Dissociable Roles of the Auditory Midbrain and Cortex in Processing the Statistical Features of Natural Sound Textures.

Sound texture perception takes advantage of a hierarchy of time-averaged statistical features of acoustic stimuli, but much remains unclear about how these statistical features are processed along the auditory pathway. Here, we compared the neural representation of sound textures in the inferior colliculus (IC) and auditory cortex (AC) of anesthetized female rats. We recorded responses to texture morph stimuli that gradually add statistical features of increasingly higher complexity. For each texture, several different exemplars were synthesized using different random seeds. An analysis of transient and ongoing multiunit responses showed that the IC units were sensitive to every type of statistical feature, albeit to a varying extent. In contrast, only a small proportion of AC units were overtly sensitive to any statistical features. Differences in texture types explained more of the variance of IC neural responses than did differences in exemplars, indicating a degree of "texture type tuning" in the IC, but the same was, perhaps surprisingly, not the case for AC responses. We also evaluated the accuracy of texture type classification from single-trial population activity and found that IC responses became more informative as more summary statistics were included in the texture morphs, while for AC population responses, classification performance remained consistently very low. These results argue against the idea that AC neurons encode sound type via an overt sensitivity in neural firing rate to fine-grain spectral and temporal statistical features.

The precedence effect in spatial hearing manifests in cortical neural population responses.

BACKGROUND: To localize sound sources accurately in a reverberant environment, human binaural hearing strongly favors analyzing the initial wave front of sounds. Behavioral studies of this "precedence effect" have so far largely been confined to human subjects, limiting the scope of complementary physiological approaches. Similarly, physiological studies have mostly looked at neural responses in the inferior colliculus, the main relay point between the inner ear and the auditory cortex, or used modeling of cochlear auditory transduction in an attempt to identify likely underlying mechanisms. Studies capable of providing a direct comparison of neural coding and behavioral measures of sound localization under the precedence effect are lacking. RESULTS: We adapted a "temporal weighting function" paradigm previously developed to quantify the precedence effect in human for use in laboratory rats. The animals learned to lateralize click trains in which each click in the train had a different interaural time difference. Computing the "perceptual weight" of each click in the train revealed a strong onset bias, very similar to that reported for humans. Follow-on electrocorticographic recording experiments revealed that onset weighting of interaural time differences is a robust feature of the cortical population response, but interestingly, it often fails to manifest at individual cortical recording sites. CONCLUSION: While previous studies suggested that the precedence effect may be caused by early processing mechanisms in the cochlea or inhibitory circuitry in the brainstem and midbrain, our results indicate that the precedence effect is not fully developed at the level of individual recording sites in the auditory cortex, but robust and consistent precedence effects are observable only in the auditory cortex at the level of cortical population responses. This indicates that the precedence effect emerges at later cortical processing stages and is a significantly "higher order" feature than has hitherto been assumed.

Contrast gain control occurs independently of both parvalbumin-positive interneuron activity and shunting inhibition in auditory cortex.

Contrast gain control is the systematic adjustment of neuronal gain in response to the contrast of sensory input. It is widely observed in sensory cortical areas and has been proposed to be a canonical neuronal computation. Here, we investigated whether shunting inhibition from parvalbumin-positive interneurons-a mechanism involved in gain control in visual cortex-also underlies contrast gain control in auditory cortex. First, we performed extracellular recordings in the auditory cortex of anesthetized male mice and optogenetically manipulated the activity of parvalbumin-positive interneurons while varying the contrast of the sensory input. We found that both activation and suppression of parvalbumin interneuron activity altered the overall gain of cortical neurons. However, despite these changes in overall gain, we found that manipulating parvalbumin interneuron activity did not alter the strength of contrast gain control in auditory cortex. Furthermore, parvalbumin-positive interneurons did not show increases in activity in response to high-contrast stimulation, which would be expected if they drive contrast gain control. Finally, we performed in vivo whole-cell recordings in auditory cortical neurons during high- and low-contrast stimulation and found that no increase in membrane conductance was observed during high-contrast stimulation. Taken together, these findings indicate that while parvalbumin-positive interneuron activity modulates the overall gain of auditory cortical responses, other mechanisms are primarily responsible for contrast gain control in this cortical area.NEW & NOTEWORTHY We investigated whether contrast gain control is mediated by shunting inhibition from parvalbumin-positive interneurons in auditory cortex. We performed extracellular and intracellular recordings in mouse auditory cortex while presenting sensory stimuli with varying contrasts and manipulated parvalbumin-positive interneuron activity using optogenetics. We show that while parvalbumin-positive interneuron activity modulates the gain of cortical responses, this activity is not the primary mechanism for contrast gain control in auditory cortex.

Microsecond sensitivity to envelope interaural time differences in rats.

Currently, there is controversy around whether rats can use interaural time differences (ITDs) to localize sound. Here, naturalistic pulse train stimuli were used to evaluate the rat's sensitivity to onset and ongoing ITDs using a two-alternative forced choice sound lateralization task. Pulse rates between 50 Hz and 4.8 kHz with rectangular or Hanning windows were delivered with ITDs between ±175 µs over a near-field acoustic setup. Similar to other mammals, rats performed with 75% accuracy at ∼50 µs ITD, demonstrating that rats are highly sensitive to envelope ITDs.

What's what in auditory cortices?

Distinct anatomical and functional pathways are postulated for analysing a sound's object-related ('what') and space-related ('where') information. It remains unresolved to which extent distinct or overlapping neural resources subserve specific object-related dimensions (i.e. who is speaking and what is being said can both be derived from the same acoustic input). To address this issue, we recorded high-density auditory evoked potentials (AEPs) while participants selectively attended and discriminated sounds according to their pitch, speaker identity, uttered syllable ('what' dimensions) or their location ('where'). Sound acoustics were held constant across blocks; the only manipulation involved the sound dimension that participants had to attend to. The task-relevant dimension was varied across blocks. AEPs from healthy participants were analysed within an electrical neuroimaging framework to differentiate modulations in response strength from modulations in response topography; the latter of which forcibly follow from changes in the configuration of underlying sources. There were no behavioural differences in discrimination of sounds across the 4 feature dimensions. As early as 90ms post-stimulus onset, AEP topographies differed across 'what' conditions, supporting a functional sub-segregation within the auditory 'what' pathway. This study characterises the spatio-temporal dynamics of segregated, yet parallel, processing of multiple sound object-related feature dimensions when selective attention is directed to them.

Contrast gain control in mouse auditory cortex.

The neocortex is thought to employ a number of canonical computations, but little is known about whether these computations rely on shared mechanisms across different neural populations. In recent years, the mouse has emerged as a powerful model organism for the dissection of the circuits and mechanisms underlying various aspects of neural processing and therefore provides an important avenue for research into putative canonical computations. One such computation is contrast gain control, the systematic adjustment of neural gain in accordance with the contrast of sensory input, which helps to construct neural representations that are robust to the presence of background stimuli. Here, we characterized contrast gain control in the mouse auditory cortex. We performed laminar extracellular recordings in the auditory cortex of the anesthetized mouse while varying the contrast of the sensory input. We observed that an increase in stimulus contrast resulted in a compensatory reduction in the gain of neural responses, leading to representations in the mouse auditory cortex that are largely contrast invariant. Contrast gain control was present in all cortical layers but was found to be strongest in deep layers, indicating that intracortical mechanisms may contribute to these gain changes. These results lay a foundation for investigations into the mechanisms underlying contrast adaptation in the mouse auditory cortex. NEW & NOTEWORTHY We investigated whether contrast gain control, the systematic reduction in neural gain in response to an increase in sensory contrast, exists in the mouse auditory cortex. We performed extracellular recordings in the mouse auditory cortex while presenting sensory stimuli with varying contrasts and found this form of processing was widespread. This finding provides evidence that contrast gain control may represent a canonical cortical computation and lays a foundation for investigations into the underlying mechanisms.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing.

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear-nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT: An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too.

Midbrain adaptation may set the stage for the perception of musical beat.

The ability to spontaneously feel a beat in music is a phenomenon widely believed to be unique to humans. Though beat perception involves the coordinated engagement of sensory, motor and cognitive processes in humans, the contribution of low-level auditory processing to the activation of these networks in a beat-specific manner is poorly understood. Here, we present evidence from a rodent model that midbrain preprocessing of sounds may already be shaping where the beat is ultimately felt. For the tested set of musical rhythms, on-beat sounds on average evoked higher firing rates than off-beat sounds, and this difference was a defining feature of the set of beat interpretations most commonly perceived by human listeners over others. Basic firing rate adaptation provided a sufficient explanation for these results. Our findings suggest that midbrain adaptation, by encoding the temporal context of sounds, creates points of neural emphasis that may influence the perceptual emergence of a beat.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

Constructing noise-invariant representations of sound in the auditory pathway.

Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics. Here we investigated the extent of neuronal adaptation to the mean and contrast of auditory stimulation as one ascends the auditory pathway. We measured these forms of adaptation by presenting complex synthetic and natural sounds, recording neuronal responses in the inferior colliculus and primary fields of the auditory cortex of anaesthetized ferrets, and comparing these responses with a sophisticated model of the auditory nerve. We find that the strength of both forms of adaptation increases as one ascends the auditory pathway. To investigate whether this adaptation to stimulus statistics contributes to the construction of noise-invariant sound representations, we also presented complex, natural sounds embedded in stationary noise, and used a decoding approach to assess the noise tolerance of the neuronal population code. We find that the code for complex sounds in the periphery is affected more by the addition of noise than the cortical code. We also find that noise tolerance is correlated with adaptation to stimulus statistics, so that populations that show the strongest adaptation to stimulus statistics are also the most noise-tolerant. This suggests that the increase in adaptation to sound statistics from auditory nerve to midbrain to cortex is an important stage in the construction of noise-invariant sound representations in the higher auditory brain.

Temporal predictability enhances auditory detection.

Periodic stimuli are common in natural environments and are ecologically relevant, for example, footsteps and vocalizations. This study reports a detectability enhancement for temporally cued, periodic sequences. Target noise bursts (embedded in background noise) arriving at the time points which followed on from an introductory, periodic "cue" sequence were more easily detected (by ∼1.5 dB SNR) than identical noise bursts which randomly deviated from the cued temporal pattern. Temporal predictability and corresponding neuronal "entrainment" have been widely theorized to underlie important processes in auditory scene analysis and to confer perceptual advantage. This is the first study in the auditory domain to clearly demonstrate a perceptual enhancement of temporally predictable, near-threshold stimuli.

Spectrotemporal contrast kernels for neurons in primary auditory cortex.

Auditory neurons are often described in terms of their spectrotemporal receptive fields (STRFs). These map the relationship between features of the sound spectrogram and firing rates of neurons. Recently, we showed that neurons in the primary fields of the ferret auditory cortex are also subject to gain control: when sounds undergo smaller fluctuations in their level over time, the neurons become more sensitive to small-level changes (Rabinowitz et al., 2011). Just as STRFs measure the spectrotemporal features of a sound that lead to changes in the firing rates of neurons, in this study, we sought to estimate the spectrotemporal regions in which sound statistics lead to changes in the gain of neurons. We designed a set of stimuli with complex contrast profiles to characterize these regions. This allowed us to estimate the STRFs of cortical neurons alongside a set of spectrotemporal contrast kernels. We find that these two sets of integration windows match up: the extent to which a stimulus feature causes the firing rate of a neuron to change is strongly correlated with the extent to which the contrast of that feature modulates the gain of the neuron. Adding contrast kernels to STRF models also yields considerable improvements in the ability to capture and predict how auditory cortical neurons respond to statistically complex sounds.

Temporal predictability as a grouping cue in the perception of auditory streams.

This study reports a role of temporal regularity on the perception of auditory streams. Listeners were presented with two-tone sequences in an A-B-A-B rhythm that was either regular or had a controlled amount of temporal jitter added independently to each of the B tones. Subjects were asked to report whether they perceived one or two streams. The percentage of trials in which two streams were reported substantially and significantly increased with increasing amounts of temporal jitter. This suggests that temporal predictability may serve as a binding cue during auditory scene analysis.

Spectral timbre perception in ferrets: discrimination of artificial vowels under different listening conditions.

Spectral timbre is an acoustic feature that enables human listeners to determine the identity of a spoken vowel. Despite its importance to sound perception, little is known about the neural representation of sound timbre and few psychophysical studies have investigated timbre discrimination in non-human species. In this study, ferrets were positively conditioned to discriminate artificial vowel sounds in a two-alternative-forced-choice paradigm. Animals quickly learned to discriminate the vowel sound /u/ from /ε/ and were immediately able to generalize across a range of voice pitches. They were further tested in a series of experiments designed to assess how well they could discriminate these vowel sounds under different listening conditions. First, a series of morphed vowels was created by systematically shifting the location of the first and second formant frequencies. Second, the ferrets were tested with single formant stimuli designed to assess which spectral cues they could be using to make their decisions. Finally, vowel discrimination thresholds were derived in the presence of noise maskers presented from either the same or a different spatial location. These data indicate that ferrets show robust vowel discrimination behavior across a range of listening conditions and that this ability shares many similarities with human listeners.

The unity hypothesis revisited: can the male/female incongruent McGurk effect be disrupted by familiarization and priming?

The unity assumption hypothesis contends that higher-level factors, such as a perceiver's belief and prior experience, modulate multisensory integration. The McGurk illusion exemplifies such integration. When a visual velar consonant /ga/ is dubbed with an auditory bilabial /ba/, listeners unify the discrepant signals with knowledge that open lips cannot produce /ba/ and a fusion percept /da/ is perceived. Previous research claimed to have falsified the unity assumption hypothesis by demonstrating the McGurk effect occurs even when a face is dubbed with a voice of the opposite sex, and thus violates expectations from prior experience. But perhaps stronger counter-evidence is needed to prevent perceptual unity than just an apparent incongruence between unfamiliar faces and voices. Here we investigated whether the McGurk illusion with male/female incongruent stimuli can be disrupted by familiarization and priming with an appropriate pairing of face and voice. In an online experiment, the susceptibility of participants to the McGurk illusion was tested with stimuli containing either a male or female face with a voice of incongruent gender. The number of times participants experienced a McGurk illusion was measured before and after a familiarization block, which familiarized them with the true pairings of face and voice. After familiarization and priming, the susceptibility to the McGurk effects decreased significantly on average. The findings support the notion that unity assumptions modulate intersensory bias, and confirm and extend previous studies using male/female incongruent McGurk stimuli.

Cross-modal implicit learning of random time patterns.

Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, implicit learning of temporal patterns in one modality can also improve their processing in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers using electroencephalography (EEG), while participants were exposed to brief sequences of randomly timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment across both modalities (Transfer) or only within a modality (Control), enabling implicit learning in one modality and its transfer. Using a novel method of analysis of single-trial EEG responses, we showed that learning temporal structures within and across modalities is reflected in neural learning curves. These putative neural correlates of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. The modality-specific mechanisms for learning of temporal information and general mechanisms which mediate learning transfer across modalities had distinct physiological signatures: temporal learning within modalities relied on modality-specific brain regions while learning transfer affected beta-band activity in frontal regions.

The laminar and temporal structure of stimulus information in the phase of field potentials of auditory cortex.

Recent studies have shown that the phase of low-frequency local field potentials (LFPs) in sensory cortices carries a significant amount of information about complex naturalistic stimuli, yet the laminar circuit mechanisms and the aspects of stimulus dynamics responsible for generating this phase information remain essentially unknown. Here we investigated these issues by means of an information theoretic analysis of LFPs and current source densities (CSDs) recorded with laminar multi-electrode arrays in the primary auditory area of anesthetized rats during complex acoustic stimulation (music and broadband 1/f stimuli). We found that most LFP phase information originated from discrete "CSD events" consisting of granular-superficial layer dipoles of short duration and large amplitude, which we hypothesize to be triggered by transient thalamocortical activation. These CSD events occurred at rates of 2-4 Hz during both stimulation with complex sounds and silence. During stimulation with complex sounds, these events reliably reset the LFP phases at specific times during the stimulation history. These facts suggest that the informativeness of LFP phase in rat auditory cortex is the result of transient, large-amplitude events, of the "evoked" or "driving" type, reflecting strong depolarization in thalamo-recipient layers of cortex. Finally, the CSD events were characterized by a small number of discrete types of infragranular activation. The extent to which infragranular regions were activated was stimulus dependent. These patterns of infragranular activations may reflect a categorical evaluation of stimulus episodes by the local circuit to determine whether to pass on stimulus information through the output layers.

Multiplexed and robust representations of sound features in auditory cortex.

We can recognize the melody of a familiar song when it is played on different musical instruments. Similarly, an animal must be able to recognize a warning call whether the caller has a high-pitched female or a lower-pitched male voice, and whether they are sitting in a tree to the left or right. This type of perceptual invariance to "nuisance" parameters comes easily to listeners, but it is unknown whether or how such robust representations of sounds are formed at the level of sensory cortex. In this study, we investigate whether neurons in both core and belt areas of ferret auditory cortex can robustly represent the pitch, formant frequencies, or azimuthal location of artificial vowel sounds while the other two attributes vary. We found that the spike rates of the majority of cortical neurons that are driven by artificial vowels carry robust representations of these features, but the most informative temporal response windows differ from neuron to neuron and across five auditory cortical fields. Furthermore, individual neurons can represent multiple features of sounds unambiguously by independently modulating their spike rates within distinct time windows. Such multiplexing may be critical to identifying sounds that vary along more than one perceptual dimension. Finally, we observed that formant information is encoded in cortex earlier than pitch information, and we show that this time course matches ferrets' behavioral reaction time differences on a change detection task.

Cochlear-implant Mandarin tone recognition with a disyllabic word corpus.

Despite pitch being considered the primary cue for discriminating lexical tones, there are secondary cues such as loudness contour and duration, which may allow some cochlear implant (CI) tone discrimination even with severely degraded pitch cues. To isolate pitch cues from other cues, we developed a new disyllabic word stimulus set (Di) whose primary (pitch) and secondary (loudness) cue varied independently. This Di set consists of 270 disyllabic words, each having a distinct meaning depending on the perceived tone. Thus, listeners who hear the primary pitch cue clearly may hear a different meaning from listeners who struggle with the pitch cue and must rely on the secondary loudness contour. A lexical tone recognition experiment was conducted, which compared Di with a monosyllabic set of natural recordings. Seventeen CI users and eight normal-hearing (NH) listeners took part in the experiment. Results showed that CI users had poorer pitch cues encoding and their tone recognition performance was significantly influenced by the "missing" or "confusing" secondary cues with the Di corpus. The pitch-contour-based tone recognition is still far from satisfactory for CI users compared to NH listeners, even if some appear to integrate multiple cues to achieve high scores. This disyllabic corpus could be used to examine the performance of pitch recognition of CI users and the effectiveness of pitch cue enhancement based Mandarin tone enhancement strategies. The Di corpus is freely available online: https://github.com/BetterCI/DiTone.