Sparse and background-invariant coding of vocalizations in auditory scenes

Detection of Individual Differences Encoded in Sequential Variations of Elements in Zebra Finch Songs

Zebra finches sing individually unique songs and recognize conspecific songs and individual identities in songs. Their songs comprise several syllables/elements that share acoustic features within the species, with unique sequential arrangements. However, the neuronal mechanisms underlying the detection of individual differences and species specificity have yet to be elucidated. Herein, we examined the neuronal auditory responsiveness of neurons in the higher auditory area, the caudal nidopallium (NCM), to songs and their elements in male zebra finches to understand the mechanism for detecting species and individual identities in zebra finch songs. We found that various adult male zebra finch songs share acoustically similar song elements but differ in their sequential arrangement between individuals. The broader spiking (BS) neurons in the NCM detected only a small subset of zebra finch songs, whereas NCM BS neurons, as a neuronal ensemble, responded to all zebra finch songs. Notably, distinct combinations of BS neurons responded to each of the 18 presented songs in one bird. Subsets of NCM BS neurons were sensitive to sequential arrangements of species-specific elements, which dramatically increasing the capacity for song variation with a limited number of species-specific elements. The naive Bayes decoder analysis further showed that the response of sequence-sensitive BS neurons increased the accuracy of song stimulus predictions based on the response strength of neuronal ensembles. Our results suggest the neuronal mechanisms that NCM neurons as an ensemble decode the individual identities of songs, while each neuron detects a small subset of song elements and their sequential arrangement.

Parsing social context in auditory forebrain of male zebra finches

To understand the influence of natural behavioral context on neural activity requires studying awake-behaving animals. Microdrive devices facilitate bridging behavior and physiology to examine neural dynamics across behavioral contexts. Impediments to long-term single unit recordings in awake-behaving animals include tradeoffs between weight, functional flexibility, expense, and fabrication difficulty in microdrive devices. We describe a straightforward and low-cost method to fabricate versatile and lightweight microdrives that remain functional for months in awake-behaving zebra finches (Taeniopygia guttata). The vocal and gregarious nature of zebra finches provide an opportunity to investigate neural representations of social and behavioral context. Using microdrives, we report how auditory responses in an auditory association region of the pallium are modulated by two naturalistic contexts: self- vs. externally-generated song (behavioral context), and solitary vs. social listening (social context). While auditory neurons exhibited invariance across behavioral contexts, in a social context, response strength and stimulus selectivity were greater in a social condition. We also report stimulus-specific correlates of audition in local field potentials. Using a versatile, lightweight, and accessible microdrive design for small animals, we find that the auditory forebrain represents social but not behavioral context in awake-behaving animals.

The Temporal Organization of Learned Vocal Behavior Is Predicted by Species Rather Than Experience

Birdsong is hierarchically organized in time, like speech and other communication behaviors. Syllables are produced in sequences to form song motifs and bouts. While syllables are copied from tutors, the factors that determine song temporal organization, including syllable sequencing (syntax), are unknown. Here, we tested the roles of learning and species genetics in song organization. We manipulated juvenile song experience and genetics in three species of estrildid finches (zebra finches, Taeniopygia guttata castanotis; long-tailed finches, Poephila acuticauda; Bengalese finches, Lonchura striata var. domestica). We analyzed the adult songs of male birds that were: (1) tutored by conspecifics; (2) untutored; (3) tutored by heterospecifics; and (4) genetic hybrids. Song macrostructure, syllable sequencing, and syllable timing were quantified and compared within and across species. Results showed that song organization was consistent within a species and differed across species, regardless of experience. Temporal features did not differ between tutored and untutored birds of the same species. The songs of birds tutored by other species were composed of heterospecific syllables produced in sequences typical of conspecific songs. The songs of genetic hybrids showed the organization of both parental species, despite the fact that only males sing. Results indicate that song organization is predicted by species rather than experience.

A Complex Acoustical Environment During Development Enhances Auditory Perception and Coding Efficiency in the Zebra Finch

Sensory experience during development has lasting effects on perception and neural processing. Exposing juvenile animals to artificial stimuli influences the tuning and functional organization of the auditory cortex, but less is known about how the rich acoustical environments experienced by vocal communicators affect the processing of complex vocalizations. Here, we show that in zebra finches (Taeniopygia guttata), a colonial-breeding songbird species, exposure to a naturalistic social-acoustical environment during development has a profound impact on auditory perceptual behavior and on cortical-level auditory responses to conspecific song. Compared to birds raised by pairs in acoustic isolation, male and female birds raised in a breeding colony were better in an operant discrimination task at recognizing conspecific songs with and without masking colony noise. Neurons in colony-reared birds had higher average firing rates, selectivity, and discriminability, especially in the narrow-spiking, putatively inhibitory neurons of a higher-order auditory area, the caudomedial nidopallium (NCM). Neurons in colony-reared birds were also less correlated in their tuning, more efficient at encoding the spectrotemporal structure of conspecific song, and better at filtering out masking noise. These results suggest that the auditory cortex adapts to noisy, complex acoustical environments by strengthening inhibitory circuitry, functionally decoupling excitatory neurons while maintaining overall excitatory-inhibitory balance.

Noise schemas aid hearing in noise

Human hearing is robust to noise, but the basis of this robustness is poorly understood. Several lines of evidence are consistent with the idea that the auditory system adapts to sound components that are stable over time, potentially achieving noise robustness by suppressing noise-like signals. Yet background noise often provides behaviorally relevant information about the environment and thus seems unlikely to be completely discarded by the auditory system. Motivated by this observation, we explored whether noise robustness might instead be mediated by internal models of noise structure that could facilitate the separation of background noise from other sounds. We found that detection, recognition, and localization in real-world background noise were better for foreground sounds positioned later in a noise excerpt, with performance improving over the initial second of exposure to a noise. These results are consistent with both adaptation-based and model-based accounts (adaptation increases over time and online noise estimation should benefit from acquiring more samples). However, performance was also robust to interruptions in the background noise and was enhanced for intermittently recurring backgrounds, neither of which would be expected from known forms of adaptation. Additionally, the performance benefit observed for foreground sounds occurring later within a noise excerpt was reduced for recurring noises, suggesting that a noise representation is built up during exposure to a new background noise and then maintained in memory. These findings suggest that noise robustness is supported by internal models-"noise schemas"-that are rapidly estimated, stored over time, and used to estimate other concurrent sounds.

Developmental encoding of natural sounds in the mouse auditory cortex

Mice communicate through high-frequency ultrasonic vocalizations, which are crucial for social interactions such as courtship and aggression. Although ultrasonic vocalization representation has been found in adult brain areas along the auditory pathway, including the auditory cortex, no evidence is available on the neuronal representation of ultrasonic vocalizations early in life. Using in vivo two-photon calcium imaging, we analyzed auditory cortex layer 2/3 neuronal responses to USVs, pure tones (4 to 90 kHz), and high-frequency modulated sweeps from postnatal day 12 (P12) to P21. We found that ACx neurons are tuned to respond to ultrasonic vocalization syllables as early as P12 to P13, with an increasing number of responsive cells as the mouse age. By P14, while pure tone responses showed a frequency preference, no syllable preference was observed. Additionally, at P14, USVs, pure tones, and modulated sweeps activate clusters of largely nonoverlapping responsive neurons. Finally, we show that while cell correlation decreases with increasing processing of peripheral auditory stimuli, neurons responding to the same stimulus maintain highly correlated spontaneous activity after circuits have attained mature organization, forming neuronal subnetworks sharing similar functional properties.

Social and auditory experience shapes forebrain responsiveness in zebra finches before the sensitive period of vocal learning

Early-life experiences with signals used in communication are instrumental in shaping an animal's social interactions. In songbirds, which use vocalizations for guiding social interactions and mate choice, recent studies show that sensory effects on development occur earlier than previously expected, even in embryos and nestlings. Here, we explored the neural dynamics underlying experience-dependent song categorization in young birds prior to the traditionally studied sensitive period of vocal learning that begins around 3 weeks post-hatch. We raised zebra finches either with their biological parents, cross-fostered by Bengalese finches beginning at embryonic day 9, or with only the non-singing mother from 2 days post-hatch. Then, 1-5 days after fledging, we conducted behavioral experiments and extracellular recordings in the auditory forebrain to test responses to zebra finch and Bengalese finch songs. Auditory forebrain neurons in cross-fostered and isolated birds showed increases in firing rate and decreases in responsiveness and selectivity. In cross-fostered birds, decreases in responsiveness and selectivity relative to white noise were specific to conspecific song stimuli, which paralleled behavioral attentiveness to conspecific songs in those same birds. This study shows that auditory and social experience can already impact song 'type' processing in the brains of nestlings, and that brain changes at this age can portend the effects of natal experience in adults.

A complex acoustical environment during development enhances auditory perception and coding efficiency in the zebra finch

Sensory experience during development has lasting effects on perception and neural processing. Exposing juvenile animals to artificial stimuli influences the tuning and functional organization of the auditory cortex, but less is known about how the rich acoustical environments experienced by vocal communicators affect the processing of complex vocalizations. Here, we show that in zebra finches (Taeniopygia guttata), a colonial-breeding songbird species, exposure to a naturalistic social-acoustical environment during development has a profound impact on auditory perceptual behavior and on cortical-level auditory responses to conspecific song. Compared to birds raised by pairs in acoustic isolation, male and female birds raised in a breeding colony were better in an operant discrimination task at recognizing conspecific songs with and without masking colony noise. Neurons in colony-reared birds had higher average firing rates, selectivity, and discriminability, especially in the narrow-spiking, putatively inhibitory neurons of a higher-order auditory area, the caudomedial nidopallium (NCM). Neurons in colony-reared birds were also less correlated in their tuning and more efficient at encoding the spectrotemporal structure of conspecific song, and better at filtering out masking noise. These results suggest that the auditory cortex adapts to noisy, complex acoustical environments by strengthening inhibitory circuitry, functionally decoupling excitatory neurons while maintaining overall excitatory-inhibitory balance.

Auditory pallial regulation of the social behavior network

Sensory cues such as vocalizations contain important social information. Processing social features of vocalizations (e.g., vocalizer identity, emotional state) necessitates unpacking the complex sound streams in song or speech; this depends on circuits in pallial cortex. But whether and how this information is then transferred to limbic and hypothalamic regions remains a mystery. Here, using gregarious, vocal songbirds (female Zebra finches), we identify a prominent influence of the auditory pallium on one specific node of the Social Behavior Network, the lateral ventromedial nucleus of the hypothalamus (VMHl). Electrophysiological recordings revealed that social and non-social auditory stimuli elicited stimulus-specific spike trains that permitted stimulus differentiation in a large majority of VMHl single units, while transient disruption of auditory pallium elevated immediate early gene activity in VMHl. Descending functional connections such as these may be critical for the range of vertebrate species that rely on nuanced communication signals to guide social decision-making.

Interference of mid-level sound statistics underlie human speech recognition sensitivity in natural noise

Recognizing speech in noise, such as in a busy restaurant, is an essential cognitive skill where the task difficulty varies across environments and noise levels. Although there is growing evidence that the auditory system relies on statistical representations for perceiving 1-5 and coding4,6-9 natural sounds, it's less clear how statistical cues and neural representations contribute to segregating speech in natural auditory scenes. We demonstrate that human listeners rely on mid-level statistics to segregate and recognize speech in environmental noise. Using natural backgrounds and variants with perturbed spectro-temporal statistics, we show that speech recognition accuracy at a fixed noise level varies extensively across natural backgrounds (0% to 100%). Furthermore, for each background the unique interference created by summary statistics can mask or unmask speech, thus hindering or improving speech recognition. To identify the neural coding strategy and statistical cues that influence accuracy, we developed generalized perceptual regression, a framework that links summary statistics from a neural model to word recognition accuracy. Whereas a peripheral cochlear model accounts for only 60% of perceptual variance, summary statistics from a mid-level auditory midbrain model accurately predicts single trial sensory judgments, accounting for more than 90% of the perceptual variance. Furthermore, perceptual weights from the regression framework identify which statistics and tuned neural filters are influential and how they impact recognition. Thus, perception of speech in natural backgrounds relies on a mid-level auditory representation involving interference of multiple summary statistics that impact recognition beneficially or detrimentally across natural background sounds.

Speech intelligibility prediction based on a physiological model of the human ear and a hierarchical spiking neural network

A speech intelligibility (SI) prediction model is proposed that includes an auditory preprocessing component based on the physiological anatomy and activity of the human ear, a hierarchical spiking neural network, and a decision back-end processing based on correlation analysis. The auditory preprocessing component effectively captures advanced physiological details of the auditory system, such as retrograde traveling waves, longitudinal coupling, and cochlear nonlinearity. The ability of the model to predict data from normal-hearing listeners under various additive noise conditions was considered. The predictions closely matched the experimental test data under all conditions. Furthermore, we developed a lumped mass model of a McGee stainless-steel piston with the middle-ear to study the recovery of individuals with otosclerosis. We show that the proposed SI model accurately simulates the effect of middle-ear intervention on SI. Consequently, the model establishes a model-based relationship between objective measures of human ear damage, like distortion product otoacoustic emissions, and speech perception. Moreover, the SI model can serve as a robust tool for optimizing parameters and for preoperative assessment of artificial stimuli, providing a valuable reference for clinical treatments of conductive hearing loss.

Noises on-How the Brain Deals with Acoustic Noise

What is noise? When does a sound form part of the acoustic background and when might it come to our attention as part of the foreground? Our brain seems to filter out irrelevant sounds in a seemingly effortless process, but how this is achieved remains opaque and, to date, unparalleled by any algorithm. In this review, we discuss how noise can be both background and foreground, depending on what a listener/brain is trying to achieve. We do so by addressing questions concerning the brain's potential bias to interpret certain sounds as part of the background, the extent to which the interpretation of sounds depends on the context in which they are heard, as well as their ethological relevance, task-dependence, and a listener's overall mental state. We explore these questions with specific regard to the implicit, or statistical, learning of sounds and the role of feedback loops between cortical and subcortical auditory structures.

Tutor auditory memory for guiding sensorimotor learning in birdsong

Memory-guided motor shaping is necessary for sensorimotor learning. Vocal learning, such as speech development in human babies and song learning in bird juveniles, begins with the formation of an auditory template by hearing adult voices followed by vocally matching to the memorized template using auditory feedback. In zebra finches, the widely used songbird model system, only males develop individually unique stereotyped songs. The production of normal songs relies on auditory experience of tutor's songs (commonly their father's songs) during a critical period in development that consists of orchestrated auditory and sensorimotor phases. "Auditory templates" of tutor songs are thought to form in the brain to guide later vocal learning, while formation of "motor templates" of own song has been suggested to be necessary for the maintenance of stereotyped adult songs. Where these templates are formed in the brain and how they interact with other brain areas to guide song learning, presumably with template-matching error correction, remains to be clarified. Here, we review and discuss studies on auditory and motor templates in the avian brain. We suggest that distinct auditory and motor template systems exist that switch their functions during development.

Social reinforcement guides operant behaviour and auditory learning in a songbird

Motivation to seek social interactions is inherent to all social species. For instance, even with risk of disease transmission in a recent pandemic, humans sought out frequent in-person social interactions. In other social animals, socialization can be prioritized even over water or food consumption. Zebra finches, Taeniopygia guttata, are highly gregarious songbirds widely used in behavioural and physiological research. Songbirds, like humans, are vocal learners during development, which rely on intense auditory learning. Aside from supporting song learning, auditory learning further supports individual identification, mate choice and outcome associations in songbirds. To study auditory learning in a laboratory setting, studies often employ operant paradigms with food restriction and reinforcement and require complete social isolation, which can result in stress and other unintended physiological consequences for social species. Thus, in this work, we designed an operant behavioural method leveraging the sociality of zebra finches for goal-directed behaviours. Our approach relies on visual social reinforcement, without depriving the animals of food or social contact. Using this task, we found that visual social reinforcement was a strong motivational drive for operant behaviour. Motivation was sensitive to familiarity towards the stimulus animal and higher when engaging with a familiar versus a novel individual. We further show that this tool can be used to assess auditory discrimination learning using either songs or synthetic pure tones as stimuli. As birds gained experience in the task, they developed a strategy to maximize reward acquisition in spite of receiving more punishment, i.e. liberal response bias. Our operant paradigm provides an alternative to tasks using food reinforcement and could be applied to a variety of highly social species, such as rodents and nonhuman primates.

Acute Aromatase Inhibition Impairs Neural and Behavioral Auditory Scene Analysis in Zebra Finches

Auditory perception can be significantly disrupted by noise. To discriminate sounds from noise, auditory scene analysis (ASA) extracts the functionally relevant sounds from acoustic input. The zebra finch communicates in noisy environments. Neurons in their secondary auditory pallial cortex (caudomedial nidopallium, NCM) can encode song from background chorus, or scenes, and this capacity may aid behavioral ASA. Furthermore, song processing is modulated by the rapid synthesis of neuroestrogens when hearing conspecific song. To examine whether neuroestrogens support neural and behavioral ASA in both sexes, we retrodialyzed fadrozole (aromatase inhibitor, FAD) and recorded in vivo awake extracellular NCM responses to songs and scenes. We found that FAD affected neural encoding of songs by decreasing responsiveness and timing reliability in inhibitory (narrow-spiking), but not in excitatory (broad-spiking) neurons. Congruently, FAD decreased neural encoding of songs in scenes for both cell types, particularly in females. Behaviorally, we trained birds using operant conditioning and tested their ability to detect songs in scenes after administering FAD orally or injected bilaterally into NCM. Oral FAD increased response bias and decreased correct rejections in females, but not in males. FAD in NCM did not affect performance. Thus, FAD in the NCM impaired neuronal ASA but that did not lead to behavioral disruption suggesting the existence of resilience or compensatory responses. Moreover, impaired performance after systemic FAD suggests involvement of other aromatase-rich networks outside the auditory pathway in ASA. This work highlights how transient estrogen synthesis disruption can modulate higher-order processing in an animal model of vocal communication.

Increased reliance on temporal coding when target sound is softer than the background

Everyday environments often contain multiple concurrent sound sources that fluctuate over time. Normally hearing listeners can benefit from high signal-to-noise ratios (SNRs) in energetic dips of temporally fluctuating background sound, a phenomenon called dip-listening. Specialized mechanisms of dip-listening exist across the entire auditory pathway. Both the instantaneous fluctuating and the long-term overall SNR shape dip-listening. An unresolved issue regarding cortical mechanisms of dip-listening is how target perception remains invariant to overall SNR, specifically, across different tone levels with an ongoing fluctuating masker. Equivalent target detection over both positive and negative overall SNRs (SNR invariance) is reliably achieved in highly-trained listeners. Dip-listening is correlated with the ability to resolve temporal fine structure, which involves temporally-varying spike patterns. Thus the current work tests the hypothesis that at negative SNRs, neuronal readout mechanisms need to increasingly rely on decoding strategies based on temporal spike patterns, as opposed to spike count. Recordings from chronically implanted electrode arrays in core auditory cortex of trained and awake Mongolian gerbils that are engaged in a tone detection task in 10 Hz amplitude-modulated background sound reveal that rate-based decoding is not SNR-invariant, whereas temporal coding is informative at both negative and positive SNRs.

Can Extensive Training Transform a Mouse into a Guinea Pig? An Evaluation Based on the Discriminative Abilities of Inferior Colliculus Neurons

Humans and animals maintain accurate discrimination between communication sounds in the presence of loud sources of background noise. In previous studies performed in anesthetized guinea pigs, we showed that, in the auditory pathway, the highest discriminative abilities between conspecific vocalizations were found in the inferior colliculus. Here, we trained CBA/J mice in a Go/No-Go task to discriminate between two similar guinea pig whistles, first in quiet conditions, then in two types of noise, a stationary noise and a chorus noise at three SNRs. Control mice were passively exposed to the same number of whistles as trained mice. After three months of extensive training, inferior colliculus (IC) neurons were recorded under anesthesia and the responses were quantified as in our previous studies. In quiet, the mean values of the firing rate, the temporal reliability and mutual information obtained from trained mice were higher than from the exposed mice and the guinea pigs. In stationary and chorus noise, there were only a few differences between the trained mice and the guinea pigs; and the lowest mean values of the parameters were found in the exposed mice. These results suggest that behavioral training can trigger plasticity in IC that allows mice neurons to reach guinea pig-like discrimination abilities.

Original speech and its echo are segregated and separately processed in the human brain

Speech recognition crucially relies on slow temporal modulations (<16 Hz) in speech. Recent studies, however, have demonstrated that the long-delay echoes, which are common during online conferencing, can eliminate crucial temporal modulations in speech but do not affect speech intelligibility. Here, we investigated the underlying neural mechanisms. MEG experiments demonstrated that cortical activity can effectively track the temporal modulations eliminated by an echo, which cannot be fully explained by basic neural adaptation mechanisms. Furthermore, cortical responses to echoic speech can be better explained by a model that segregates speech from its echo than by a model that encodes echoic speech as a whole. The speech segregation effect was observed even when attention was diverted but would disappear when segregation cues, i.e., speech fine structure, were removed. These results strongly suggested that, through mechanisms such as stream segregation, the auditory system can build an echo-insensitive representation of speech envelope, which can support reliable speech recognition.

Convergent Circuit Computation for Categorization in the Brains of Primates and Songbirds

Categorization is crucial for behavioral flexibility because it enables animals to group stimuli into meaningful classes that can easily be generalized to new circumstances. A most abstract quantitative category is set size, the number of elements in a set. This review explores how categorical number representations are realized by the operations of excitatory and inhibitory neurons in associative telencephalic microcircuits in primates and songbirds. Despite the independent evolution of the primate prefrontal cortex and the avian nidopallium caudolaterale, the neuronal computations of these associative pallial circuits show surprising correspondence. Comparing cellular functions in distantly related taxa can inform about the evolutionary principles of circuit computations for cognition in distinctly but convergently realized brain structures.

The neurobiology of vocal communication in marmosets

An increasingly popular animal model for studying the neural basis of social behavior, cognition, and communication is the common marmoset (Callithrix jacchus). Interest in this New World primate across neuroscience is now being driven by their proclivity for prosociality across their repertoire, high volubility, and rapid development, as well as their amenability to naturalistic testing paradigms and freely moving neural recording and imaging technologies. The complement of these characteristics set marmosets up to be a powerful model of the primate social brain in the years to come. Here, we focus on vocal communication because it is the area that has both made the most progress and illustrates the prodigious potential of this species. We review the current state of the field with a focus on the various brain areas and networks involved in vocal perception and production, comparing the findings from marmosets to other animals, including humans.

A robust and compact population code for competing sounds in auditory cortex

Cortical circuits encoding sensory information consist of populations of neurons, yet how information aggregates via pooling individual cells remains poorly understood. Such pooling may be particularly important in noisy settings where single-neuron encoding is degraded. One example is the cocktail party problem, with competing sounds from multiple spatial locations. How populations of neurons in auditory cortex code competing sounds have not been previously investigated. Here, we apply a novel information-theoretic approach to estimate information in populations of neurons in mouse auditory cortex about competing sounds from multiple spatial locations, including both summed population (SP) and labeled line (LL) codes. We find that a small subset of neurons is sufficient to nearly maximize mutual information over different spatial configurations, with the labeled line code outperforming the summed population code and approaching information levels attained in the absence of competing stimuli. Finally, information in the labeled line code increases with spatial separation between target and masker, in correspondence with behavioral results on spatial release from masking in humans and animals. Taken together, our results reveal that a compact population of neurons in auditory cortex provides a robust code for competing sounds from different spatial locations.NEW & NOTEWORTHY Little is known about how populations of neurons within cortical circuits encode sensory stimuli in the presence of competing stimuli at other spatial locations. Here, we investigate this problem in auditory cortex using a recently proposed information-theoretic approach. We find a small subset of neurons nearly maximizes information about target sounds in the presence of competing maskers, approaching information levels for isolated stimuli, and provides a noise-robust code for sounds in a complex auditory scene.

Dynamic encoding of phonetic categories in zebra finch auditory forebrain

Vocal communication requires the formation of acoustic categories to enable invariant representations of sounds despite superficial variations. Humans form acoustic categories for speech phonemes, enabling the listener to recognize words independent of speakers; animals can also discriminate speech phonemes. We investigated the neural mechanisms of this process using electrophysiological recordings from the zebra finch secondary auditory area, caudomedial nidopallium (NCM), during passive exposure to human speech stimuli consisting of two naturally spoken words produced by multiple speakers. Analysis of neural distance and decoding accuracy showed improvements in neural discrimination between word categories over the course of exposure, and this improved representation transferred to the same words by novel speakers. We conclude that NCM neurons formed generalized representations of word categories independent of speaker-specific variations that became more refined over the course of passive exposure. The discovery of this dynamic encoding process in NCM suggests a general processing mechanism for forming categorical representations of complex acoustic signals that humans share with other animals.

Time as a supervisor: temporal regularity and auditory object learning

Sensory systems appear to learn to transform incoming sensory information into perceptual representations, or "objects," that can inform and guide behavior with minimal explicit supervision. Here, we propose that the auditory system can achieve this goal by using time as a supervisor, i.e., by learning features of a stimulus that are temporally regular. We will show that this procedure generates a feature space sufficient to support fundamental computations of auditory perception. In detail, we consider the problem of discriminating between instances of a prototypical class of natural auditory objects, i.e., rhesus macaque vocalizations. We test discrimination in two ethologically relevant tasks: discrimination in a cluttered acoustic background and generalization to discriminate between novel exemplars. We show that an algorithm that learns these temporally regular features affords better or equivalent discrimination and generalization than conventional feature-selection algorithms, i.e., principal component analysis and independent component analysis. Our findings suggest that the slow temporal features of auditory stimuli may be sufficient for parsing auditory scenes and that the auditory brain could utilize these slowly changing temporal features.

Top-down, auditory pallial regulation of the social behavior network

Social encounters rely on sensory cues that carry nuanced information to guide social decision-making. While high-level features of social signals are processed in the telencephalic pallium, nuclei controlling social behaviors, called the social behavior network (SBN), reside mainly in the diencephalon. Although it is well known how mammalian olfactory pallium interfaces with the SBN, there is little information for how pallial processing of other sensory modalities can modulate SBN circuits. This is surprising given the importance of complex vocalizations, for example, for social behavior in many vertebrate taxa such as humans and birds. Using gregarious and highly vocal songbirds, female Zebra finches, we asked to what extent auditory pallial circuits provide consequential input to the SBN as it processes social sensory cues. We transiently inactivated auditory pallium of female Zebra finches during song playback and examined song-induced activation in SBN nuclei. Auditory pallial inactivation impaired responses to song specifically within the lateral ventromedial nucleus of the hypothalamus (VMHl), providing the first evidence in vertebrates of a connection between auditory pallium and the SBN. This same treatment elevated feeding behavior, which also correlated with VMHl activation. This suggests that signals from auditory pallium to VMHl can tune the balance between social attention and feeding drive. A descending influence of sensory pallium on hypothalamic circuits could therefore provide a functional connection for the integration of social stimuli with internal state to influence social decision-making.

Significance

Sensory cues such as vocalizations contain important social information. These social signals can be substantially nuanced, containing information about vocalizer identity, prior experience, valence, and emotional state. Processing these features of vocalizations necessitates processing the fast, complex sound streams in song or speech, which depends on circuits in pallial cortex. But whether and how this information is then transferred to social circuits in limbic and hypothalamic regions remains a mystery. Here, we identify a top-down influence of the songbird auditory pallium on one specific node of the social behavior network within the hypothalamus. Descending functional connections such as these may be critical for the wide range of vertebrate species that rely on intricate sensory communication signals to guide social decision-making.

Sparse ensemble neural code for a complete vocal repertoire

The categorization of animal vocalizations into distinct behaviorally relevant groups for communication is an essential operation that must be performed by the auditory system. This auditory object recognition is a difficult task that requires selectivity to the group identifying acoustic features and invariance to renditions within each group. We find that small ensembles of auditory neurons in the forebrain of a social songbird can code the bird's entire vocal repertoire (∼10 call types). Ensemble neural discrimination is not, however, correlated with single unit selectivity, but instead with how well the joint single unit tunings to characteristic spectro-temporal modulations span the acoustic subspace optimized for the discrimination of call types. Thus, akin to face recognition in the visual system, call type recognition in the auditory system is based on a sparse code representing a small number of high-level features and not on highly selective grandmother neurons.

Deep neural networks effectively model neural adaptation to changing background noise and suggest nonlinear noise filtering methods in auditory cortex

The human auditory system displays a robust capacity to adapt to sudden changes in background noise, allowing for continuous speech comprehension despite changes in background environments. However, despite comprehensive studies characterizing this ability, the computations that underly this process are not well understood. The first step towards understanding a complex system is to propose a suitable model, but the classical and easily interpreted model for the auditory system, the spectro-temporal receptive field (STRF), cannot match the nonlinear neural dynamics involved in noise adaptation. Here, we utilize a deep neural network (DNN) to model neural adaptation to noise, illustrating its effectiveness at reproducing the complex dynamics at the levels of both individual electrodes and the cortical population. By closely inspecting the model's STRF-like computations over time, we find that the model alters both the gain and shape of its receptive field when adapting to a sudden noise change. We show that the DNN model's gain changes allow it to perform adaptive gain control, while the spectro-temporal change creates noise filtering by altering the inhibitory region of the model's receptive field. Further, we find that models of electrodes in nonprimary auditory cortex also exhibit noise filtering changes in their excitatory regions, suggesting differences in noise filtering mechanisms along the cortical hierarchy. These findings demonstrate the capability of deep neural networks to model complex neural adaptation and offer new hypotheses about the computations the auditory cortex performs to enable noise-robust speech perception in real-world, dynamic environments.

A Redundant Cortical Code for Speech Envelope

Animal communication sounds exhibit complex temporal structure because of the amplitude fluctuations that comprise the sound envelope. In human speech, envelope modulations drive synchronized activity in auditory cortex (AC), which correlates strongly with comprehension (Giraud and Poeppel, 2012; Peelle and Davis, 2012; Haegens and Zion Golumbic, 2018). Studies of envelope coding in single neurons, performed in nonhuman animals, have focused on periodic amplitude modulation (AM) stimuli and use response metrics that are not easy to juxtapose with data from humans. In this study, we sought to bridge these fields. Specifically, we looked directly at the temporal relationship between stimulus envelope and spiking, and we assessed whether the apparent diversity across neurons' AM responses contributes to the population representation of speech-like sound envelopes. We gathered responses from single neurons to vocoded speech stimuli and compared them to sinusoidal AM responses in auditory cortex (AC) of alert, freely moving Mongolian gerbils of both sexes. While AC neurons displayed heterogeneous tuning to AM rate, their temporal dynamics were stereotyped. Preferred response phases accumulated near the onsets of sinusoidal AM periods for slower rates (<8 Hz), and an over-representation of amplitude edges was apparent in population responses to both sinusoidal AM and vocoded speech envelopes. Crucially, this encoding bias imparted a decoding benefit: a classifier could discriminate vocoded speech stimuli using summed population activity, while higher frequency modulations required a more sophisticated decoder that tracked spiking responses from individual cells. Together, our results imply that the envelope structure relevant to parsing an acoustic stream could be read-out from a distributed, redundant population code.SIGNIFICANCE STATEMENT Animal communication sounds have rich temporal structure and are often produced in extended sequences, including the syllabic structure of human speech. Although the auditory cortex (AC) is known to play a crucial role in representing speech syllables, the contribution of individual neurons remains uncertain. Here, we characterized the representations of both simple, amplitude-modulated sounds and complex, speech-like stimuli within a broad population of cortical neurons, and we found an overrepresentation of amplitude edges. Thus, a phasic, redundant code in auditory cortex can provide a mechanistic explanation for segmenting acoustic streams like human speech.

Auditory sensitivity and vocal acoustics in five species of estrildid songbirds

Comparative studies of acoustic communication in clades with diverse signal features provide a powerful framework for testing relationships between perception and behaviour. We measured auditory sensitivity in five species of estrildid songbirds with acoustically distinct songs and tested whether differences aligned with species differences in song frequency content. Species were chosen based on phylogeny and differences in song acoustics. Behavioural audiograms were obtained using operant training and testing. Adult audiograms were compared across species and between sexes within a species. Juvenile and adult audiograms were compared in one species. The audiograms of adults reared by their own species and those reared and tutored by another species were compared in one species. Results showed that audiograms were similar across species and similar to previous reports of songbird auditory sensitivity. Species differed in the highest frequency detected and the frequency of peak sensitivity. While hearing frequency range was not correlated with song frequency bandwidth, the frequency of peak sensitivity was highly corelated with the frequency of peak energy in song. Sensitivity did not differ based on sex, age or tutoring experience. Our findings suggest that adaptations in songbird auditory sensitivity are largely constrained by shared peripheral and central encoding mechanisms, with species-specific perception appearing only at peak sensitivity.

Distinct neuronal types contribute to hybrid temporal encoding strategies in primate auditory cortex

Studies of the encoding of sensory stimuli by the brain often consider recorded neurons as a pool of identical units. Here, we report divergence in stimulus-encoding properties between subpopulations of cortical neurons that are classified based on spike timing and waveform features. Neurons in auditory cortex of the awake marmoset (Callithrix jacchus) encode temporal information with either stimulus-synchronized or nonsynchronized responses. When we classified single-unit recordings using either a criteria-based or an unsupervised classification method into regular-spiking, fast-spiking, and bursting units, a subset of intrinsically bursting neurons formed the most highly synchronized group, with strong phase-locking to sinusoidal amplitude modulation (SAM) that extended well above 20 Hz. In contrast with other unit types, these bursting neurons fired primarily on the rising phase of SAM or the onset of unmodulated stimuli, and preferred rapid stimulus onset rates. Such differentiating behavior has been previously reported in bursting neuron models and may reflect specializations for detection of acoustic edges. These units responded to natural stimuli (vocalizations) with brief and precise spiking at particular time points that could be decoded with high temporal stringency. Regular-spiking units better reflected the shape of slow modulations and responded more selectively to vocalizations with overall firing rate increases. Population decoding using time-binned neural activity found that decoding behavior differed substantially between regular-spiking and bursting units. A relatively small pool of bursting units was sufficient to identify the stimulus with high accuracy in a manner that relied on the temporal pattern of responses. These unit type differences may contribute to parallel and complementary neural codes.

Neurons in auditory cortex show highly diverse responses to sounds. This study suggests that neuronal type inferred from baseline firing properties accounts for much of this diversity, with a subpopulation of bursting units being specialized for precise temporal encoding.

A neural circuit perspective on brain aromatase

This review explores the role of aromatase in the brain as illuminated by a set of conserved network-level connections identified in several vertebrate taxa. Aromatase-expressing neurons are neurochemically heterogeneous but the brain regions in which they are found are highly-conserved across the vertebrate lineage. During development, aromatase neurons have a prominent role in sexual differentiation of the brain and resultant sex differences in behavior and human brain diseases. Drawing on literature primarily from birds and rodents, we delineate brain regions that express aromatase and that are strongly interconnected, and suggest that, in many species, aromatase expression essentially defines the Social Behavior Network. Moreover, in several cases the inputs to and outputs from this core Social Behavior Network also express aromatase. Recent advances in molecular and genetic tools for neuroscience now enable in-depth and taxonomically diverse studies of the function of aromatase at the neural circuit level.

Cell-type specific pallial circuits shape categorical tuning responses in the crow telencephalon

The nidopallium caudolaterale (NCL), an integration centre in the telencephalon of birds, plays a crucial role in representing and maintaining abstract categories and concepts. However, the computational principles allowing pallial microcircuits consisting of excitatory and inhibitory neurons to shape the tuning to abstract categories remain elusive. Here we identified the major pallial cell types, putative excitatory projection cells and inhibitory interneurons, by characterizing the waveforms of action potentials recorded in crows performing a cognitively demanding numerical categorization task. Both cell types showed clear differences in their capacity to encode categorical information. Nearby and functionally coupled putative projection neurons generally exhibited similar tuning, whereas putative interneurons showed mainly opposite tuning. The results favour feedforward mechanisms for the shaping of categorical tuning in microcircuits of the NCL. Our findings help to decipher the workings of pallial microcircuits in birds during complex cognition and to compare them vis-a-vis neocortical processes in mammals.

Neural recordings from the caudolateral nidopallium in crows during a numerosity task suggest there are two subsets of projection neurons and inhibitory interneurons involved in complex cognition.

Contributions of Distinct Auditory Cortical Inhibitory Neuron Types to the Detection of Sounds in Background Noise

The ability to separate background noise from relevant acoustic signals is essential for appropriate sound-driven behavior in natural environments. Examples of this separation are apparent in the auditory system, where neural responses to behaviorally relevant stimuli become increasingly noise invariant along the ascending auditory pathway. However, the mechanisms that underlie this reduction in responses to background noise are not well understood. To address this gap in knowledge, we first evaluated the effects of auditory cortical inactivation on mice of both sexes trained to perform a simple auditory signal-in-noise detection task and found that outputs from the auditory cortex are important for the detection of auditory stimuli in noisy environments. Next, we evaluated the contributions of the two most common cortical inhibitory cell types, parvalbumin-expressing (PV+) and somatostatin-expressing (SOM+) interneurons, to the perception of masked auditory stimuli. We found that inactivation of either PV+ or SOM+ cells resulted in a reduction in the ability of mice to determine the presence of auditory stimuli masked by noise. These results indicate that a disruption of auditory cortical network dynamics by either of these two types of inhibitory cells is sufficient to impair the ability to separate acoustic signals from noise.

Hearing in Complex Environments: Auditory Gain Control, Attention, and Hearing Loss

Listening in noisy or complex sound environments is difficult for individuals with normal hearing and can be a debilitating impairment for those with hearing loss. Extracting meaningful information from a complex acoustic environment requires the ability to accurately encode specific sound features under highly variable listening conditions and segregate distinct sound streams from multiple overlapping sources. The auditory system employs a variety of mechanisms to achieve this auditory scene analysis. First, neurons across levels of the auditory system exhibit compensatory adaptations to their gain and dynamic range in response to prevailing sound stimulus statistics in the environment. These adaptations allow for robust representations of sound features that are to a large degree invariant to the level of background noise. Second, listeners can selectively attend to a desired sound target in an environment with multiple sound sources. This selective auditory attention is another form of sensory gain control, enhancing the representation of an attended sound source while suppressing responses to unattended sounds. This review will examine both “bottom-up” gain alterations in response to changes in environmental sound statistics as well as “top-down” mechanisms that allow for selective extraction of specific sound features in a complex auditory scene. Finally, we will discuss how hearing loss interacts with these gain control mechanisms, and the adaptive and/or maladaptive perceptual consequences of this plasticity.

Altered Response Dynamics and Increased Population Correlation to Tonal Stimuli Embedded in Noise in Aging Auditory Cortex

Age-related hearing loss (presbycusis) is a chronic health condition that affects one-third of the world population. One hallmark of presbycusis is a difficulty hearing in noisy environments. Presbycusis can be separated into two components: alterations of peripheral mechanotransduction of sound in the cochlea and central alterations of auditory processing areas of the brain. Although the effects of the aging cochlea in hearing loss have been well studied, the role of the aging brain in hearing loss is less well understood. Therefore, to examine how age-related central processing changes affect hearing in noisy environments, we used a mouse model (Thy1-GCaMP6s X CBA) that has excellent peripheral hearing in old age. We used in vivo two-photon Ca2+ imaging to measure the responses of neuronal populations in auditory cortex (ACtx) of adult (2-6 months, nine male, six female, 4180 neurons) and aging mice (15-17 months, six male, three female, 1055 neurons) while listening to tones in noisy backgrounds. We found that ACtx neurons in aging mice showed larger responses to tones and have less suppressed responses consistent with reduced inhibition. Aging neurons also showed less sensitivity to temporal changes. Population analysis showed that neurons in aging mice showed higher pairwise activity correlations and showed a reduced diversity in responses to sound stimuli. Using neural decoding techniques, we show a loss of information in neuronal populations in the aging brain. Thus, aging not only affects the responses of single neurons but also affects how these neurons jointly represent stimuli.SIGNIFICANCE STATEMENT Aging results in hearing deficits particularly under challenging listening conditions. We show that auditory cortex contains distinct subpopulations of excitatory neurons that preferentially encode different stimulus features and that aging selectively reduces certain subpopulations. We also show that aging increases correlated activity between neurons and thereby reduces the response diversity in auditory cortex. The loss of population response diversity leads to a decrease of stimulus information and deficits in sound encoding, especially in noisy backgrounds. Future work determining the identities of circuits affected by aging could provide new targets for therapeutic strategies.

Distinct timescales for the neuronal encoding of vocal signals in a high-order auditory area

The ability of the auditory system to selectively recognize natural sound categories while maintaining a certain degree of tolerance towards variations within these categories, which may have functional roles, is thought to be crucial for vocal communication. To date, it is still largely unknown how the balance between tolerance and sensitivity to variations in acoustic signals is coded at a neuronal level. Here, we investigate whether neurons in a high-order auditory area in zebra finches, a songbird species, are sensitive to natural variations in vocal signals by recording their responses to repeated exposures to identical and variant sound sequences. We used the songs of male birds which tend to be highly repetitive with only subtle variations between renditions. When playing these songs to both anesthetized and awake birds, we found that variations between songs did not affect the neuron firing rate but the temporal reliability of responses. This suggests that auditory processing operates on a range of distinct timescales, namely a short one to detect variations in vocal signals, and longer ones that allow the birds to tolerate variations in vocal signal structure and to encode the global context.

Lemniscal Corticothalamic Feedback in Auditory Scene Analysis

Sound information is transmitted from the ear to central auditory stations of the brain via several nuclei. In addition to these ascending pathways there exist descending projections that can influence the information processing at each of these nuclei. A major descending pathway in the auditory system is the feedback projection from layer VI of the primary auditory cortex (A1) to the ventral division of medial geniculate body (MGBv) in the thalamus. The corticothalamic axons have small glutamatergic terminals that can modulate thalamic processing and thalamocortical information transmission. Corticothalamic neurons also provide input to GABAergic neurons of the thalamic reticular nucleus (TRN) that receives collaterals from the ascending thalamic axons. The balance of corticothalamic and TRN inputs has been shown to refine frequency tuning, firing patterns, and gating of MGBv neurons. Therefore, the thalamus is not merely a relay stage in the chain of auditory nuclei but does participate in complex aspects of sound processing that include top-down modulations. In this review, we aim (i) to examine how lemniscal corticothalamic feedback modulates responses in MGBv neurons, and (ii) to explore how the feedback contributes to auditory scene analysis, particularly on frequency and harmonic perception. Finally, we will discuss potential implications of the role of corticothalamic feedback in music and speech perception, where precise spectral and temporal processing is essential.

When and How Does the Auditory Cortex Influence Subcortical Auditory Structures? New Insights About the Roles of Descending Cortical Projections

For decades, the corticofugal descending projections have been anatomically well described but their functional role remains a puzzling question. In this review, we will first describe the contributions of neuronal networks in representing communication sounds in various types of degraded acoustic conditions from the cochlear nucleus to the primary and secondary auditory cortex. In such situations, the discrimination abilities of collicular and thalamic neurons are clearly better than those of cortical neurons although the latter remain very little affected by degraded acoustic conditions. Second, we will report the functional effects resulting from activating or inactivating corticofugal projections on functional properties of subcortical neurons. In general, modest effects have been observed in anesthetized and in awake, passively listening, animals. In contrast, in behavioral tasks including challenging conditions, behavioral performance was severely reduced by removing or transiently silencing the corticofugal descending projections. This suggests that the discriminative abilities of subcortical neurons may be sufficient in many acoustic situations. It is only in particularly challenging situations, either due to the task difficulties and/or to the degraded acoustic conditions that the corticofugal descending connections bring additional abilities. Here, we propose that it is both the top-down influences from the prefrontal cortex, and those from the neuromodulatory systems, which allow the cortical descending projections to impact behavioral performance in reshaping the functional circuitry of subcortical structures. We aim at proposing potential scenarios to explain how, and under which circumstances, these projections impact on subcortical processing and on behavioral responses.

Dopamine D1 Receptor Activation Drives Plasticity in the Songbird Auditory Pallium

Vocal learning species must form and extensively hone associations between sounds and social contingencies. In songbirds, dopamine signaling guides song motor production, variability, and motivation, but it is unclear how dopamine regulates fundamental auditory associations for learning new sounds. We hypothesized that dopamine regulates learning in the auditory pallium, in part by interacting with local neuroestradiol signaling. Here, we show that zebra finch auditory neurons frequently coexpress D1 receptor (D1R) protein, neuroestradiol-synthase, GABA, and parvalbumin (PV). Auditory classical conditioning increased neuroplasticity gene induction in D1R-positive neurons. In vitro, D1R pharmacological activation reduced the amplitude of GABAergic and glutamatergic currents and increased the latter's frequency. In vivo, D1R activation reduced the firing of putative interneurons, increased the firing of putative excitatory neurons, and made both neuronal types unable to adapt to novel stimuli. Together, these findings support the hypothesis that dopamine acting via D1Rs modulates auditory association in the songbird sensory pallium.SIGNIFICANCE STATEMENT Our key finding is that auditory forebrain D1 receptors (D1Rs) modulate auditory plasticity, in support of the hypothesis that dopamine modulates the formation of associations between sounds and outcomes. Recent work in songbirds has identified roles for dopamine in driving reinforcement learning and motor variability in song production. This leaves open whether dopamine shapes the initial events that are critical for learning vocalizations, e.g., auditory learning. Our study begins to address this question in the songbird caudomedial nidopallium (NCM), an analog of the mammalian secondary auditory cortex. Our findings indicate that dopamine receptors are important modulators of excitatory/inhibitory balance and sound association learning mechanisms in the NCM, a system that could be a fundamental feature of vertebrate ascending auditory pathways.

Cellular and Widefield Imaging of Sound Frequency Organization in Primary and Higher Order Fields of the Mouse Auditory Cortex

The mouse auditory cortex (ACtx) contains two core fields-primary auditory cortex (A1) and anterior auditory field (AAF)-arranged in a mirror reversal tonotopic gradient. The best frequency (BF) organization and naming scheme for additional higher order fields remain a matter of debate, as does the correspondence between smoothly varying global tonotopy and heterogeneity in local cellular tuning. Here, we performed chronic widefield and two-photon calcium imaging from the ACtx of awake Thy1-GCaMP6s reporter mice. Data-driven parcellation of widefield maps identified five fields, including a previously unidentified area at the ventral posterior extreme of the ACtx (VPAF) and a tonotopically organized suprarhinal auditory field (SRAF) that extended laterally as far as ectorhinal cortex. Widefield maps were stable over time, where single pixel BFs fluctuated by less than 0.5 octaves throughout a 1-month imaging period. After accounting for neuropil signal and frequency tuning strength, BF organization in neighboring layer 2/3 neurons was intermediate to the heterogeneous salt and pepper organization and the highly precise local organization that have each been described in prior studies. Multiscale imaging data suggest there is no ultrasonic field or secondary auditory cortex in the mouse. Instead, VPAF and a dorsal posterior (DP) field emerged as the strongest candidates for higher order auditory areas.

Genetically identified neurons in avian auditory pallium mirror core principles of their mammalian counterparts

In vertebrates, advanced cognitive abilities are typically associated with the telencephalic pallium. In mammals, the pallium is a layered mixture of excitatory and inhibitory neuronal populations with distinct molecular, physiological, and network phenotypes. This cortical architecture is proposed to support efficient, high-level information processing. Comparative perspectives across vertebrates provide a lens to understand the common features of pallium that are important for advanced cognition. Studies in songbirds have established strikingly parallel features of neuronal types between mammalian and avian pallium. However, lack of genetic access to defined pallial cell types in non-mammalian vertebrates has hindered progress in resolving connections between molecular and physiological phenotypes. A definitive mapping of the physiology of pallial cells onto their molecular identities in birds is critical for understanding how synaptic and computational properties depend on underlying molecular phenotypes. Using viral tools to target excitatory versus inhibitory neurons in the zebra finch auditory association pallium (calmodulin-dependent kinase alpha [CaMKIIα] and glutamate decarboxylase 1 [GAD1] promoters, respectively), we systematically tested predictions derived from mammalian pallium. We identified two genetically distinct neuronal populations that exhibit profound physiological and computational similarities with mammalian excitatory and inhibitory pallial cells, definitively aligning putative cell types in avian caudal nidopallium with these molecular identities. Specifically, genetically identified CaMKIIα and GAD1 cell types in avian auditory association pallium exhibit distinct intrinsic physiological parameters, distinct auditory coding principles, and inhibitory-dependent pallial synchrony, gamma oscillations, and local suppression. The retention, or convergence, of these molecular and physiological features in both birds and mammals clarifies the characteristics of pallial circuits for advanced cognitive abilities.

Generalizable dimensions of human cortical auditory processing of speech in natural soundscapes: A data-driven ultra high field fMRI approach

Speech comprehension in natural soundscapes rests on the ability of the auditory system to extract speech information from a complex acoustic signal with overlapping contributions from many sound sources. Here we reveal the canonical processing of speech in natural soundscapes on multiple scales by using data-driven modeling approaches to characterize sounds to analyze ultra high field fMRI recorded while participants listened to the audio soundtrack of a movie. We show that at the functional level the neuronal processing of speech in natural soundscapes can be surprisingly low dimensional in the human cortex, highlighting the functional efficiency of the auditory system for a seemingly complex task. Particularly, we find that a model comprising three functional dimensions of auditory processing in the temporal lobes is shared across participants' fMRI activity. We further demonstrate that the three functional dimensions are implemented in anatomically overlapping networks that process different aspects of speech in natural soundscapes. One is most sensitive to complex auditory features present in speech, another to complex auditory features and fast temporal modulations, that are not specific to speech, and one codes mainly sound level. These results were derived with few a-priori assumptions and provide a detailed and computationally reproducible account of the cortical activity in the temporal lobe elicited by the processing of speech in natural soundscapes.

Temporal Encoding is Required for Categorization, But Not Discrimination

Core auditory cortex (AC) neurons encode slow fluctuations of acoustic stimuli with temporally patterned activity. However, whether temporal encoding is necessary to explain auditory perceptual skills remains uncertain. Here, we recorded from gerbil AC neurons while they discriminated between a 4-Hz amplitude modulation (AM) broadband noise and AM rates >4 Hz. We found a proportion of neurons possessed neural thresholds based on spike pattern or spike count that were better than the recorded session's behavioral threshold, suggesting that spike count could provide sufficient information for this perceptual task. A population decoder that relied on temporal information outperformed a decoder that relied on spike count alone, but the spike count decoder still remained sufficient to explain average behavioral performance. This leaves open the possibility that more demanding perceptual judgments require temporal information. Thus, we asked whether accurate classification of different AM rates between 4 and 12 Hz required the information contained in AC temporal discharge patterns. Indeed, accurate classification of these AM stimuli depended on the inclusion of temporal information rather than spike count alone. Overall, our results compare two different representations of time-varying acoustic features that can be accessed by downstream circuits required for perceptual judgments.

Auditory Cortical Plasticity Dependent on Environmental Noise Statistics

During critical periods, neural circuits develop to form receptive fields that adapt to the sensory environment and enable optimal performance of relevant tasks. We hypothesized that early exposure to background noise can improve signal-in-noise processing, and the resulting receptive field plasticity in the primary auditory cortex can reveal functional principles guiding that important task. We raised rat pups in different spectro-temporal noise statistics during their auditory critical period. As adults, they showed enhanced behavioral performance in detecting vocalizations in noise. Concomitantly, encoding of vocalizations in noise in the primary auditory cortex improves with noise-rearing. Significantly, spectro-temporal modulation plasticity shifts cortical preferences away from the exposed noise statistics, thus reducing noise interference with the foreground sound representation. Auditory cortical plasticity shapes receptive field preferences to optimally extract foreground information in noisy environments during noise-rearing. Early noise exposure induces cortical circuits to implement efficient coding in the joint spectral and temporal modulation domain.

After rearing rats in moderately loud spectro-temporally modulated background noise, Homma et al. investigated signal-in-noise processing in the primary auditory cortex. Noise-rearing improved vocalization-in-noise performance in both behavioral testing and neural decoding. Cortical plasticity shifted neuronal spectro-temporal modulation preferences away from the exposed noise statistics.

Robustness to Noise in the Auditory System: A Distributed and Predictable Property

Background noise strongly penalizes auditory perception of speech in humans or vocalizations in animals. Despite this, auditory neurons are still able to detect communications sounds against considerable levels of background noise. We collected neuronal recordings in cochlear nucleus (CN), inferior colliculus (IC), auditory thalamus, and primary and secondary auditory cortex in response to vocalizations presented either against a stationary or a chorus noise in anesthetized guinea pigs at three signal-to-noise ratios (SNRs; −10, 0, and 10 dB). We provide evidence that, at each level of the auditory system, five behaviors in noise exist within a continuum, from neurons with high-fidelity representations of the signal, mostly found in IC and thalamus, to neurons with high-fidelity representations of the noise, mostly found in CN for the stationary noise and in similar proportions in each structure for the chorus noise. The two cortical areas displayed fewer robust responses than the IC and thalamus. Furthermore, between 21% and 72% of the neurons (depending on the structure) switch categories from one background noise to another, even if the initial assignment of these neurons to a category was confirmed by a severe bootstrap procedure. Importantly, supervised learning pointed out that assigning a recording to one of the five categories can be predicted up to a maximum of 70% based on both the response to signal alone and noise alone.

Adult-like neural representation of species-specific songs in the auditory forebrain of zebra finch nestlings

Encoding of conspecific signals during development can reinforce species barriers as well as set the stage for learning and production of species-typical vocalizations. In altricial songbirds, the development of the auditory system is not complete at hatching, so it is unknown the degree to which recently hatched young can process auditory signals like birdsong. We measured in vivo extracellular responses to song stimuli in a zebra finch (Taeniopygia guttata) secondary auditory forebrain region, the caudomedial nidopallium (NCM). We recorded from three age groups between 13 days post-hatch and adult to identify possible shifts in stimulus encoding that occur before the opening of the sensitive period of song motor learning. We did not find differences in putative cell type composition, firing rate, response strength, and selectivity across ages. Across ages narrow-spiking units had higher firing rates, response strength, accuracy, and trial-by-trial reliability along with lower selectivity than broad-spiking units. In addition, we showed that stimulus-specific adaptation, a characteristic of adult NCM, was also present in nestlings and fledglings. These results indicate that most features of secondary auditory processing are already adult-like shortly after hatching. Furthermore, we showed that selectivity for species-specific stimuli is similar across all ages, with the greatest fidelity in temporal coding in response to conspecific song and domesticated Bengalese finch song, and reduced fidelity in response to owl finch song, a more ecologically relevant heterospecific, and white noise. Our study provides the first evidence that the electrophysiological properties of higher-order auditory neurons are already mature in nestling songbirds.

The effect of input noises on the activity of auditory neurons using GLM-based metrics

CONTEXT

The auditory system is extremely efficient in extracting auditory information in the presence of background noise. However, people with auditory implants have a hard time understanding speech in noisy conditions. Understanding the mechanisms of perception in noise could lead to better stimulation or preprocessing strategies for such implants.

OBJECTIVE

The neural mechanisms related to the processing of background noise, especially in the inferior colliculus (IC) where the auditory midbrain implant is located, are still not well understood. We thus wish to investigate if there is a difference in the activity of neurons in the IC when presenting noisy vocalizations with different types of noise (stationary vs. non-stationary), input signal-to-noise ratios (SNR) and signal levels.

APPROACH

We developed novel metrics based on a generalized linear model (GLM) to investigate the effect of a given input noise on neural activity. We used these metrics to analyze neural data recorded from the IC in ketamine-anesthetized female Hartley guinea pigs while presenting noisy vocalizations.

MAIN RESULTS

We found that non-stationary noise clearly contributes to the multi-unit neural activity in the IC by causing excitation, regardless of the SNR, input level or vocalization type. However, when presenting white or natural stationary noises, a great diversity of responses was observed for the different conditions, where the multi-unit activity of some sites was affected by the presence of noise and the activity of others was not.

SIGNIFICANCE

The GLM-based metrics allowed the identification of a clear distinction between the effect of white or natural stationary noises and that of non-stationary noise on the multi-unit activity in the IC. This had not been observed before and indicates that the so-called noise invariance in the IC is dependent on the input noisy conditions. This could suggest different preprocessing or stimulation approaches for auditory midbrain implants depending on the noisy conditions.

Pupillometry as a reliable metric of auditory detection and discrimination across diverse stimulus paradigms in animal models

Estimates of detection and discrimination thresholds are often used to explore broad perceptual similarities between human subjects and animal models. Pupillometry shows great promise as a non-invasive, easily-deployable method of comparing human and animal thresholds. Using pupillometry, previous studies in animal models have obtained threshold estimates to simple stimuli such as pure tones, but have not explored whether similar pupil responses can be evoked by complex stimuli, what other stimulus contingencies might affect stimulus-evoked pupil responses, and if pupil responses can be modulated by experience or short-term training. In this study, we used an auditory oddball paradigm to estimate detection and discrimination thresholds across a wide range of stimuli in guinea pigs. We demonstrate that pupillometry yields reliable detection and discrimination thresholds across a range of simple (tones) and complex (conspecific vocalizations) stimuli; that pupil responses can be robustly evoked using different stimulus contingencies (low-level acoustic changes, or higher level categorical changes); and that pupil responses are modulated by short-term training. These results lay the foundation for using pupillometry as a reliable method of estimating thresholds in large experimental cohorts, and unveil the full potential of using pupillometry to explore broad similarities between humans and animal models.

The second harmonic neurons in auditory midbrain of Hipposideros pratti are more tolerant to background white noise

Although acoustic communication is inevitably influenced by noise, behaviorally relevant sounds are perceived reliably. The noise-tolerant and -invariant responses of auditory neurons are thought to be the underlying mechanism. So, it is reasonable to speculate that neurons with best frequency tuned to behaviorally relevant sounds will play important role in noise-tolerant perception. Echolocating bats live in groups and emit multiple harmonic signals and analyze the returning echoes to extract information about the target features, making them prone to deal with noise in their natural habitat. The echolocation signal of Hipposideros pratti usually contains 3-4 harmonics (H₁H₄), the second harmonic has the highest amplitude and is thought to play an essential role during echolocation behavior. Therefore, it is reasonable to propose that neurons tuned to the H₂, named the H₂ neurons, can be more noise-tolerant to background noise. Taking advantage of bat's stereotypical echolocation signal and single-cell recording, our present study showed that the minimal threshold increases (12.2 dB) of H₂ neurons in the auditory midbrain were comparable to increase in bat's call intensity (14.2 dB) observed in 70 dB SPL white noise condition, indicating that the H₂ neurons could work as background noise monitor. The H₂ neurons had higher minimal thresholds and sharper frequency tuning, which enabled them to be more tolerant to background noise. Furthermore, the H₂ neurons had consistent best amplitude spikes and sharper intensity tuning in background white noise condition than in silence. Taken together, these results suggest that the H₂ neurons might account for noise-tolerant perception of behaviorally relevant sounds.

A modular high-density μECoG system on macaque vlPFC for auditory cognitive decoding

OBJECTIVE

A fundamental goal of the auditory system is to parse the auditory environment into distinct perceptual representations. Auditory perception is mediated by the ventral auditory pathway, which includes the ventrolateral prefrontal cortex (vlPFC). Because large-scale recordings of auditory signals are quite rare, the spatiotemporal resolution of the neuronal code that underlies vlPFC's contribution to auditory perception has not been fully elucidated. Therefore, we developed a modular, chronic, high-resolution, multi-electrode array system with long-term viability in order to identify the information that could be decoded from μECoG vlPFC signals.

APPROACH

We molded three separate μECoG arrays into one and implanted this system in a non-human primate. A custom 3D-printed titanium chamber was mounted on the left hemisphere. The molded 294-contact μECoG array was implanted subdurally over the vlPFC. μECoG activity was recorded while the monkey participated in a 'hearing-in-noise' task in which they reported hearing a 'target' vocalization from a background 'chorus' of vocalizations. We titrated task difficulty by varying the sound level of the target vocalization, relative to the chorus (target-to-chorus ratio, TCr).

MAIN RESULTS

We decoded the TCr and the monkey's behavioral choices from the μECoG signal. We analyzed decoding accuracy as a function of number of electrodes, spatial resolution, and time from implantation. Over a one-year period, we found significant decoding with individual electrodes that increased significantly as we decoded simultaneously more electrodes. Further, we found that the decoding for behavioral choice was better than the decoding of TCr. Finally, because the decoding accuracy of individual electrodes varied on a day-by-day basis, electrode arrays with high channel counts ensure robust decoding in the long term.

SIGNIFICANCE

Our results demonstrate the utility of high-resolution and high-channel-count, chronic µECoG recording. We developed a surface electrode array that can be scaled to cover larger cortical areas without increasing the chamber footprint.