> One neuron is equivalent to one bit in a computer. One bit of information is insufficient to distinguish between faces.

"Seen <particular face>" is a binary state, so one output neuron that fires on recognizing a particular face is actually quite reasonable.

Obviously, the inputs that contribute to that recognition must be more complicated.

You need to learn some neuroscience buddy. One neuron is not one bit. A neuron works in much complex way than a single bit in a computer. A neuron has hundreds to thousands axons and dendrites and connect with other neurons in a dense network. I am surprised by your knowledge of neuroscience yet attacking me. very strange.

EDIT: As dragonwriter says below, lower levels of neural networks are responsible for general facial recognition but that triggers more specific neurons once the recognition is done from generic face -> specific person. Even in artificial neural networks single bit is sufficient at the end of the classification.

In that case, your original claim was false -- either one neuron is acting alone as you claimed, or it isn't. Your claim was that one neuron was acting alone, which is absurd.

A neuron is interconnected to many others, but this doesn't mean one neuron is many neurons, any more than one binary bit is 64 binary bits by virtue of its position in a binary word.

The link is posted above. It is not nonsense. The research was done at Caltech by neuroscientist Christof Koch , one of the top neuroscientists in the world.

http://www.klab.caltech.edu/koch/

Sorry my post evoked such a harsh response from you.