Effect of temperature and light intensity on the representation of motion information in the fly's visual system

To comprehend how the brain performs efficient computation, it is
important to understand the way sensory information is represented
in the nervous system. Under natural conditions, sensory signals
have to be processed with sufficient accuracy under functional and
resources constraints. Here I use motion vision in the fly
Calliphora vicina to study the influence of two behaviorally
relevant environmental properties - temperature and light intensity
- on the representation of motion information in the responses of
the neuron H1. The goal was to quantify how these environmental
properties affect the response variability, information content,
coding efficiency and temporal scale. I show that the firing
precision is determined largely by the light intensity rather than
by temperature. Moreover, a better firing precision barely improves
the information rate, which closely follows the mean firing rate.
Altogether, my results suggest that the robustness of the motion
information processing against temperature variations depends on
the quality of the input signal. Furthermore, flies seem to use the
input signal-to-noise ratio to improve the information rate and
reduce the time-scale of the response simultaneously, by increasing
the mean firing rate, rather than the firing precision.