Rapid adaptation is a prominent feature of biological neuronal systems. From a functional perspective the adaptation of neuronal properties, namely the input-output relation of sensory neurons, is usually interpreted as an adaptation of the sensory system to changing environments as characterized by their stimulus statistics. Here we argue that this interpretation is only applicable as long as the adaptation processes are slower than the time-scale at which the stimulus statistics change. We present a definition of optimality of a neuronal code which still captures the idea of efficient coding, but which can also explain rapid adaptation without referring to an adaptation to different sensory environments. Finally, we apply our new idea to a simple model of an orientation hypercolumn in the primary visual cortex and predict that the interactions between orientation columns should adapt at the time-scale of a single stimulus presentation.