Musical complexity governs a tradeoff between reliability and dimensionality in the neural code

Abstract

The rich experience of listening to music depends on the neural integration of its constituent elements within the early auditory pathway. Here, we performed the first large-scale study of neural responses to complex music to characterize the neural coding of individual instruments and mixtures with both normal hearing and mild-to-moderate hearing loss. Using coherence and manifold analyses along with deep learning, we identified strong nonlinear interactions in mixed music that impacted the fidelity and geometry of the neural code. We found that increasing musical complexity resulted in the creation of new neural modes, but this increased dimensionality was associated with decreased reliability. This tradeoff persisted even after hearing loss, the effects of which were largely corrected with suitable amplification. These results suggest that the neural coding of music is governed by an inherent tradeoff and highlight a fundamental challenge in maintaining fidelity while processing sensory inputs with increasing complexity.