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Travelling waves are the physical basis of frequency discrimination in many vertebrate and invertebrate taxa, including mammals, birds, and some insects. In bushcrickets (Tettigoniidae), the crista acustica is the hearing organ that has been shown to use sound-induced travelling waves. Up to now, data on mechanical characteristics of sound-induced travelling waves were only available along the longitudinal (proximal-distal) direction. In this study, we use laser Doppler vibrometry to investigate in-vivo radial (anterior-posterior) features of travelling waves in the tropical bushcricket Mecopoda elongata. Our results demonstrate that the maximum of sound-induced travelling wave amplitude response is always shifted towards the anterior part of the crista acustica. This lateralization of the travelling wave response induces a tilt in the motion of the crista acustica, which presumably optimizes sensory transduction by exerting a shear motion on the sensory cilia in this hearing organ.
In mammals, acoustic communication plays an important role during social behaviors. Despite their ethological relevance, the mechanisms by which the auditory cortex represents different communication call properties remain elusive. Recent studies have pointed out that communication-sound encoding could be based on discharge patterns of neuronal populations. Following this idea, we investigated whether the activity of local neuronal networks, such as those occurring within individual cortical columns, is sufficient for distinguishing between sounds that differed in their spectro-temporal properties. To accomplish this aim, we analyzed simple pure-tone and complex communication call elicited multi-unit activity (MUA) as well as local field potentials (LFP), and current source density (CSD) waveforms at the single-layer and columnar level from the primary auditory cortex of anesthetized Mongolian gerbils. Multi-dimensional scaling analysis was used to evaluate the degree of “call-specificity” in the evoked activity. The results showed that whole laminar profiles segregated 1.8-2.6 times better across calls than single-layer activity. Also, laminar LFP and CSD profiles segregated better than MUA profiles. Significant differences between CSD profiles evoked by different sounds were more pronounced at mid and late latencies in the granular and infragranular layers and these differences were based on the absence and/or presence of current sinks and on sink timing. The stimulus-specific activity patterns observed within cortical columns suggests that the joint activity of local cortical populations (as local as single columns) could indeed be important for encoding sounds that differ in their acoustic attributes.
Deviance detection describes an increase of neural response strength caused by a stimulus with a low probability of occurrence. This ubiquitous phenomenon has been reported for multiple species, from subthalamic areas to auditory cortex. While cortical deviance detection has been well characterised by a range of studies covering neural activity at population level (mismatch negativity, MMN) as well as at cellular level (stimulus-specific adaptation, SSA), subcortical deviance detection has been studied mainly on cellular level in the form of SSA. Here, we aim to bridge this gap by using noninvasively recorded auditory brainstem responses (ABRs) to investigate deviance detection at population level in the lower stations of the auditory system of a hearing specialist: the bat Carollia perspicillata. Our present approach uses behaviourally relevant vocalisation stimuli that are closer to the animals' natural soundscape than artificial stimuli used in previous studies that focussed on subcortical areas. We show that deviance detection in ABRs is significantly stronger for echolocation pulses than for social communication calls or artificial sounds, indicating that subthalamic deviance detection depends on the behavioural meaning of a stimulus. Additionally, complex physical sound features like frequency- and amplitude-modulation affected the strength of deviance detection in the ABR. In summary, our results suggest that at population level, the bat brain can detect different types of deviants already in the brainstem. This shows that subthalamic brain structures exhibit more advanced forms of deviance detection than previously known.
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.