A Linear Superposition Model of Envelope and Frequency Following Responses May Help Identify Generators Based on Latency

Envelope and frequency-following responses (FFRENV and FFRTFS) are scalp-recorded electrophysiological potentials that closely follow the periodicity of complex sounds such as speech. These signals have been established as important biomarkers in speech and learning disorders. However, despite important advances, it has remained challenging to map altered FFRENV and FFRTFS to altered processing in specific brain regions. Here we explore the utility of a deconvolution approach based on the assumption that FFRENV and FFRTFS reflect the linear superposition of responses that are triggered by the glottal pulse in each cycle of the fundamental frequency (F0 responses). We tested the deconvolution method by applying it to FFRENV and FFRTFS of rhesus monkeys to human speech and click trains with time-varying pitch patterns. Our analyses show that F0ENV responses could be measured with high signal-to-noise ratio and featured several spectro-temporally and topographically distinct components that likely reflect the activation of brainstem (