A hierarchical dynamical map as a basic frame for cortical mapping and itsapplication to priming

A hierarchical dynamical map is proposed as the basic framework for sensory cortical mapping. To show how the hierarchical dynamical map works in cogn itive processes, we applied it to a typical cognitive task known as priming , in which cognitive performance is facilitated as a consequence of prior e xperience. Prior to the priming task, the network memorizes a sensory scene containing multiple objects presented simultaneously using a hierarchical dynamical map. Each object is composed of different sensory features. The h ierarchical dynamical map presented here is formed by random itinerancy amo ng limit-cycle attractors into which these objects are encoded. Each limit- cycle attractor contains multiple point attractors into which elemental fea tures belonging to the same object are encoded. When a feature stimulus is presented as a priming cue, the network state is changed from the itinerant state to a limit-cycle attractor relevant to the priming cue. After a shor t priming period, the network state reverts to the itinerant state. Under a pplication of the test cue, consisting of some feature belonging to the obj ect relevant to the priming cue and fragments of features belonging to othe rs, the network state is changed to a limit-cycle attractor and finally to a point attractor relevant to the target feature. This process is considere d as the identification of the target. The model consistently reproduces va rious observed results for priming processes such as the difference in iden tification time between cross-modality and within-modality priming tasks, t he effect of interval between priming cue and test cue on identification ti me, the effect of priming duration on the time, and the effect of repetitio n of the same priming task on neural activity.