Learning universal computations with spikes

Understand

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g.~for locomotion.

• Many such computations require previous building of intrinsic world models.
• Here we show how spiking neural networks may solve these different tasks.
• Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing.