An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs

• Main Authors: Yu Dong, H. Christiaan Stronks, Jeroen J. Briaire, Johan H.M. Frijns
• Format: Article
• Language: English
• Published: Elsevier 2021-01-01
• Series: MethodsX
• Subjects: An iterative deconvolution model for extracting temporal firing properties of the auditory nerve in human eCAPs
• Online Access: http://www.sciencedirect.com/science/article/pii/S2215016121000339

The electrically evoked compound action potential (eCAP) has been widely studied for its clinical value for the evaluation of the surviving auditory nerve (AN) cells. However, many unknowns remain about the temporal firing properties of the AN fibers that underlie the eCAP in CI recipients. These temporal properties may contain valuable information about the condition of the AN. Here, we propose an iterative deconvolution model for estimating the human evoked unitary response (UR) and for extracting the compound discharge latency distribution (CDLD) from eCAP recordings, under the assumption that all AN fibers have the same UR. In this model, an eCAP is modeled by convolving a parameterized UR and a parameterized CDLD model. Both the UR and CDLD are optimized with an iterative deconvolution fitting error minimization routine to minimize the error between the modeled eCAP and the recorded eCAP. • This method first estimates the human UR from eCAP recordings. The human eCAP is unknown at the time of this writing. The UR is subsequently used to extract the underlying temporal neural excitation pattern (the CDLD) that reflects the contributions from individual AN fibers in human eCAPs. • By calculating the CDLD, the synchronicity of AN fibers can be evaluated.