The summating potential in human electrocochleography: Gaussian models and Fourier analysis.

Abstract

In recent electrocochleographic studies, the amplitude of the summating potential (SP) was an important predictor of performance on word-recognition in difficult listening environments among normal-hearing listeners; paradoxically the SP was largest in those with the worst scores. SP has traditionally been extracted by visual inspection, a technique prone to subjectivity and error. Here, we assess the utility of a fitting algorithm [Kamerer, Neely, and Rasetshwane (2020). J Acoust Soc Am. 147, 25-31] using a summed-Gaussian model to objectify and improve SP identification. Results show that SPs extracted by visual inspection correlate better with word scores than those from the model fits. We also use fast Fourier transform to decompose these evoked responses into their spectral components to gain insight into the cellular generators of SP. We find a component at 310 Hz associated with word-identification tasks that correlates with SP amplitude. This component is absent in patients with genetic mutations affecting synaptic transmission and may reflect a contribution from excitatory post-synaptic potentials in auditory nerve fibers.