Auditory steady-state response and gamma oscillations in an excitatory-inhibitory balanced neuronal network

Abstract

This study introduces a novel auditory neuronal network model that integrates speech signal input, cochlear processing, and a cortical excitatory-inhibitory (E-I) balanced network. Our findings reveal that increasing noise intensity attenuates the auditory steady-state responses in gamma oscillations, a mechanism validated by public EEG data. Moreover, enhancing the brain's E-I balance significantly improves auditory attention during speech recognition. This work not only elucidates the neural basis of selective attention in noisy environments but also offers a promising therapeutic strategy for auditory attention disorders, marking a significant advancement in the field of computational neuroscience and auditory processing.