Neural Nets, Temporal Composites, and Tonality

Publisher Summary This chapter describes the neural nets, temporal composites, and tonality. The chapter outlines a framework in which aspects of cognition can be understand as the result of the neural association of patterns. Subsequent advances helps in understanding that how these neural associations can be learned. Models based on these mechanisms are called neural net models. Neural net models have a number of properties that recommend them as models of music cognition. Neural net models are not intended to be statements of fact about how the brain is wired. Like all models, they are systematic hypotheses based on available data, and they represent attempts to account for known phenomena and guide further research. Some neural net models are sufficiently closely tied to known physiology that they serve as hypotheses of actual neural circuitry. The chapter helps in gaining knowledge that different types of neurons are interconnected within the parts of the brain that are thought to play major roles in cognition, namely, the cerebral cortex, and the cerebellum. The chapter concludes that either neural nets are implementations of grammars, or grammars are formal descriptions of neural nets. Future research need to bridge the gap either way.