An artificial neuron needs values to compare (the sum of weighted inputs). You can add values with transistors of course, but you need more than a dozen just to do simple addition. The activation function could be a simple binary comparison (e.g. between a weight and a threshold), but it’s usually more complicated.

Artificial neurons are significantly more complex that single transistors, and even a minimal hardwired circuit to implement just one neuron requires quite a number of transistors.