Rapid adaptation to internal states as a coding strategy in visual cortex?
Adaptation is a prominent feature of biological neuronal systems. A common interpretation of adaptation in terms of function is that it provides flexibility for a neuronal system to perform well under varying external conditions, for example by adjusting the input/output relation of a sensory system with reference to the ensemble of stimuli the organism currently perceives. This interpretation, however, only applies if the time-scale of adaptation is slower than the time-scale at which the environment changes. Experimentally it is observed, however, that adaptation can be very rapid. Spike-frequency adaptation of cortical neurons, for example, occurs on a time-scale of approximately 100 ms. Here we show that those rapid adaptation processes can also be understood within the framework of information theory. We start with the hypothesis that neuronal codes are designed to optimize the information a neuronal representation conveys about an input stimulus for any increasing time window beginning with stimulus onset, and we show that this implies a rapid adaptation of the neuronal code on the time-scale of stimulus presentation. Adaptation, however, does not occur because the state of the environment changes. Rather it is a reaction to changes of the organisms own internal state, e.g. the level of noise in the neuronal representation. We apply this approach to a model of an orientation hypercolumn in the primary visual cortex, and predict that inter-columnar interactions should adapt on the time-scale of a typical fixation period ( approximately 300 ms).