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Abstract:
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.
