Multiplexed and robust representations of sound features in auditory cortex

Temporal Coherence Shapes Cortical Responses to Speech Mixtures in a Ferret Cocktail Party

Segregation of complex sounds such as speech, music and animal vocalizations as they simultaneously emanate from multiple sources (referred to as the "cocktail party problem") is a remarkable ability that is common in humans and animals alike. The neural underpinnings of this process have been extensively studied behaviorally and physiologically in non-human animals primarily with simplified sounds (tones and noise sequences). In humans, segregation experiments utilizing more complex speech mixtures are common; but physiological experiments have relied on EEG/MEG/ECoG recordings that sample activity from thousands of neurons, often obscuring the detailed processes that give rise to the observed segregation. The present study combines the insights from animal single-unit physiology with segregation of speech-like mixtures. Ferrets were trained to attend to a female voice and detect a target word, both in presence or absence of a concurrent, equally salient male voice. Single neuron recordings were obtained from primary and secondary ferret auditory cortical fields, as well as frontal cortex. During task performance, representation of the female words became more enhanced relative to those of the (distractor) male in all cortical regions, especially in the higher auditory cortical field. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings are consistent with the temporal coherence theory whereby attention to a target voice anchors neural activity in cortical networks hence binding together channels that are coherently temporally-modulated with the target, and ultimately forming a common auditory stream.

Basic Properties of Coordinated Neuronal Ensembles in the Auditory Thalamus

Coordinated neuronal activity has been identified to play an important role in information processing and transmission in the brain. However, current research predominantly focuses on understanding the properties and functions of neuronal coordination in hippocampal and cortical areas, leaving subcortical regions relatively unexplored. In this study, we use single-unit recordings in female Sprague Dawley rats to investigate the properties and functions of groups of neurons exhibiting coordinated activity in the auditory thalamus-the medial geniculate body (MGB). We reliably identify coordinated neuronal ensembles (cNEs), which are groups of neurons that fire synchronously, in the MGB. cNEs are shown not to be the result of false-positive detections or by-products of slow-state oscillations in anesthetized animals. We demonstrate that cNEs in the MGB have enhanced information-encoding properties over individual neurons. Their neuronal composition is stable between spontaneous and evoked activity, suggesting limited stimulus-induced ensemble dynamics. These MGB cNE properties are similar to what is observed in cNEs in the primary auditory cortex (A1), suggesting that ensembles serve as a ubiquitous mechanism for organizing local networks and play a fundamental role in sensory processing within the brain.

Neural responses to syllable-induced P1m and social impairment in children with autism spectrum disorder and typically developing Peers

In previous magnetoencephalography (MEG) studies, children with autism spectrum disorder (ASD) have been shown to respond differently to speech stimuli than typically developing (TD) children. Quantitative evaluation of this difference in responsiveness may support early diagnosis and intervention for ASD. The objective of this research is to investigate the relationship between syllable-induced P1m and social impairment in children with ASD and TD children. We analyzed 49 children with ASD aged 40-92 months and age-matched 26 TD children. We evaluated their social impairment by means of the Social Responsiveness Scale (SRS) and their intelligence ability using the Kaufman Assessment Battery for Children (K-ABC). Multiple regression analysis with SRS score as the dependent variable and syllable-induced P1m latency or intensity and intelligence ability as explanatory variables revealed that SRS score was associated with syllable-induced P1m latency in the left hemisphere only in the TD group and not in the ASD group. A second finding was that increased leftward-lateralization of intensity was correlated with higher SRS scores only in the ASD group. These results provide valuable insights but also highlight the intricate nature of neural mechanisms and their relationship with autistic traits.

Evidence for Multiscale Multiplexed Representation of Visual Features in EEG

Distinct neural processes such as sensory and memory processes are often encoded over distinct timescales of neural activations. Animal studies have shown that this multiscale coding strategy is also implemented for individual components of a single process, such as individual features of a multifeature stimulus in sensory coding. However, the generalizability of this encoding strategy to the human brain has remained unclear. We asked if individual features of visual stimuli were encoded over distinct timescales. We applied a multiscale time-resolved decoding method to electroencephalography (EEG) collected from human subjects presented with grating visual stimuli to estimate the timescale of individual stimulus features. We observed that the orientation and color of the stimuli were encoded in shorter timescales, whereas spatial frequency and the contrast of the same stimuli were encoded in longer timescales. The stimulus features appeared in temporally overlapping windows along the trial supporting a multiplexed coding strategy. These results provide evidence for a multiplexed, multiscale coding strategy in the human visual system.

Different hemispheric lateralization for periodicity and formant structure of vowels in the auditory cortex and its changes between childhood and adulthood

The spectral formant structure and periodicity pitch are the major features that determine the identity of vowels and the characteristics of the speaker. However, very little is known about how the processing of these features in the auditory cortex changes during development. To address this question, we independently manipulated the periodicity and formant structure of vowels while measuring auditory cortex responses using magnetoencephalography (MEG) in children aged 7-12 years and adults. We analyzed the sustained negative shift of source current associated with these vowel properties, which was present in the auditory cortex in both age groups despite differences in the transient components of the auditory response. In adults, the sustained activation associated with formant structure was lateralized to the left hemisphere early in the auditory processing stream requiring neither attention nor semantic mapping. This lateralization was not yet established in children, in whom the right hemisphere contribution to formant processing was strong and decreased during or after puberty. In contrast to the formant structure, periodicity was associated with a greater response in the right hemisphere in both children and adults. These findings suggest that left-lateralization for the automatic processing of vowel formant structure emerges relatively late in ontogenesis and pose a serious challenge to current theories of hemispheric specialization for speech processing.

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.

Toward reproducible models of sequence learning: replication and analysis of a modular spiking network with reward-based learning

To acquire statistical regularities from the world, the brain must reliably process, and learn from, spatio-temporally structured information. Although an increasing number of computational models have attempted to explain how such sequence learning may be implemented in the neural hardware, many remain limited in functionality or lack biophysical plausibility. If we are to harvest the knowledge within these models and arrive at a deeper mechanistic understanding of sequential processing in cortical circuits, it is critical that the models and their findings are accessible, reproducible, and quantitatively comparable. Here we illustrate the importance of these aspects by providing a thorough investigation of a recently proposed sequence learning model. We re-implement the modular columnar architecture and reward-based learning rule in the open-source NEST simulator, and successfully replicate the main findings of the original study. Building on these, we perform an in-depth analysis of the model's robustness to parameter settings and underlying assumptions, highlighting its strengths and weaknesses. We demonstrate a limitation of the model consisting in the hard-wiring of the sequence order in the connectivity patterns, and suggest possible solutions. Finally, we show that the core functionality of the model is retained under more biologically-plausible constraints.

Functional network properties of the auditory cortex

The auditory system transforms auditory stimuli from the external environment into perceptual auditory objects. Recent studies have focused on the contribution of the auditory cortex to this transformation. Other studies have yielded important insights into the contributions of neural activity in the auditory cortex to cognition and decision-making. However, despite this important work, the relationship between auditory-cortex activity and behavior/perception has not been fully elucidated. Two of the more important gaps in our understanding are (1) the specific and differential contributions of different fields of the auditory cortex to auditory perception and behavior and (2) the way networks of auditory neurons impact and facilitate auditory information processing. Here, we focus on recent work from non-human-primate models of hearing and review work related to these gaps and put forth challenges to further our understanding of how single-unit activity and network activity in different cortical fields contribution to behavior and perception.

Distribution of multiunit pitch responses recorded intracranially from human auditory cortex

The perception of pitch is a fundamental percept, which is mediated by the auditory system, requiring the abstraction of stimulus properties related to the spectro-temporal structure of sound. Despite its importance, there is still debate as to the precise areas responsible for its encoding, which may be due to species differences or differences in the recording measures and choices of stimuli used in previous studies. Moreover, it was unknown whether the human brain contains pitch neurons and how distributed such neurons might be. Here, we present the first study to measure multiunit neural activity in response to pitch stimuli in the auditory cortex of intracranially implanted humans. The stimulus sets were regular-interval noise with a pitch strength that is related to the temporal regularity and a pitch value determined by the repetition rate and harmonic complexes. Specifically, we demonstrate reliable responses to these different pitch-inducing paradigms that are distributed throughout Heschl's gyrus, rather than being localized to a particular region, and this finding was evident regardless of the stimulus presented. These data provide a bridge across animal and human studies and aid our understanding of the processing of a critical percept associated with acoustic stimuli.

Reversible Inactivation of Ferret Auditory Cortex Impairs Spatial and Nonspatial Hearing

A key question in auditory neuroscience is to what extent are brain regions functionally specialized for processing specific sound features, such as location and identity. In auditory cortex, correlations between neural activity and sounds support both the specialization of distinct cortical subfields, and encoding of multiple sound features within individual cortical areas. However, few studies have tested the contribution of auditory cortex to hearing in multiple contexts. Here we determined the role of ferret primary auditory cortex in both spatial and nonspatial hearing by reversibly inactivating the middle ectosylvian gyrus during behavior using cooling (n = 2 females) or optogenetics (n = 1 female). Optogenetic experiments used the mDLx promoter to express Channelrhodopsin-2 in GABAergic interneurons, and we confirmed both viral expression (n = 2 females) and light-driven suppression of spiking activity in auditory cortex, recorded using Neuropixels under anesthesia (n = 465 units from 2 additional untrained female ferrets). Cortical inactivation via cooling or optogenetics impaired vowel discrimination in colocated noise. Ferrets implanted with cooling loops were tested in additional conditions that revealed no deficit when identifying vowels in clean conditions, or when the temporally coincident vowel and noise were spatially separated by 180 degrees. These animals did, however, show impaired sound localization when inactivating the same auditory cortical region implicated in vowel discrimination in noise. Our results demonstrate that, as a brain region showing mixed selectivity for spatial and nonspatial features of sound, primary auditory cortex contributes to multiple forms of hearing.SIGNIFICANCE STATEMENT Neurons in primary auditory cortex are often sensitive to the location and identity of sounds. Here we inactivated auditory cortex during spatial and nonspatial listening tasks using cooling, or optogenetics. Auditory cortical inactivation impaired multiple behaviors, demonstrating a role in both the analysis of sound location and identity and confirming a functional contribution of mixed selectivity observed in neural activity. Parallel optogenetic experiments in two additional untrained ferrets linked behavior to physiology by demonstrating that expression of Channelrhodopsin-2 permitted rapid light-driven suppression of auditory cortical activity recorded under anesthesia.

New insights on single-neuron selectivity in the era of population-level approaches

In the past, neuroscience was focused on individual neurons seen as the functional units of the nervous system, but this approach fell short over time to account for new experimental evidence, especially for what concerns associative and motor cortices. For this reason and thanks to great technological advances, a part of modern research has shifted the focus from the responses of single neurons to the activity of neural ensembles, now considered the real functional units of the system. However, on a microscale, individual neurons remain the computational components of these networks, thus the study of population dynamics cannot prescind from studying also individual neurons which represent their natural substrate. In this new framework, ideas such as the capability of single cells to encode a specific stimulus (neural selectivity) may become obsolete and need to be profoundly revised. One step in this direction was made by introducing the concept of “mixed selectivity,” the capacity of single cells to integrate multiple variables in a flexible way, allowing individual neurons to participate in different networks. In this review, we outline the most important features of mixed selectivity and we also present recent works demonstrating its presence in the associative areas of the posterior parietal cortex. Finally, in discussing these findings, we present some open questions that could be addressed by future studies.

Interaction of bottom-up and top-down neural mechanisms in spatial multi-talker speech perception

How the human auditory cortex represents spatially separated simultaneous talkers and how talkers' locations and voices modulate the neural representations of attended and unattended speech are unclear. Here, we measured the neural responses from electrodes implanted in neurosurgical patients as they performed single-talker and multi-talker speech perception tasks. We found that spatial separation between talkers caused a preferential encoding of the contralateral speech in Heschl's gyrus (HG), planum temporale (PT), and superior temporal gyrus (STG). Location and spectrotemporal features were encoded in different aspects of the neural response. Specifically, the talker's location changed the mean response level, whereas the talker's spectrotemporal features altered the variation of response around response's baseline. These components were differentially modulated by the attended talker's voice or location, which improved the population decoding of attended speech features. Attentional modulation due to the talker's voice only appeared in the auditory areas with longer latencies, but attentional modulation due to location was present throughout. Our results show that spatial multi-talker speech perception relies upon a separable pre-attentive neural representation, which could be further tuned by top-down attention to the location and voice of the talker.

Auditory salience using natural scenes: An online study

Salience is the quality of a sensory signal that attracts involuntary attention in humans. While it primarily reflects conspicuous physical attributes of a scene, our understanding of processes underlying what makes a certain object or event salient remains limited. In the vision literature, experimental results, theoretical accounts, and large amounts of eye-tracking data using rich stimuli have shed light on some of the underpinnings of visual salience in the brain. In contrast, studies of auditory salience have lagged behind due to limitations in both experimental designs and stimulus datasets used to probe the question of salience in complex everyday soundscapes. In this work, we deploy an online platform to study salience using a dichotic listening paradigm with natural auditory stimuli. The study validates crowd-sourcing as a reliable platform to collect behavioral responses to auditory salience by comparing experimental outcomes to findings acquired in a controlled laboratory setting. A model-based analysis demonstrates the benefits of extending behavioral measures of salience to broader selection of auditory scenes and larger pools of subjects. Overall, this effort extends our current knowledge of auditory salience in everyday soundscapes and highlights the limitations of low-level acoustic attributes in capturing the richness of natural soundscapes.

An Emergent Population Code in Primary Auditory Cortex Supports Selective Attention to Spectral and Temporal Sound Features

Textbook descriptions of primary sensory cortex (PSC) revolve around single neurons' representation of low-dimensional sensory features, such as visual object orientation in primary visual cortex (V1), location of somatic touch in primary somatosensory cortex (S1), and sound frequency in primary auditory cortex (A1). Typically, studies of PSC measure neurons' responses along few (one or two) stimulus and/or behavioral dimensions. However, real-world stimuli usually vary along many feature dimensions and behavioral demands change constantly. In order to illuminate how A1 supports flexible perception in rich acoustic environments, we recorded from A1 neurons while rhesus macaques (one male, one female) performed a feature-selective attention task. We presented sounds that varied along spectral and temporal feature dimensions (carrier bandwidth and temporal envelope, respectively). Within a block, subjects attended to one feature of the sound in a selective change detection task. We found that single neurons tend to be high-dimensional, in that they exhibit substantial mixed selectivity for both sound features, as well as task context. We found no overall enhancement of single-neuron coding of the attended feature, as attention could either diminish or enhance this coding. However, a population-level analysis reveals that ensembles of neurons exhibit enhanced encoding of attended sound features, and this population code tracks subjects' performance. Importantly, surrogate neural populations with intact single-neuron tuning but shuffled higher-order correlations among neurons fail to yield attention- related effects observed in the intact data. These results suggest that an emergent population code not measurable at the single-neuron level might constitute the functional unit of sensory representation in PSC.SIGNIFICANCE STATEMENT The ability to adapt to a dynamic sensory environment promotes a range of important natural behaviors. We recorded from single neurons in monkey primary auditory cortex (A1), while subjects attended to either the spectral or temporal features of complex sounds. Surprisingly, we found no average increase in responsiveness to, or encoding of, the attended feature across single neurons. However, when we pooled the activity of the sampled neurons via targeted dimensionality reduction (TDR), we found enhanced population-level representation of the attended feature and suppression of the distractor feature. This dissociation of the effects of attention at the level of single neurons versus the population highlights the synergistic nature of cortical sound encoding and enriches our understanding of sensory cortical function.

Interpreting wide-band neural activity using convolutional neural networks

Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires considerable knowledge about the nature of the representation and often depends on manual operations. Decoding provides a means to infer the information content of such recordings but typically requires highly processed data and prior knowledge of the encoding scheme. Here, we developed a deep-learning framework able to decode sensory and behavioral variables directly from wide-band neural data. The network requires little user input and generalizes across stimuli, behaviors, brain regions, and recording techniques. Once trained, it can be analyzed to determine elements of the neural code that are informative about a given variable. We validated this approach using electrophysiological and calcium-imaging data from rodent auditory cortex and hippocampus as well as human electrocorticography (ECoG) data. We show successful decoding of finger movement, auditory stimuli, and spatial behaviors - including a novel representation of head direction - from raw neural activity.

Functional characterization of human Heschl's gyrus in response to natural speech

Heschl's gyrus (HG) is a brain area that includes the primary auditory cortex in humans. Due to the limitations in obtaining direct neural measurements from this region during naturalistic speech listening, the functional organization and the role of HG in speech perception remain uncertain. Here, we used intracranial EEG to directly record neural activity in HG in eight neurosurgical patients as they listened to continuous speech stories. We studied the spatial distribution of acoustic tuning and the organization of linguistic feature encoding. We found a main gradient of change from posteromedial to anterolateral parts of HG. We also observed a decrease in frequency and temporal modulation tuning and an increase in phonemic representation, speaker normalization, speech sensitivity, and response latency. We did not observe a difference between the two brain hemispheres. These findings reveal a functional role for HG in processing and transforming simple to complex acoustic features and inform neurophysiological models of speech processing in the human auditory cortex.

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.

Information diversity in individual auditory cortical neurons is associated with functionally distinct coordinated neuronal ensembles

Neuronal activity in auditory cortex is often highly synchronous between neighboring neurons. Such coordinated activity is thought to be crucial for information processing. We determined the functional properties of coordinated neuronal ensembles (cNEs) within primary auditory cortical (AI) columns relative to the contributing neurons. Nearly half of AI cNEs showed robust spectro-temporal receptive fields whereas the remaining cNEs showed little or no acoustic feature selectivity. cNEs can therefore capture either specific, time-locked information of spectro-temporal stimulus features or reflect stimulus-unspecific, less-time specific processing aspects. By contrast, we show that individual neurons can represent both of those aspects through membership in multiple cNEs with either high or absent feature selectivity. These associations produce functionally heterogeneous spikes identifiable by instantaneous association with different cNEs. This demonstrates that single neuron spike trains can sequentially convey multiple aspects that contribute to cortical processing, including stimulus-specific and unspecific information.

Listening in complex acoustic scenes

Being able to pick out particular sounds, such as speech, against a background of other sounds represents one of the key tasks performed by the auditory system. Understanding how this happens is important because speech recognition in noise is particularly challenging for older listeners and for people with hearing impairments. Central to this ability is the capacity of neurons to adapt to the statistics of sounds reaching the ears, which helps to generate noise-tolerant representations of sounds in the brain. In more complex auditory scenes, such as a cocktail party — where the background noise comprises other voices, sound features associated with each source have to be grouped together and segregated from those belonging to other sources. This depends on precise temporal coding and modulation of cortical response properties when attending to a particular speaker in a multi-talker environment. Furthermore, the neural processing underlying auditory scene analysis is shaped by experience over multiple timescales.

Nonlinear mixed selectivity supports reliable neural computation

Neuronal activity in the brain is variable, yet both perception and behavior are generally reliable. How does the brain achieve this? Here, we show that the conjunctive coding of multiple stimulus features, commonly known as nonlinear mixed selectivity, may be used by the brain to support reliable information transmission using unreliable neurons. Nonlinearly mixed feature representations have been observed throughout primary sensory, decision-making, and motor brain areas. In these areas, different features are almost always nonlinearly mixed to some degree, rather than represented separately or with only additive (linear) mixing, which we refer to as pure selectivity. Mixed selectivity has been previously shown to support flexible linear decoding for complex behavioral tasks. Here, we show that it has another important benefit: in many cases, it makes orders of magnitude fewer decoding errors than pure selectivity even when both forms of selectivity use the same number of spikes. This benefit holds for sensory, motor, and more abstract, cognitive representations. Further, we show experimental evidence that mixed selectivity exists in the brain even when it does not enable behaviorally useful linear decoding. This suggests that nonlinear mixed selectivity may be a general coding scheme exploited by the brain for reliable and efficient neural computation.

Neurons in the brain are unreliable, while both perception and behavior are generally reliable. In this work, we study how the neural population response to sensory, motor, and cognitive features can produce this reliability. Across the brain, single neurons have been shown to respond to particular conjunctions of multiple features, termed nonlinear mixed selectivity. In this work, we show that populations of these mixed selective neurons lead to many fewer decoding errors than populations without mixed selectivity, even when both neural codes are given the same number of spikes. We show that the reliability benefits from mixed selectivity are quite general, holding under different assumptions about metabolic costs and neural noise as well as for both categorical and sensory errors. Further, previous theoretical work has shown that mixed selectivity enables the learning of complex behaviors with simple decoders. Through the analysis of neural data, we show that the brain implements mixed selectivity even when it would not serve this purpose. Thus, we argue that the brain also implements mixed selectivity to exploit its general benefits for reliable and efficient neural computation.

Joint Representation of Spatial and Phonetic Features in the Human Core Auditory Cortex

The human auditory cortex simultaneously processes speech and determines the location of a speaker in space. Neuroimaging studies in humans have implicated core auditory areas in processing the spectrotemporal and the spatial content of sound; however, how these features are represented together is unclear. We recorded directly from human subjects implanted bilaterally with depth electrodes in core auditory areas as they listened to speech from different directions. We found local and joint selectivity to spatial and spectrotemporal speech features, where the spatial and spectrotemporal features are organized independently of each other. This representation enables successful decoding of both spatial and phonetic information. Furthermore, we found that the location of the speaker does not change the spectrotemporal tuning of the electrodes but, rather, modulates their mean response level. Our findings contribute to defining the functional organization of responses in the human auditory cortex, with implications for more accurate neurophysiological models of speech processing.

Emergence of an Invariant Representation of Texture in Primate Somatosensory Cortex

A major function of sensory processing is to achieve neural representations of objects that are stable across changes in context and perspective. Small changes in exploratory behavior can lead to large changes in signals at the sensory periphery, thus resulting in ambiguous neural representations of objects. Overcoming this ambiguity is a hallmark of human object recognition across sensory modalities. Here, we investigate how the perception of tactile texture remains stable across exploratory movements of the hand, including changes in scanning speed, despite the concomitant changes in afferent responses. To this end, we scanned a wide range of everyday textures across the fingertips of rhesus macaques at multiple speeds and recorded the responses evoked in tactile nerve fibers and somatosensory cortical neurons (from Brodmann areas 3b, 1, and 2). We found that individual cortical neurons exhibit a wider range of speed-sensitivities than do nerve fibers. The resulting representations of speed and texture in cortex are more independent than are their counterparts in the nerve and account for speed-invariant perception of texture. We demonstrate that this separation of speed and texture information is a natural consequence of previously described cortical computations.

Hierarchical Encoding of Attended Auditory Objects in Multi-talker Speech Perception

Humans can easily focus on one speaker in a multi-talker acoustic environment, but how different areas of the human auditory cortex (AC) represent the acoustic components of mixed speech is unknown. We obtained invasive recordings from the primary and nonprimary AC in neurosurgical patients as they listened to multi-talker speech. We found that neural sites in the primary AC responded to individual speakers in the mixture and were relatively unchanged by attention. In contrast, neural sites in the nonprimary AC were less discerning of individual speakers but selectively represented the attended speaker. Moreover, the encoding of the attended speaker in the nonprimary AC was invariant to the degree of acoustic overlap with the unattended speaker. Finally, this emergent representation of attended speech in the nonprimary AC was linearly predictable from the primary AC responses. Our results reveal the neural computations underlying the hierarchical formation of auditory objects in human AC during multi-talker speech perception.

The Rapid Emergence of Auditory Object Representations in Cortex Reflect Central Acoustic Attributes

Human listeners are bombarded by acoustic information that the brain rapidly organizes into coherent percepts of objects and events in the environment, which aids speech and music perception. The efficiency of auditory object recognition belies the critical constraint that acoustic stimuli necessarily require time to unfold. Using magnetoencephalography, we studied the time course of the neural processes that transform dynamic acoustic information into auditory object representations. Participants listened to a diverse set of 36 tokens comprising everyday sounds from a typical human environment. Multivariate pattern analysis was used to decode the sound tokens from the magnetoencephalographic recordings. We show that sound tokens can be decoded from brain activity beginning 90 msec after stimulus onset with peak decoding performance occurring at 155 msec poststimulus onset. Decoding performance was primarily driven by differences between category representations (e.g., environmental vs. instrument sounds), although within-category decoding was better than chance. Representational similarity analysis revealed that these emerging neural representations were related to harmonic and spectrotemporal differences among the stimuli, which correspond to canonical acoustic features processed by the auditory pathway. Our findings begin to link the processing of physical sound properties with the perception of auditory objects and events in cortex.

Invariant neural responses for sensory categories revealed by the time-varying information for communication calls

Although information theoretic approaches have been used extensively in the analysis of the neural code, they have yet to be used to describe how information is accumulated in time while sensory systems are categorizing dynamic sensory stimuli such as speech sounds or visual objects. Here, we present a novel method to estimate the cumulative information for stimuli or categories. We further define a time-varying categorical information index that, by comparing the information obtained for stimuli versus categories of these same stimuli, quantifies invariant neural representations. We use these methods to investigate the dynamic properties of avian cortical auditory neurons recorded in zebra finches that were listening to a large set of call stimuli sampled from the complete vocal repertoire of this species. We found that the time-varying rates carry 5 times more information than the mean firing rates even in the first 100 ms. We also found that cumulative information has slow time constants (100–600 ms) relative to the typical integration time of single neurons, reflecting the fact that the behaviorally informative features of auditory objects are time-varying sound patterns. When we correlated firing rates and information values, we found that average information correlates with average firing rate but that higher-rates found at the onset response yielded similar information values as the lower-rates found in the sustained response: the onset and sustained response of avian cortical auditory neurons provide similar levels of independent information about call identity and call-type. Finally, our information measures allowed us to rigorously define categorical neurons; these categorical neurons show a high degree of invariance for vocalizations within a call-type. Peak invariance is found around 150 ms after stimulus onset. Surprisingly, call-type invariant neurons were found in both primary and secondary avian auditory areas.

Just as the recognition of faces requires neural representations that are invariant to scale and rotation, the recognition of behaviorally relevant auditory objects, such as spoken words, requires neural representations that are invariant to the speaker uttering the word and to his or her location. Here, we used information theory to investigate the time course of the neural representation of bird communication calls and of behaviorally relevant categories of these same calls: the call-types of the bird’s repertoire. We found that neurons in both the primary and secondary avian auditory cortex exhibit invariant responses to call renditions within a call-type, suggestive of a potential role for extracting the meaning of these communication calls. We also found that time plays an important role: first, neural responses carry significantly more information when represented by temporal patterns calculated at the small time scale of 10 ms than when measured as average rates and, second, this information accumulates in a non-redundant fashion up to long integration times of 600 ms. This rich temporal neural representation is matched to the temporal richness found in the communication calls of this species.

Direct electrophysiological mapping of human pitch-related processing in auditory cortex

This work sought correlates of pitch perception, defined by neural activity above the lower limit of pitch (LLP), in auditory cortical neural ensembles, and examined their topographical distribution. Local field potentials (LFPs) were recorded in eight patients undergoing invasive recordings for pharmaco-resistant epilepsy. Stimuli consisted of bursts of broadband noise followed by regular interval noise (RIN). RIN was presented at rates below and above the LLP to distinguish responses related to the regularity of the stimulus and the presence of pitch itself. LFPs were recorded from human cortical homologues of auditory core, belt, and parabelt regions using multicontact depth electrodes implanted in Heschl's gyrus (HG) and Planum Temporale (PT), and subdural grid electrodes implanted over lateral superior temporal gyrus (STG). Evoked responses corresponding to the temporal regularity of the stimulus were assessed using autocorrelation of the evoked responses, and occurred for stimuli below and above the LLP. Induced responses throughout the high gamma range (60-200 Hz) were present for pitch values above the LLP, with onset latencies of approximately 70 ms. Mapping of the induced responses onto a common brain space demonstrated variability in the topographical distribution of high gamma responses across subjects. Induced responses were present throughout the length of HG and on PT, which is consistent with previous functional neuroimaging studies. Moreover, in each subject, a region within lateral STG showed robust induced responses at pitch-evoking stimulus rates. This work suggests a distributed representation of pitch processing in neural ensembles in human homologues of core and non-core auditory cortex.

Neurons in primary auditory cortex represent sound source location in a cue-invariant manner

Auditory cortex is required for sound localisation, but how neural firing in auditory cortex underlies our perception of sound sources in space remains unclear. Specifically, whether neurons in auditory cortex represent spatial cues or an integrated representation of auditory space across cues is not known. Here, we measured the spatial receptive fields of neurons in primary auditory cortex (A1) while ferrets performed a relative localisation task. Manipulating the availability of binaural and spectral localisation cues had little impact on ferrets’ performance, or on neural spatial tuning. A subpopulation of neurons encoded spatial position consistently across localisation cue type. Furthermore, neural firing pattern decoders outperformed two-channel model decoders using population activity. Together, these observations suggest that A1 encodes the location of sound sources, as opposed to spatial cue values.

The brain's auditory cortex is involved not just in detection of sounds, but also in localizing them. Here, the authors show that neurons in ferret primary auditory cortex (A1) encode the location of sound sources, as opposed to merely reflecting spatial cues.

Pairing vagus nerve stimulation with tones drives plasticity across the auditory pathway

Previous studies have demonstrated that pairing vagus nerve stimulation (VNS) with sounds can enhance the primary auditory cortex (A1) response to the paired sound. The neural response to sounds following VNS-sound pairing in other subcortical and cortical auditory fields has not been documented. We predicted that VNS-tone pairing would increase neural responses to the paired tone frequency across the auditory pathway. In this study, we paired VNS with the presentation of a 9-kHz tone 300 times a day for 20 days. We recorded neural responses to tones from 2,950 sites in the inferior colliculus (IC), A1, anterior auditory field (AAF), and posterior auditory field (PAF) 24 h after the last pairing session in anesthetized rats. We found that VNS-tone pairing increased the percentage of IC, A1, AAF, and PAF that responds to the paired tone frequency. Across all tested auditory fields, the response strength to tones was strengthened in VNS-tone paired rats compared with control rats. VNS-tone pairing reduced spontaneous activity, frequency selectivity, and response threshold across the auditory pathway. This is the first study to document both cortical and subcortical plasticity following VNS-sound pairing. Our findings suggest that VNS paired with sound presentation is an effective method to enhance auditory processing.NEW & NOTEWORTHY Previous studies have reported primary auditory cortex plasticity following vagus nerve stimulation (VNS) paired with a sound. This study extends previous findings by documenting that fields across the auditory pathway are altered by VNS-tone pairing. VNS-tone pairing increases the percentage of each field that responds to the paired tone frequency. This is the first study to document both cortical and subcortical plasticity following VNS-sound pairing.

The Encoding of Speech Sounds in the Superior Temporal Gyrus

The human superior temporal gyrus (STG) is critical for extracting meaningful linguistic features from speech input. Local neural populations are tuned to acoustic-phonetic features of all consonants and vowels and to dynamic cues for intonational pitch. These populations are embedded throughout broader functional zones that are sensitive to amplitude-based temporal cues. Beyond speech features, STG representations are strongly modulated by learned knowledge and perceptual goals. Currently, a major challenge is to understand how these features are integrated across space and time in the brain during natural speech comprehension. We present a theory that temporally recurrent connections within STG generate context-dependent phonological representations, spanning longer temporal sequences relevant for coherent percepts of syllables, words, and phrases.

Sensitivity to Vocalization Pitch in the Caudal Auditory Cortex of the Marmoset: Comparison of Core and Belt Areas

Based on anatomical connectivity and basic response characteristics, primate auditory cortex is divided into a central core surrounded by belt and parabelt regions. The encoding of pitch, a prototypical element of sound identity, has been studied in primary auditory cortex (A1) but little is known about how it is encoded and represented beyond A1. The caudal auditory belt and parabelt cortical fields process spatial information but also contain information on non-spatial aspects of sounds. In this study, we examined neuronal responses in these areas to pitch-varied marmoset vocalizations, to derive the consequent representation of pitch in these regions and the potential underlying mechanisms, to compare to the encoding and representation of pitch of the same sounds in A1. With respect to response patterns to the vocalizations, neurons in caudal medial belt (CM) showed similar short-latency and short-duration response patterns to A1, but caudal lateral belt (CL) neurons at the same hierarchical level and caudal parabelt (CPB) neurons at a higher hierarchical level showed delayed or much delayed response onset and prolonged response durations. With respect to encoding of pitch, neurons in all cortical fields showed sensitivity to variations in the vocalization pitch either through modulation of spike-count or of first spike-latency. The utility of the encoding mechanism differed between fields: pitch sensitivity was reliably represented by spike-count variations in A1 and CM, while first spike-latency variation was better for encoding pitch in CL and CPB. In summary, our data show that (a) the traditionally-defined belt area CM is functionally very similar to A1 with respect to the representation and encoding of complex naturalistic sounds, (b) the CL belt area, at the same hierarchical level as CM, and the CPB area, at a higher hierarchical level, have very different response patterns and appear to use different pitch-encoding mechanisms, and (c) caudal auditory fields, proposed to be specialized for encoding spatial location, can also contain robust representations of sound identity.

Sound identity is represented robustly in auditory cortex during perceptual constancy

Perceptual constancy requires neural representations that are selective for object identity, but also tolerant across identity-preserving transformations. How such representations arise in the brain and support perception remains unclear. Here, we study tolerant representation of sound identity in the auditory system by recording neural activity in auditory cortex of ferrets during perceptual constancy. Ferrets generalize vowel identity across variations in fundamental frequency, sound level and location, while neurons represent sound identity robustly across acoustic variations. Stimulus features are encoded with distinct time-courses in all conditions, however encoding of sound identity is delayed when animals fail to generalize and during passive listening. Neurons also encode information about task-irrelevant sound features, as well as animals’ choices and accuracy, while population decoding out-performs animals’ behavior. Our results show that during perceptual constancy, sound identity is represented robustly in auditory cortex across widely varying conditions, and behavioral generalization requires conserved timing of identity information.

Perceptual constancy requires neural representations selective for object identity, yet tolerant of identity-preserving transformations. Here, the authors show that sound identity is represented robustly in auditory cortex and that behavioral generalization requires precise timing of identity information.

Recent advances in understanding the auditory cortex

Our ability to make sense of the auditory world results from neural processing that begins in the ear, goes through multiple subcortical areas, and continues in the cortex. The specific contribution of the auditory cortex to this chain of processing is far from understood. Although many of the properties of neurons in the auditory cortex resemble those of subcortical neurons, they show somewhat more complex selectivity for sound features, which is likely to be important for the analysis of natural sounds, such as speech, in real-life listening conditions. Furthermore, recent work has shown that auditory cortical processing is highly context-dependent, integrates auditory inputs with other sensory and motor signals, depends on experience, and is shaped by cognitive demands, such as attention. Thus, in addition to being the locus for more complex sound selectivity, the auditory cortex is increasingly understood to be an integral part of the network of brain regions responsible for prediction, auditory perceptual decision-making, and learning. In this review, we focus on three key areas that are contributing to this understanding: the sound features that are preferentially represented by cortical neurons, the spatial organization of those preferences, and the cognitive roles of the auditory cortex.

Activation in the auditory pathway of the gerbil studied with 18F-FDG PET: effects of anesthesia

Here, we present results from an ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) study in the Mongolian gerbil, a preferred animal model in auditory research. One major issue in preclinical nuclear imaging, as well as in most of the neurophysiological methods investigating auditory processing, is the need of anesthesia. We compared the usability of two types of anesthesia which are frequently employed in electrophysiology, ketamine/xylazine (KX), and fentanyl/midazolam/medetomidine (FMM), for valid measurements of auditory activation with ¹⁸F-FDG PET. Gerbils were placed in a sound-shielding box and injected with ¹⁸F-FDG. Two acoustic free-field conditions were used: (1) baseline (no stimulation, 25 dB background noise) and (2) 90 dB frequency-modulated tones (FM). After 40 min of ¹⁸F-FDG uptake, a 30 min acquisition was performed using a small animal PET/CT system. Blood glucose levels were measured after the uptake phase before scanning. Standardized uptake value ratios for relevant regions were determined after implementing image and volume of interest templates. Scans demonstrated a significantly higher uptake in the inferior colliculus with FM stimulation compared to baseline in awake subjects (+ 12%; p = 0.02) and with FMM anesthesia (+ 13%; p = 0.0012), but not with KX anesthesia. In non-auditory brain regions, no significant difference was detected. Blood glucose levels were significantly higher under KX compared to FMM anesthesia (17.29 ± 0.42 mmol/l vs. 14.30 ± 1.91 mmol/l; p = 0.024). These results suggest that valid ¹⁸F-FDG PET measurements of auditory activation comparable to electrophysiology can be obtained from gerbils during opioid-based anesthesia due to its limited effects on interfering blood glucose levels.

Optimal dynamic coding by mixed-dimensionality neurons in the head-direction system of bats

Ethologically relevant stimuli are often multidimensional. In many brain systems, neurons with “pure” tuning to one stimulus dimension are found along with “conjunctive” neurons that encode several dimensions, forming an apparently redundant representation. Here we show using theoretical analysis that a mixed-dimensionality code can efficiently represent a stimulus in different behavioral regimes: encoding by conjunctive cells is more robust when the stimulus changes quickly, whereas on long timescales pure cells represent the stimulus more efficiently with fewer neurons. We tested our predictions experimentally in the bat head-direction system and found that many head-direction cells switched their tuning dynamically from pure to conjunctive representation as a function of angular velocity—confirming our theoretical prediction. More broadly, our results suggest that optimal dimensionality depends on population size and on the time available for decoding—which might explain why mixed-dimensionality representations are common in sensory, motor, and higher cognitive systems across species.

Multidimensional stimuli are often represented by neurons encoding only a single dimension and those encoding multiple dimensions. Here, the authors present theoretical and experimental analyses to show that mixed representations are optimal to efficiently encode such stimuli under different behavioral modes.

Neural representation of vowel formants in tonotopic auditory cortex

Speech sounds are encoded by distributed patterns of activity in bilateral superior temporal cortex. However, it is unclear whether speech sounds are topographically represented in cortex, or which acoustic or phonetic dimensions might be spatially mapped. Here, using functional MRI, we investigated the potential spatial representation of vowels, which are largely distinguished from one another by the frequencies of their first and second formants, i.e. peaks in their frequency spectra. This allowed us to generate clear hypotheses about the representation of specific vowels in tonotopic regions of auditory cortex. We scanned participants as they listened to multiple natural tokens of the vowels [ɑ] and [i], which we selected because their first and second formants overlap minimally. Formant-based regions of interest were defined for each vowel based on spectral analysis of the vowel stimuli and independently acquired tonotopic maps for each participant. We found that perception of [ɑ] and [i] yielded differential activation of tonotopic regions corresponding to formants of [ɑ] and [i], such that each vowel was associated with increased signal in tonotopic regions corresponding to its own formants. This pattern was observed in Heschl's gyrus and the superior temporal gyrus, in both hemispheres, and for both the first and second formants. Using linear discriminant analysis of mean signal change in formant-based regions of interest, the identity of untrained vowels was predicted with ∼73% accuracy. Our findings show that cortical encoding of vowels is scaffolded on tonotopy, a fundamental organizing principle of auditory cortex that is not language-specific.

How We Hear: The Perception and Neural Coding of Sound

Auditory perception is our main gateway to communication with others via speech and music, and it also plays an important role in alerting and orienting us to new events. This review provides an overview of selected topics pertaining to the perception and neural coding of sound, starting with the first stage of filtering in the cochlea and its profound impact on perception. The next topic, pitch, has been debated for millennia, but recent technical and theoretical developments continue to provide us with new insights. Cochlear filtering and pitch both play key roles in our ability to parse the auditory scene, enabling us to attend to one auditory object or stream while ignoring others. An improved understanding of the basic mechanisms of auditory perception will aid us in the quest to tackle the increasingly important problem of hearing loss in our aging population.

Single Neurons in the Avian Auditory Cortex Encode Individual Identity and Propagation Distance in Naturally Degraded Communication Calls

One of the most complex tasks performed by sensory systems is "scene analysis": the interpretation of complex signals as behaviorally relevant objects. The study of this problem, universal to species and sensory modalities, is particularly challenging in audition, where sounds from various sources and localizations, degraded by propagation through the environment, sum to form a single acoustical signal. Here we investigated in a songbird model, the zebra finch, the neural substrate for ranging and identifying a single source. We relied on ecologically and behaviorally relevant stimuli, contact calls, to investigate the neural discrimination of individual vocal signature as well as sound source distance when calls have been degraded through propagation in a natural environment. Performing electrophysiological recordings in anesthetized birds, we found neurons in the auditory forebrain that discriminate individual vocal signatures despite long-range degradation, as well as neurons discriminating propagation distance, with varying degrees of multiplexing between both information types. Moreover, the neural discrimination performance of individual identity was not affected by propagation-induced degradation beyond what was induced by the decreased intensity. For the first time, neurons with distance-invariant identity discrimination properties as well as distance-discriminant neurons are revealed in the avian auditory cortex. Because these neurons were recorded in animals that had prior experience neither with the vocalizers of the stimuli nor with long-range propagation of calls, we suggest that this neural population is part of a general-purpose system for vocalizer discrimination and ranging.SIGNIFICANCE STATEMENT Understanding how the brain makes sense of the multitude of stimuli that it continually receives in natural conditions is a challenge for scientists. Here we provide a new understanding of how the auditory system extracts behaviorally relevant information, the vocalizer identity and its distance to the listener, from acoustic signals that have been degraded by long-range propagation in natural conditions. We show, for the first time, that single neurons, in the auditory cortex of zebra finches, are capable of discriminating the individual identity and sound source distance in conspecific communication calls. The discrimination of identity in propagated calls relies on a neural coding that is robust to intensity changes, signals' quality, and decreases in the signal-to-noise ratio.

Distributed feature binding in the auditory modality: experimental evidence toward reconciliation of opposing views on the basis of mismatch negativity and behavioral measures

Current understanding of feature binding remains controversial. Studies involving mismatch negativity (MMN) measurement show a low level of binding, whereas behavioral experiments suggest a higher level. We examined the possibility that the two levels of feature binding coexist and may be shown within one experiment. The electroencephalogram was recorded while participants were engaged in an auditory two-alternative choice task, which was a combination of the oddball and the condensation tasks. Two types of deviant target stimuli were used - complex stimuli, which required feature conjunction to be identified, and simple stimuli, which differed from standard stimuli in a single feature. Two behavioral outcomes - correct responses and errors - were analyzed separately. Responses to complex stimuli were slower and less accurate than responses to simple stimuli. MMN was prominent and its amplitude was similar for both simple and complex stimuli, whereas the respective stimuli differed from standards in a single feature or two features respectively. Errors in response only to complex stimuli were associated with decreased MMN amplitude. P300 amplitude was greater for complex stimuli than for simple stimuli. Our data are compatible with the explanation that feature binding in auditory modality depends on two concurrent levels of processing. We speculate that the earlier level related to MMN generation is an essential and critical stage. Yet, a later analysis is also carried out, affecting P300 amplitude and response time. The current findings provide resolution to conflicting views on the nature of feature binding and show that feature binding is a distributed multilevel process.

Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex

Successful speech perception in real-world environments requires that the auditory system segregate competing voices that overlap in frequency and time into separate streams. Vowels are major constituents of speech and are comprised of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). The pitch and identity of a vowel are determined by its F0 and spectral envelope (formant structure), respectively. When two spectrally overlapping vowels differing in F0 are presented concurrently, they can be readily perceived as two separate “auditory objects” with pitches at their respective F0s. A difference in pitch between two simultaneous vowels provides a powerful cue for their segregation, which in turn, facilitates their individual identification. The neural mechanisms underlying the segregation of concurrent vowels based on pitch differences are poorly understood. Here, we examine neural population responses in macaque primary auditory cortex (A1) to single and double concurrent vowels (/a/ and /i/) that differ in F0 such that they are heard as two separate auditory objects with distinct pitches. We find that neural population responses in A1 can resolve, via a rate-place code, lower harmonics of both single and double concurrent vowels. Furthermore, we show that the formant structures, and hence the identities, of single vowels can be reliably recovered from the neural representation of double concurrent vowels. We conclude that A1 contains sufficient spectral information to enable concurrent vowel segregation and identification by downstream cortical areas.

Six Degrees of Auditory Spatial Separation

The location of a sound is derived computationally from acoustical cues rather than being inherent in the topography of the input signal, as in vision. Since Lord Rayleigh, the descriptions of that representation have swung between "labeled line" and "opponent process" models. Employing a simple variant of a two-point separation judgment using concurrent speech sounds, we found that spatial discrimination thresholds changed nonmonotonically as a function of the overall separation. Rather than increasing with separation, spatial discrimination thresholds first declined as two-point separation increased before reaching a turning point and increasing thereafter with further separation. This "dipper" function, with a minimum at 6 ° of separation, was seen for regions around the midline as well as for more lateral regions (30 and 45 °). The discrimination thresholds for the binaural localization cues were linear over the same range, so these cannot explain the shape of these functions. These data and a simple computational model indicate that the perception of auditory space involves a local code or multichannel mapping emerging subsequent to the binaural cue coding.

Attentional and Contextual Priors in Sound Perception

Behavioral and neural studies of selective attention have consistently demonstrated that explicit attentional cues to particular perceptual features profoundly alter perception and performance. The statistics of the sensory environment can also provide cues about what perceptual features to expect, but the extent to which these more implicit contextual cues impact perception and performance, as well as their relationship to explicit attentional cues, is not well understood. In this study, the explicit cues, or attentional prior probabilities, and the implicit cues, or contextual prior probabilities, associated with different acoustic frequencies in a detection task were simultaneously manipulated. Both attentional and contextual priors had similarly large but independent impacts on sound detectability, with evidence that listeners tracked and used contextual priors for a variety of sound classes (pure tones, harmonic complexes, and vowels). Further analyses showed that listeners updated their contextual priors rapidly and optimally, given the changing acoustic frequency statistics inherent in the paradigm. A Bayesian Observer model accounted for both attentional and contextual adaptations found with listeners. These results bolster the interpretation of perception as Bayesian inference, and suggest that some effects attributed to selective attention may be a special case of contextual prior integration along a feature axis.

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.

Periodotopy in the gerbil inferior colliculus: local clustering rather than a gradient map

Periodicities in sound waveforms are widespread, and shape important perceptual attributes of sound including rhythm and pitch. Previous studies have indicated that, in the inferior colliculus (IC), a key processing stage in the auditory midbrain, neurons tuned to different periodicities might be arranged along a periodotopic axis which runs approximately orthogonal to the tonotopic axis. Here we map out the topography of frequency and periodicity tuning in the IC of gerbils in unprecedented detail, using pure tones and different periodic sounds, including click trains, sinusoidally amplitude modulated (SAM) noise and iterated rippled noise. We found that while the tonotopic map exhibited a clear and highly reproducible gradient across all animals, periodotopic maps varied greatly across different types of periodic sound and from animal to animal. Furthermore, periodotopic gradients typically explained only about 10% of the variance in modulation tuning between recording sites. However, there was a strong local clustering of periodicity tuning at a spatial scale of ca. 0.5 mm, which also differed from animal to animal.

Sound localization in a changing world

In natural environments, neural systems must be continuously updated to reflect changes in sensory inputs and behavioral goals. Recent studies of sound localization have shown that adaptation and learning involve multiple mechanisms that operate at different timescales and stages of processing, with other sensory and motor-related inputs playing a key role. We are only just beginning to understand, however, how these processes interact with one another to produce adaptive changes at the level of neuronal populations and behavior. Because there is no explicit map of auditory space in the cortex, studies of sound localization may also provide much broader insight into the plasticity of complex neural representations that are not topographically organized.

Cortico-Cortical Connectivity Within Ferret Auditory Cortex

Despite numerous studies of auditory cortical processing in the ferret (Mustela putorius), very little is known about the connections between the different regions of the auditory cortex that have been characterized cytoarchitectonically and physiologically. We examined the distribution of retrograde and anterograde labeling after injecting tracers into one or more regions of ferret auditory cortex. Injections of different tracers at frequency‐matched locations in the core areas, the primary auditory cortex (A1) and anterior auditory field (AAF), of the same animal revealed the presence of reciprocal connections with overlapping projections to and from discrete regions within the posterior pseudosylvian and suprasylvian fields (PPF and PSF), suggesting that these connections are frequency specific. In contrast, projections from the primary areas to the anterior dorsal field (ADF) on the anterior ectosylvian gyrus were scattered and non‐overlapping, consistent with the non‐tonotopic organization of this field. The relative strength of the projections originating in each of the primary fields differed, with A1 predominantly targeting the posterior bank fields PPF and PSF, which in turn project to the ventral posterior field, whereas AAF projects more heavily to the ADF, which then projects to the anteroventral field and the pseudosylvian sulcal cortex. These findings suggest that parallel anterior and posterior processing networks may exist, although the connections between different areas often overlap and interactions were present at all levels. J. Comp. Neurol. 523:2187–2210, 2015. © 2015 Wiley Periodicals, Inc.

A Neural Substrate for Rapid Timbre Recognition? Neural and Behavioral Discrimination of Very Brief Acoustic Vowels

The timbre of a sound plays an important role in our ability to discriminate between behaviorally relevant auditory categories, such as different vowels in speech. Here, we investigated, in the primary auditory cortex (A1) of anesthetized guinea pigs, the neural representation of vowels with impoverished timbre cues. Five different vowels were presented with durations ranging from 2 to 128 ms. A psychophysical experiment involving human listeners showed that identification performance was near ceiling for the longer durations and degraded close to chance level for the shortest durations. This was likely due to spectral splatter, which reduced the contrast between the spectral profiles of the vowels at short durations. Effects of vowel duration on cortical responses were well predicted by the linear frequency responses of A1 neurons. Using mutual information, we found that auditory cortical neurons in the guinea pig could be used to reliably identify several vowels for all durations. Information carried by each cortical site was low on average, but the population code was accurate even for durations where human behavioral performance was poor. These results suggest that a place population code is available at the level of A1 to encode spectral profile cues for even very short sounds.

The role of spectral cues in timbre discrimination by ferrets and humans

Timbre distinguishes sounds of equal loudness, pitch, and duration; however, little is known about the neural mechanisms underlying timbre perception. Such understanding requires animal models such as the ferret in which neuronal and behavioral observation can be combined. The current study asked what spectral cues ferrets use to discriminate between synthetic vowels. Ferrets were trained to discriminate vowels differing in the position of the first (F1) and second formants (F2), inter-formant distance, and spectral centroid. In experiment 1, ferrets responded to probe trials containing novel vowels in which the spectral cues of trained vowels were mismatched. Regression models fitted to behavioral responses determined that F2 and spectral centroid were stronger predictors of ferrets' behavior than either F1 or inter-formant distance. Experiment 2 examined responses to single formant vowels and found that individual spectral peaks failed to account for multi-formant vowel perception. Experiment 3 measured responses to unvoiced vowels and showed that ferrets could generalize vowel identity across voicing conditions. Experiment 4 employed the same design as experiment 1 but with human participants. Their responses were also predicted by F2 and spectral centroid. Together these findings further support the ferret as a model for studying the neural processes underlying timbre perception.

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.

Auditory cortical processing in real-world listening: the auditory system going real

The auditory sense of humans transforms intrinsically senseless pressure waveforms into spectacularly rich perceptual phenomena: the music of Bach or the Beatles, the poetry of Li Bai or Omar Khayyam, or more prosaically the sense of the world filled with objects emitting sounds that is so important for those of us lucky enough to have hearing. Whereas the early representations of sounds in the auditory system are based on their physical structure, higher auditory centers are thought to represent sounds in terms of their perceptual attributes. In this symposium, we will illustrate the current research into this process, using four case studies. We will illustrate how the spectral and temporal properties of sounds are used to bind together, segregate, categorize, and interpret sound patterns on their way to acquire meaning, with important lessons to other sensory systems as well.