Neurons In Auditory Cortex Research Articles

Massive multiplexing of spatially resolved single neuron projections with axonal BARseq

Neurons in the cortex are heterogeneous, sending diverse axonal projections to multiple brain regions. Unraveling the logic of these projections requires single-neuron resolution. Although a growing number of techniques have enabled high-throughput reconstruction, these techniques are typically limited to dozens or at most hundreds of neurons per brain, requiring that statistical analyses combine data from different specimens. Here we present axonal BARseq, a high-throughput approach based on reading out nucleic acid barcodes using in situ RNA sequencing, which enables analysis of even densely labeled neurons. As a proof of principle, we have mapped the long-range projections of >8000 primary auditory cortex neurons from a single male mouse. We identified major cell types based on projection targets and axonal trajectory. The large sample size enabled us to systematically quantify the projections of intratelencephalic (IT) neurons, and revealed that individual IT neurons project to different layers in an area-dependent fashion. Axonal BARseq is a powerful technique for studying the heterogeneity of single neuronal projections at high throughput within individual brains.

The serotonergic psychedelic DOI impairs deviance detection in the auditory cortex.

Psychedelics are known to induce profound perceptual distortions, yet the neural mechanisms underlying these effects, particularly within the auditory system, remain poorly understood. In this study, we investigated the effects of the psychedelic compound 2,5-Dimethoxy-4-iodoamphetamine (DOI), a serotonin 2A receptor agonist, on the activity of neurons in the auditory cortex of awake mice. We examined whether DOI administration alters sound-frequency tuning, variability in neural responses, and deviance detection (a neural process reflecting the balance between top-down and bottom-up processing). Our results show that while DOI does not alter the frequency selectivity of auditory cortical neurons in a consistent manner, it increases trial-by-trial variability in responses and consistently diminishes the neural distinction between expected (standard) and unexpected (oddball) stimuli. This reduction in deviance detection was primarily driven by a decrease in the response to oddball sounds, suggesting that DOI dampens the auditory cortex's sensitivity to unexpected events. These findings provide insights into how psychedelics disrupt sensory processing and shed light on the neural mechanisms underlying the altered perception of auditory stimuli observed in the psychedelic state.

Receptive-field nonlinearities in primary auditory cortex: a comparative perspective.

Cortical processing of auditory information can be affected by interspecies differences as well as brain states. Here we compare multifeature spectro-temporal receptive fields (STRFs) and associated input/output functions or nonlinearities (NLs) of neurons in primary auditory cortex (AC) of four mammalian species. Single-unit recordings were performed in awake animals (female squirrel monkeys, female, and male mice) and anesthetized animals (female squirrel monkeys, rats, and cats). Neuronal responses were modeled as consisting of two STRFs and their associated NLs. The NLs for the STRF with the highest information content show a broad distribution between linear and quadratic forms. In awake animals, we find a higher percentage of quadratic-like NLs as opposed to more linear NLs in anesthetized animals. Moderate sex differences of the shape of NLs were observed between male and female unanesthetized mice. This indicates that the core AC possesses a rich variety of potential computations, particularly in awake animals, suggesting that multiple computational algorithms are at play to enable the auditory system's robust recognition of auditory events.

Bidirectional generative adversarial representation learning for natural stimulus synthesis.

Thousands of species use vocal signals to communicate with one another. Vocalizations carry rich information, yet characterizing and analyzing these complex, high-dimensional signals is difficult and prone to human bias. Moreover, animal vocalizations are ethologically relevant stimuli whose representation by auditory neurons is an important subject of research in sensory neuroscience. A method that can efficiently generate naturalistic vocalization waveforms would offer an unlimited supply of stimuli with which to probe neuronal computations. Although unsupervised learning methods allow for the projection of vocalizations into low-dimensional latent spaces learned from the waveforms themselves, and generative modeling allows for the synthesis of novel vocalizations for use in downstream tasks, we are not aware of any model that combines these tasks to synthesize naturalistic vocalizations in the waveform domain for stimulus playback. In this paper, we demonstrate BiWaveGAN: a bidirectional generative adversarial network (GAN) capable of learning a latent representation of ultrasonic vocalizations (USVs) from mice. We show that BiWaveGAN can be used to generate, and interpolate between, realistic vocalization waveforms. We then use these synthesized stimuli along with natural USVs to probe the sensory input space of mouse auditory cortical neurons. We show that stimuli generated from our method evoke neuronal responses as effectively as real vocalizations, and produce receptive fields with the same predictive power. BiWaveGAN is not restricted to mouse USVs but can be used to synthesize naturalistic vocalizations of any animal species and interpolate between vocalizations of the same or different species, which could be useful for probing categorical boundaries in representations of ethologically relevant auditory signals.NEW & NOTEWORTHY A new type of artificial neural network is presented that can be used to generate animal vocalization waveforms and interpolate between them to create new vocalizations. We find that our synthetic naturalistic stimuli drive auditory cortical neurons in the mouse equally well and produce receptive field features with the same predictive power as those obtained with natural mouse vocalizations, confirming the quality of the stimuli produced by the neural network.

Physiological properties of auditory neurons responding to omission deviants in the anesthetized rat

SummaryThe detection of novel, low probability events in the environment is critical for survival. To perform this vital task, our brain is continuously building and updating a model of the outside world; an extensively studied phenomenon commonly referred to as predictive coding. Predictive coding posits that the brain is continuously extracting regularities from the environment to generate predictions. These predictions are then used to supress neuronal responses to redundant information, filtering those inputs, which then automatically enhances the remaining, unexpected inputs.We have recently described the ability of auditory neurons to generate predictions about expected sensory inputs by detecting their absence in an oddball paradigm using omitted tones as deviants. Here, we studied the responses of individual neurons to omitted tones by presenting individual sequences of repetitive pure tones, using both random and periodic omissions, presented at both fast and slow rates in the inferior colliculus and auditory cortex neurons of anesthetized rats. Our goal was to determine whether feature-specific dependence of these predictions exists. Results showed that omitted tones could be detected at both high (8 Hz) and slow repetition rates (2 Hz), with detection being more robust at the non-lemniscal auditory pathway.

Time scale of adaptation at the tonal sequence processing in the awake mice auditory cortex neurons

The study was firstly carried out on stimulus-specific adaptation of neurons in the primary and anterior fields of the awake house mice auditory cortex to sound sequences of four 100-ms tonal signals, with frequency of tones corresponding to the neuronal characteristic frequency, and also with the inter-tone interval constant for one sequence and varying from 0 to 2000 ms in different sequences. The analysis of the data obtained showed the adaptation effect in the responses of all studied primary auditory cortex neurons, which was observed as the absence or significant decrease in activity evoked by the components of a series of tones following the 1st, at inter-stimulus intervals of 0–500 ms. A quantitative assessment of the adaptation effects as a function of inter-stimulus intervals within the tonal sequence, performed over whole population of studied neurons, showed that the individual time scales of adaptation of neurons varied significantly, which may be crucial for the formation of optimal time windows for the processing of grouping and separation of sound events, which are important both for perception of animal vocalizations and human speech.

Dynamic gating of perceptual flexibility by non-classically responsive cortical neurons.

The ability to flexibly respond to sensory cues in dynamic environments is essential to adaptive auditory-guided behaviors. Cortical spiking responses during behavior are highly diverse, ranging from reliable trial-averaged responses to seemingly random firing patterns. While the reliable responses of 'classically responsive' cells have been extensively studied for decades, the contribution of irregular spiking 'non-classically responsive' cells to behavior has remained underexplored despite their prevalence. Here, we show that flexible auditory behavior results from interactions between local auditory cortical circuits comprised of heterogeneous responses and inputs from secondary motor cortex. Strikingly, non-classically responsive neurons in auditory cortex were preferentially recruited during learning, specifically during rapid learning phases when the greatest gains in behavioral performance occur. Population-level decoding revealed that during rapid learning mixed ensembles comprised of both classically and non-classically responsive cells encode significantly more task information than homogenous ensembles of either type and emerge as a functional unit critical for learning. Optogenetically silencing inputs from secondary motor cortex selectively modulated non-classically responsive cells in the auditory cortex and impaired reversal learning by preventing the remapping of a previously learned stimulus-reward association. Top-down inputs orchestrated highly correlated non-classically responsive ensembles in sensory cortex providing a unique task-relevant manifold for learning. Thus, non-classically responsive cells in sensory cortex are preferentially recruited by top-down inputs to enable neural and behavioral flexibility.

Contributions of cortical neuron firing patterns, synaptic connectivity, and plasticity to task performance

Neuronal responses during behavior are diverse, ranging from highly reliable ‘classical’ responses to irregular ‘non-classically responsive’ firing. While a continuum of response properties is observed across neural systems, little is known about the synaptic origins and contributions of diverse responses to network function, perception, and behavior. To capture the heterogeneous responses measured from auditory cortex of rodents performing a frequency recognition task, we use a novel task-performing spiking recurrent neural network incorporating spike-timing-dependent plasticity. Reliable and irregular units contribute differentially to task performance via output and recurrent connections, respectively. Excitatory plasticity shifts the response distribution while inhibition constrains its diversity. Together both improve task performance with full network engagement. The same local patterns of synaptic inputs predict spiking response properties of network units and auditory cortical neurons from in vivo whole-cell recordings during behavior. Thus, diverse neural responses contribute to network function and emerge from synaptic plasticity rules.

Ionic mechanisms involved in arginine vasopressin-mediated excitation of auditory cortical and thalamic neurons

The axons containing arginine vasopressin (AVP) from the hypothalamus innervate a variety of structures including the cerebral cortex, thalamus, hippocampus and amygdala. A plethora amount of evidence indicates that activation of the V1a subtype of the vasopressin receptors facilitates anxiety-like and fear responses. As an essential structure involved in fear and anxiety responses, the amygdala, especially the lateral nucleus of amygdala (LA), receives glutamatergic innervations from the auditory cortex and auditory thalamus where high density of V1a receptors have been detected. However, the roles and mechanisms of AVP in these two important areas have not been determined, which prevents the understanding of the mechanisms whereby V1a activation augments anxiety and fear responses. Here, we used coronal brain slices and studied the effects of AVP on neuronal activities of the auditory cortical and thalamic neurons. Our results indicate that activation of V1a receptors excited both auditory cortical and thalamic neurons. In the auditory cortical neurons, AVP increased neuronal excitability by depressing multiple subtypes of inwardly rectifying K+ (Kir) channels including the Kir2 subfamily, the ATP-sensitive K+ channels and the G protein-gated inwardly rectifying K+ (GIRK) channels, whereas activation of V1a receptors excited the auditory thalamic neurons by depressing the Kir2 subfamily of the Kir channels as well as activating the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels and a persistent Na+ channel. Our results may help explain the roles of V1a receptors in facilitating fear and anxiety responses.Categories: Cell Physiology.

Sampling bias corrections for accurate neural measures of redundant, unique, and synergistic information.

Shannon Information theory has long been a tool of choice to measure empirically how populations of neurons in the brain encode information about cognitive variables. Recently, Partial Information Decomposition (PID) has emerged as principled way to break down this information into components identifying not only the unique information carried by each neuron, but also whether relationships between neurons generate synergistic or redundant information. While it has been long recognized that Shannon information measures on neural activity suffer from a (mostly upward) limited sampling estimation bias, this issue has largely been ignored in the burgeoning field of PID analysis of neural activity. We used simulations to investigate the limited sampling bias of PID computed from discrete probabilities (suited to describe neural spiking activity). We found that PID suffers from a large bias that is uneven across components, with synergy by far the most biased. Using approximate analytical expansions, we found that the bias of synergy increases quadratically with the number of discrete responses of each neuron, whereas the bias of unique and redundant information increase only linearly or sub-linearly. Based on the understanding of the PID bias properties, we developed simple yet effective procedures that correct for the bias effectively, and that improve greatly the PID estimation with respect to current state-of-the-art procedures. We apply these PID bias correction procedures to datasets of 53117 pairs neurons in auditory cortex, posterior parietal cortex and hippocampus of mice performing cognitive tasks, deriving precise estimates and bounds of how synergy and redundancy vary across these brain regions.

Cortical dysmorphology and reduced cortico-collicular projections in an animal model of autism spectrum disorder.

Autism spectrum disorder is a neurodevelopmental disability that includes sensory disturbances. Hearing is frequently affected and ranges from deafness to hypersensitivity. In utero exposure to the antiepileptic valproic acid is associated with increased risk of autism spectrum disorder in humans and timed valproic acid exposure is a biologically relevant and validated animal model of autism spectrum disorder. Valproic acid-exposed rats have fewer neurons in their auditory brainstem and thalamus, fewer calbindin-positive neurons, reduced ascending projections to the midbrain and thalamus, elevated thresholds, and delayed auditory brainstem responses. Additionally, in the auditory cortex, valproic acid exposure results in abnormal responses, decreased phase-locking, elevated thresholds, and abnormal tonotopic maps. We therefore hypothesized that in utero, valproic acid exposure would result in fewer neurons in auditory cortex, neuronal dysmorphology, fewer calbindin-positive neurons, and reduced connectivity. We approached this hypothesis using morphometric analyses, immunohistochemistry, and retrograde tract tracing. We found thinner cortical layers but no changes in the density of neurons, smaller pyramidal and non-pyramidal neurons in several regions, fewer neurons immunoreactive for calbindin-positive, and fewer cortical neurons projecting to the inferior colliculus. These results support the widespread impact of the auditory system in autism spectrum disorder and valproic acid-exposed animals and emphasize the utility of simple, noninvasive auditory screening for autism spectrum disorder.

Distinct electrophysiological properties of long-range GABAergic and glutamatergic neurons from the lateral amygdala to the auditory cortex of the mouse.

Differentiating between auditory signals of various emotional significance plays a crucial role in an individual's ability to thrive and excel in social interactions and in survival. Multiple approaches, including anatomical studies, electrophysiological investigations, imaging techniques, optogenetics and chemogenetics, have confirmed that the auditory cortex (AC) impacts fear-related behaviours driven by auditory stimuli by conveying auditory information to the lateral amygdala (LA) through long-range excitatory glutamatergic and GABAergic connections. In addition, the LA provides glutamatergic projections to the AC which are important to fear memory expression and are modified by associative fear learning. Here we test the hypothesis that the LA also sends long-range direct inhibitory inputs to the cortex. To address this fundamental question, we used anatomical and electrophysiological approaches, allowing us to directly assess the nature of GABAergic inputs from the LA to the AC in the mouse. Our findings elucidate the existence of a long-range inhibitory pathway from the LA to the AC (LAC) via parvalbumin-expressing (LAC-Parv) and somatostatin-expressing (LAC-SOM) neurons. This research identifies distinct electrophysiological properties for genetically defined long-range GABAergic neurons involved in the communication between the LA and the cortex (LAC-Parv inhibitory projections → AC neurons; LAC-Som inhibitory projections → AC neurons) within the lateral amygdala cortical network. KEY POINTS: The mouse auditory cortex receives inputs from the lateral amygdala. Retrograde viral tracing techniques allowed us to identify two previously undescribed lateral amygdala to auditory cortex (LAC) GABAergic projecting neurons. Extensive electrophysiological, morphological and anatomical characterization of LAC neurons is provided here, demonstrating key differences in the three populations. This study paves the way for a better understanding of the growing complexity of the cortico-amygdala-cortico circuit.

Movement-Related Modulation in Mouse Auditory Cortex Is Widespread Yet Locally Diverse.

Neurons in the mouse auditory cortex are strongly influenced by behavior, including both suppression and enhancement of sound-evoked responses during movement. The mouse auditory cortex comprises multiple fields with different roles in sound processing and distinct connectivity to movement-related centers of the brain. Here, we asked whether movement-related modulation in male mice might differ across auditory cortical fields, thereby contributing to the heterogeneity of movement-related modulation at the single-cell level. We used wide-field calcium imaging to identify distinct cortical fields and cellular-resolution two-photon calcium imaging to visualize the activity of layer 2/3 excitatory neurons within each field. We measured each neuron's responses to three sound categories (pure tones, chirps, and amplitude-modulated white noise) as mice rested and ran on a non-motorized treadmill. We found that individual neurons in each cortical field typically respond to just one sound category. Some neurons are only active during rest and others during locomotion, and those that are responsive across conditions retain their sound-category tuning. The effects of locomotion on sound-evoked responses vary at the single-cell level, with both suppression and enhancement of neural responses, and the net modulatory effect of locomotion is largely conserved across cortical fields. Movement-related modulation in auditory cortex also reflects more complex behavioral patterns, including instantaneous running speed and nonlocomotor movements such as grooming and postural adjustments, with similar patterns seen across all auditory cortical fields. Our findings underscore the complexity of movement-related modulation throughout the mouse auditory cortex and indicate that movement-related modulation is a widespread phenomenon.

Dissociable Roles of the Auditory Midbrain and Cortex in Processing the Statistical Features of Natural Sound Textures.

Sound texture perception takes advantage of a hierarchy of time-averaged statistical features of acoustic stimuli, but much remains unclear about how these statistical features are processed along the auditory pathway. Here, we compared the neural representation of sound textures in the inferior colliculus (IC) and auditory cortex (AC) of anesthetized female rats. We recorded responses to texture morph stimuli that gradually add statistical features of increasingly higher complexity. For each texture, several different exemplars were synthesized using different random seeds. An analysis of transient and ongoing multiunit responses showed that the IC units were sensitive to every type of statistical feature, albeit to a varying extent. In contrast, only a small proportion of AC units were overtly sensitive to any statistical features. Differences in texture types explained more of the variance of IC neural responses than did differences in exemplars, indicating a degree of "texture type tuning" in the IC, but the same was, perhaps surprisingly, not the case for AC responses. We also evaluated the accuracy of texture type classification from single-trial population activity and found that IC responses became more informative as more summary statistics were included in the texture morphs, while for AC population responses, classification performance remained consistently very low. These results argue against the idea that AC neurons encode sound type via an overt sensitivity in neural firing rate to fine-grain spectral and temporal statistical features.

Time Scale of Adaptation at the Tonal Sequence Processing in the Awake Mice Auditory Cortex Neurons

Time Scale of Adaptation at the Tonal Sequence Processing in the Awake Mice Auditory Cortex Neurons

Behavioural relevance of redundant and synergistic stimulus information between functionally connected neurons in mouse auditory cortex

Measures of functional connectivity have played a central role in advancing our understanding of how information is transmitted and processed within the brain. Traditionally, these studies have focused on identifying redundant functional connectivity, which involves determining when activity is similar across different sites or neurons. However, recent research has highlighted the importance of also identifying synergistic connectivity—that is, connectivity that gives rise to information not contained in either site or neuron alone. Here, we measured redundant and synergistic functional connectivity between neurons in the mouse primary auditory cortex during a sound discrimination task. Specifically, we measured directed functional connectivity between neurons simultaneously recorded with calcium imaging. We used Granger Causality as a functional connectivity measure. We then used Partial Information Decomposition to quantify the amount of redundant and synergistic information about the presented sound that is carried by functionally connected or functionally unconnected pairs of neurons. We found that functionally connected pairs present proportionally more redundant information and proportionally less synergistic information about sound than unconnected pairs, suggesting that their functional connectivity is primarily redundant. Further, synergy and redundancy coexisted both when mice made correct or incorrect perceptual discriminations. However, redundancy was much higher (both in absolute terms and in proportion to the total information available in neuron pairs) in correct behavioural choices compared to incorrect ones, whereas synergy was higher in absolute terms but lower in relative terms in correct than in incorrect behavioural choices. Moreover, the proportion of redundancy reliably predicted perceptual discriminations, with the proportion of synergy adding no extra predictive power. These results suggest a crucial contribution of redundancy to correct perceptual discriminations, possibly due to the advantage it offers for information propagation, and also suggest a role of synergy in enhancing information level during correct discriminations.

A sparse code for natural sound context in auditory cortex

Accurate sound perception can require integrating information over hundreds of milliseconds or even seconds. Spectro-temporal models of sound coding by single neurons in auditory cortex indicate that the majority of sound-evoked activity can be attributed to stimuli with a few tens of milliseconds. It remains uncertain how the auditory system integrates information about sensory context on a longer timescale. Here we characterized long-lasting contextual effects in auditory cortex (AC) using a diverse set of natural sound stimuli. We measured context effects as the difference in a neuron's response to a single probe sound following two different context sounds. Many AC neurons showed context effects lasting longer than the temporal window of a traditional spectro-temporal receptive field. The duration and magnitude of context effects varied substantially across neurons and stimuli. This diversity of context effects formed a sparse code across the neural population that encoded a wider range of contexts than any constituent neuron. Encoding model analysis indicates that context effects can be explained by activity in the local neural population, suggesting that recurrent local circuits support a long-lasting representation of sensory context in auditory cortex.

Altered corollary discharge signaling in the auditory cortex of a mouse model of schizophrenia predisposition

The ability to distinguish sensations that are self-generated from those caused by external events is disrupted in schizophrenia patients. However, the neural circuit abnormalities underlying this sensory impairment and its relationship to the risk factors for the disease is not well understood. To address this, we examined the processing of self-generated sounds in male Df(16)A+/− mice, which model one of the largest genetic risk factors for schizophrenia, the 22q11.2 microdeletion. We find that auditory cortical neurons in Df(16)A+/− mice fail to attenuate their responses to self-generated sounds, recapitulating deficits seen in schizophrenia patients. Notably, the auditory cortex of Df(16)A+/− mice displayed weaker motor-related signals and received fewer inputs from the motor cortex, suggesting an anatomical basis underlying the sensory deficit. These results provide insights into the mechanisms by which a major genetic risk factor for schizophrenia disrupts the top-down processing of sensory information.

Naturalistic behaviors for studying object identification in auditory cortex

Localizing and identifying sensory objects while exploring the environment are fundamental brain functions. Yet despite decades of study, we still do not fully understand how auditory cortex neurons represent sound locations, or how those representations are affected by context and behavior. In particular, little is known about brain function when sensory inputs are processed during active sensing. Here, we present results of gerbils, freely moving, performing the Sensory Island Task (SIT). In SIT, animals are free to forage for a specific spot (the island) in the experimental arena which, upon being found, triggers a change in the auditory stimulation location; which animals report by staying within the island for an extended time period, in order to receive a reward. By coupling one of the sound sources to reward delivery, we demonstrate that sound source identity shapes single cell spatial preference in the primary auditory cortex during active navigation. We further showcase other implementations of SIT which enable the study of the neural processes and behaviors underlying active perception in ethologically relevant scenes.

Orbitofrontal cortex conveys stimulus and task information to the auditory cortex

Auditory cortical neurons modify their response profiles in response to numerous external factors. During task performance, changes in primary auditory cortex (A1) responses are thought to be driven by top-down inputs from the orbitofrontal cortex (OFC), which may lead to response modification on a trial-by-trial basis. While OFC neurons respond to auditory stimuli and project to A1, the function of OFC projections to A1 during auditory tasks is unknown. Here, we observed the activity of putative OFC terminals in A1 in mice by using invivo two-photon calcium imaging of OFC terminals under passive conditions and during a tone detection task. We found that behavioral activity modulates but is not necessary to evoke OFC terminal responses in A1. OFC terminals in A1 form distinct populations that exclusively respond to either the tone, reward, or error. Using tones against a background of white noise, we found that OFC terminal activity was modulated by the signal-to-noise ratio (SNR) in both the passive and active conditions and that OFC terminal activity varied with SNR, and thus task difficulty in the active condition. Therefore, OFC projections in A1 are heterogeneous in their modulation of auditory encoding and likely contribute to auditory processing under various auditory conditions.