A mathematical equation within a neuron that determines its output by processing the weighted sum of inputs. Modern DNNs use smoother, non-linear functions like ReLU, tanh, or sigmoid to enable learning complex patterns and apply gradient descent, unlike the binary threshold function of the perceptron.