Generating smooth context-dependent neural representations

In many cognitive situations, context is specified globally-encompassing the entire duration of an episode, but explicitly identified only at its initiation. Examples of such contexts are social situations, spatial environments, task specifications, etc. In many such cases, a neural system needs to respond differently to the same immediate stimulus depending on the global context. Clearly, the system must be able to switch into different response regimes and remain there while the context remains fixed. Simultaneously, it must remain sensitive to external stimuli, and respond to them in a reliable and informative manner. We propose a neurally plausible approach for handling these requirements