Input Pattern Complexity Determines Specialist and Generalist Populations in Drosophila Neural Network

摘要

Neural heterogeneity has been reported as beneficial for information processing in neural networks. An example of this heterogeneity can be observed in the neural responses to stimuli, which divide the neurons into two populations: specialists and generalists. Being observed in the neural network of the locust olfactory system that a balance of these two neural populations is crucial for achieving a correct pattern recognition. However, these results may not be generalizable to other biological neural networks. Therefore, we took advantage of a recent biological study about the Drosophila connectome to study the balance of these two neural populations in its neural network. We conclude that the balance between specialists and generalists also occurs in the Drosophila. This balancing process does not affect the neural network connectivity, since specialist and generalist neurons are not differentiable by the number of incoming connections.