A single piece of music may begin as a melody. The rules by which the piece expands are that of recursive incorporation, replication, cleaving, and displacement, one transformation of the basic pattern nesting inside another. The notes of the basic melody are replicated several times throughout the piece, and incorporated within this replication may be its play at twice or half the speed and this may be assigned to different instrument voices. The core melody may be played at other times in retrograde and assigned to a different instrument to increase the beauty of the piece. The texture may change further with an inversion of everything that was done so far as in Johan Sebastian Bach's Musical Offering. 

Other behavior, whether routine or creative, is also constructed of similar primitives. 

## Learning

Learning requires networks that have the capacity to generalize very quickly since the decision time is short. It was the motivation to model short-term memory that led to the development of the corner classification (CC) family of the instantaneously trained neural networks (ITNN) [911] that learn instantaneously and have very good generalization performance. ITNN networks are an example of prescriptive learning; they train the network by isolating the corner in the ndimensional cube of the inputs represented by the input vector being learnt. In specific modules, the processors may have strong feedback connections [12-15]. Another approach to learning is that of using recursive structures which are implicitly mapped to the recursive primitives of the information process. This approach which is called the Network of Networks (NoN) approach is based on a model of cortical processing. It is based on two fundamental ideas in neurobiology: (1) groups of interacting nerve cells, or neurons, encode functional information, and (2) processing occurs simultaneously across different levels of neural organization. Although the NoN model makes simplifying assumptions about neural activity, systems using this approach have performed very well. Nested distributed systems denote the core architecture of the model. In the context of describing computational features of the cerebral cortex, this organizing principle was proposed by Mountcastle [16] and applied by Sutton and Anderson [17]. The formation of clusters and levels among neurons is based on their interconnections. The NoN model suggests that despite enormous diversity in the connection patterns associated with individual neurons, many neural circuits can be subdivided into essentially similar sub-circuits, where each sub circuit contains many types of neurons. This hierarchy is evident in the cerebral cortex, which has long been considered the most complex and elusive of neural circuits. (See Figure 4 adapted from [17]). This nesting arrangement serves to link different and often widely separated regions of the cortex in a precise but distributed manner. Several physiological responses, such as those occurring in the visual cortex in response to optical stimuli, may be associated with each first-level sub-circuit. Regarding the question of universals underlying aesthetics in art and music [18], it has been argued that although there are no specific universals that have a quantitative form, there are qualitative ones that are ultimately related to the neurophysiological basis of the cognitive system. These qualitative universals also have a recursive nature. 

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