Contribution of spiking activity in the primary auditory cortex to detection in noise

Localized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex

Adaptive behavior requires integrating prior knowledge of action outcomes and sensory evidence for making decisions while maintaining prior knowledge for future actions. As outcome- and sensory-based decisions are often tested separately, it is unclear how these processes are integrated in the brain. In a tone frequency discrimination task with two sound durations and asymmetric reward blocks, we found that neurons in the medial prefrontal cortex of male mice represented the additive combination of prior reward expectations and choices. The sensory inputs and choices were selectively decoded from the auditory cortex irrespective of reward priors and the secondary motor cortex, respectively, suggesting localized computations of task variables are required within single trials. In contrast, all the recorded regions represented prior values that needed to be maintained across trials. We propose localized and global computations of task variables in different time scales in the cerebral cortex.

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

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

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative-choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in the auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animal's performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouse's choice could be reliably decoded from the recorded neural activity. Our findings suggest that, in spite of modulation of auditory cortical activity by task priors, the auditory cortex does not represent sufficient information about these priors to exploit them optimally. Thus, the combination of rapidly changing sensory information with more slowly varying task information required for decisions in this task might be represented in brain regions other than the auditory cortex.

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animal's performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouse's choice could be reliably decoded from the recorded neural activity. Our findings suggest that in spite of modulation of auditory cortical activity by task priors, auditory cortex does not represent sufficient information about these priors to exploit them optimally and that decisions in this task require that rapidly changing sensory information be combined with more slowly varying task information extracted and represented in brain regions other than auditory cortex.

Dynamics of cortical contrast adaptation predict perception of signals in noise

Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. Contrast gain control is a form of adaptation in the auditory cortex, but it is unclear whether the dynamics of gain control reflect efficient adaptation, and whether they shape behavioral perception. Here, we trained mice to detect a target presented in background noise shortly after a change in the contrast of the background. The observed changes in cortical gain and behavioral detection followed the dynamics of a normative model of efficient contrast gain control; specifically, target detection and sensitivity improved slowly in low contrast, but degraded rapidly in high contrast. Auditory cortex was required for this task, and cortical responses were not only similarly affected by contrast but predicted variability in behavioral performance. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts the perception of sounds in noise.

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.

Hierarchical differences in the encoding of sound and choice in the subcortical auditory system

Detection of sounds is a fundamental function of the auditory system. Although studies of auditory cortex have gained substantial insight into detection performance using behaving animals, previous subcortical studies have mostly taken place under anesthesia, in passively listening animals, or have not measured performance at threshold. These limitations preclude direct comparisons between neuronal responses and behavior. To address this, we simultaneously measured auditory detection performance and single-unit activity in the inferior colliculus (IC) and cochlear nucleus (CN) in macaques. The spontaneous activity and response variability of CN neurons were higher than those observed for IC neurons. Signal detection theoretic methods revealed that the magnitude of responses of IC neurons provided more reliable estimates of psychometric threshold and slope compared with the responses of single CN neurons. However, pooling small populations of CN neurons provided reliable estimates of psychometric threshold and slope, suggesting sufficient information in CN population activity. Trial-by-trial correlations between spike count and behavioral response emerged 50-75 ms after sound onset for most IC neurons, but for few neurons in the CN. These results highlight hierarchical differences between neurometric-psychometric correlations in CN and IC and have important implications for how subcortical information could be decoded.NEW & NOTEWORTHY The cerebral cortex is widely recognized to play a role in sensory processing and decision-making. Accounts of the neural basis of auditory perception and its dysfunction are based on this idea. However, significantly less attention has been paid to midbrain and brainstem structures in this regard. Here, we find that subcortical auditory neurons represent stimulus information sufficient for detection and predict behavioral choice on a trial-by-trial basis.

An assessment of ambient noise and other environmental variables in a nonhuman primate housing facility

Acoustic noise and other environmental variables represent potential confounds for animal research. Of relevance to auditory research, sustained high levels of ambient noise may modify hearing sensitivity and decrease well-being among laboratory animals. The present study was conducted to assess environmental conditions in an animal facility that houses nonhuman primates used for auditory research at the Vanderbilt University Medical Center. Sound levels, vibration, temperature, humidity and luminance were recorded using an environmental monitoring device placed inside of an empty cage in a macaque housing room. Recordings lasted 1 week each, at three different locations within the room. Vibration, temperature, humidity and luminance all varied within recommended levels for nonhuman primates, with one exception of low luminance levels in the bottom cage location. Sound levels at each cage location were characterized by a low baseline of 58-62 dB sound pressure level, with transient peaks up to 109 dB sound pressure level. Sound levels differed significantly across locations, but only by about 1.5 dB. The transient peaks beyond recommended sound levels reflected a very low noise dose, but exceeded startle-inducing levels, which could elicit stress responses. Based on these findings, ambient noise levels in the housing rooms in this primate facility are within acceptable levels and unlikely to contribute to hearing deficits in the nonhuman primates. Our results establish normative values for environmental conditions in a primate facility, can be used to inform best practices for nonhuman primate research and care, and form a baseline for future studies of aging and chronic noise exposure.

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

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

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

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

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.

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.

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

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

Timescales of Evidence Evaluation for Decision Making and Associated Confidence Judgments Are Adapted to Task Demands

Decision making often involves choosing actions based on relevant evidence. This can benefit from focussing evidence evaluation on the timescale of greatest relevance based on the situation. Here, we use an auditory change detection task to determine how people adjust their timescale of evidence evaluation depending on task demands for detecting changes in their environment and assessing their internal confidence in those decisions. We confirm previous results that people adopt shorter timescales of evidence evaluation for detecting changes in contexts with shorter signal durations, while bolstering those results with model-free analyses not previously used and extending the results to the auditory domain. We also extend these results to show that in contexts with shorter signal durations, people also adopt correspondingly shorter timescales of evidence evaluation for assessing confidence in their decision about detecting a change. These results provide important insights into adaptability and flexible control of evidence evaluation for decision making.

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

OBJECTIVE

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

APPROACH

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

MAIN RESULTS

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

SIGNIFICANCE

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

Invariance to background noise as a signature of non-primary auditory cortex

Despite well-established anatomical differences between primary and non-primary auditory cortex, the associated representational transformations have remained elusive. Here we show that primary and non-primary auditory cortex are differentiated by their invariance to real-world background noise. We measured fMRI responses to natural sounds presented in isolation and in real-world noise, quantifying invariance as the correlation between the two responses for individual voxels. Non-primary areas were substantially more noise-invariant than primary areas. This primary-nonprimary difference occurred both for speech and non-speech sounds and was unaffected by a concurrent demanding visual task, suggesting that the observed invariance is not specific to speech processing and is robust to inattention. The difference was most pronounced for real-world background noise-both primary and non-primary areas were relatively robust to simple types of synthetic noise. Our results suggest a general representational transformation between auditory cortical stages, illustrating a representational consequence of hierarchical organization in the auditory system.

Neuronal adaptation to sound statistics in the inferior colliculus of behaving macaques does not reduce the effectiveness of the masking noise

The detectability of target sounds embedded within noisy backgrounds is affected by the regularities that summarize acoustic sceneries. Previous studies suggested that the dynamic range of neurons in the inferior colliculus (IC) of anesthetized guinea pigs shifts toward the mean sound pressure level in irregular acoustic environments. Yet, it is unclear how this neuronal adaptation processes may influence the effectiveness of sounds as a masker, both behaviorally and in terms of neuronal encoding. To answer this question, we measured the neural response of IC neurons while macaque monkeys performed a Go/No-Go tone detection task. Macaques detected a 50-ms tone that was either simultaneously gated with a burst of noise or embedded within a continuous noise background, whose levels were randomly sampled (every 50 ms) from a probability distribution. The mean of the distribution matched the level of the gated burst of noise. Psychometric and IC neurometric thresholds to tones did not differ between the two masking conditions. However, the neuronal firing rate versus level function was significantly affected by the temporal characteristics of the noise masker. Simultaneously gated noise caused higher baseline responses and greater dynamic range compression compared with noise distribution. The slopes of psychometric and neurometric functions were significantly shallower for higher variance distributions, suggesting that neuronal sensitivity might change with the variability of the sound. Our results suggest that the adaptive response of IC neurons to sound regularities does not affect the effectiveness of the noise-masking signal, which remains invariant to surrounding noise amplitudes. NEW & NOTEWORTHY Auditory neurons adapt to the statistics of sound levels in the acoustic scene. However, it is still unclear to what extent such adaptation influences the effectiveness of the stimulus as a masker. Our study represents the first attempt to investigate how the adaptation to the statistics of masking stimuli may be related to the effectiveness of masking, and to the single-unit encoding of the midbrain auditory neurons in behaving animals.

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.

The Contribution of Primary Auditory Cortex to Auditory Categorization in Behaving Monkeys

The specific contribution of core auditory cortex to auditory perception –such as categorization– remains controversial. To identify a contribution of the primary auditory cortex (A1) to perception, we recorded A1 activity while monkeys reported whether a temporal sequence of tone bursts was heard as having a “small” or “large” frequency difference. We found that A1 had frequency-tuned responses that habituated, independent of frequency content, as this auditory sequence unfolded over time. We also found that A1 firing rate was modulated by the monkeys’ reports of “small” and “large” frequency differences; this modulation correlated with their behavioral performance. These findings are consistent with the hypothesis that A1 contributes to the processes underlying auditory categorization.

Developmental deprivation-induced perceptual and cortical processing deficits in awake-behaving animals

Sensory deprivation during development induces lifelong changes to central nervous system function that are associated with perceptual impairments. However, the relationship between neural and behavioral deficits is uncertain due to a lack of simultaneous measurements during task performance. Therefore, we telemetrically recorded from auditory cortex neurons in gerbils reared with developmental conductive hearing loss as they performed an auditory task in which rapid fluctuations in amplitude are detected. These data were compared to a measure of auditory brainstem temporal processing from each animal. We found that developmental HL diminished behavioral performance, but did not alter brainstem temporal processing. However, the simultaneous assessment of neural and behavioral processing revealed that perceptual deficits were associated with a degraded cortical population code that could be explained by greater trial-to-trial response variability. Our findings suggest that the perceptual limitations that attend early hearing loss are best explained by an encoding deficit in auditory cortex.