Data from: Computational methods for tracking, quantitative assessment, and visualization of C. elegans locomotory behavior

The nematode Caenorhabditis elegans provides a unique opportunity to
interrogate the neural basis of behavior at single neuron resolution. In
C. elegans, neural circuits that control behaviors can be formulated based
on its complete neural connection map, and easily assessed by applying
advanced genetic tools that allow for modulation in the activity of
specific neurons. Importantly, C. elegans exhibits several elaborate
behaviors that can be empirically quantified and analyzed, thus providing
a means to assess the contribution of specific neural circuits to
behavioral output. Particularly, locomotory behavior can be recorded and
analyzed with computational and mathematical tools. Here, we describe a
robust single worm-tracking system, which is based on the open-source
Python programming language, and an analysis system, which implements
path-related algorithms. Our tracking system was designed to accommodate
worms that explore a large area with frequent turns and reversals at high
speeds. As a proof of principle, we used our tracker to record the
movements of wild-type animals that were freshly removed from abundant
bacterial food, and determined how wild-type animals change locomotory
behavior over a long period of time. Consistent with previous findings, we
observed that wild-type animals show a transition from area-restricted
local search to global search over time. Intriguingly, we found that
wild-type animals initially exhibit short, random movements interrupted by
infrequent long trajectories. This movement pattern often coincides with
local/global search behavior, and visually resembles Lévy flight search, a
search behavior conserved across species. Our mathematical analysis showed
that while most of the animals exhibited Brownian walks, approximately 20%
of the animals exhibited Lévy flights, indicating that C. elegans can use
Lévy flights for efficient food search. In summary, our tracker and
analysis software will help analyze the neural basis of the alteration and
transition of C. elegans locomotory behavior in a food-deprived condition.