Sparse spike trains and the limitation of rate codes underlying rapid behaviours

Animals live in dynamic worlds where they use sensorimotor circuits to rapidly process information and drive behaviours. For example, dragonflies are aerial predators that react to movements of prey within tens of milliseconds. These pursuits are likely controlled by identified neurons in the dragonfly, which have well-characterized physiological responses to moving targets. Predominantly, neural activity in these circuits is interpreted in context of a rate code, where information is conveyed by changes in the number of spikes over a time period. However, such a description of neuronal activity is difficult to achieve in real-world, real-time scenarios. Here, we contrast a neuroscientists' post-hoc view of spiking activity with the information available to the animal in real-time. We describe how performance of a rate code is readily overestimated and outline a rate code's significant limitations in driving rapid behaviours.

Automated summary

Animals, such as dragonflies, rely on sensorimotor circuits to process information and drive behaviors in their dynamic environments. While neuroscientists typically interpret neural activity using a rate code, which measures changes in spike frequency over time, this method has limitations in accurately capturing real-time information available to the animal. This study challenges the effectiveness of rate codes in driving rapid behaviors and highlights the need for a better understanding of how animals process information.