Computational model for synthesizing auditory brainstem responses to assess neuronal alterations in aging and autistic animal models
The auditory brainstem response (ABR) is a widely used objective electrophysiology measure for non-invasively assessing auditory function and neural activities in the auditory brainstem, but its ability to reflect detailed neuronal processes is limited due to the averaging nature of the electroencephalogram recordings. This study addresses this limitation by developing a computational model of the auditory brainstem which is capable of synthesizing ABR traces based on a large, population scale neural extrapolation of a spiking neuronal network of auditory brainstem neural circuitry. The model was able to recapitulate alterations in ABR waveform morphology that have been shown to be present in two medical conditions: animal models of autism and aging. Moreover, in both of these conditions, these ABR alterations are caused by known distinct changes in auditory brainstem physiology, and the model could recapitulate these changes. In the autism model, the simulation revealed myelin deficits and hyperexcitability, which caused a decreased wave III amplitude and a prolonged wave III-V interval, consistent with experimentally recorded ABRs in Fmr1-KO mice. In the aging model, the model recapitulated ABRs recorded in aged gerbils and indicated a reduction in activity in the medial nucleus of the trapezoid body (MNTB), a finding validated by confocal imaging data. These results demonstrate not only the model's accuracy but also its capability of linking features of ABR morphologies to underlying neuronal properties and suggesting follow-up physiological experiments.