The correct answer is True. Artificial neural network units can have different activation functions, which determine how the inputs are transformed into outputs. Different activation functions can lead to different behaviors and outputs for the same set of inputs. For example, a unit with a sigmoid activation function may produce a different output than a unit with a rectified linear activation function for the same inputs.
