  In continuous attractor neural networks (CANNs), spatially continuous
information such as orientation, head direction, and spatial location is
represented by Gaussian-like tuning curves that can be displaced continuously
in the space of the preferred stimuli of the neurons. We investigate how
short-term synaptic depression (STD) can reshape the intrinsic dynamics of the
CANN model and its responses to a single static input. In particular, CANNs
with STD can support various complex firing patterns and chaotic behaviors.
These chaotic behaviors have the potential to encode various stimuli in the
neuronal system.
