  Individual-intelligence research, from a neurological perspective, discusses
the hierarchical layers of the cortex as a structure that performs conceptual
abstraction and specification. This theory has been used to explain how
motor-cortex regions responsible for different behavioral modalities such as
writing and speaking can be utilized to express the same general concept
represented higher in the cortical hierarchy. For example, the concept of a
dog, represented across a region of high-level cortical-neurons, can either be
written or spoken about depending on the individual's context. The higher-layer
cortical areas project down the hierarchy, sending abstract information to
specific regions of the motor-cortex for contextual implementation. In this
paper, this idea is expanded to incorporate collective-intelligence within a
hyper-cortical construct. This hyper-cortex is a multi-layered network used to
represent abstract collective concepts. These ideas play an important role in
understanding how collective-intelligence systems can be engineered to handle
problem abstraction and solution specification. Finally, a collection of common
problems in the scientific community are solved using an artificial
hyper-cortex generated from digital-library metadata.
