Dynamics and Hierarchical Encoding of Non-compact Acoustic Categories in Auditory and Frontal Cortex

Spatially clustered neurons in the bat midbrain encode vocalization categories

Rapid categorization of vocalizations enables adaptive behavior across species. While categorical perception is thought to arise in the neocortex, humans and animals could benefit from a functional organization tailored to ethologically relevant sound processing earlier in the auditory pathway. Here we developed two-photon calcium imaging in the awake echolocating bat (Eptesicus fuscus) to study the representation of vocalizations in the inferior colliculus, which is as few as two synapses from the inner ear. Echolocating bats rely on frequency-sweep-based vocalizations for social communication and navigation. Auditory playback experiments demonstrated that individual neurons responded selectively to social or navigation calls, enabling robust population-level decoding across categories. When social calls were morphed into navigation calls in equidistant step-wise increments, individual neurons showed switch-like properties and population-level response patterns sharply transitioned at the category boundary. Strikingly, category-selective neurons formed spatial clusters, independent of tonotopy within the dorsal cortex of the inferior colliculus. These findings support a revised view of categorical processing in which specified channels for ethologically relevant sounds are spatially segregated early in the auditory hierarchy, enabling rapid subcortical organization into categorical primitives.

Expectation-driven sensory adaptations support enhanced acuity during categorical perception

Expectations can influence perception in seemingly contradictory ways, either by directing attention to expected stimuli and enhancing perceptual acuity or by stabilizing perception and diminishing acuity within expected stimulus categories. The neural mechanisms supporting these dual roles of expectation are not well understood. Here, we trained European starlings to classify ambiguous song syllables in both expected and unexpected acoustic contexts. We show that birds employ probabilistic, Bayesian integration to classify syllables, leveraging their expectations to stabilize their perceptual behavior. However, auditory sensory neural populations do not reflect this integration. Instead, expectation enhances the acuity of auditory sensory neurons in high-probability regions of the stimulus space. This modulation diverges from patterns typically observed in motor areas, where Bayesian integration of sensory inputs and expectations predominates. Our results suggest that peripheral sensory systems use expectation to improve sensory representations and maintain high-fidelity representations of the world, allowing downstream circuits to flexibly integrate this information with expectations to drive behavior.

Temporal-coherence induces binding of responses to sound sequences in ferret auditory cortex

Binding the attributes of a sensory source is necessary to perceive it as a unified entity within its surrounding scene as in the cocktail party problem in auditory perception. It is postulated that coherent temporal modulation of a source's features binds them and enhances their perception. This study seeks evidence for rapid binding among coherently responsive single-neurons in ferret auditory cortex. In one experiment, ferrets attended to a sequence of noise bursts while we contrasted responses to simultaneous synchronized versus alternating tone sequences. We found that the contrast between synchronized (enhanced) and desynchronized (suppressed) responses rapidly increased, thus promoting their segregation. In another experiment, a sequence of an irregularly repeated multi-tone complex was embedded in a background of randomly dispersed tones. Single-unit and functional ultrasound imaging of responses to the temporally coherent tones of the complex became rapidly enhanced against the background responses, demonstrating the role of temporal-coherence in binding and segregation.

Individual-specific strategies inform category learning

Categorization is an essential task for sensory perception. Individuals learn category labels using a variety of strategies to ensure that sensory signals, such as sounds or images, can be assigned to proper categories. Categories are often learned on the basis of extreme examples, and the boundary between categories can differ among individuals. The trajectories for learning also differ among individuals, as different individuals rely on different strategies, such as repeating or alternating choices. However, little is understood about the relationship between individual learning trajectories and learned categorization. To study this relationship, we trained mice to categorize auditory stimuli into two categories using a two-alternative forced choice task. Because the mice took several weeks to learn the task, we were able to quantify the time course of individual strategies and how they relate to how mice categorize stimuli around the categorization boundary. Different mice exhibited different trajectories while learning the task. Mice displayed preferences for a specific category, manifested by a choice bias in their responses, but this bias drifted with learning. We found that this drift in choice bias correlated with variability in the category boundary for sounds with ambiguous category membership. Next, we asked how stimulus-independent, individual-specific strategies informed learning. We found that the tendency to repeat choices, which is a form of perseveration, contributed to long-term learning. These results indicate that long-term trends in individual strategies during category learning affect learned category boundaries.

Individual-specific strategies inform category learning

Categorization is an essential task for sensory perception. Individuals learn category labels using a variety of strategies to ensure that sensory signals, such as sounds or images, can be assigned to proper categories. Categories are often learned on the basis of extreme examples, and the boundary between categories can differ among individuals. The trajectories for learning also differ among individuals, as different individuals rely on different strategies, such as repeating or alternating choices. However, little is understood about the relationship between individual learning trajectories and learned categorization. To study this relationship, we trained mice to categorize auditory stimuli into two categories using a two-alternative forced choice task. Because the mice took several weeks to learn the task, we were able to quantify the time course of individual strategies and how they relate to how mice categorize stimuli around the categorization boundary. Different mice exhibited different trajectories while learning the task. Mice displayed preferences for a specific category, manifested by a choice bias in their responses, but this bias drifted with learning. We found that this drift in choice bias correlated with variability in the category boundary for sounds with ambiguous category membership. Next, we asked how stimulus-independent, individual-specific strategies informed learning. We found that the tendency to repeat choices, which is a form of perseveration, contributed to long-term learning. These results indicate that long-term trends in individual strategies during category learning affect learned category boundaries.

Temporal coherence shapes cortical responses to speech mixtures in a ferret cocktail party

Perceptual segregation of complex sounds such as speech and music simultaneously emanating from multiple sources is a remarkable ability that is common in humans and other animals alike. Unlike animal physiological experiments with simplified sounds or human investigations with spatially broad imaging techniques, this study combines insights from animal single-unit recordings with segregation of speech-like sound mixtures. Ferrets are trained to attend to a female voice and detect a target word, both in presence and absence of a concurrent equally salient male voice. Recordings are made in primary and secondary auditory cortical fields, and in frontal cortex. During task performance, representation of the female words becomes enhanced relative to the male in all, but especially in higher cortical regions. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings underscore the role of the principle of temporal coherence whereby attention to a target voice binds together all neural responses coherently modulated with the target, thus ultimately forming and extracting a common auditory stream.

Systematic changes in neural selectivity reflect the acquired salience of category-diagnostic dimensions

Humans and other animals develop remarkable behavioral specializations for identifying, differentiating, and acting on classes of ecologically important signals. Ultimately, this expertise is flexible enough to support diverse perceptual judgments: a voice, for example, simultaneously conveys what a talker says as well as myriad cues about her identity and state. Mature perception across complex signals thus involves both discovering and learning regularities that best inform diverse perceptual judgments, and weighting this information flexibly as task demands change. Here, we test whether this flexibility may involve endogenous attentional gain to task-relevant dimensions. We use two prospective auditory category learning tasks to relate a complex, entirely novel soundscape to four classes of "alien identity" and two classes of "alien size." Identity, but not size, categorization requires discovery and learning of patterned acoustic input situated in one of two simultaneous, frequency-delimited bands. This allows us to capitalize on the coarsely segregated frequency-band-specific channels of auditory tonotopic maps using fMRI to ask whether category-relevant perceptual information is prioritized relative to simultaneous, uninformative information. Among participants expert at alien identity categorization, we observe prioritization of the diagnostic frequency band that persists even when the diagnostic information becomes irrelevant in the size categorization task. Tellingly, the neural selectivity evoked implicitly in categorization aligns closely with activation driven by explicit, sustained selective attention to other sounds presented in the same frequency band. Additionally, we observe fingerprints of individual differences in the learning trajectories taken to achieve expert-level categorization in patterns of neural activity associated with the diagnostic dimension. In all, this indicates that acquiring categories can drive the emergence of acquired attentional salience to dimensions of acoustic input.

The Neural and Computational Architecture of Feedback Dynamics in Mouse Cortex during Stimulus Report

Conscious reportability of visual input is associated with a bimodal neural response in the primary visual cortex (V1): an early-latency response coupled to stimulus features and a late-latency response coupled to stimulus report or detection. This late wave of activity, central to major theories of consciousness, is thought to be driven by the prefrontal cortex (PFC), responsible for "igniting" it. Here we analyzed two electrophysiological studies in mice performing different stimulus detection tasks and characterized neural activity profiles in three key cortical regions: V1, posterior parietal cortex (PPC), and PFC. We then developed a minimal network model, constrained by known connectivity between these regions, reproducing the spatiotemporal propagation of visual- and report-related activity. Remarkably, while PFC was indeed necessary to generate report-related activity in V1, this occurred only through the mediation of PPC. PPC, and not PFC, had the final veto in enabling the report-related late wave of V1 activity.

Ferret as a model system for studying the anatomy and function of the prefrontal cortex: A systematic review

There is a lack of consensus on anatomical nomenclature, standards of documentation, and functional equivalence of the frontal cortex between species. There remains a major gap between human prefrontal function and interpretation of findings in the mouse brain that appears to lack several key prefrontal areas involved in cognition and psychiatric illnesses. The ferret is an emerging model organism that has gained traction as an intermediate model species for the study of top-down cognitive control and other higher-order brain functions. However, this research has yet to benefit from synthesis. Here, we provide a summary of all published research pertaining to the frontal and/or prefrontal cortex of the ferret across research scales. The targeted location within the ferret brain is summarized visually for each experiment, and the anatomical terminology used at time of publishing is compared to what would be the appropriate term to use presently. By doing so, we hope to improve clarity in the interpretation of both previous and future publications on the comparative study of frontal cortex.

Temporal-Coherence Induces Binding of Responses to Sound Sequences in Ferret Auditory Cortex

Binding the attributes of a sensory source is necessary to perceive it as a unified entity, one that can be attended to and extracted from its surrounding scene. In auditory perception, this is the essence of the cocktail party problem in which a listener segregates one speaker from a mixture of voices, or a musical stream from simultaneous others. It is postulated that coherence of the temporal modulations of a source's features is necessary to bind them. The focus of this study is on the role of temporal-coherence in binding and segregation, and specifically as evidenced by the neural correlates of rapid plasticity that enhance cortical responses among synchronized neurons, while suppressing them among asynchronized ones. In a first experiment, we find that attention to a sound sequence rapidly binds it to other coherent sequences while suppressing nearby incoherent sequences, thus enhancing the contrast between the two groups. In a second experiment, a sequence of synchronized multi-tone complexes, embedded in a cloud of randomly dispersed background of desynchronized tones, perceptually and neurally pops-out after a fraction of a second highlighting the binding among its coherent tones against the incoherent background. These findings demonstrate the role of temporal-coherence in binding and segregation.

Auditory discrimination learning differentially modulates neural representation in auditory cortex subregions and inter-areal connectivity

Changes in sound-evoked responses in the auditory cortex (ACtx) occur during learning, but how learning alters neural responses in different ACtx subregions and changes their interactions is unclear. To address these questions, we developed an automated training and widefield imaging system to longitudinally track the neural activity of all mouse ACtx subregions during a tone discrimination task. We find that responses in primary ACtx are highly informative of learned stimuli and behavioral outcomes throughout training. In contrast, representations of behavioral outcomes in the dorsal posterior auditory field, learned stimuli in the dorsal anterior auditory field, and inter-regional correlations between primary and higher-order areas are enhanced with training. Moreover, ACtx response changes vary between stimuli, and such differences display lag synchronization with the learning rate. These results indicate that learning alters functional connections between ACtx subregions, inducing region-specific modulations by propagating behavioral information from primary to higher-order areas.

Topography and Ensemble Activity in the Auditory Cortex of a Mouse Model of Fragile X Syndrome

Autism spectrum disorder (ASD) is often associated with social communication impairments and specific sound processing deficits, for example, problems in following speech in noisy environments. To investigate underlying neuronal processing defects located in the auditory cortex (AC), we performed two-photon Ca2+ imaging in FMR1 (fragile X messenger ribonucleoprotein 1) knock-out (KO) mice, a model for fragile X syndrome (FXS), the most common cause of hereditary ASD in humans. For primary AC (A1) and the anterior auditory field (AAF), topographic frequency representation was less ordered compared with control animals. We additionally analyzed ensemble AC activity in response to various sounds and found subfield-specific differences. In A1, ensemble correlations were lower in general, while in secondary AC (A2), correlations were higher in response to complex sounds, but not to pure tones. Furthermore, sound specificity of ensemble activity was decreased in AAF. Repeating these experiments 1 week later revealed no major differences regarding representational drift. Nevertheless, we found subfield- and genotype-specific changes in ensemble correlation values between the two times points, hinting at alterations in network stability in FMR1 KO mice. These detailed insights into AC network activity and topography in FMR1 KO mice add to the understanding of auditory processing defects in FXS.

Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement

Grouping sets of sounds into relevant categories is an important cognitive ability that enables the association of stimuli with appropriate goal-directed behavioral responses. In perceptual tasks, the primary auditory cortex (A1) assumes a prominent role by concurrently encoding both sound sensory features and task-related variables. Here, we sought to explore the role of A1 in the initiation of sound categorization, shedding light on its involvement in this cognitive process. We trained ferrets to discriminate click trains of different rates in a Go/No-Go delayed categorization task and recorded neural activity during both active behavior and passive exposure to the same sounds. Purely categorical response components were extracted and analyzed separately from sensory responses to reveal their contributions to the overall population response throughout the trials. We found that categorical activity emerged during sound presentation in the population average and was present in both active behavioral and passive states. However, upon task engagement, categorical responses to the No-Go category became suppressed in the population code, leading to an asymmetrical representation of the Go stimuli relative to the No-Go sounds and pre-stimulus baseline. The population code underwent an abrupt change at stimulus offset, with sustained responses after the Go sounds during the delay period. Notably, the categorical responses observed during the stimulus period exhibited a significant correlation with those extracted from the delay epoch, suggesting an early involvement of A1 in stimulus categorization.

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.

Organization of orbitofrontal-auditory pathways in the Mongolian gerbil

Sound perception is highly malleable, rapidly adjusting to the acoustic environment and behavioral demands. This flexibility is the result of ongoing changes in auditory cortical activity driven by fluctuations in attention, arousal, or prior expectations. Recent work suggests that the orbitofrontal cortex (OFC) may mediate some of these rapid changes, but the anatomical connections between the OFC and the auditory system are not well characterized. Here, we used virally mediated fluorescent tracers to map the projection from OFC to the auditory midbrain, thalamus, and cortex in a classic animal model for auditory research, the Mongolian gerbil (Meriones unguiculatus). We observed no connectivity between the OFC and the auditory midbrain, and an extremely sparse connection between the dorsolateral OFC and higher order auditory thalamic regions. In contrast, we observed a robust connection between the ventral and medial subdivisions of the OFC and the auditory cortex, with a clear bias for secondary auditory cortical regions. OFC axon terminals were found in all auditory cortical lamina but were significantly more concentrated in the infragranular layers. Tissue-clearing and lightsheet microscopy further revealed that auditory cortical-projecting OFC neurons send extensive axon collaterals throughout the brain, targeting both sensory and non-sensory regions involved in learning, decision-making, and memory. These findings provide a more detailed map of orbitofrontal-auditory connections and shed light on the possible role of the OFC in supporting auditory cognition.

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.

Distinct topographic organization and network activity patterns of corticocollicular neurons within layer 5 auditory cortex

The auditory cortex (AC) modulates the activity of upstream pathways in the auditory brainstem via descending (corticofugal) projections. This feedback system plays an important role in the plasticity of the auditory system by shaping response properties of neurons in many subcortical nuclei. The majority of layer (L) 5 corticofugal neurons project to the inferior colliculus (IC). This corticocollicular (CC) pathway is involved in processing of complex sounds, auditory-related learning, and defense behavior. Partly due to their location in deep cortical layers, CC neuron population activity patterns within neuronal AC ensembles remain poorly understood. We employed two-photon imaging to record the activity of hundreds of L5 neurons in anesthetized as well as awake animals. CC neurons are broader tuned than other L5 pyramidal neurons and display weaker topographic order in core AC subfields. Network activity analyses revealed stronger clusters of CC neurons compared to non-CC neurons, which respond more reliable and integrate information over larger distances. However, results obtained from secondary auditory cortex (A2) differed considerably. Here CC neurons displayed similar or higher topography, depending on the subset of neurons analyzed. Furthermore, specifically in A2, CC activity clusters formed in response to complex sounds were spatially more restricted compared to other L5 neurons. Our findings indicate distinct network mechanism of CC neurons in analyzing sound properties with pronounced subfield differences, demonstrating that the topography of sound-evoked responses within AC is neuron-type dependent.

Spatially clustered neurons encode vocalization categories in the bat midbrain

Rapid categorization of vocalizations enables adaptive behavior across species. While categorical perception is thought to arise in the neocortex, humans and other animals could benefit from functional organization of ethologically-relevant sounds at earlier stages in the auditory hierarchy. Here, we developed two-photon calcium imaging in the awake echolocating bat (Eptesicus fuscus) to study encoding of sound meaning in the Inferior Colliculus, which is as few as two synapses from the inner ear. Echolocating bats produce and interpret frequency sweep-based vocalizations for social communication and navigation. Auditory playback experiments demonstrated that individual neurons responded selectively to social or navigation calls, enabling robust population-level decoding across categories. Strikingly, category-selective neurons formed spatial clusters, independent of tonotopy within the IC. These findings support a revised view of categorical processing in which specified channels for ethologically-relevant sounds are spatially segregated early in the auditory hierarchy, enabling rapid subcortical organization of call meaning.

Categorical representation of abstract spatial magnitudes in the executive telencephalon of crows

The ability to group abstract continuous magnitudes into meaningful categories is cognitively demanding but key to intelligent behavior. To explore its neuronal mechanisms, we trained carrion crows to categorize lines of variable lengths into arbitrary "short" and "long" categories. Single-neuron activity in the nidopallium caudolaterale (NCL) of behaving crows reflected the learned length categories of visual stimuli. The length categories could be reliably decoded from neuronal population activity to predict the crows' conceptual decisions. NCL activity changed with learning when a crow was retrained with the same stimuli assigned to more categories with new boundaries ("short", "medium," and "long"). Categorical neuronal representations emerged dynamically so that sensory length information at the beginning of the trial was transformed into behaviorally relevant categorical representations shortly before the crows' decision making. Our data show malleable categorization capabilities for abstract spatial magnitudes mediated by the flexible networks of the crow NCL.

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.

Perception of color in primates: A conceptual color neurons hypothesis

Perception of color by humans and other primates is a complex problem, studied by neurophysiology, psychophysiology, psycholinguistics, and even philosophy. Being mostly trichromats, simian primates have three types of opsin proteins, expressed in cone neurons in the eye, which allow for the sensing of color as the physical wavelength of light. Further, in neural networks of the retina, the coding principle changes from three types of sensor proteins to two opponent channels: activity of one type of neuron encode the evolutionarily ancient blue-yellow axis of color stimuli, and another more recent evolutionary channel, encoding the axis of red-green color stimuli. Both color channels are distinctive in neural organization at all levels from the eye to the neocortex, where it is thought that the perception of color (as philosophical qualia) emerges from the activity of some neuron ensembles. Here, using data from neurophysiology as a starting point, we propose a hypothesis on how the perception of color can be encoded in the activity of certain neurons in the neocortex. These conceptual neurons, herein referred to as 'color neurons', code only the hue of the color of visual stimulus, similar to place cells and number neurons, already described in primate brains. A case study with preliminary, but direct, evidence for existing conceptual color neurons in the human brain was published in 2008. We predict that the upcoming studies in non-human primates will be more extensive and provide a more detailed description of conceptual color neurons.

Vocalization categorization behavior explained by a feature-based auditory categorization model

Vocal animals produce multiple categories of calls with high between- and within-subject variability, over which listeners must generalize to accomplish call categorization. The behavioral strategies and neural mechanisms that support this ability to generalize are largely unexplored. We previously proposed a theoretical model that accomplished call categorization by detecting features of intermediate complexity that best contrasted each call category from all other categories. We further demonstrated that some neural responses in the primary auditory cortex were consistent with such a model. Here, we asked whether a feature-based model could predict call categorization behavior. We trained both the model and guinea pigs (GPs) on call categorization tasks using natural calls. We then tested categorization by the model and GPs using temporally and spectrally altered calls. Both the model and GPs were surprisingly resilient to temporal manipulations, but sensitive to moderate frequency shifts. Critically, the model predicted about 50% of the variance in GP behavior. By adopting different model training strategies and examining features that contributed to solving specific tasks, we could gain insight into possible strategies used by animals to categorize calls. Our results validate a model that uses the detection of intermediate-complexity contrastive features to accomplish call categorization.

An academic survey on theoretical foundations, common assumptions and the current state of consciousness science

We report the results of an academic survey into the theoretical and methodological foundations, common assumptions, and the current state of the field of consciousness research. The survey consisted of 22 questions and was distributed on two different occasions of the annual meeting of the Association of the Scientific Study of Consciousness (2018 and 2019). We examined responses from 166 consciousness researchers with different backgrounds (e.g. philosophy, neuroscience, psychology, and computer science) and at various stages of their careers (e.g. junior/senior faculty and graduate/undergraduate students). The results reveal that there remains considerable discussion and debate between the surveyed researchers about the definition of consciousness and the way it should be studied. To highlight a few observations, a majority of respondents believe that machines could have consciousness, that consciousness is a gradual phenomenon in the animal kingdom, and that unconscious processing is extensive, encompassing both low-level and high-level cognitive functions. Further, we show which theories of consciousness are currently considered most promising by respondents and how supposedly different theories cluster together, which dependent measures are considered best to index the presence or absence of consciousness, and which neural measures are thought to be the most likely signatures of consciousness. These findings provide us with a snapshot of the current views of researchers in the field and may therefore help prioritize research and theoretical approaches to foster progress.

Sequential transmission of task-relevant information in cortical neuronal networks

Cortical processing of task-relevant information enables recognition of behaviorally meaningful sensory events. It is unclear how task-related information is represented within cortical networks by the activity of individual neurons and their functional interactions. Here, we use two-photon imaging to record neuronal activity from the primary auditory cortex of mice during a pure-tone discrimination task. We find that a subset of neurons transiently encode sensory information used to inform behavioral choice. Using Granger causality analysis, we show that these neurons form functional networks in which information transmits sequentially. Network structures differ for target versus non-target tones, encode behavioral choice, and differ between correct versus incorrect behavioral choices. Correct behavioral choices are associated with shorter communication timescales, larger functional correlations, and greater information redundancy. In summary, specialized neurons in primary auditory cortex integrate task-related information and form functional networks whose structures encode both sensory input and behavioral choice.

Francis et al. find that, as mice perform an auditory discrimination task, cortical neurons form functional networks in which task-relevant information transmits sequentially between neurons. Network structures encode behavioral choice, and correct behavioral choices are associated with shorter communication timescales, larger functional correlations, and greater information redundancy between neurons.

What can we learn from inactivation studies? Lessons from auditory cortex

Inactivation experiments in auditory cortex (AC) produce widely varying results that complicate interpretations regarding the precise role of AC in auditory perception and ensuing behaviour. The advent of optogenetic methods in neuroscience offers previously unachievable insight into the mechanisms transforming brain activity into behaviour. With a view to aiding the design and interpretation of future studies in and outside AC, here we discuss the methodological challenges faced in manipulating neural activity. While considering AC’s role in auditory behaviour through the prism of inactivation experiments, we consider the factors that confound the interpretation of the effects of inactivation on behaviour, including the species, the type of inactivation, the behavioural task employed, and the exact location of the inactivation.

Wide variation in the outcome of auditory cortex inactivation has been an impediment to clear conclusions regarding the roles of the auditory cortex in behaviour.

Inactivation methods differ in their efficacy and specificity. The likelihood of observing a behavioural deficit is additionally influenced by factors such as the species being used, task design and reward.

A synthesis of previous results suggests that auditory cortex involvement is critical for tasks that require integrating across multiple stimulus features, and less likely to be critical for simple feature discriminations.

New methods of neural silencing provide opportunities for spatially and temporally precise manipulation of activity, allowing perturbation of individual subfields and specific circuits.

Mapping between sound, brain and behaviour: four-level framework for understanding rhythm processing in humans and non-human primates

Humans perceive and spontaneously move to one or several levels of periodic pulses (a meter, for short) when listening to musical rhythm, even when the sensory input does not provide prominent periodic cues to their temporal location. Here, we review a multi-levelled framework to understanding how external rhythmic inputs are mapped onto internally represented metric pulses. This mapping is studied using an approach to quantify and directly compare representations of metric pulses in signals corresponding to sensory inputs, neural activity and behaviour (typically body movement). Based on this approach, recent empirical evidence can be drawn together into a conceptual framework that unpacks the phenomenon of meter into four levels. Each level highlights specific functional processes that critically enable and shape the mapping from sensory input to internal meter. We discuss the nature, constraints and neural substrates of these processes, starting with fundamental mechanisms investigated in macaque monkeys that enable basic forms of mapping between simple rhythmic stimuli and internally represented metric pulse. We propose that human evolution has gradually built a robust and flexible system upon these fundamental processes, allowing more complex levels of mapping to emerge in musical behaviours. This approach opens promising avenues to understand the many facets of rhythmic behaviours across individuals and species. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'.

Source identity shapes spatial preference in primary auditory cortex during active navigation

Information about the position of sensory objects and identifying their concurrent behavioral relevance is vital to navigate the environment. In the auditory system, spatial information is computed in the brain based on the position of the sound source relative to the observer and thus assumed to be egocentric throughout the auditory pathway. This assumption is largely based on studies conducted in either anesthetized or head-fixed and passively listening animals, thus lacking self-motion and selective listening. Yet these factors are fundamental components of natural sensing¹ that may crucially impact the nature of spatial coding and sensory object representation.² How individual objects are neuronally represented during unrestricted self-motion and active sensing remains mostly unexplored. Here, we trained gerbils on a behavioral foraging paradigm that required localization and identification of sound sources during free navigation. Chronic tetrode recordings in primary auditory cortex during task performance revealed previously unreported sensory object representations. Strikingly, the egocentric angle preference of the majority of spatially sensitive neurons changed significantly depending on the task-specific identity (outcome association) of the sound source. Spatial tuning also exhibited large temporal complexity. Moreover, we encountered egocentrically untuned neurons whose response magnitude differed between source identities. Using a neural network decoder, we show that, together, these neuronal response ensembles provide spatiotemporally co-existent information about both the egocentric location and the identity of individual sensory objects during self-motion, revealing a novel cortical computation principle for naturalistic sensing.

When and How Does the Auditory Cortex Influence Subcortical Auditory Structures? New Insights About the Roles of Descending Cortical Projections

For decades, the corticofugal descending projections have been anatomically well described but their functional role remains a puzzling question. In this review, we will first describe the contributions of neuronal networks in representing communication sounds in various types of degraded acoustic conditions from the cochlear nucleus to the primary and secondary auditory cortex. In such situations, the discrimination abilities of collicular and thalamic neurons are clearly better than those of cortical neurons although the latter remain very little affected by degraded acoustic conditions. Second, we will report the functional effects resulting from activating or inactivating corticofugal projections on functional properties of subcortical neurons. In general, modest effects have been observed in anesthetized and in awake, passively listening, animals. In contrast, in behavioral tasks including challenging conditions, behavioral performance was severely reduced by removing or transiently silencing the corticofugal descending projections. This suggests that the discriminative abilities of subcortical neurons may be sufficient in many acoustic situations. It is only in particularly challenging situations, either due to the task difficulties and/or to the degraded acoustic conditions that the corticofugal descending connections bring additional abilities. Here, we propose that it is both the top-down influences from the prefrontal cortex, and those from the neuromodulatory systems, which allow the cortical descending projections to impact behavioral performance in reshaping the functional circuitry of subcortical structures. We aim at proposing potential scenarios to explain how, and under which circumstances, these projections impact on subcortical processing and on behavioral responses.

Auditory decisions in the supplementary motor area

In human speech and communication across various species, recognizing and categorizing sounds is fundamental for the selection of appropriate behaviors. However, how does the brain decide which action to perform based on sounds? We explored whether the supplementary motor area (SMA), responsible for linking sensory information to motor programs, also accounts for auditory-driven decision making. To this end, we trained two rhesus monkeys to discriminate between numerous naturalistic sounds and words learned as target (T) or non-target (nT) categories. We found that the SMA at single and population neuronal levels perform decision-related computations that transition from auditory to movement representations in this task. Moreover, we demonstrated that the neural population is organized orthogonally during the auditory and the movement periods, implying that the SMA performs different computations. In conclusion, our results suggest that the SMA integrates acoustic information in order to form categorical signals that drive behavior.

Top-Down Inference in the Auditory System: Potential Roles for Corticofugal Projections

It has become widely accepted that humans use contextual information to infer the meaning of ambiguous acoustic signals. In speech, for example, high-level semantic, syntactic, or lexical information shape our understanding of a phoneme buried in noise. Most current theories to explain this phenomenon rely on hierarchical predictive coding models involving a set of Bayesian priors emanating from high-level brain regions (e.g., prefrontal cortex) that are used to influence processing at lower-levels of the cortical sensory hierarchy (e.g., auditory cortex). As such, virtually all proposed models to explain top-down facilitation are focused on intracortical connections, and consequently, subcortical nuclei have scarcely been discussed in this context. However, subcortical auditory nuclei receive massive, heterogeneous, and cascading descending projections at every level of the sensory hierarchy, and activation of these systems has been shown to improve speech recognition. It is not yet clear whether or how top-down modulation to resolve ambiguous sounds calls upon these corticofugal projections. Here, we review the literature on top-down modulation in the auditory system, primarily focused on humans and cortical imaging/recording methods, and attempt to relate these findings to a growing animal literature, which has primarily been focused on corticofugal projections. We argue that corticofugal pathways contain the requisite circuitry to implement predictive coding mechanisms to facilitate perception of complex sounds and that top-down modulation at early (i.e., subcortical) stages of processing complement modulation at later (i.e., cortical) stages of processing. Finally, we suggest experimental approaches for future studies on this topic.

Correlates of Auditory Decision-Making in Prefrontal, Auditory, and Basal Lateral Amygdala Cortical Areas

Spatial selective listening and auditory choice underlie important processes including attending to a speaker at a cocktail party and knowing how (or whether) to respond. To examine task encoding and the relative timing of potential neural substrates underlying these behaviors, we developed a spatial selective detection paradigm for monkeys, and recorded activity in primary auditory cortex (AC), dorsolateral prefrontal cortex (dlPFC), and the basolateral amygdala (BLA). A comparison of neural responses among these three areas showed that, as expected, AC encoded the side of the cue and target characteristics before dlPFC and BLA. Interestingly, AC also encoded the choice of the monkey before dlPFC and around the time of BLA. Generally, BLA showed weak responses to all task features except the choice. Decoding analyses suggested that errors followed from a failure to encode the target stimulus in both AC and dlPFC, but again, these differences arose earlier in AC. The similarities between AC and dlPFC responses were abolished during passive sensory stimulation with identical trial conditions, suggesting that the robust sensory encoding in dlPFC is contextually gated. Thus, counter to a strictly PFC-driven decision process, in this spatial selective listening task AC neural activity represents the sensory and decision information before dlPFC. Unlike in the visual domain, in this auditory task, the BLA does not appear to be robustly involved in selective spatial processing.SIGNIFICANCE STATEMENT We examined neural correlates of an auditory spatial selective listening task by recording single-neuron activity in behaving monkeys from the amygdala, dorsolateral prefrontal cortex, and auditory cortex. We found that auditory cortex coded spatial cues and choice-related activity before dorsolateral prefrontal cortex or the amygdala. Auditory cortex also had robust delay period activity. Therefore, we found that auditory cortex could support the neural computations that underlie the behavioral processes in the task.

Categorical Auditory Working Memory in Crows

The ability to group sensory data into behaviorally meaningful classes and to maintain these perceptual categories active in working memory is key to intelligent behavior. Here, we show that carrion crows, highly vocal and cognitively advanced corvid songbirds, possess categorical auditory working memory. The crows were trained in a delayed match-to-category task that required them to flexibly match remembered sounds based on the upward or downward shift of the sounds' frequency modulation. After training, the crows instantaneously classified novel sounds into the correct auditory categories. The crows showed sharp category boundaries as a function of the relative frequency interval of the modulation. In addition, the crows generalized frequency-modulated sounds within a category and correctly classified novel sounds kept in working memory irrespective of other acoustic features of the sound. This suggests that crows can form and actively memorize auditory perceptual categories in the service of cognitive control of their goal-directed behaviors.

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Crows performed a delayed match-to-category task with frequency modulated sounds

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Crows classified novel sounds into upward or downward modulated sound categories

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Crows showed sharp category boundaries and within-category generalization

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Crows can actively memorize auditory perceptual categories for cognitive control

Computational and neurophysiological principles underlying auditory perceptual decisions

A fundamental scientific goal in auditory neuroscience is identifying what mechanisms allow the brain to transform an unlabeled mixture of auditory stimuli into distinct perceptual representations. This transformation is accomplished by a complex interaction of multiple neurocomputational processes, including Gestalt grouping mechanisms, categorization, attention, and perceptual decision-making. Despite a great deal of scientific energy devoted to understanding these principles of hearing, we still do not understand either how auditory perception arises from neural activity or the causal relationship between neural activity and auditory perception. Here, we review the contributions of cortical and subcortical regions to auditory perceptual decisions with an emphasis on those studies that simultaneously measure behavior and neural activity. We also put forth challenges to the field that must be faced if we are to further our understanding of the relationship between neural activity and auditory perception.