The Panoramic ECAP Method: estimating patient-specific patterns of current spread and neural health in cochlear implant users
The knowledge of patient-specific neural excitation patterns from cochlear implants can provide important information for optimising efficacy and improving speech perception outcomes. The Panoramic ECAP (or ‘PECAP’) method (Cosentino, et al., 2015) uses forward-masked electrically evoked compound action potentials (ECAPs) to estimate neural activation patterns of cochlear implant (CI) stimulation. The algorithm requires ECAPs be measured for loudness-balanced stimuli from all combinations of probe and masker electrodes, and takes advantage of ECAP amplitudes being a result of the overlapping excitatory areas of both probes and maskers. Here we present an improved version of the PECAP algorithm that imposes biologically realistic constraints on the solution and produces separate estimates of current spread and neural health along the length of the electrode array. The algorithm was evaluated for reliability and accuracy in three ways: (1) computer-simulated current-spread and neural-health scenarios, (2) comparisons to psychophysical correlates of neural health and electrode-modiolus distances in human CI users, and (3) detection of simulated neural ‘dead’ regions (using forward masking) in human CI users. The PECAP algorithm reliably estimated the computer simulated scenarios. A moderate but significant negative correlation between focused thresholds and PECAP’s neural health estimates was found, consistent with previous literature. It also correctly identified simulated dead regions in seven CI users. The revised PECAP algorithm provides an estimate of the electrode-to-neuron interface in CIs that could be used to inform and optimize CI stimulation strategies for individual patients in clinical settings.