How is Nengo different from other neural simulators?

I’ve heard of PyNN, Brian, NEST, NEURON, etc. Is Nengo basically the same as these other simulators?

The main difference is in how the connection strengths between neurons are specified. For other neural simulators, you either set these weights manually or you set them randomly and specify a learning rule. Nengo allows you to specify the overall function that should be computed, and then it will solve for the connection weights that will best approximate that function. This allows the model designer to work at a higher level of abstraction (vectors and functions) and yet still produce a detailed model using realistic spiking neurons. You can use the other methods to specify and/or adapt weights as well.