  In the past decade, a small corner of the fly's visual system has become an
important testing ground for ideas about coding and computation in the nervous
system. A number of results demonstrate that this system operates with a
precision and efficiency near the limits imposed by physics, and more generally
these results point to the reliability and efficiency of the strategies that
nature has selected for representing and processing visual signals. A recent
series of papers by Egelhaaf and coworkers, however, suggests that almost all
these conclusions are incorrect. In this contribution we place these
controversies in a larger context, emphasizing that the arguments are not just
about flies, but rather about how we should quantify the neural response to
complex, naturalistic inputs. As an example, Egelhaaf et al. (and many others)
compute certain correlation functions and use the apparent correlation times as
a measure of temporal precision in the neural response. This analysis neglects
the structure of the correlation function at short times, and we show how to
analyze this structure to reveal a temporal precision 30 times better than
suggested by the correlation time; this precision is confirmed by a much more
detailed information theoretic analysis. In reviewing other aspects of the
controversy, we find that the analysis methods used by Egelhaaf et al. suffer
from some mathematical inconsistencies, and that in some cases we are unable to
reproduce their experimental results. Finally, we present results from new
experiments that probe the neural response to inputs that approach more closely
the natural context for freely flying flies. These new experiments demonstrate
that the fly's visual system is even more precise and efficient under natural
conditions than had been inferred from our earlier work.
