  Quantitative models of associative learning that explain the behavior of real
animals with high precision have turned out very difficult to construct. We do
this in the context of the dynamics of the thermal preference of C. elegans.
For this, we quantify C. elegans thermotaxis in response to various
conditioning parameters, genetic perturbations, and operant behavior using a
fast, high-throughput microfluidic droplet assay. We then model this data
comprehensively, within a new, biologically interpretable, multi-modal
framework. We discover that the dynamics of thermal preference are described by
two independent contributions and require a model with at least four dynamical
variables. One pathway positively associates the experienced temperature
independently of food and the other negatively associates to the temperature
when food is absent.
