Before revision: Class selectivity, typically defined as how different a neuron's responses are across different classes of stimuli or data samples, is a common metric used to interpret the function of individual neurons in biological and artificial neural networks .
After revision: Class selectivity, typically defined as how different a neuron's responses are across different classes of stimuli or data samples-is commonly used for this purpose .