Rhythm in Music, Encoded in Neural Networks, and in the Mind

Abstract

Rhythm is ubiquitous in nature and has fascinated scholars from times immemorial. Rhythmic activity also underlies many forms of communicative interaction both in biology and in artificial computational systems. A rapidly growing issue, both in technology and philosophy, is whether this kind of communicative interaction from the most sophisticated applications of artificial intelligence (AI) is comparable to the interaction of human beings and their minds. A now historic debate on this quickly suffers from exceeding the limits that must be imposed on the use of terms from different reference domains, like the concept of intentionality and the emergence of conscious representations in a mental world. In this paper rhythm in music, with its characteristic roots in a culture, is explored as a representation of encoded information with particular Gestalt character, but meanwhile, in the composition of modulated frequencies, also comparable to the oscillatory activity in neural networks. Rhythm in music is a complex phenomenon and the carrier or “medium” of meaningful representations, while it can ultimately be traced back to modulated oscillations in sound waves, the auditory system and related sensorimotor and information supporting networks in the brain. The phenomenon of rhythm in music is explored, in such a way that it becomes clear why it can serve as an illustrative representation for the comparison of “intelligence” in the living brain and that in AI.