Forming Concepts of Mozart and Homer Using Short-Term and Long-TermMemory:A Computational Model Based on Chunking

A fundamental issue in cognitive science concerns the mentalprocesses that underlie the formation and retrieval of conceptsin the short-term and long-term memory (STM and LTMrespectively). This study advances Chunking Theory and itscomputational embodiment CHREST to propose a singlemodel that accounts for significant aspects of conceptformation in the domains of literature and music. The proposedmodel inherits CHREST’s architecture with its integratedSTM/LTM stores, while also adding a moving attentionwindow and an “LTM chunk activation” mechanism. Theseadditions address the overly destructive nature of primacyeffect in discrimination network based architectures andexpand Chunking Theory to account for learning, retrieval andcategorisation of complex sequential symbolic patterns – likereal-life text and written music scores. The model was trainedthrough exposure to labelled stimuli and learned to categoriseclassical poets/writers and composers. The model categorisedpreviously unseen literature pieces by Homer, Chaucer,Shakespeare, Walter Scott, Dickens and Joyce, as well asunseen sheet music scores by Bach, Mozart, Beethoven andChopin. These findings offer further support to mechanismsproposed by Chunking Theory and expand it into thepsychology of music.