Neural representation in the auditory midbrain of the envelope of vocalizations based on a peripheral ear model

Abstract

The auditory midbrain implant (AMI) consists of a single shank array (20 sites) for stimulation along the tonotopic axis of the central nucleus of the inferior colliculus (ICC) and has been safely implanted in deaf patients who cannot benefit from a cochlear implant (CI). The AMI improves lip-reading abilities and environmental awareness in the implanted patients. However, the AMI cannot achieve the high levels of speech perception possible with the CI. It appears the AMI can transmit sufficient spectral cues but with limited temporal cues required for speech understanding. Currently, the AMI uses a CI-based strategy, which was originally designed to stimulate each frequency region along the cochlea with amplitude-modulated pulse trains matching the envelope of the bandpass-filtered sound components. However, it is unclear if this type of stimulation with only a single site within each frequency lamina of the ICC can elicit sufficient temporal cues for speech perception. At least speech understanding in quiet is still possible with envelope cues as low as 50 Hz. Therefore, we investigated how ICC neurons follow the bandpass-filtered envelope structure of natural stimuli in ketamine-anesthetized guinea pigs. We identified a subset of ICC neurons that could closely follow the envelope structure (up to ß100 Hz) of a diverse set of species-specific calls, which was revealed by using a peripheral ear model to estimate the true bandpass-filtered envelopes observed by the brain. Although previous studies have suggested a complex neural transformation from the auditory nerve to the ICC, our data suggest that the brain maintains a robust temporal code in a subset of ICC neurons matching the envelope structure of natural stimuli. Clinically, these findings suggest that a CI-based strategy may still be effective for the AMI if the appropriate neurons are entrained to the envelope of the acoustic stimulus and can transmit sufficient temporal cues to higher centers.

Improving neural decoding in the central auditory system using bio-inspired spectro-temporal representations and a generalized bilinear model

“…The dataset used in this study consists of multi-unit neural recordings from the inferior colliculus of ketamineanesthetized guinea pigs; the detailed experimental setup can be found in [13]. Recordings were performed simultaneously at 32 different sites following the successive presentation of 6 different guinea pig vocalizations, having both voiced and unvoiced characteristics, for 20 trials each ( Fig.…”

Auditory midbrain implant: Research and development towards a second clinical trial

“…Several studies have shown that ICC neurons can follow envelope modulations of simple and natural stimuli up to a few hundred hertz (Krishna et al, 2000; Langner et al, 2002; Rees et al, 1987; Suta et al, 2003; Woolley et al, 2006). One particular study performed experiments in 10 ketamine-anesthetized guinea pigs to further assess if a CI type of strategy could potentially be effective for the AMI (Rode et al, 2013). Natural vocalizations (i.e., guinea pig speech; Figure 7), which exhibit similar temporal and spectral patterns to human speech, were presented to the left ear of the animals and neural spiking activity was recorded across the right ICC using 32-site arrays in multiple locations per animal.…”

“…There were multiple neurons that exhibited high correlation values close to 1 for all three vocalizations, and thus for a wide range of spectral and temporal sound patterns. Based on visual inspection of all the raw data, R values ≥0.85 corresponded to neurons that accurately followed the stimulus envelope (for further examples and justifications of this criterion, see (Rode et al, 2013)). The high 0.85 criterion was achieved by 15%, 60%, and 58% of neurons for scream, squeal, and tooth-chatter, respectively.…”

“…The vocalizations presented to the animals were bandpass filtered (500 Hz – 40 kHz) and calibrated with respect to the speaker-ear interface. Figure was taken from (Rode et al, 2013) and reprinted with open access rights by the authors.…”

“…N: total number of neurons (i.e., multi-unit sites) per vocalization. Figure was taken from (Rode et al, 2013) and reprinted with open access rights by the authors.…”