  Synaptic plasticity allows cortical circuits to learn new tasks and to adapt
to changing environments. How do cortical circuits use plasticity to acquire
functions such as decision-making or working memory? Neurons are connected in
complex ways, forming recurrent neural networks, and learning modifies the
strength of their connections. Moreover, neurons communicate emitting brief
discrete electric signals. Here we describe how to train recurrent neural
networks in tasks like those used to train animals in neuroscience
laboratories, and how computations emerge in the trained networks.
Surprisingly, artificial networks and real brains can use similar computational
strategies.
