A generalized linear model for estimating spectrotemporal receptive fields from responses to natural sounds

In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF), a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM). In this model, each cell's input is described by: 1) a stimulus filter (STRF); and 2) a post-spike filter, which captures dependencies on the neuron's spiking history. The output of the model is given by a series of spike trains rather than instantaneous firing rate, allowing the prediction of spike train responses to novel stimuli. We fit the model by maximum penalized likelihood to the spiking activity of zebra finch auditory midbrain neurons in response to conspecific vocalizations (songs) and modulation limited (ml) noise. We compare this model to normalized reverse correlation (NRC), the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs. We find that a GLM with a sparse prior predicts novel responses to both stimulus classes significantly better than NRC. Importantly, we find that STRFs from the two models derived from the same responses can differ substantially and that GLM STRFs are more consistent between stimulus classes than NRC STRFs. These results suggest that a GLM with a sparse prior provides a more accurate characterization of spectrotemporal tuning than does the NRC method when responses to complex sounds are studied in these neurons.     

Selective and Efficient Neural Coding of Communication Signals Depends on Early Acoustic and Social Environment

Previous research has shown that postnatal exposure to simple, synthetic sounds can affect the sound representation in the auditory cortex as reflected by changes in the tonotopic map or other relatively simple tuning properties, such as AM tuning. However, their functional implications for neural processing in the generation of ethologically-based perception remain unexplored. Here we examined the effects of noise-rearing and social isolation on the neural processing of communication sounds such as species-specific song, in the primary auditory cortex analog of adult zebra finches. Our electrophysiological recordings reveal that neural tuning to simple frequency-based synthetic sounds is initially established in all the laminae independent of patterned acoustic experience; however, we provide the first evidence that early exposure to patterned sound statistics, such as those found in native sounds, is required for the subsequent emergence of neural selectivity for complex vocalizations and for shaping neural spiking precision in superficial and deep cortical laminae, and for creating efficient neural representations of song and a less redundant ensemble code in all the laminae. Our study also provides the first causal evidence for ‘sparse coding’, such that when the statistics of the stimuli were changed during rearing, as in noise-rearing, that the sparse or optimal representation for species-specific vocalizations disappeared. Taken together, these results imply that a layer-specific differential development of the auditory cortex requires patterned acoustic input, and a specialized and robust sensory representation of complex communication sounds in the auditory cortex requires a rich acoustic and social environment.     

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.     

Neural mechanisms of auditory species recognition in birds

Auditory communication in humans and other animals frequently takes place in noisy environments with many co‐occurring signallers. Receivers are thus challenged to rapidly recognize salient auditory signals and filter out irrelevant sounds. Most bird species produce a variety of complex vocalizations that function to communicate with other members of their own species and behavioural evidence broadly supports preferences for conspecific over heterospecific sounds (auditory species recognition). However, it remains unclear whether such auditory signals are categorically recognized by the sensory and central nervous system. Here, we review 53 published studies that compare avian neural responses between conspecific versus heterospecific vocalizations. Irrespective of the techniques used to characterize neural activity, distinct nuclei of the auditory forebrain are consistently shown to be repeatedly conspecific selective across taxa, even in response to unfamiliar individuals with distinct acoustic properties. Yet, species‐specific neural discrimination is not a stereotyped auditory response, but is modulated according to its salience depending, for example, on ontogenetic exposure to conspecific versus heterospecific stimuli. Neuromodulators, in particular norepinephrine, may mediate species recognition by regulating the accuracy of neuronal coding for salient conspecific stimuli. Our review lends strong support for neural structures that categorically recognize conspecific signals despite the highly variable physical properties of the stimulus. The available data are in support of a ‘perceptual filter’‐based mechanism to determine the saliency of the signal, in that species identity and social experience combine to influence the neural processing of species‐specific auditory stimuli. Finally, we present hypotheses and their testable predictions, to propose next steps in species‐recognition research into the emerging model of the neural conceptual construct in avian auditory recognition.     

Spectrotemporal Response Properties of Core Auditory Cortex Neurons in Awake Monkey

So far, most studies of core auditory cortex (AC) have characterized the spectral and temporal tuning properties of cells in non-awake, anesthetized preparations. As experiments in awake animals are scarce, we here used dynamic spectral-temporal broadband ripples to study the properties of the spectrotemporal receptive fields (STRFs) of AC cells in awake monkeys. We show that AC neurons were typically most sensitive to low ripple densities (spectral) and low velocities (temporal), and that most cells were not selective for a particular spectrotemporal sweep direction. A substantial proportion of neurons preferred amplitude-modulated sounds (at zero ripple density) to dynamic ripples (at non-zero densities). The vast majority (>93%) of modulation transfer functions were separable with respect to spectral and temporal modulations, indicating that time and spectrum are independently processed in AC neurons. We also analyzed the linear predictability of AC responses to natural vocalizations on the basis of the STRF. We discuss our findings in the light of results obtained from the monkey midbrain inferior colliculus by comparing the spectrotemporal tuning properties and linear predictability of these two important auditory stages.     

Response variability in the mammalian auditory cortex: an objection to feature detection?

Research strategy in the auditory system has tended to parallel that in the visual system, where neurons have been shown to respond selectively to specific stimulus parameters. Auditory neurons have been shown to be sensitive to changes in acoustic parameters, but only rarely have neurons been reported that respond exclusively to only one biologically significant sound. Even at higher levels of the auditory system very few cells have been found that could be described as "vocalization detectors." In addition, variability in responses to artificial sounds have been reported for auditory cortical neurons similar to the response variability that has been reported in the visual system. Recent evidence indicates that the responses of auditory cortical neurons to species-specific vocalizations can also be labile, varying in both strength and selectivity. This is especially true of the secondary auditory cortex. This variability, coupled with the lack of extreme specificity in the secondary auditory cortex, suggests that secondary cortical neurons are not well suited for the role of "vocalization detectors."     

Serotonin modulates responses to species-specific vocalizations in the inferior colliculus

Neuromodulators such as serotonin are capable of altering the neural processing of stimuli across many sensory modalities. In the inferior colliculus, a major midbrain auditory gateway, serotonin alters the way that individual neurons respond to simple tone bursts and linear frequency modulated sweeps. The effects of serotonin are complex, and vary among neurons. How serotonin transforms the responses to spectrotemporally complex sounds of the type normally heard in natural settings has been poorly examined. To explore this issue further, the effects of iontophoretically applied serotonin on the responses of individual inferior colliculus neurons to a variety of recorded species-specific vocalizations were examined. These experiments were performed in the Mexican free-tailed bat, a species that uses a rich repertoire of vocalizations for the purposes of communication as well as echolocation. Serotonin frequently changed the number of recorded calls that were capable of evoking a response from individual neurons, sometimes increasing (15% of serotonin-responsive neurons), but usually decreasing (62% of serotonin-responsive neurons), this number. A functional consequence of these serotonin-evoked changes would be to change the population response to species-specific vocalizations.     

Neurophysiological response selectivity for conspecific songs over synthetic sounds in the auditory forebrain of non-singing female songbirds

Female choice plays a critical role in the evolution of male acoustic displays. Yet there is limited information on the neurophysiological basis of female songbirds’ auditory recognition systems. To understand the neural mechanisms of how non-singing female songbirds perceive behaviorally relevant vocalizations, we recorded responses of single neurons to acoustic stimuli in two auditory forebrain regions, the caudal lateral mesopallium (CLM) and Field L, in anesthetized adult female zebra finches (Taeniopygia guttata). Using various metrics of response selectivity, we found consistently higher response strengths for unfamiliar conspecific songs compared to tone pips and white noise in Field L but not in CLM. We also found that neurons in the left auditory forebrain had lower response strengths to synthetics sounds, leading to overall higher neural selectivity for song in neurons of the left hemisphere. This laterality effect is consistent with previously published behavioral data in zebra finches. Overall, our results from Field L are in parallel and from CLM are in contrast with the patterns of response selectivity reported for conspecific songs over synthetic sounds in male zebra finches, suggesting some degree of sexual dimorphism of auditory perception mechanisms in songbirds.     

Comparison of Neural Responses to Cat Meows and Human Vowels in the Anterior and Posterior Auditory Field of Awake Cats

For humans and animals, the ability to discriminate speech and conspecific vocalizations is an important physiological assignment of the auditory system. To reveal the underlying neural mechanism, many electrophysiological studies have investigated the neural responses of the auditory cortex to conspecific vocalizations in monkeys. The data suggest that vocalizations may be hierarchically processed along an anterior/ventral stream from the primary auditory cortex (A1) to the ventral prefrontal cortex. To date, the organization of vocalization processing has not been well investigated in the auditory cortex of other mammals. In this study, we examined the spike activities of single neurons in two early auditory cortical regions with different anteroposterior locations: anterior auditory field (AAF) and posterior auditory field (PAF) in awake cats, as the animals were passively listening to forward and backward conspecific calls (meows) and human vowels. We found that the neural response patterns in PAF were more complex and had longer latency than those in AAF. The selectivity for different vocalizations based on the mean firing rate was low in both AAF and PAF, and not significantly different between them; however, more vocalization information was transmitted when the temporal response profiles were considered, and the maximum transmitted information by PAF neurons was higher than that by AAF neurons. Discrimination accuracy based on the activities of an ensemble of PAF neurons was also better than that of AAF neurons. Our results suggest that AAF and PAF are similar with regard to which vocalizations they represent but differ in the way they represent these vocalizations, and there may be a complex processing stream between them.     

Encoding properties of auditory neurons in the brain of a soniferous damselfish: response to simple tones and complex conspecific signals

The fish auditory system encodes important acoustic stimuli used in social communication, but few studies have examined response properties of central auditory neurons to natural signals. We determined the features and responses of single hindbrain and midbrain auditory neurons to tone bursts and playbacks of conspecific sounds in the soniferous damselfish, Abudefduf abdominalis. Most auditory neurons were either silent or had slow irregular resting discharge rates <20 spikes s⁻¹. Average best frequency for neurons to tone stimuli was ~130 Hz but ranged from 80 to 400 Hz with strong phase-locking. This low-frequency sensitivity matches the frequency band of natural sounds. Auditory neurons were also modulated by playbacks of conspecific sounds with thresholds similar to 100 Hz tones, but these thresholds were lower than that of tones at other test frequencies. Thresholds of neurons to natural sounds were lower in the midbrain than the hindbrain. This is the first study to compare response properties of auditory neurons to both simple tones and complex stimuli in the brain of a recently derived soniferous perciform that lacks accessory auditory structures. These data demonstrate that the auditory fish brain is most sensitive to the frequency and temporal components of natural pulsed sounds that provide important signals for conspecific communication.     

Responses of midbrain auditory neurons in rats to FM and AM tones presented simultaneously

Speech and other communication signals contain components of frequency and amplitude modulations (FM, AM) that often occur together. Auditory midbrain (or inferior colliculus, IC) is an important center for coding time-varying features of sounds. It remains unclear how IC neurons respond when FM and AM stimuli are both presented. Here we studied IC neurons in the urethane-anesthetized rats when animals were simultaneously stimulated with FM and AM tones. Of 122 units that were sensitive to the dual stimuli, the responses could be grossly divided into two types: one that resembled the respective responses to FM or AM stimuli presented separately ("simple" sensitivity, 45% of units), and another that appeared markedly different from their respective responses to FM or AM tones ("complex" sensitivity, 55%). These types of combinational sensitivities were further correlated with individual cell's frequency tuning pattern (response area) and with their common response pattern to FM and AM sounds. Results suggested that such combinational sensitivity could reflect local synaptic interactions on IC neurons and that the neural mechanisms could underlie more developed sensitivities to acoustic combinations found at the auditory cortex.     

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons'' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.     

Coding of communication calls in the subcortical and cortical structures of the auditory system

The processing of species-specific communication signals in the auditory system represents an important aspect of animal behavior and is crucial for its social interactions, reproduction, and survival. In this article the neuronal mechanisms underlying the processing of communication signals in the higher centers of the auditory system--inferior colliculus (IC), medial geniculate body (MGB) and auditory cortex (AC)--are reviewed, with particular attention to the guinea pig. The selectivity of neuronal responses for individual calls in these auditory centers in the guinea pig is usually low--most neurons respond to calls as well as to artificial sounds; the coding of complex sounds in the central auditory nuclei is apparently based on the representation of temporal and spectral features of acoustical stimuli in neural networks. Neuronal response patterns in the IC reliably match the sound envelope for calls characterized by one or more short impulses, but do not exactly fit the envelope for long calls. Also, the main spectral peaks are represented by neuronal firing rates in the IC. In comparison to the IC, response patterns in the MGB and AC demonstrate a less precise representation of the sound envelope, especially in the case of longer calls. The spectral representation is worse in the case of low-frequency calls, but not in the case of broad-band calls. The emotional content of the call may influence neuronal responses in the auditory pathway, which can be demonstrated by stimulation with time-reversed calls or by measurements performed under different levels of anesthesia. The investigation of the principles of the neural coding of species-specific vocalizations offers some keys for understanding the neural mechanisms underlying human speech perception.     

Sparse representation of sounds in the unanesthetized auditory cortex

How do neuronal populations in the auditory cortex represent acoustic stimuli? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. To quantify the relative contributions of these different subpopulations in the awake preparation, we have estimated the representation of sounds across the neuronal population using a representative ensemble of stimuli. We used cell-attached recording with a glass electrode, a method for which single-unit isolation does not depend on neuronal activity, to quantify the fraction of neurons engaged by acoustic stimuli (tones, frequency modulated sweeps, white-noise bursts, and natural stimuli) in the primary auditory cortex of awake head-fixed rats. We find that the population response is sparse, with stimuli typically eliciting high firing rates (>20 spikes/second) in less than 5% of neurons at any instant. Some neurons had very low spontaneous firing rates (<0.01 spikes/second). At the other extreme, some neurons had driven rates in excess of 50 spikes/second. Interestingly, the overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. Our results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.     

Neural Processing of Short-Term Recurrence in Songbird Vocal Communication

Background

Many situations involving animal communication are dominated by recurring, stereotyped signals. How do receivers optimally distinguish between frequently recurring signals and novel ones? Cortical auditory systems are known to be pre-attentively sensitive to short-term delivery statistics of artificial stimuli, but it is unknown if this phenomenon extends to the level of behaviorally relevant delivery patterns, such as those used during communication.

Methodology/Principal Findings

We recorded and analyzed complete auditory scenes of spontaneously communicating zebra finch (Taeniopygia guttata) pairs over a week-long period, and show that they can produce tens of thousands of short-range contact calls per day. Individual calls recur at time scales (median interval 1.5 s) matching those at which mammalian sensory systems are sensitive to recent stimulus history. Next, we presented to anesthetized birds sequences of frequently recurring calls interspersed with rare ones, and recorded, in parallel, action and local field potential responses in the medio-caudal auditory forebrain at 32 unique sites. Variation in call recurrence rate over natural ranges leads to widespread and significant modulation in strength of neural responses. Such modulation is highly call-specific in secondary auditory areas, but not in the main thalamo-recipient, primary auditory area.

Conclusions/Significance

Our results support the hypothesis that pre-attentive neural sensitivity to short-term stimulus recurrence is involved in the analysis of auditory scenes at the level of delivery patterns of meaningful sounds. This may enable birds to efficiently and automatically distinguish frequently recurring vocalizations from other events in their auditory scene.     

Representation of spectrotemporal sound information in the ascending auditory pathway

The representation of sound information in the central nervous system relies on the analysis of time-varying features in communication and other environmental sounds. How are auditory physiologists and theoreticians to choose an appropriate method for characterizing spectral and temporal acoustic feature representations in single neurons and neural populations? A brief survey of currently available scientific methods and their potential usefulness is given, with a focus on the strengths and weaknesses of using noise analysis techniques for approximating spectrotemporal response fields (STRFs). Noise analysis has been used to foster several conceptual advances in describing neural acoustic feature representation in a variety of species and auditory nuclei. STRFs have been used to quantitatively assess spectral and temporal transformations across mutually connected auditory nuclei, to identify neuronal interactions between spectral and temporal sound dimensions, and to compare linear vs. nonlinear response properties through state-dependent comparisons. We propose that noise analysis techniques used in combination with novel stimulus paradigms and parametric experiment designs will provide powerful means of exploring acoustic feature representations in the central nervous system.     

Degraded auditory processing in a rat model of autism limits the speech representation in non‐primary auditory cortex

Although individuals with autism are known to have significant communication problems, the cellular mechanisms responsible for impaired communication are poorly understood. Valproic acid (VPA) is an anticonvulsant that is a known risk factor for autism in prenatally exposed children. Prenatal VPA exposure in rats causes numerous neural and behavioral abnormalities that mimic autism. We predicted that VPA exposure may lead to auditory processing impairments which may contribute to the deficits in communication observed in individuals with autism. In this study, we document auditory cortex responses in rats prenatally exposed to VPA. We recorded local field potentials and multiunit responses to speech sounds in primary auditory cortex, anterior auditory field, ventral auditory field. and posterior auditory field in VPA exposed and control rats. Prenatal VPA exposure severely degrades the precise spatiotemporal patterns evoked by speech sounds in secondary, but not primary auditory cortex. This result parallels findings in humans and suggests that secondary auditory fields may be more sensitive to environmental disturbances and may provide insight into possible mechanisms related to auditory deficits in individuals with autism. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 74: 972–986, 2014     

Neural Resolution of Formant Frequencies in the Primary Auditory Cortex of Rats

Pulse-resonance sounds play an important role in animal communication and auditory object recognition, yet very little is known about the cortical representation of this class of sounds. In this study we shine light on one simple aspect: how well does the firing rate of cortical neurons resolve resonant (“formant”) frequencies of vowel-like pulse-resonance sounds. We recorded neural responses in the primary auditory cortex (A1) of anesthetized rats to two-formant pulse-resonance sounds, and estimated their formant resolving power using a statistical kernel smoothing method which takes into account the natural variability of cortical responses. While formant-tuning functions were diverse in structure across different penetrations, most were sensitive to changes in formant frequency, with a frequency resolution comparable to that reported for rat cochlear filters.     

Sparse Spectro-Temporal Receptive Fields Based on Multi-Unit and High-Gamma Responses in Human Auditory Cortex

Spectro-Temporal Receptive Fields (STRFs) were estimated from both multi-unit sorted clusters and high-gamma power responses in human auditory cortex. Intracranial electrophysiological recordings were used to measure responses to a random chord sequence of Gammatone stimuli. Traditional methods for estimating STRFs from single-unit recordings, such as spike-triggered-averages, tend to be noisy and are less robust to other response signals such as local field potentials. We present an extension to recently advanced methods for estimating STRFs from generalized linear models (GLM). A new variant of regression using regularization that penalizes non-zero coefficients is described, which results in a sparse solution. The frequency-time structure of the STRF tends toward grouping in different areas of frequency-time and we demonstrate that group sparsity-inducing penalties applied to GLM estimates of STRFs reduces the background noise while preserving the complex internal structure. The contribution of local spiking activity to the high-gamma power signal was factored out of the STRF using the GLM method, and this contribution was significant in 85 percent of the cases. Although the GLM methods have been used to estimate STRFs in animals, this study examines the detailed structure directly from auditory cortex in the awake human brain. We used this approach to identify an abrupt change in the best frequency of estimated STRFs along posteromedial-to-anterolateral recording locations along the long axis of Heschl’s gyrus. This change correlates well with a proposed transition from core to non-core auditory fields previously identified using the temporal response properties of Heschl’s gyrus recordings elicited by click-train stimuli.     

Development of Auditory-Vocal Perceptual Skills in Songbirds

Songbirds are one of the few groups of animals that learn the sounds used for vocal communication during development. Like humans, songbirds memorize vocal sounds based on auditory experience with vocalizations of adult “tutors”, and then use auditory feedback of self-produced vocalizations to gradually match their motor output to the memory of tutor sounds. In humans, investigations of early vocal learning have focused mainly on perceptual skills of infants, whereas studies of songbirds have focused on measures of vocal production. In order to fully exploit songbirds as a model for human speech, understand the neural basis of learned vocal behavior, and investigate links between vocal perception and production, studies of songbirds must examine both behavioral measures of perception and neural measures of discrimination during development. Here we used behavioral and electrophysiological assays of the ability of songbirds to distinguish vocal calls of varying frequencies at different stages of vocal learning. The results show that neural tuning in auditory cortex mirrors behavioral improvements in the ability to make perceptual distinctions of vocal calls as birds are engaged in vocal learning. Thus, separate measures of neural discrimination and behavioral perception yielded highly similar trends during the course of vocal development. The timing of this improvement in the ability to distinguish vocal sounds correlates with our previous work showing substantial refinement of axonal connectivity in cortico-basal ganglia pathways necessary for vocal learning.