Do cortical maps adapt to optimize information density?
Topographic maps are found in many biological and artificial neural systems. In biological systems, some parts of these can form a significantly expanded representation of their sensory input, such as the representation of the fovea in the visual cortex. We propose that a cortical feature map should be organized to optimize the efficiency of information transmission through it. This leads to a principle of uniform cortical information density across the map as the desired optimum. An expanded representation in the cortex for a particular sensory area (i.e. a high magnification factor) means that a greater information density is concentrated in that sensory area, leading to finer discrimination thresholds. Improvement may ultimately be limited by the construction of the sensors themselves. This approach gives a good fit to threshold versus cortical area data of Recanzone et al on owl monkeys trained on a tactile frequency-discrimination task.