  Understanding and even defining what constitutes animal interactions remains
a challenging problem. Correlational tools may be inappropriate for detecting
communication between a set of many agents exhibiting nonlinear behavior. A
different approach is to define coordinated motions in terms of an information
theoretic channel of direct causal information flow. In this work, we consider
time series data obtained by an experimental protocol of optical tracking of
the insect species Chironomus riparius. The data constitute reconstructed 3-D
spatial trajectories of the insects' flight trajectories and kinematics. We
present an application of the optimal causation entropy (oCSE) principle to
identify direct causal relationships or information channels among the insects.
The collection of channels inferred by oCSE describes a network of information
flow within the swarm. We find that information channels with a long spatial
range are more common than expected under the assumption that causal
information flows should be spatially localized. The tools developed herein are
general and applicable to the inference and study of intercommunication
networks in a wide variety of natural settings.
