Neurons with graded response have collective computational properties like those of two-state neurons.

A model for a large network of 'neurons' with graded response (or sigmoid input-output relation) is studied. This deterministic system has collective properties in very close correspondence with the earlier stochastic model based on McCulloch-Pitts neurons. The content addressable memory and other emergent collective properties of the original model also are present in the response model. The idea that such collective properties are used in biological systems is given added credence by the continued presence of such properties for more nearly biological 'neurons'.