Given that our knowledge of the computational complexity of a single neuron is growing steadily, I think it's safe to say your FPGA cell estimate for a neuron was significantly too low. For example, scientists now know that one single neuron (of certain types) is an entire neural network all by itself. Dendrites with multiple localized spikes communicating with each other and with other cells. Ultimately performing non-linear computation prior to forwarding any signal to cell body.
Right you are. The absolute give-away (in addition to the ridiculous low-ball answer he provided) was "... that was pretty straightforward..." which shows the Dunning-Kruger Effect in full bloom. He had no idea now little he knows about the subject.
The example I like to use to illustrate how much smoke is being blown about this my tech types is the model organism Caenorhabditis elegans. This 1 mm long nematode has had every one of its 302 neurons in its nervous mapped out, including all connections to every other neuron, as well as the process of development from the initial fertilized egg - we have mapped out exactly how the nervous system develops (indeed every one of the 959 cells in its body have been similarly traced out).
Given this complete map of C. elegans nervous system we must have a spiffy computer of the little worm's "brain" able to replicate its behavior? Right?
Not even close. So far we cannot accurate model the behavior of even a single neuron in C. elegans. Even one single neuron represents computational complexity that we are still trying to understand.