Computational models and neural bases of statistical learning in music and language Comment on 'Creativity, information, and consciousness: The information dynamics of thinking' by Wiggins

摘要

The review by Wiggins [1] offers a comprehensive theory of the brain's mechanism in the framework of statistical learning (SL). The theory, referred to as Information Dynamics of Thinking (IDyOT) implements memory representation, consolidation, and categorization under entropy (uncertainty) encoding, aiming to be information-efficient. The work also sheds new light on the links between SL and creativity, and opens up interdisciplinary perspectives on computational and neurophysiological underpinnings of SL. Here, I discuss how the IDyOT theory links with neural function in SL.