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.

Neural Correlates of Auditory Pattern Learning in the Auditory Cortex.

Learning of new auditory stimuli often requires repetitive exposure to the stimulus. Fast and implicit learning of sounds presented at random times enables efficient auditory perception. However, it is unclear how such sensory encoding is processed on a neural level. We investigated neural responses that are developed from a passive, repetitive exposure to a specific sound in the auditory cortex of anesthetized rats, using electrocorticography. We presented a series of random sequences that are generated afresh each time, except for a specific reference sequence that remains constant and re-appears at random times across trials. We compared induced activity amplitudes between reference and fresh sequences. Neural responses from both primary and non-primary auditory cortical regions showed significantly decreased induced activity amplitudes for reference sequences compared to fresh sequences, especially in the beta band. This is the first study showing that neural correlates of auditory pattern learning can be evoked even in anesthetized, passive listening animal models.

Choice-related activity and neural encoding in primary auditory cortex and lateral belt during feature-selective attention.

Selective attention is necessary to sift through, form a coherent percept of, and make behavioral decisions on the vast amount of information present in most sensory environments. How and where selective attention is employed in cortex and how this perceptual information then informs the relevant behavioral decisions is still not well understood. Studies probing selective attention and decision-making in visual cortex have been enlightening as to how sensory attention might work in that modality; whether or not similar mechanisms are employed in auditory attention is not yet clear. Therefore, we trained rhesus macaques on a feature-selective attention task, where they switched between reporting changes in temporal (amplitude modulation, AM) and spectral (carrier bandwidth) features of a broadband noise stimulus. We investigated how the encoding of these features by single neurons in primary (A1) and secondary (middle lateral belt, ML) auditory cortex was affected by the different attention conditions. We found that neurons in A1 and ML showed mixed selectivity to the sound and task features. We found no difference in AM encoding between the attention conditions. We found that choice-related activity in both A1 and ML neurons shifts between attentional conditions. This finding suggests that choice-related activity in auditory cortex does not simply reflect motor preparation or action and supports the relationship between reported choice-related activity and the decision and perceptual process.NEW & NOTEWORTHY We recorded from primary and secondary auditory cortex while monkeys performed a nonspatial feature attention task. Both areas exhibited rate-based choice-related activity. The manifestation of choice-related activity was attention dependent, suggesting that choice-related activity in auditory cortex does not simply reflect arousal or motor influences but relates to the specific perceptual choice.

Amplitude modulation encoding in the auditory cortex: comparisons between the primary and middle lateral belt regions.

In macaques, the middle lateral auditory cortex (ML) is a belt region adjacent to the primary auditory cortex (A1) and believed to be at a hierarchically higher level. Although ML single-unit responses have been studied for several auditory stimuli, the ability of ML cells to encode amplitude modulation (AM)-an ability that has been widely studied in A1-has not yet been characterized. Here, we compared the responses of A1 and ML neurons to amplitude-modulated (AM) noise in awake macaques. Although several of the basic properties of A1 and ML responses to AM noise were similar, we found several key differences. ML neurons were less likely to phase lock, did not phase lock as strongly, and were more likely to respond in a nonsynchronized fashion than A1 cells, consistent with a temporal-to-rate transformation as information ascends the auditory hierarchy. ML neurons tended to have lower temporally (phase-locking) based best modulation frequencies than A1 neurons. Neurons that decreased their firing rate in response to AM noise relative to their firing rate in response to unmodulated noise became more common at the level of ML than they were in A1. In both A1 and ML, we found a prevalent class of neurons that usually have enhanced rate responses relative to responses to the unmodulated noise at lower modulation frequencies and suppressed rate responses relative to responses to the unmodulated noise at middle modulation frequencies.NEW & NOTEWORTHY ML neurons synchronized less than A1 neurons, consistent with a hierarchical temporal-to-rate transformation. Both A1 and ML had a class of modulation transfer functions previously unreported in the cortex with a low-modulation-frequency (MF) peak, a middle-MF trough, and responses similar to unmodulated noise responses at high MFs. The results support a hierarchical shift toward a two-pool opponent code, where subtraction of neural activity between two populations of oppositely tuned neurons encodes AM.

Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.

Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations (rnoise) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on rnoise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in rnoise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments.SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations (rnoise) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on rnoise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning to the distractor feature as well. We suggest that these effects represent an efficient process by which sensory cortex simultaneously enhances relevant information and suppresses irrelevant information.

Hierarchical differences in population coding within auditory cortex.

Most models of auditory cortical (AC) population coding have focused on primary auditory cortex (A1). Thus our understanding of how neural coding for sounds progresses along the cortical hierarchy remains obscure. To illuminate this, we recorded from two AC fields: A1 and middle lateral belt (ML) of rhesus macaques. We presented amplitude-modulated (AM) noise during both passive listening and while the animals performed an AM detection task ("active" condition). In both fields, neurons exhibit monotonic AM-depth tuning, with A1 neurons mostly exhibiting increasing rate-depth functions and ML neurons approximately evenly distributed between increasing and decreasing functions. We measured noise correlation (rnoise) between simultaneously recorded neurons and found that whereas engagement decreased average rnoise in A1, engagement increased average rnoise in ML. This finding surprised us, because attentive states are commonly reported to decrease average rnoise We analyzed the effect of rnoise on AM coding in both A1 and ML and found that whereas engagement-related shifts in rnoise in A1 enhance AM coding, rnoise shifts in ML have little effect. These results imply that the effect of rnoise differs between sensory areas, based on the distribution of tuning properties among the neurons within each population. A possible explanation of this is that higher areas need to encode nonsensory variables (e.g., attention, choice, and motor preparation), which impart common noise, thus increasing rnoise Therefore, the hierarchical emergence of rnoise-robust population coding (e.g., as we observed in ML) enhances the ability of sensory cortex to integrate cognitive and sensory information without a loss of sensory fidelity.NEW & NOTEWORTHY Prevailing models of population coding of sensory information are based on a limited subset of neural structures. An important and under-explored question in neuroscience is how distinct areas of sensory cortex differ in their population coding strategies. In this study, we compared population coding between primary and secondary auditory cortex. Our findings demonstrate striking differences between the two areas and highlight the importance of considering the diversity of neural structures as we develop models of population coding.

Segregating two simultaneous sounds in elevation using temporal envelope: Human psychophysics and a physiological model.

The ability to segregate simultaneous sound sources based on their spatial locations is an important aspect of auditory scene analysis. While the role of sound azimuth in segregation is well studied, the contribution of sound elevation remains unknown. Although previous studies in humans suggest that elevation cues alone are not sufficient to segregate simultaneous broadband sources, the current study demonstrates they can suffice. Listeners segregating a temporally modulated noise target from a simultaneous unmodulated noise distracter differing in elevation fall into two statistically distinct groups: one that identifies target direction accurately across a wide range of modulation frequencies (MF) and one that cannot identify target direction accurately and, on average, reports the opposite direction of the target for low MF. A non-spiking model of inferior colliculus neurons that process single-source elevation cues suggests that the performance of both listener groups at the population level can be accounted for by the balance of excitatory and inhibitory inputs in the model. These results establish the potential for broadband elevation cues to contribute to the computations underlying sound source segregation and suggest a potential mechanism underlying this contribution.

Task engagement selectively modulates neural correlations in primary auditory cortex.

Noise correlations (r(noise)) between neurons can affect a neural population's discrimination capacity, even without changes in mean firing rates of neurons. r(noise), the degree to which the response variability of a pair of neurons is correlated, has been shown to change with attention with most reports showing a reduction in r(noise). However, the effect of reducing r(noise) on sensory discrimination depends on many factors, including the tuning similarity, or tuning correlation (r(tuning)), between the pair. Theoretically, reducing r(noise) should enhance sensory discrimination when the pair exhibits similar tuning, but should impair discrimination when tuning is dissimilar. We recorded from pairs of neurons in primary auditory cortex (A1) under two conditions: while rhesus macaque monkeys (Macaca mulatta) actively performed a threshold amplitude modulation (AM) detection task and while they sat passively awake. We report that, for pairs with similar AM tuning, average r(noise) in A1 decreases when the animal performs the AM detection task compared with when sitting passively. For pairs with dissimilar tuning, the average r(noise) did not significantly change between conditions. This suggests that attention-related modulation can target selective subcircuits to decorrelate noise. These results demonstrate that engagement in an auditory task enhances population coding in primary auditory cortex by selectively reducing deleterious r(noise) and leaving beneficial r(noise) intact.

Differences between primary auditory cortex and auditory belt related to encoding and choice for AM sounds.

We recorded from middle-lateral (ML) and primary (A1) auditory cortex while macaques discriminated amplitude-modulated (AM) noise from unmodulated noise. Compared with A1, ML had a higher proportion of neurons that encoded increasing AM depth by decreasing their firing rates ("decreasing" neurons), particularly with responses that were not synchronized to the modulation. Choice probability (CP) analysis revealed that A1 and ML activity were different during the first half of the test stimulus. In A1, significant CP began before the test stimulus, remained relatively constant (or increased slightly) during the stimulus, and increased greatly within 200 ms of lever release. Neurons in ML behaved similarly, except that significant CP disappeared during the first half of the stimulus and reappeared during the second half and prerelease periods. CP differences between A1 and ML depend on neural response type. In ML (but not A1), when activity was lower during the first half of the stimulus in nonsynchronized, decreasing neurons, the monkey was more likely to report AM. Neurons that both increased firing rate with increasing modulation depth ("increasing" neurons) and synchronized their responses to AM had similar choice-related activity dynamics in ML and A1. These results suggest that, when ascending the auditory system, there is a transformation in coding AM from primarily synchronized increasing responses in A1 to nonsynchronized and dual (increasing/decreasing) coding in ML. This sensory transformation is accompanied by changes in the timing of activity related to choice, suggesting functional differences between A1 and ML related to attention and/or behavior.

Active engagement improves primary auditory cortical neurons' ability to discriminate temporal modulation.

The effect of attention on single neuron responses in the auditory system is unresolved. We found that when monkeys discriminated temporally amplitude modulated (AM) from unmodulated sounds, primary auditory cortical (A1) neurons better discriminated those sounds than when the monkeys were not discriminating them. This was observed for both average firing rate and vector strength (VS), a measure of how well neurons temporally follow the stimulus' temporal modulation. When data were separated by nonsynchronized and synchronized responses, the firing rate of nonsynchronized responses best distinguished AM- noise from unmodulated noise, followed by VS for synchronized responses, with firing rate for synchronized neurons providing the poorest AM discrimination. Firing rate-based AM discrimination for synchronized neurons, however, improved most with task engagement, showing that the least sensitive code in the passive condition improves the most with task engagement. Rate coding improved due to larger increases in absolute firing rate at higher modulation depths than for lower depths and unmodulated sounds. Relative to spontaneous activity (which increased with engagement), the response to unmodulated sounds decreased substantially. The temporal coding improvement--responses more precisely temporally following a stimulus when animals were required to attend to it--expands the framework of possible mechanisms of attention to include increasing temporal precision of stimulus following. These findings provide a crucial step to understanding the coding of temporal modulation and support a model in which rate and temporal coding work in parallel, permitting a multiplexed code for temporal modulation, and for a complementary representation of rate and temporal coding.

Ability of primary auditory cortical neurons to detect amplitude modulation with rate and temporal codes: neurometric analysis.

Amplitude modulation (AM) is a common feature of natural sounds, and its detection is biologically important. Even though most sounds are not fully modulated, the majority of physiological studies have focused on fully modulated (100% modulation depth) sounds. We presented AM noise at a range of modulation depths to awake macaque monkeys while recording from neurons in primary auditory cortex (A1). The ability of neurons to detect partial AM with rate and temporal codes was assessed with signal detection methods. On average, single-cell synchrony was as or more sensitive than spike count in modulation detection. Cells are less sensitive to modulation depth if tested away from their best modulation frequency, particularly for temporal measures. Mean neural modulation detection thresholds in A1 are not as sensitive as behavioral thresholds, but with phase locking the most sensitive neurons are more sensitive, suggesting that for temporal measures the lower-envelope principle cannot account for thresholds. Three methods of preanalysis pooling of spike trains (multiunit, similar to convergence from a cortical column; within cell, similar to convergence of cells with matched response properties; across cell, similar to indiscriminate convergence of cells) all result in an increase in neural sensitivity to modulation depth for both temporal and rate codes. For the across-cell method, pooling of a few dozen cells can result in detection thresholds that approximate those of the behaving animal. With synchrony measures, indiscriminate pooling results in sensitive detection of modulation frequencies between 20 and 60 Hz, suggesting that differences in AM response phase are minor in A1.

Activity related to perceptual judgment and action in primary auditory cortex.

Recent evidence is reshaping the view of primary auditory cortex (A1) from a unisensory area to one more involved in dynamically integrating multisensory- and task-related information. We found A1 single- (SU) and multiple-unit (MU) activity correlated with macaques' choices in an amplitude modulation (AM) discrimination task. Animals were trained to discriminate AM noise from unmodulated noise by releasing a lever for AM noise and holding down the lever for unmodulated noise. Activity for identical stimuli was compared between trials where the animals reported AM and trials where they did not. We found 47.4% of MUs and 22.8% of SUs significantly increased firing shortly before the animal's behavioral response to report AM when compared to the equivalent time period on trials where AM was not reported. Activity was also linked to lever release in a different task context, suggesting A1 modulation by somatosensory, or efference copy, input. When spikes were counted only during the stimulus, 19.6% of MUs and 13.8% of SUs increased firing rate when animals reported AM compared to when they did not, suggesting an attentional effect, or that A1 activity can be used by higher decision areas, or that such areas provide feedback to A1. Activity associated with AM reporting was correlated with a unit's AM sensitivity, suggesting AM sensitive neurons' involvement in task performance. A1 neurons' phase locking to AM correlated more weakly (compared to firing rate) with the animals' report of AM, suggesting a preferential role for rate-codes in A1 for this AM discrimination task.

Amplitude modulation detection as a function of modulation frequency and stimulus duration: comparisons between macaques and humans.

Previous observations show that humans outperform non-human primates on some temporally-based auditory discrimination tasks, suggesting there are species differences in the proficiency of auditory temporal processing among primates. To further resolve these differences we compared the abilities of rhesus macaques and humans to detect sine-amplitude modulation (AM) of a broad-band noise carrier as a function of both AM frequency (2.5 Hz-2 kHz) and signal duration (50-800 ms), under similar testing conditions. Using a go/no-go AM detection task, we found that macaques were less sensitive than humans at the lower frequencies and shorter durations tested but were as, or slightly more, sensitive at higher frequencies and longer durations. Humans had broader AM tuning functions, with lower frequency regions of peak sensitivity (10-60 Hz) than macaques (30-120 Hz). These results support the notion that there are species differences in temporal processing among primates, and underscore the importance of stimulus duration when making cross-species comparisons for temporally-based tasks.

Evolutionary conservation and neuronal mechanisms of auditory perceptual restoration.

Auditory perceptual 'restoration' occurs when the auditory system restores an occluded or masked sound of interest. Behavioral work on auditory restoration in humans began over 50 years ago using it to model a noisy environmental scene with competing sounds. It has become clear that not only humans experience auditory restoration: restoration has been broadly conserved in many species. Behavioral studies in humans and animals provide a necessary foundation to link the insights being obtained from human EEG and fMRI to those from animal neurophysiology. The aggregate of data resulting from multiple approaches across species has begun to clarify the neuronal bases of auditory restoration. Different types of neural responses supporting restoration have been found, supportive of multiple mechanisms working within a species. Yet a general principle has emerged that responses correlated with restoration mimic the response that would have been given to the uninterrupted sound of interest. Using the same technology to study different species will help us to better harness animal models of 'auditory scene analysis' to clarify the conserved neural mechanisms shaping the perceptual organization of sound and to advance strategies to improve hearing in natural environmental settings.

Coding of amplitude modulation in primary auditory cortex.

Conflicting results have led to different views about how temporal modulation is encoded in primary auditory cortex (A1). Some studies find a substantial population of neurons that change firing rate without synchronizing to temporal modulation, whereas other studies fail to see these nonsynchronized neurons. As a result, the role and scope of synchronized temporal and nonsynchronized rate codes in AM processing in A1 remains unresolved. We recorded A1 neurons' responses in awake macaques to sinusoidal AM noise. We find most (37-78%) neurons synchronize to at least one modulation frequency (MF) without exhibiting nonsynchronized responses. However, we find both exclusively nonsynchronized neurons (7-29%) and "mixed-mode" neurons (13-40%) that synchronize to at least one MF and fire nonsynchronously to at least one other. We introduce new measures for modulation encoding and temporal synchrony that can improve the analysis of how neurons encode temporal modulation. These include comparing AM responses to the responses to unmodulated sounds, and a vector strength measure that is suitable for single-trial analysis. Our data support a transformation from a temporally based population code of AM to a rate-based code as information ascends the auditory pathway. The number of mixed-mode neurons found in A1 indicates this transformation is not yet complete, and A1 neurons may carry multiplexed temporal and rate codes.

Complex spectral interactions encoded by auditory cortical neurons: relationship between bandwidth and pattern.

The focus of most research on auditory cortical neurons has concerned the effects of rather simple stimuli, such as pure tones or broad-band noise, or the modulation of a single acoustic parameter. Extending these findings to feature coding in more complex stimuli such as natural sounds may be difficult, however. Generalizing results from the simple to more complex case may be complicated by non-linear interactions occurring between multiple, simultaneously varying acoustic parameters in complex sounds. To examine this issue in the frequency domain, we performed a parametric study of the effects of two global features, spectral pattern (here ripple frequency) and bandwidth, on primary auditory (A1) neurons in awake macaques. Most neurons were tuned for one or both variables and most also displayed an interaction between bandwidth and pattern implying that their effects were conditional or interdependent. A spectral linear filter model was able to qualitatively reproduce the basic effects and interactions, indicating that a simple neural mechanism may be able to account for these interdependencies. Our results suggest that the behavior of most A1 neurons is likely to depend on multiple parameters, and so most are unlikely to respond independently or invariantly to specific acoustic features.

The biological basis of audition.

Interest has recently surged in the neural mechanisms of audition, particularly with regard to functional imaging studies in human subjects. This review emphasizes recent work on two aspects of auditory processing. The first explores auditory spatial processing and the role of the auditory cortex in both nonhuman primates and human subjects. The interactions with visual stimuli, the ventriloquism effect, and the ventriloquism aftereffect are also reviewed. The second aspect is temporal processing. Studies investigating temporal integration, forward masking, and gap detection are reviewed, as well as examples from the birdsong system and echolocating bats.

Encoding of illusory continuity in primary auditory cortex.

When interfering objects occlude a scene, the visual system restores the occluded information. Similarly, when a sound of interest (a "foreground" sound) is interrupted (occluded) by loud noise, the auditory system restores the occluded information. This process, called auditory induction, can be exploited to create a continuity illusion. When a segment of a foreground sound is deleted and loud noise fills the missing portion, listeners incorrectly report hearing the foreground continuing through the noise. Here we reveal the neurophysiological underpinnings of illusory continuity in single-neuron responses from awake macaque monkeys' primary auditory cortex (A1). A1 neurons represented the missing segment of occluded tonal foregrounds by responding to discontinuous foregrounds interrupted by intense noise as if they were responding to the complete foregrounds. By comparison, simulated peripheral responses represented only the noise and not the occluded foreground. The results reveal that many A1 single-neuron responses closely follow the illusory percept.

Adaptive stimulus optimization for auditory cortical neurons.

Despite the extensive physiological work performed on auditory cortex, our understanding of the basic functional properties of auditory cortical neurons is incomplete. For example, it remains unclear what stimulus features are most important for these cells. Determining these features is challenging given the considerable size of the relevant stimulus parameter space as well as the unpredictable nature of many neurons' responses to complex stimuli due to nonlinear integration across frequency. Here we used an adaptive stimulus optimization technique to obtain the preferred spectral input for neurons in macaque primary auditory cortex (AI). This method uses a neuron's response to progressively modify the frequency composition of a stimulus to determine the preferred spectrum. This technique has the advantage of being able to incorporate nonlinear stimulus interactions into a "best estimate" of a neuron's preferred spectrum. The resulting spectra displayed a consistent, relatively simple circumscribed form that was similar across scale and frequency in which excitation and inhibition appeared about equally prominent. In most cases, this structure could be described using two simple models, the Gabor and difference of Gaussians functions. The findings indicate that AI neurons are well suited for extracting important scale-invariant features in sound spectra and suggest that they are designed to efficiently represent natural sounds.

Auditory perceptual grouping and attention in dyslexia.

Despite dyslexia affecting a large number of people, the mechanisms underlying the disorder remain undetermined. There are numerous theories about the origins of dyslexia. Many of these relate dyslexia to low-level, sensory temporal processing deficits. Another group of theories attributes dyslexia to language-specific impairments. Here, we show that dyslexics perform worse than controls on an auditory perceptual grouping task. The results show differences in performance between the groups that depend on sound frequency and not solely on parameters related to temporal processing. Performance on this task suggests that dyslexics' deficits may result from impaired attentional control mechanisms. Such deficits are neither modality nor language-specific and may help to reconcile differences between theories of dyslexia.