The development offers greater possibilities for advances in robotics and computing and a new way of understanding the brain, researchers said.
For instance, a chip as fast and efficient as the human brain could drive prosthetic limbs with the speed and complexity of our own actions.
For all their sophistication, computers pale in comparison to the brain. The modest cortex of the mouse, for instance, operates 9,000 times faster than a personal computer simulation of its functions.
Not only is the PC slower, it takes 40,000 times more power to run, said Kwabena Boahen, associate professor of bioengineering at Stanford University.
Boahen and his team developed Neurogrid, a circuit board consisting of 16 custom-designed "Neurocore" chips that can simulate 1 million neurons and billions of synaptic connections.
The team designed these chips with power efficiency in mind. Their strategy was to enable certain synapses to share hardware circuits.
The result was a device about the size of an iPad that can simulate orders of magnitude more neurons and synapses than other brain mimics on the power it takes to run a tablet computer.
Its speed and low power characteristics make Neurogrid ideal for more than just modelling the human brain.
Each of the current million-neuron Neurogrid circuit boards cost about USD 40,000. Boahen believes dramatic cost reductions are possible.
By switching to modern manufacturing processes and fabricating the chips in large volumes, he could cut a Neurocore's cost 100-fold suggesting a million-neuron board for USD 400 a copy.
With that cheaper hardware and compiler software to make it easy to configure, these neuromorphic systems could find numerous applications, researchers said.
For instance, a chip as fast and efficient as the human brain could drive prosthetic limbs with the speed and complexity of our own actions - but without being tethered to a power source.
Boahen envisions a Neurocore-like chip that could be implanted in a paralysed person's brain, interpreting those intended movements and translating them to commands for prosthetic limbs without overheating the brain.