pursuit of understanding behavior has led to investigations of how genes, the environment, and the nervous system all work together to produce and influence behavior, giving rise to a field of research known as behavioral neurogenetics. This review focuses on the research journeys of two pioneers of aspects of behavioral neurogenetic research: Dr. Marla Sokolowski and Dr. Catharine Rankin as examples of how different approaches have been used to understand relationships between genes and behavior. Marla Sokolowski's research is centered around the discovery and analysis of <i>foraging</i>, a gene responsible for the natural behavioral polymorphism of <i>Drosophila melanogaster</i> larvae foraging behavior. Catharine Rankin's work began with demonstrating the ability to learn in <i>Caenorhabditis elegans</i> and then setting out to investigate the mechanisms underlying the &quot;simplest&quot; form of learning, habituation. Using these simple invertebrate organisms both investigators were able to perform in-depth dissections of behavior at genetic and molecular levels. By exploring their research and highlighting their findings we present ways their work has furthered our understanding of behavior and contributed to the field of behavioral neurogenetics.

Wicks SR et al. (1996) J Neurosci "A dynamic network simulation of the nematode tap withdrawal circuit: predictions concerning synaptic function using behavioral criteria."

Wicks SR, Rankin CH, Roehrig CJ

[J Neurosci, 1996]

The nematode tap withdrawal reflex demonstrates several forms of behavioral plasticity. Although the neural connectivity that supports this behavior is identified (Integration of mechanosensory stimuli in Caenorhabditis elegans, Wicks and Rankin, 1995, J Neurosci 15:2434-2444), the neurotransmitter phenotypes, and hence whether the synapses in the circuit are excitatory or inhibitory, remain uncharacterized. Here we use a novel strategy to predict the polarity configuration, i.e., the array of excitatory and inhibitory connections, of the nematode tap withdrawal circuit using an anatomically and physiologically justifiable dynamic network simulation of that circuit. The output of the modeled circuit was optimized to the behavior of animals, which possessed circuits altered by surgical ablation by exhaustively enumerating an array of synaptic signs that constituted the modeled circuit. All possible polarity configurations were then compared, and a statistical analysis was used to determine whether, for a given synaptic class, a particular polarity was associated with a good fit to behavioral data. The results from four related experiments were used to predict the polarities of seven of the nine cell classes of the tap withdrawal circuit. In addition, the model was used to assess possible roles for two novel mechanosensory integration neurons: DVA and PVD.