Correlates of deviance detection in auditory brainstem responses of bats

Abstract

Identifying unexpected acoustic inputs, which allows to react appropriately to new situations, is of major importance for animals. Neural deviance detection describes a change of neural response strength to a stimulus solely caused by the stimulus' probability of occurrence. In the present study, we searched for correlates of deviance detection in auditory brainstem responses obtained in anaesthetised bats (Carollia perspicillata). In an oddball paradigm, we used two pure tone stimuli that represented the main frequencies used by the animal during echolocation (60 kHz) and communication (20 kHz). For both stimuli, we could demonstrate significant differences of response strength between deviant and standard response in slow and fast components of the auditory brainstem response. The data suggest the presence of correlates of deviance detection in brain stations below the inferior colliculus (IC), at the level of the cochlea nucleus and lateral lemniscus. Additionally, our results suggest that deviance detection is mainly driven by repetition suppression in the echolocation frequency band, while in the communication band, a deviant‐related enhancement of the response plays a more important role. This finding suggests a contextual dependence of the mechanisms underlying subcortical deviance detection. The present study demonstrates the value of auditory brainstem responses for studying deviance detection and suggests that auditory specialists, such as bats, use different frequency‐specific strategies to ensure an appropriate sensation of unexpected sounds.

Deviance detection in subthalamic neural population responses to natural stimuli in bats

“…This filtering method is different from the usual narrowband filters between 300-2500 Hz that are used in many ABR studies and that will be discussed later. The strong effect of deviance detection in this late part of the response is in line with previous studies that investigated deviance detection in broadband filtered ABRs with pure tones [7,8]. This confirms that this slow, most likely inferior colliculus-generated [9] wave plays a key role in ABR-based deviance detection.…”

“…Given that wave ii and iii represent neural activity in the cochlear nucleus and superior olivary complex, respectively [14], this finding strongly supports the hypothesis that auditory probability encoding at population level is happening already below the inferior colliculus, as it has been suggested in former studies [8,15]. In fact, effects of novelty detection have recently been described for an even lower auditory structure, the cochlea [16,17].…”

“…Those mechanisms seem to get active only when the acoustic input becomes more variable and appear to have complex, nonlinear effects on ABRs. Interestingly, they are restricted to natural stimuli, as a previous study by Wetekam et al [8] in the same species did not find similar effects in the MS ABRs to pure tones. However, the 50 % control was very similar to the deviant and standard response, confirming that probability encoding did not affect the ABR size to the social communication call (Fig.…”

“…Subsequently, the averaging procedure was restricted to those deviant responses that followed a standard response and, vice versa, those standard responses that preceded a deviant response. This method allows to use the same number of trials to calculate the deviant and standard average of each animal (here between 89 and 92 trials) and, at the same time, maximises the effects of deviance detection in the responses [8]. In the case of the 50 % control, the same number of trials that was used to calculate the deviant and standard average for a given animal was used to randomly choose trials out of the 500 available responses to each stimulus.…”

Spectrally non-overlapping background noise disturbs echolocation via acoustic masking in the CF-FM bat, Hipposideros pratti

“…The audiogram of H. pratti showed that their auditory systems responded to a frequency range of 5 to 80 kHz. Therefore, spectrally non-overlapping noise can activate some neurons, and these neurons may synapse on neurons in the frequency range of echolocation signals through local neural circuits, activating an inhibitory neural network ( Seybold et al, 2015 ; López-Jury et al, 2021 ; Wetekam et al, 2022 ).…”