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Cortical neuronal populations can use a multitude of codes to represent information, each with different advantages and trade-offs. The auditory cortex represents sounds via a sparse code, which lies on the continuum between a localist representation with different cells responding to different stimuli, and a distributed representation, in which each stimulus is encoded in the relative response of each cell in the population. Being able to dynamically shift the neuronal code along this axis may help with certain tasks that require categorical or invariant representations. Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons may have distinct effects on population neuronal codes, differentially shifting the encoding of sounds between distributed and localist representations. We stimulated optogenetically SST or VIP neurons while simultaneously measuring the response of populations of hundreds of neurons to sounds presented at different sound pressure levels. SST activation shifted the neuronal population responses toward a more localist code, whereas VIP activation shifted them towards a more distributed code. Upon SST activation, sound representations became more discrete, relying on cell identity rather than strength. In contrast, upon VIP activation, distinct sounds activated overlapping populations at different rates. These shifts were implemented at the single-cell level by modulating the response-level curve of monotonic and nonmonotonic neurons. These results suggest a novel function for distinct inhibitory neurons in the auditory cortex in dynamically controlling cortical population codes.

Auditory perception requires categorizing sound sequences, such as speech, into classes, such as syllables. Auditory categorization depends not only on the sequences’ acoustic waveform, but also on the listener’s sensory uncertainty, any individual sound’s relevance to the task, and learning the temporal statistics of the acoustic environment. However, whether and how these factors interact to shape categorization is unknown. Here, we measured human participants’ performance on a multi-tone categorization task. Task-relevant tones contributed more to category choice than task-irrelevant tones, confirming that participants combined information about sensory features with task relevance. Conversely, poor estimates of tones’ task relevance or high sensory uncertainty adversely impacted category choice. Learning temporal statistics of sound category also affected decisions. The magnitude of this effect correlated inversely with participants’ relevance estimates. These results demonstrate that humans differentially weigh sensory uncertainty, task relevance and learning, providing a novel understanding of sensory decision-making under real-life behavioral demands.

Sensory processing is frequently conceptualized as a linear flow of information from peripheral receptors through hierarchically organized brain regions, ultimately reaching the cortex. In reality, this ascending stream is accompanied by massive descending connections that cascade from the cortex toward more peripheral subcortical structures. In the central auditory system, these feedback connections influence information processing at virtually every level of the pathway, including the thalamus, midbrain, and brainstem, and exert influence even at the level of the cochlea. The auditory cortico-collicular system, which connects the auditory cortex to the inferior colliculus, or auditory midbrain, has received increasing attention in recent years and has been found to mediate manifold functions ranging from tuning shifts to defense behavior. In this review, we first summarize recent findings regarding the anatomical organization and physiological properties of the auditory cortico-collicular pathway. We then highlight several new studies that show that this projection system mediates high-level cognitive processes, acoustic-motor behaviors, and auditory plasticity, and discuss the circuit mechanisms through which they are mediated. Finally, we discuss remaining unanswered questions regarding cortico-collicular circuitry and function and potential avenues for future exploration.

Sensory systems must account for both contextual factors and prior experience to adaptively engage with the dynamic external environment. In the central auditory system, neurons modulate their responses to sounds based on statistical context. These response modulations can be understood through a hierarchical predictive coding lens: responses to repeated stimuli are progressively decreased, in a process known as repetition suppression, whereas unexpected stimuli produce a prediction error signal. Prediction error incrementally increases along the auditory hierarchy from the inferior colliculus (IC) to the auditory cortex (AC), suggesting that these regions may engage in hierarchical predictive coding. A potential substrate for top-down predictive cues is the massive set of descending projections from the AC to subcortical structures, although the role of this system in predictive processing has never been directly assessed. We tested the effect of optogenetic inactivation of the auditory cortico-collicular feedback in awake mice on responses of IC neurons to stimuli designed to test prediction error and repetition suppression. Inactivation of the cortico-collicular pathway led to a decrease in prediction error in IC. Repetition suppression was unaffected by cortico-collicular inactivation, suggesting that this metric may reflect fatigue of bottom-up sensory inputs rather than predictive processing. We also discovered populations of IC units that exhibit repetition enhancement, a sequential increase in firing with stimulus repetition. Cortico-collicular inactivation led to a decrease in repetition enhancement in the central nucleus of IC, suggesting that it is a top-down phenomenon. Negative prediction error, a stronger response to a tone in a predictable rather than unpredictable sequence, was suppressed in shell IC units during cortico-collicular inactivation. These changes in predictive coding metrics arose from bidirectional modulations in the response to the standard and deviant contexts, such that the units in IC responded more similarly to each context in the absence of cortical input. We also investigated how these metrics compare between the anesthetized and awake states by recording from the same units under both conditions. We found that metrics of predictive coding and deviance detection differ depending on the anesthetic state of the animal, with negative prediction error emerging in the central IC and repetition enhancement and prediction error being more prevalent in the absence of anesthesia. Overall, our results demonstrate that the AC provides cues about the statistical context of sound to subcortical brain regions via direct feedback, regulating processing of both prediction and repetition.

Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. This adaptation is thought to be efficient, resulting in neuronal codes that maximize information about the stimulus. Contrast gain control is a form of efficient adaptation in the auditory cortex and is believed to be crucial for enhancing the detection of signals embedded in background noise. However, it is unclear whether the dynamics of contrast gain control reflect efficient adaptation, and how they inform behavioral perception in noise. 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 to target level improved in low contrast backgrounds relative to high contrast backgrounds. Additionally, the time course of target detectability adapted asymmetrically depending on contrast, decreasing rapidly after a transition to high contrast, and increasing slowly after a transition to low contrast. Auditory cortex was required for detection of targets in background noise and cortical neuronal responses exhibited the patterns of target detectability observed during behavior and in the normative model. Furthermore, variability in cortical gain predicted behavioral performance beyond the effect of stimulus-driven gain control. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts behavioral performance in a target-in-background detection task.

In everyday life, we integrate visual and auditory information in routine tasks such as navigation and communication. Whereas concurrent sound can improve visual perception, the neuronal correlates of this audiovisual integration are not fully understood. Specifically, it remains unclear whether neuronal firing patters in the primary visual cortex (V1) of awake animals demonstrate similar sound-induced improvement in visual discriminability. Furthermore, presentation of sound is associated with movement in the subjects, but little is understood about whether and how sound-associated movement affects audiovisual integration in V1. We investigated how sound and movement interact to modulate V1 visual responses in awake, head-fixed mice and whether this interaction improves neuronal encoding of the visual stimulus. We presented visual drifting gratings with and without simultaneous auditory white noise to awake male and female mice while recording mouse movement and V1 neuronal activity. Sound modulated light-evoked activity of 80% of light-responsive neurons, with 95% of neurons increasing activity when the auditory stimulus was present. Sound consistently enhanced movement, however, a generalized linear model revealed that sound and movement had distinct and complementary effects of the neuronal visual responses. Furthermore, decoding of the visual stimulus from the neuronal activity was improved with sound, even when controlling for movement. Thus, sound and movement modulate visual responses in complementary ways, improving neuronal representation of the visual stimulus. This study clarifies the role of movement as a potential confound in neuronal audiovisual responses and expands our knowledge of how multimodal processing is mediated in the awake brain.Significance statementSound and movement are both known to modulate visual responses in the primary visual cortex, however sound-induced movement has largely remained unaccounted for as a potential confound in audiovisual studies in awake animals. Here, authors found that sound and movement both modulate visual responses in an important visual brain area, the primary visual cortex, in distinct, yet complementary ways. Furthermore, sound improved encoding of the visual stimulus even when accounting for movement. This study reconciles contrasting theories on the mechanism underlying audiovisual integration and asserts the primary visual cortex as a key brain region participating in tripartite sensory interactions.

Sensory systems must account for both contextual factors and prior experience to adaptively engage with the dynamic external environment. In the central auditory system, neurons modulate their responses to sounds based on statistical context. These response modulations can be understood through a hierarchical predictive coding lens: responses to repeated stimuli are progressively decreased, in a process known as repetition suppression, whereas unexpected stimuli produce a prediction error signal. Prediction error incrementally increases along the auditory hierarchy from the inferior colliculus (IC) to the auditory cortex (AC), suggesting that these regions may engage in hierarchical predictive coding. A potential substrate for top-down predictive cues is the massive set of descending projections from the auditory cortex to subcortical structures, although the role of this system in predictive processing has never been directly assessed. We tested the effect of optogenetic inactivation of the auditory cortico-collicular feedback in awake mice on responses of IC neurons to stimuli designed to test prediction error and repetition suppression. Inactivation of the cortico-collicular pathway led to a decrease in prediction error in IC. Repetition suppression was unaffected by cortico-collicular inactivation, suggesting that this metric may reflect fatigue of bottom-up sensory inputs rather than predictive processing. We also discovered populations of IC neurons that exhibit repetition enhancement, a sequential increase in firing with stimulus repetition. Cortico-collicular inactivation led to a decrease in repetition enhancement in the central nucleus of IC, suggesting that it is a top-down phenomenon. Negative prediction error, a stronger response to a tone in a predictable rather than unpredictable sequence, was suppressed in shell IC units during cortico-collicular inactivation. These changes in predictive coding metrics arose from bidirectional modulations in the response to the standard and deviant contexts, such that neurons in IC responded more similarly to each context in the absence of cortical input. We also investigated how these metrics compare between the anesthetized and awake states by recording from the same neurons under both conditions. We found that metrics of predictive coding and deviance detection differ depending on the anesthetic state of the animal, with negative prediction error emerging in the central IC and repetition enhancement and prediction error being more prevalent in the absence of anesthesia. Overall, our results demonstrate that the auditory cortex provides cues about the statistical context of sound to subcortical brain regions via direct feedback, regulating processing of both prediction and repetition.

Learning to avoid dangerous signals while preserving normal responses to safe stimuli is essential for everyday behavior and survival. Following identical experiences, subjects exhibit fear specificity ranging from high (specializing fear to only the dangerous stimulus) to low (generalizing fear to safe stimuli), yet the neuronal basis of fear specificity remains unknown. Here, we identified the neuronal code that underlies inter-subject variability in fear specificity using longitudinal imaging of neuronal activity before and after differential fear conditioning in the auditory cortex of mice. Neuronal activity prior to, but not after learning predicted the level of specificity following fear conditioning across subjects. Stimulus representation in auditory cortex was reorganized following conditioning. However, the reorganized neuronal activity did not relate to the specificity of learning. These results present a novel neuronal code that determines individual patterns in learning.

Cortical responses to sensory stimuli are strongly modulated by temporal context. One of the best studied examples of such modulation is sensory adaptation. We first show that in response to repeated tones pyramidal (Pyr) neurons in male mouse auditory cortex (A1) exhibit facilitating and stable responses, in addition to adapting responses. To examine the potential mechanisms underlying these distinct temporal profiles, we developed a reduced spiking model of sensory cortical circuits that incorporated the signature short-term synaptic plasticity (STP) profiles of the inhibitory parvalbumin (PV) and somatostatin (SST) interneurons. The model accounted for all three temporal response profiles as the result of dynamic changes in excitatory/inhibitory balance produced by STP, primarily through shifts in the relative latency of Pyr and inhibitory neurons. Transition between the three response profiles was possible by changing the strength of the inhibitory PV→Pyr and SST→Pyr synapses. The model predicted that a unit's latency would be related to its temporal profile. Consistent with this prediction, the latency of stable units was significantly shorter than that of adapting and facilitating units. Furthermore, because of the history-dependence of STP the model generated a paradoxical prediction: that inactivation of inhibitory neurons during one tone would decrease the response of A1 neurons to a subsequent tone. Indeed, we observed that optogenetic inactivation of PV neurons during one tone counterintuitively decreased the spiking of Pyr neurons to a subsequent tone 400 ms later. These results provide evidence that STP is critical to temporal context-dependent responses in the sensory cortex.SIGNIFICANCE STATEMENTOur perception of speech and music depends strongly on temporal context, i.e., the significance of a stimulus depends on the preceding stimuli. Complementary neural mechanisms are needed to sometimes ignore repetitive stimuli (e.g., the tic of a clock) or detect meaningful repetition (e.g., consecutive tones in Morse code). We modeled a neural circuit that accounts for diverse experimentally-observed response profiles in auditory cortex (A1) neurons, based on known forms of short-term synaptic plasticity (STP). Whether the simulated circuit reduced, maintained, or enhanced its response to repeated tones depended on the relative dominance of two different types of inhibitory cells. The model made novel predictions that were experimentally validated. Results define an important role for STP in temporal context-dependent perception.

Learning to avoid dangerous signals while preserving normal behavioral responses to safe stimuli is essential for everyday behavior and survival. Like other forms of learning, fear learning has a high level of inter-subject variability. Following an identical fear conditioning protocol, different subjects exhibit a range of fear specificity. Under high specificity, subjects specialize fear to only the paired (dangerous) stimulus, whereas under low specificity, subjects generalize fear to other (safe) sensory stimuli. Pathological fear generalization underlies emotional disorders, such as post-traumatic stress disorder. Despite decades of work, the neuronal basis that determines fear specificity level remains unknown. We identified the neuronal code that underlies variability in fear specificity. We performed longitudinal imaging of activity of neuronal ensembles in the auditory cortex of mice prior to and after the mice were subjected to differential fear conditioning. The neuronal code in the auditory cortex prior to learning predicted the level of specificity following fear learning across subjects. After fear learning, population neuronal responses were reorganized: the responses to the safe stimulus decreased, whereas the responses to the dangerous stimulus remained the same, rather than decreasing as in pseudo-conditioned subjects. The magnitude of these changes, however, did not correlate with learning specificity, suggesting that they did not reflect the fear memory. Together, our results identify a new, temporally restricted, function for cortical activity in associative learning. These results reconcile seemingly conflicting previous findings and provide for a neuronal code for determining individual patterns in learning.

In everyday acoustic environments, we navigate through a maze of sounds that possess a complex spectrotemporal structure, spanning many frequencies and exhibiting temporal modulations that differ within frequency bands. Our auditory system needs to efficiently encode the same sounds in a variety of different contexts, while preserving the ability to separate complex sounds within an acoustic scene. Recent work in auditory neuroscience has made substantial progress in studying how sounds are represented in the auditory system under different contexts, demonstrating that auditory processing of seemingly simple acoustic features, such as frequency and time, is highly dependent on co-occurring acoustic and behavioral stimuli. Through a combination of electrophysiological recordings, computational analysis and behavioral techniques, recent research identified the interactions between external spectral and temporal context of stimuli, as well as the internal behavioral state.

Excitatory and inhibitory neurons in the mammalian sensory cortex form interconnected circuits that control cortical stimulus selectivity and sensory acuity. Theoretical studies have predicted that suppression of inhibition in such excitatory-inhibitory networks can lead to either an increase or, paradoxically, a decrease in excitatory neuronal firing, with consequent effects on stimulus selectivity. We tested whether modulation of inhibition or excitation in the auditory cortex could evoke such a variety of effects in tone-evoked responses and in behavioral frequency discrimination acuity. We found that, indeed, the effects of optogenetic manipulation on stimulus selectivity and behavior varied in both magnitude and sign across subjects, possibly reflecting differences in circuitry or expression of optogenetic factors. Changes in neural population responses consistently predicted behavioral changes for individuals separately, including improvement and impairment in acuity. This correlation between cortical and behavioral change demonstrates that, despite complex and varied effects these manipulations can have on neuronal dynamics, the resulting changes in cortical activity account for accompanying changes in behavioral acuity.Author summaryExcitatory and inhibitory interactions determine stimulus specificity and tuning in sensory cortex, thereby controlling perceptual discrimination acuity. Modeling of such excitatory-inhibitory circuits has predicted that suppressing the activity of inhibitory neurons can lead to increases or, paradoxically, decreases in excitatory activity, depending on the architecture and modulation parameters of the inhibitory component of the network. Here, we capitalized on differences between subjects to test whether suppressing/activating inhibition and excitation across a range of parameters in sensory cortex can in fact exhibit such paradoxical effects for both stimulus sensitivity and behavioral discriminability. Indeed, we found that the same optogenetic manipulation in the auditory cortices of different mice could improve or impair frequency discrimination acuity, in a fashion that was predictable from the effects on cortical responses to tones. The same manipulations sometimes produced opposite changes in the behavior of different individuals, supporting theoretical predictions for inhibition-stabilized networks.

Inhibitory and excitatory neurons form intricate interconnected circuits in the mammalian sensory cortex. Whereas the function of excitatory neurons is largely to integrate and transmit information within and between brain areas, inhibitory neurons are thought to shape the way excitatory neurons integrate information, and they exhibit context-specific and behavior-specific responses. Over the last few years, work across sensory modalities has begun unraveling the function of distinct types of cortical inhibitory neurons in sensory processing, identifying their contribution to controlling stimulus selectivity of excitatory neurons and modulating information processing based on the behavioral state of the subject. Here, we review results from recent studies and discuss the implications for the contribution of inhibition to cortical circuit activity and information processing.

Summary: Neuronal stimulus selectivity is shaped by feedforward and recurrent excitatory-inhibitory interactions. In the auditory cortex (AC), parvalbumin- (PV) and somatostatin-positive (SOM) inhibitory interneurons differentially modulate frequency-dependent responses of excitatory neurons. Responsiveness of neurons in the AC to sound is also dependent on stimulus history. We found that the inhibitory effects of SOMs and PVs diverged as a function of adaptation to temporal repetition of tones. Prior to adaptation, suppressing either SOM or PV inhibition drove both increases and decreases in excitatory spiking activity. After adaptation, suppressing SOM activity caused predominantly disinhibitory effects, whereas suppressing PV activity still evoked bi-directional changes. SOM, but not PV-driven inhibition, dynamically modulated frequency tuning with adaptation. Unlike PV-driven inhibition, SOM-driven inhibition elicited gain-like increases in frequency tuning reflective of adaptation. Our findings suggest that distinct cortical interneurons differentially shape tuning to sensory stimuli across the neuronal receptive field, altering frequency selectivity of excitatory neurons during adaptation. : Natan et al. describe how a specific component in the neural circuitry in a key auditory part of the brain helps the auditory system tease apart complex sounds. This happens through adaptation of neuronal responses to temporally repeated sounds. Keywords: auditory cortex, interneurons, cortical processing, inhibition, adaptation, frequency tuning, auditory processing, optogenetics, archaerhodopsin

Neural systems can be modeled as networks of functionally connected neural elements. The resulting network can be analyzed using mathematical tools from network science and graph theory to quantify the system's topological organization and to better understand its function. While the network-based approach is common in the analysis of large-scale neural systems probed by non-invasive neuroimaging, few studies have used network science to study the organization of networks reconstructed at the cellular level, and thus many very basic and fundamental questions remain unanswered. Here, we used two-photon calcium imaging to record spontaneous activity from the same set of cells in mouse auditory cortex over the course of several weeks. We reconstruct functional networks in which cells are linked to one another by edges weighted according to the correlation of their fluorescence traces. We show that the networks exhibit modular structure across multiple topological scales and that these multi-scale modules unfold as part of a hierarchy. We also show that, on average, network architecture becomes increasingly dissimilar over time, with similarity decaying monotonically with the distance (in time) between sessions. Finally, we show that a small fraction of cells maintain strongly-correlated activity over multiple days, forming a stable temporal core surrounded by a fluctuating and variable periphery. Our work provides a careful methodological blueprint for future studies of spontaneous activity measured by two-photon calcium imaging using cutting-edge computational methods and machine learning algorithms informed by explicit graphical models from network science. The methods are easily extended to additional datasets, opening the possibility of studying cellular level network organization of neural systems and how that organization is modulated by stimuli or altered in models of disease., Comment: 15 pages, 3 figures

Many forms of behavior require selective amplification of neuronal representations of relevant environmental signals. Following emotional learning, sensory stimuli drive enhanced responses in the sensory cortex. However, the brain circuits that underlie emotionally driven control of the sensory representations remain poorly understood. Here we identify a novel pathway between the basolateral amygdala (BLA), an emotional learning center in the mouse brain, and the inhibitory nucleus of the thalamus (TRN). We demonstrate that activation of this pathway amplifies sound-evoked activity in the central auditory pathway. Optogenetic activation of BLA suppressed spontaneous, but not tone-evoked activity in the auditory cortex (AC), effectively amplifying tone-evoked responses in AC. Anterograde and retrograde viral tracing identified robust BLA projections terminating at TRN. Optogenetic activation of amygdala-TRN pathway mimicked the effect of direct BLA activation, amplifying tone-evoked responses in the auditory thalamus and cortex. The results are explained by a computational model of the thalamocortical circuitry. In our model, activation of TRN by BLA suppresses spontaneous activity in thalamocortical cells, and as a result, thalamocortical neurons are primed to relay relevant sensory input. These results demonstrate a novel circuit mechanism for shining a neural spotlight on behaviorally relevant signals and provide a potential target for treatment of neuropsychological disorders, in which emotional control of sensory processing is disrupted.

The extensive feedback from the auditory cortex (AC) to the inferior colliculus (IC) supports critical aspects of auditory behavior but has not been extensively characterized. Previous studies demonstrated that activity in IC is altered by focal electrical stimulation and pharmacological inactivation of AC, but these methods lack the ability to selectively manipulate projection neurons. We measured the effects of selective optogenetic modulation of cortico-collicular feedback projections on IC sound responses in mice. Activation of feedback increased spontaneous activity and decreased stimulus selectivity in IC, whereas suppression had no effect. To further understand how microcircuits in AC may control collicular activity, we optogenetically modulated the activity of different cortical neuronal subtypes, specifically parvalbumin-positive (PV) and somatostatin-positive (SST) inhibitory interneurons. We found that modulating the activity of either type of interneuron did not affect IC sound-evoked activity. Combined, our results identify that activation of excitatory projections, but not inhibition-driven changes in cortical activity, affects collicular sound responses., eLife digest How do we hear the world around us? Hearing begins when hair cells in the inner ear translate incoming sound waves into electrical signals. These signals travel via the auditory nerve and the brainstem to the midbrain, where an area called the inferior colliculus processes them. The inferior colliculus then passes the signals on to another area deep within the brain, the thalamus, which processes the signals further before it too passes them on to an area of the brain’s outer layer called the auditory cortex. At each stage of the auditory pathway, the signals undergo more complex processing than at the previous stage. Researchers have tended to think of this pathway as a one-way route from the ear to the brain. But in reality, feedback occurs at various points along the pathway, enabling areas that do higher processing to shape the responses of areas earlier in the pathway. This feedback is particularly prevalent in the auditory system, where one such strong feedback route is from the auditory cortex to the inferior colliculus. This reverse connection helps animals learn new behavioral responses to sounds, for example, to run away from a loud noise. By manipulating the activity of this pathway in mice using a technique called optogenetics, Blackwell et al. provide further clues to how the auditory pathway works. Optogenetics involves introducing light-sensitive ion channels into neurons, and then using light to activate or inhibit those neurons on demand. Blackwell et al. show that activating the feedback pathway from the auditory cortex to the inferior colliculus in awake mice changes how the inferior colliculus responds to sounds. By contrast, inhibiting the pathway has no effect on inferior colliculus responses. This suggests that the feedback pathway is not active all the time, but instead influences inferior colliculus activity only during specific behavior, for example, perhaps when we are listening for a specific sound like the ringing of a phone. Understanding how the brain processes sound is important for understanding how we communicate and why we appreciate music. It could also help in treating hearing loss. Stimulating the inferior colliculus using a device implanted in the brainstem can improve hearing in people with certain types of deafness. Strengthening or weakening the feedback pathway from the auditory cortex to the inferior colliculus could make these implants more effective. In the future, it may even be possible that stimulating the pathway directly could restore hearing without any implant being required.

A new study sheds light on how sensitivity to communication sounds is established in the brain. Juvenile finches raised with tutors of either the same or different species always learned the tutors’ songs. Cortical neurons developed selectivity for the learned song by tuning for its secondary acoustic features.

An essential task of the auditory system is to discriminate between different communication signals, such as vocalizations. In everyday acoustic environments, the auditory system needs to be capable of performing the discrimination under different acoustic distortions of vocalizations. To achieve this, the auditory system is thought to build a representation of vocalizations that is invariant to their basic acoustic transformations. The mechanism by which neuronal populations create such an invariant representation within the auditory cortex is only beginning to be understood. We recorded the responses of populations of neurons in the primary and nonprimary auditory cortex of rats to original and acoustically distorted vocalizations. We found that populations of neurons in the nonprimary auditory cortex exhibited greater invariance in encoding vocalizations over acoustic transformations than neuronal populations in the primary auditory cortex. These findings are consistent with the hypothesis that invariant representations are created gradually through hierarchical transformation within the auditory pathway.

SUMMARY Many forms of behavior require selective amplification of neuronal representations of relevant environmental signals. Emotional learning enhances sensory responses in the sensory cortex, yet the underlying circuits remain poorly understood. We identify a pathway between the basolateral amygdala (BLA), an emotional learning center in the mouse brain, and the inhibitory reticular nucleus of the thalamus (TRN). Optogenetic activation of BLA suppressed spontaneous, but not tone-evoked, activity in the auditory cortex (AC), amplifying tone-evoked responses. Viral tracing identified BLA projections terminating at TRN. Optogenetic activation of amygdala-TRN projections further amplified tone-evoked responses in the auditory thalamus and cortex. The results are explained by a computational model of the thalamocortical circuitry, in which activation of TRN by BLA primes thalamocortical neurons to relay relevant sensory input. This circuit mechanism shines a neural spotlight on behaviorally relevant signals and provides a potential target for the treatment of neuropsychological disorders., Graphical Abstract, In Brief Aizenberg et al. show that the projection from the emotional center of the brain, the basolateral amygdala, to the auditory thalamic control area, the thalamic reticular nucleus, gates sensory processing in the cortex.

Neurons throughout the sensory pathway are tuned to specific aspects of stimuli. This selectivity is shaped by feedforward and recurrent excitatory-inhibitory interactions. In the auditory cortex (AC), two large classes of interneurons, parvalbumin- (PVs) and somatostatin- positive (SOMs) interneurons, differentially modulate frequency-dependent responses across the frequency response function of excitatory neurons. At the same time, the responsiveness of neurons in AC to sounds is dependent on the temporal context, with the majority of neurons exhibiting adaptation to repeated sounds. Here, we asked whether and how inhibitory neurons shape the frequency response function of excitatory neurons as a function of adaptation to temporal repetition of tones. The effects of suppressing both SOMs and PVs diverged for responses to preferred versus non-preferred frequencies following adaptation. Prior to adaptation, suppressing either SOM or PV inhibition drove both increases and decreases in spiking activity among cortical neurons. After adaptation, suppressing SOM activity caused predominantly disinhibitory effects, whereas suppressing PV activity still evoked bi-directional changes. SOM, but not PV-driven inhibition dynamically modulated frequency tuning as a function of adaptation. Additionally, testing across frequency tuning revealed that, unlike PVs, SOM-driven inhibition exhibited gain-like increases reflective of adaptation. Our findings suggest that distinct cortical interneurons differentially shape tuning to sensory stimuli across the neuronal receptive field, maintaining frequency selectivity of excitatory neurons during adaptation.

One of the central tasks of the mammalian auditory system is to represent information about acoustic communicative signals, such as vocalizations. However, the neuronal computations underlying vocalization encoding in the central auditory system are poorly understood. To learn how the rat auditory cortex encodes information about conspecific vocalizations, we presented a library of natural and temporally transformed ultrasonic vocalizations (USVs) to awake rats while recording neural activity in the primary auditory cortex (A1) with chronically implanted multielectrode probes. Many neurons reliably and selectively responded to USVs. The response strength to USVs correlated strongly with the response strength to frequency-modulated (FM) sweeps and the FM rate tuning index, suggesting that related mechanisms generate responses to USVs as to FM sweeps. The response strength further correlated with the neuron's best frequency, with the strongest responses produced by neurons whose best frequency was in the ultrasonic frequency range. For responses of each neuron to each stimulus group, we fitted a novel predictive model: a reduced generalized linear-nonlinear model (GLNM) that takes the frequency modulation and single-tone amplitude as the only two input parameters. The GLNM accurately predicted neuronal responses to previously unheard USVs, and its prediction accuracy was higher than that of an analogous spectrogram-based linear-nonlinear model. The response strength of neurons and the model prediction accuracy were higher for original, rather than temporally transformed, vocalizations. These results indicate that A1 processes original USVs differentially than transformed USVs, indicating preference for temporal statistics of the original vocalizations.

Natural sounds exhibit statistical variation in their spectrotemporal structure. This variation is central to identification of unique environmental sounds and to vocal communication. Using limited resources, the auditory system must create a faithful representation of sounds across the full range of variation in temporal statistics. Imaging studies in humans demonstrated that the auditory cortex is sensitive to temporal correlations. However, the mechanisms by which the auditory cortex represents the spectrotemporal structure of sounds and how neuronal activity adjusts to vastly different statistics remain poorly understood. In this study, we recorded responses of neurons in the primary auditory cortex of awake rats to sounds with systematically varied temporal correlation, to determine whether and how this feature alters sound encoding. Neuronal responses adapted to changing stimulus temporal correlation. This adaptation was mediated by a change in the firing rate gain of neuronal responses rather than their spectrotemporal properties. This gain adaptation allowed neurons to maintain similar firing rates across stimuli with different statistics, preserving their ability to efficiently encode temporal modulation. This dynamic gain control mechanism may underlie comprehension of vocalizations and other natural sounds under different contexts, subject to distortions in temporal correlation structure via stretching or compression.

Olfactory processing in the insect antennal lobe is a highly dynamic process, yet it has been studied primarily with static step stimuli. To approximate the rapid odor fluctuations encountered in nature, we presented flickering "white-noise" odor stimuli to the antenna of the locust and recorded spike trains from antennal lobe projection neurons (PNs). The responses varied greatly across PNs and across odors for the same PN. Surprisingly, this diversity across the population was highly constrained, and most responses were captured by a quantitative model with just 3 parameters. Individual PNs were found to communicate odor information at rates up to approximately 4 bits/s. A small group of PNs was sufficient to provide an accurate representation of the dynamic odor time course, whose quality was maximal for fluctuations of frequency approximately 0.8 Hz. We develop a simple model for the encoding of dynamic odor stimuli that accounts for many prior observations on the population response.

Reliably detecting unexpected sounds is important for environmental awareness and survival. By selectively reducing responses to frequently, but not rarely, occurring sounds, auditory cortical neurons are thought to enhance the brain's ability to detect unexpected events through stimulus-specific adaptation (SSA). The majority of neurons in the primary auditory cortex exhibit SSA, yet little is known about the underlying cortical circuits. We found that two types of cortical interneurons differentially amplify SSA in putative excitatory neurons. Parvalbumin-positive interneurons (PVs) amplify SSA by providing non-specific inhibition: optogenetic suppression of PVs led to an equal increase in responses to frequent and rare tones. In contrast, somatostatin-positive interneurons (SOMs) selectively reduce excitatory responses to frequent tones: suppression of SOMs led to an increase in responses to frequent, but not to rare tones. A mutually coupled excitatory-inhibitory network model accounts for distinct mechanisms by which cortical inhibitory neurons enhance the brain's sensitivity to unexpected sounds. DOI: http://dx.doi.org/10.7554/eLife.09868.001, eLife digest In everyday life, we are often exposed to a mix of different sounds. An essential task for our brain is to separate the important sounds from the unimportant ones. For example, stepping out onto a busy street, you may at first be very aware of the noise of traffic. Later, you may start to ignore the din and instead only notice sounds that break the monotony: a honking car horn or maybe a stranger's voice. This is because the neurons in the auditory pathway respond differently to common and rare sounds. In particular, excitatory neurons in the region termed the ‘auditory cortex’ send fewer nerve impulses in response to frequent sounds, but respond vigorously to rare sounds. This phenomenon is called ‘stimulus-specific adaptation’, but it is not known exactly which neurons in this brain region enable this process to occur. Now, Natan et al. have combined different cutting-edge neuroscience techniques to identify the circuit of brain cells that drives this stimulus specific adaptation. A technique called optogenetics was used to effectively ‘turn off’ each of two kinds of inhibitory neuron in the auditory cortex of mice, by exposing the brain to colored light from a laser. Natan et al. found that both kinds of inhibitory neuron amplified stimulus-specific adaptation, but via different mechanisms. One of these neuron types, called ‘parvalbumin-positive interneurons’, exerted a general effect on excitatory neurons and suppressed responses to both frequent and rare sounds As the responses to rare sounds started off greater than the responses to frequent sounds, suppressing both by an equal amount actually led to an increase in the relative difference between them. On the other hand, the second kind of inhibitory neuron, called ‘somatostatin-positive interneurons’, only reduced the excitatory neurons' responses to frequent sounds; these neurons had no effect on responses to rare noises. Future studies will test how specific adaptation in different contexts can help us to behaviorally detect rare sounds while ignoring common ones, and search for the circuits beyond the auditory cortex that support hearing in complex sound environments. DOI: http://dx.doi.org/10.7554/eLife.09868.002

Natural auditory scenes possess highly structured statistical regularities, which are dictated by the physics of sound production in nature, such as scale‐invariance. We recently identified that natural water sounds exhibit a particular type of scale invariance, in which the temporal modulation within spectral bands scales with the centre frequency of the band. Here, we tested how neurons in the mammalian primary auditory cortex encode sounds that exhibit this property, but differ in their statistical parameters. The stimuli varied in spectro‐temporal density and cyclo‐temporal statistics over several orders of magnitude, corresponding to a range of water‐like percepts, from pattering of rain to a slow stream. We recorded neuronal activity in the primary auditory cortex of awake rats presented with these stimuli. The responses of the majority of individual neurons were selective for a subset of stimuli with specific statistics. However, as a neuronal population, the responses were remarkably stable over large changes in stimulus statistics, exhibiting a similar range in firing rate, response strength, variability and information rate, and only minor variation in receptive field parameters. This pattern of neuronal responses suggests a potentially general principle for cortical encoding of complex acoustic scenes: while individual cortical neurons exhibit selectivity for specific statistical features, a neuronal population preserves a constant response structure across a broad range of statistical parameters.

Tinnitus is an auditory disorder, which affects millions of Americans, including active duty service members and veterans. It is manifested by a phantom sound that is commonly restricted to a specific frequency range. Because tinnitus is associated with hearing deficits, understanding how tinnitus affects hearing perception is important for guiding therapies to improve the quality of life in this vast group of patients. In a rodent model of tinnitus, prolonged exposure to a tone leads to a selective decrease in gap detection in specific frequency bands. However, whether and how hearing acuity is affected for sounds within and outside those frequency bands is not well understood. We induced tinnitus in mice by prolonged exposure to a loud mid-range tone, and behaviorally assayed whether mice exhibited a change in frequency discrimination acuity for tones embedded within the mid-frequency range and high-frequency range at 1, 4, and 8 weeks post-exposure. A subset of tone-exposed mice exhibited tinnitus-like symptoms, as demonstrated by selective deficits in gap detection, which were restricted to the high frequency range. These mice exhibited impaired frequency discrimination both for tones in the mid-frequency range and high-frequency range. The remaining tone exposed mice, which did not demonstrate behavioral evidence of tinnitus, showed temporary deficits in frequency discrimination for tones in the mid-frequency range, while control mice remained unimpaired. Our findings reveal that the high frequency-specific deficits in gap detection, indicative of tinnitus, are associated with impairments in frequency discrimination at the frequency of the presumed tinnitus.

Tinnitus is an auditory disorder, which affects millions of Americans, including active duty service members and veterans. It is manifested by a phantom sound that is commonly restricted to a specific frequency range. Because tinnitus is associated with hearing deficits, understanding how tinnitus affects hearing perception is important for guiding therapies to improve the quality of life in this vast group of patients. In a rodent model of tinnitus, prolonged exposure to a tone leads to a selective decrease in gap detection in specific frequency bands. However, whether and how hearing acuity is affected for sounds within and outside those frequency bands is not well understood. We induced tinnitus in mice by prolonged exposure to a loud mid-range tone, and behaviorally assayed whether mice exhibited a change in frequency discrimination acuity for tones embedded within the mid-frequency range and high-frequency range at 1, 4, and 8 weeks post-exposure. A subset of tone-exposed mice exhibited tinnitus-like symptoms, as demonstrated by selective deficits in gap detection, which were restricted to the high frequency range. These mice exhibited impaired frequency discrimination both for tones in the mid-frequency range and high-frequency range. The remaining tone exposed mice, which did not demonstrate behavioral evidence of tinnitus, showed temporary deficits in frequency discrimination for tones in the mid-frequency range, while control mice remained unimpaired. Our findings reveal that the high frequency-specific deficits in gap detection, indicative of tinnitus, are associated with impairments in frequency discrimination at the frequency of the presumed tinnitus.

A central goal of neuroscience is to understand how populations of neurons build and manipulate representations of percepts that provide useful information about the environment. This symposium explores the fundamental properties of these representations and the perceptual spaces in which they are organized. Spanning the domains of color, visual texture, environmental sound, music, tactile quality, and odor, we show how the geometric structures of perceptual spaces can be determined experimentally and how these structures provide insights into the principles of neural coding and the neural mechanisms that generate the codes, and into the neural processing of complex sensory stimuli. The diversity of the neural architecture in these different sensory systems provides an opportunity to compare their different solutions to common problems: the need for dimensionality reduction, strategies for topographic or nontopographic mapping, the utility of the higher-order statistical structure inherent in natural sensory stimuli, and the constraints of neural hardware.

Although emotional learning affects sensory acuity, little is known about how these changes are facilitated in the brain. We found that auditory fear conditioning in mice elicited either an increase or a decrease in frequency discrimination acuity depending on how specific the learned response was to the conditioned tone. Using reversible pharmacological inactivation, we found that the auditory cortex mediated learning-evoked changes in acuity in both directions.

Many natural signals, including environmental sounds, exhibit scale-invariant statistics: their structure is repeated at multiple scales. Such scale-invariance has been identified separately across spectral and temporal correlations of natural sounds (Clarke and Voss, 1975; Attias and Schreiner, 1997; Escabi et al., 2003; Singh and Theunissen, 2003). Yet the role of scale-invariance across overall spectro-temporal structure of the sound has not been explored directly in auditory perception. Here, we identify that the acoustic waveform from the recording of running water is a self-similar fractal, exhibiting scale-invariance not only within spectral channels, but also across the full spectral bandwidth. The auditory perception of the water sound did not change with its scale. We tested the role of scale-invariance in perception by using an artificial sound, which could be rendered scale-invariant. We generated a random chirp stimulus: an auditory signal controlled by two parameters, Q, controlling the relative, and r, controlling the absolute, temporal structure of the sound. Imposing scale-invariant statistics on the artificial sound was required for its perception as natural and water-like. Further, Q had to be restricted to a specific range for the sound to be perceived as natural. To detect self-similarity in the water sound, and identify Q, the auditory system needs to process the temporal dynamics of the waveform across spectral bands in terms of the number of cycles, rather than absolute timing. We propose a two-stage neural model implementing this computation. This computation may be carried out by circuits of neurons in the auditory cortex. The set of auditory stimuli developed in this study are particularly suitable for measurements of response properties of neurons in the auditory pathway, allowing for quantification of the effects of varying the statistics of the spectro-temporal statistical structure of the stimulus.

Retinal ganglion cells are commonly classified as On-center or Off-center depending on whether they are excited predominantly by brightening or dimming within the receptive field. Here we report that many ganglion cells in the salamander retina can switch from one response type to the other, depending on stimulus events far from the receptive field. Specifically, a shift of the peripheral image—as produced by a rapid eye movement—causes a brief transition in visual sensitivity from Off-type to On-type for approximately 100 ms. We show that these ganglion cells receive inputs from both On and Off bipolar cells, and the Off inputs are normally dominant. The peripheral shift strongly modulates the strength of these two inputs in opposite directions, facilitating the On pathway and suppressing the Off pathway. Furthermore, we identify certain wide-field amacrine cells that contribute to this modulation. Depolarizing such an amacrine cell affects nearby ganglion cells in the same way as the peripheral image shift, facilitating the On inputs and suppressing the Off inputs. This study illustrates how inhibitory interneurons can rapidly gate the flow of information within a circuit, dramatically altering the behavior of the principal neurons in the course of a computation., Author Summary The eye communicates to the brain all the information needed for vision in the form of electrical pulses, or spikes, on optic nerve fibers. These spikes are produced by retinal ganglion cells, the output neurons of the retina. In a popular view of retinal function, each ganglion cell responds to a small region of interest in the visual image, known as its receptive field, and is specialized for certain image features within that window. When a cell encounters that image feature, the neuron responds by firing one or more spikes. Different neurons are tuned to different features. For example, some ganglion cells fire when light dims, others when it brightens. Here we show that a rapid shift in the image on the retina can cause a dramatic change in a neuron's preferred feature: For example, a dimming-detector can briefly turn into a brightening-detector. We explore the mechanisms that implement such a switch of feature tuning, and the consequences it might have for visual processing., A peripheral image shift produces a transient switch in retinal ganglion cell responses from Off-dominated to On-dominated. This modulation is exerted at least in part presynaptically, presumably at the bipolar cell synaptic terminal.

In PLoS Biology, volume 5, issue 3: doi: 10.1371/journal.pbio.0050136 Figue 8A was published without a scale bar. The corrected figure is as follows. The legend remains the same.