BAN: Neuroanatomical Aligning in Auditory Recognition between Artificial Neural Network and Human Cortex

TL;DR

This paper introduces BAN, a brain-inspired recurrent neural network designed to mirror human auditory recognition pathways, validated by a novel similarity metric and achieving high performance in music genre classification.

Contribution

BAN is the first recurrent neural network model that closely aligns with human cortical auditory pathways using a neuroanatomically guided structure and a new similarity metric.

Findings

BAN achieves high neuroanatomical similarity with human cortex.

BAN performs well on music genre classification.

High brain-like auditory score (BAS) indicates strong cortical alignment.

Abstract

Drawing inspiration from neurosciences, artificial neural networks (ANNs) have evolved from shallow architectures to highly complex, deep structures, yielding exceptional performance in auditory recognition tasks. However, traditional ANNs often struggle to align with brain regions due to their excessive depth and lack of biologically realistic features, like recurrent connection. To address this, a brain-like auditory network (BAN) is introduced, which incorporates four neuroanatomically mapped areas and recurrent connection, guided by a novel metric called the brain-like auditory score (BAS). BAS serves as a benchmark for evaluating the similarity between BAN and human auditory recognition pathway. We further propose that specific areas in the cerebral cortex, mainly the middle and medial superior temporal (T2/T3) areas, correspond to the designed network structure, drawing parallels with the brain's auditory perception pathway. Our findings suggest that the neuroanatomical similarity in the cortex and auditory classification abilities of the ANN are well-aligned. In addition to delivering excellent performance on a music genre classification task, the BAN demonstrates a high BAS score. In conclusion, this study presents BAN as a recurrent, brain-inspired ANN, representing the first model that mirrors the cortical pathway of auditory recognition.