Coding principles of the canonical cortical microcircuit in the avian brain

Social and auditory experience shapes forebrain responsiveness in zebra finches before the sensitive period of vocal learning

Early-life experiences with signals used in communication are instrumental in shaping an animal's social interactions. In songbirds, which use vocalizations for guiding social interactions and mate choice, recent studies show that sensory effects on development occur earlier than previously expected, even in embryos and nestlings. Here, we explored the neural dynamics underlying experience-dependent song categorization in young birds prior to the traditionally studied sensitive period of vocal learning that begins around 3 weeks post-hatch. We raised zebra finches either with their biological parents, cross-fostered by Bengalese finches beginning at embryonic day 9, or with only the non-singing mother from 2 days post-hatch. Then, 1-5 days after fledging, we conducted behavioral experiments and extracellular recordings in the auditory forebrain to test responses to zebra finch and Bengalese finch songs. Auditory forebrain neurons in cross-fostered and isolated birds showed increases in firing rate and decreases in responsiveness and selectivity. In cross-fostered birds, decreases in responsiveness and selectivity relative to white noise were specific to conspecific song stimuli, which paralleled behavioral attentiveness to conspecific songs in those same birds. This study shows that auditory and social experience can already impact song 'type' processing in the brains of nestlings, and that brain changes at this age can portend the effects of natal experience in adults.

Digital Twin Studies for Reverse Engineering the Origins of Visual Intelligence

What are the core learning algorithms in brains? Nativists propose that intelligence emerges from innate domain-specific knowledge systems, whereas empiricists propose that intelligence emerges from domain-general systems that learn domain-specific knowledge from experience. We address this debate by reviewing digital twin studies designed to reverse engineer the learning algorithms in newborn brains. In digital twin studies, newborn animals and artificial agents are raised in the same environments and tested with the same tasks, permitting direct comparison of their learning abilities. Supporting empiricism, digital twin studies show that domain-general algorithms learn animal-like object perception when trained on the first-person visual experiences of newborn animals. Supporting nativism, digital twin studies show that domain-general algorithms produce innate domain-specific knowledge when trained on prenatal experiences (retinal waves). We argue that learning across humans, animals, and machines can be explained by a universal principle, which we call space-time fitting. Space-time fitting explains both empiricist and nativist phenomena, providing a unified framework for understanding the origins of intelligence.

Cortical Processing of Conspecific Vocalizations in Zebra Finches Depends on the Early Acoustical Environment

Sensory experience during development has lasting effects on perception and neural processing. Exposing animals to artificial stimuli early in life influences the tuning and functional organization of the auditory cortex, but less is known about how the rich acoustical environments experienced by vocal communicators affect the processing of complex vocalizations. Here, we show that in zebra finches (Taeniopygia guttata), a colonial-breeding songbird species, exposure to a naturalistic social-acoustical environment during development has a profound impact on cortical-level auditory responses to conspecific song. Compared to birds raised by pairs in acoustic isolation, birds raised in a breeding colony had higher average firing rates, selectivity, and discriminability, especially in the narrow-spiking, putatively inhibitory neurons of a higher-order auditory area, the caudomedial nidopallium (NCM). Neurons in colony-reared birds were also less correlated in their tuning and more efficient at encoding the spectrotemporal structure of conspecific song. These results suggest that the auditory cortex adapts to noisy, complex acoustical environments by strengthening inhibitory circuitry, functionally decoupling excitatory neurons while maintaining overall excitatory-inhibitory balance.

Acute Aromatase Inhibition Impairs Neural and Behavioral Auditory Scene Analysis in Zebra Finches

Auditory perception can be significantly disrupted by noise. To discriminate sounds from noise, auditory scene analysis (ASA) extracts the functionally relevant sounds from acoustic input. The zebra finch communicates in noisy environments. Neurons in their secondary auditory pallial cortex (caudomedial nidopallium, NCM) can encode song from background chorus, or scenes, and this capacity may aid behavioral ASA. Furthermore, song processing is modulated by the rapid synthesis of neuroestrogens when hearing conspecific song. To examine whether neuroestrogens support neural and behavioral ASA in both sexes, we retrodialyzed fadrozole (aromatase inhibitor, FAD) and recorded in vivo awake extracellular NCM responses to songs and scenes. We found that FAD affected neural encoding of songs by decreasing responsiveness and timing reliability in inhibitory (narrow-spiking), but not in excitatory (broad-spiking) neurons. Congruently, FAD decreased neural encoding of songs in scenes for both cell types, particularly in females. Behaviorally, we trained birds using operant conditioning and tested their ability to detect songs in scenes after administering FAD orally or injected bilaterally into NCM. Oral FAD increased response bias and decreased correct rejections in females, but not in males. FAD in NCM did not affect performance. Thus, FAD in the NCM impaired neuronal ASA but that did not lead to behavioral disruption suggesting the existence of resilience or compensatory responses. Moreover, impaired performance after systemic FAD suggests involvement of other aromatase-rich networks outside the auditory pathway in ASA. This work highlights how transient estrogen synthesis disruption can modulate higher-order processing in an animal model of vocal communication.

The Development of Object Recognition Requires Experience with the Surface Features of Objects

What role does visual experience play in the development of object recognition? Prior controlled-rearing studies suggest that newborn animals require slow and smooth visual experiences to develop object recognition. Here, we examined whether the development of object recognition also requires experience with the surface features of objects. We raised newborn chicks in automated controlled-rearing chambers that contained a single virtual object, then tested their ability to recognize that object from familiar and novel viewpoints. When chicks were reared with an object that had surface features, the chicks developed view-invariant object recognition. In contrast, when chicks were reared with a line drawing of an object, the chicks failed to develop object recognition. The chicks reared with line drawings performed at chance level, despite acquiring over 100 h of visual experience with the object. These results indicate that the development of object recognition requires experience with the surface features of objects.

Convergent Circuit Computation for Categorization in the Brains of Primates and Songbirds

Categorization is crucial for behavioral flexibility because it enables animals to group stimuli into meaningful classes that can easily be generalized to new circumstances. A most abstract quantitative category is set size, the number of elements in a set. This review explores how categorical number representations are realized by the operations of excitatory and inhibitory neurons in associative telencephalic microcircuits in primates and songbirds. Despite the independent evolution of the primate prefrontal cortex and the avian nidopallium caudolaterale, the neuronal computations of these associative pallial circuits show surprising correspondence. Comparing cellular functions in distantly related taxa can inform about the evolutionary principles of circuit computations for cognition in distinctly but convergently realized brain structures.

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.

Partial inactivation of songbird auditory cortex impairs both tempo and pitch discrimination

Neuronal tuning for spectral and temporal features has been studied extensively in the auditory system. In the auditory cortex, diverse combinations of spectral and temporal tuning have been found, but how specific feature tuning contributes to the perception of complex sounds remains unclear. Neurons in the avian auditory cortex are spatially organized in terms of spectral or temporal tuning widths, providing an opportunity for investigating the link between auditory tuning and perception. Here, using naturalistic conspecific vocalizations, we asked whether subregions of the auditory cortex that are tuned for broadband sounds are more important for discriminating tempo than pitch, due to the lower frequency selectivity. We found that bilateral inactivation of the broadband region impairs performance on both tempo and pitch discrimination. Our results do not support the hypothesis that the lateral, more broadband subregion of the songbird auditory cortex contributes more to processing temporal than spectral information.

Could theropod dinosaurs have evolved to a human level of intelligence?

Noting that some theropod dinosaurs had large brains, large grasping hands, and likely binocular vision, paleontologist Dale Russell suggested that a branch of these dinosaurs might have evolved to a human intelligence level, had dinosaurs not become extinct. I offer reasons why the likely pallial organization in dinosaurs would have made this improbable, based on four assumptions. First, it is assumed that achieving human intelligence requires evolving an equivalent of the about 200 functionally specialized cortical areas characteristic of humans. Second, it is assumed that dinosaurs had an avian nuclear type of pallial organization, in contrast to the mammalian cortical organization. Third, it is assumed that the interactions between the different neuron types making up an information processing unit within pallium are critical to its role in analyzing information. Finally, it is assumed that increasing axonal length between the neuron sets carrying out this operation impairs its efficacy. Based on these assumptions, I present two main reasons why dinosaur pallium might have been unable to add the equivalent of 200 efficiently functioning cortical areas. First, a nuclear pattern of pallial organization would require increasing distances between the neuron groups corresponding to the separate layers of any given mammalian cortical area, as more sets of nuclei equivalent to a cortical area are interposed between the existing sets, increasing axon length and thereby impairing processing efficiency. Second, because of its nuclear organization, dinosaur pallium could not reduce axon length by folding to bring adjacent areas closer together, as occurs in cerebral cortex.

Convergent and divergent neural circuit architectures that support acoustic communication

Vocal communication is used across extant vertebrates, is evolutionarily ancient, and been maintained, in many lineages. Here I review the neural circuit architectures that support intraspecific acoustic signaling in representative anuran, mammalian and avian species as well as two invertebrates, fruit flies and Hawaiian crickets. I focus on hindbrain motor control motifs and their ties to respiratory circuits, expression of receptors for gonadal steroids in motor, sensory, and limbic neurons as well as divergent modalities that evoke vocal responses. Hindbrain and limbic participants in acoustic communication are highly conserved, while forebrain participants have diverged between anurans and mammals, as well as songbirds and rodents. I discuss the roles of natural and sexual selection in driving speciation, as well as exaptation of circuit elements with ancestral roles in respiration, for producing sounds and driving rhythmic vocal features. Recent technical advances in whole brain fMRI across species will enable real time imaging of acoustic signaling partners, tying auditory perception to vocal production.

The effect of progressive image scrambling on neuronal responses at three stations of the pigeon tectofugal pathway

The progressive image scrambling procedure is an effective way of determining sensitivity to image features at different stages of the visual system, but it hasn’t yet been used to evaluate neuronal responses in birds. We determined the effect of progressively scrambling images of objects on the population responses of anterior entopallium (ENTO), mesopallium ventrolaterale (MVL), and posterior nidopallium intermediate pars lateralis (NIL) in pigeons. We found that MVL responses were more sensitive to both the intact objects and the highly scrambled images, whereas ENTO showed no clear preference for the different stimuli. In contrast, the NIL population response strongly preferred the original images over the scrambled images. These findings suggest that the anterior tectofugal pathway may process local shape in a hierarchical manner, and the posterior tectofugal pathway may process global shape of greater complexity. Another possibility is that the differential responses between ENTO/MVL and NIL may reflect an anterior–posterior map of varying sensitivity to spatial frequency.

Cell-type specific pallial circuits shape categorical tuning responses in the crow telencephalon

The nidopallium caudolaterale (NCL), an integration centre in the telencephalon of birds, plays a crucial role in representing and maintaining abstract categories and concepts. However, the computational principles allowing pallial microcircuits consisting of excitatory and inhibitory neurons to shape the tuning to abstract categories remain elusive. Here we identified the major pallial cell types, putative excitatory projection cells and inhibitory interneurons, by characterizing the waveforms of action potentials recorded in crows performing a cognitively demanding numerical categorization task. Both cell types showed clear differences in their capacity to encode categorical information. Nearby and functionally coupled putative projection neurons generally exhibited similar tuning, whereas putative interneurons showed mainly opposite tuning. The results favour feedforward mechanisms for the shaping of categorical tuning in microcircuits of the NCL. Our findings help to decipher the workings of pallial microcircuits in birds during complex cognition and to compare them vis-a-vis neocortical processes in mammals.

Neural recordings from the caudolateral nidopallium in crows during a numerosity task suggest there are two subsets of projection neurons and inhibitory interneurons involved in complex cognition.

Expression of oxytocin receptors in the zebra finch brain during vocal development

Like human language, song in songbirds is learned during an early sensitive period and is facilitated by motivation to seek out social interactions with vocalizing adults. Songbirds are therefore powerful models with which to understand the neural underpinnings of vocal learning. Social motivation and early social orienting are thought to be mediated by the oxytocin system; however, the developmental trajectory of oxytocin receptors in songbirds, particularly as it relates to song learning, is currently unknown. This gap in knowledge has hindered the development of songbirds as a model of the role of social orienting in vocal learning. In this study, we used quantitative PCR to measure oxytocin receptor expression during the sensitive period of song learning in zebra finches (Taeniopygia guttata). We focused on brain regions important for social motivation, attachment, song recognition, and song learning. We detected expression in these regions in both sexes from posthatch day 5 to adulthood, encompassing the entire period of song learning. In this species, only males sing; we found that in regions implicated in song learning specifically, oxytocin receptor mRNA expression was higher in males than females. These sex differences were largest during the developmental phase when males attend to and memorize tutor song, suggesting a functional role of expression in learning. Our results show that oxytocin receptors are expressed in relevant brain regions during song learning, and thus provide a foundation for developing the zebra finch as a model for understanding the mechanisms underlying the role of social motivation in vocal development.

Resurgent Na+ currents promote ultrafast spiking in projection neurons that drive fine motor control

The underlying mechanisms that promote precise spiking in upper motor neurons controlling fine motor skills are not well understood. Here we report that projection neurons in the adult zebra finch song nucleus RA display robust high-frequency firing, ultra-narrow spike waveforms, superfast Na⁺ current inactivation kinetics, and large resurgent Na⁺ currents (I_NaR). These properties of songbird pallial motor neurons closely resemble those of specialized large pyramidal neurons in mammalian primary motor cortex. They emerge during the early phases of song development in males, but not females, coinciding with a complete switch of Na+ channel subunit expression from Navβ3 to Navβ4. Dynamic clamping and dialysis of Navβ4's C-terminal peptide into juvenile RA neurons provide evidence that Navβ4, and its associated I_NaR, promote neuronal excitability. We thus propose that I_NaR modulates the excitability of upper motor neurons that are required for the execution of fine motor skills.

Computational benefits of structural plasticity, illustrated in songbirds

The plasticity of nervous systems allows animals to quickly adapt to a changing environment. In particular, the structural plasticity of brain networks is often critical to the development of the central nervous system and the acquisition of complex behaviors. As an example, structural plasticity is central to the development of song-related brain circuits and may be critical for song acquisition in juvenile songbirds. Here, we review current evidences for structural plasticity and their significance from a computational point of view. We start by reviewing evidence for structural plasticity across species and categorizing them along the spatial axes as well as the along the time course during development. We introduce the vocal learning circuitry in zebra finches, as a useful example of structural plasticity, and use this specific case to explore the possible contributions of structural plasticity to computational models. Finally, we discuss current modeling studies incorporating structural plasticity and unexplored questions which are raised by such models.

From Cell Types to an Integrated Understanding of Brain Evolution: The Case of the Cerebral Cortex

With the discovery of the incredible diversity of neurons, Cajal and coworkers laid the foundation of modern neuroscience. Neuron types are not only structural units of nervous systems but also evolutionary units, because their identities are encoded in the genome. With the advent of high-throughput cellular transcriptomics, neuronal identities can be characterized and compared systematically across species. The comparison of neurons in mammals, reptiles, and birds indicates that the mammalian cerebral cortex is a mosaic of deeply conserved and recently evolved neuron types. Using the cerebral cortex as a case study, this review illustrates how comparing neuron types across species is key to reconciling observations on neural development, neuroanatomy, circuit wiring, and physiology for an integrated understanding of brain evolution.

Avian pallial circuits and cognition: A comparison to mammals

Cognitive functions are similar in birds and mammals. So, are therefore pallial cellular circuits and neuronal computations also alike? In search of answers, we move in from bird's pallial connectomes, to cortex-like sensory canonical circuits and connections, to forebrain micro-circuitries and finally to the avian "prefrontal" area. This voyage from macro- to micro-scale networks and areas reveals that both birds and mammals evolved similar neural and computational properties in either convergent or parallel manner, based upon circuitries inherited from common ancestry. Thus, these two vertebrate classes evolved separately within 315 million years with highly similar pallial architectures that produce comparable cognitive functions.

Midbrain-Level Neural Correlates of Behavioral Tone-in-Noise Detection: Dependence on Energy and Envelope Cues

Hearing in noise is a problem often assumed to depend on encoding of energy level by channels tuned to target frequencies, but few studies have tested this hypothesis. The present study examined neural correlates of behavioral tone-in-noise (TIN) detection in budgerigars (Melopsittacus undulatus, either sex), a parakeet species with human-like behavioral sensitivity to many simple and complex sounds. Behavioral sensitivity to tones in band-limited noise was assessed using operant-conditioning procedures. Neural recordings were made in awake animals from midbrain-level neurons in the inferior colliculus, the first processing stage of the ascending auditory pathway with pronounced rate-based encoding of stimulus amplitude modulation. Budgerigar TIN detection thresholds were similar to human thresholds across the full range of frequencies (0.5-4 kHz) and noise levels (45-85 dB SPL) tested. Also as in humans, thresholds were minimally affected by a challenging roving-level condition with random variation in background-noise level. Many midbrain neurons showed a decreasing response rate as TIN signal-to-noise ratio (SNR) was increased by elevating the tone level, a pattern attributable to amplitude-modulation tuning in these cells and the fact that higher SNR tone-plus-noise stimuli have flatter amplitude envelopes. TIN thresholds of individual neurons were as sensitive as behavioral thresholds under most conditions, perhaps surprisingly even when the unit's characteristic frequency was tuned an octave or more away from the test frequency. A model that combined responses of two cell types enhanced TIN sensitivity in the roving-level condition. These results highlight the importance of midbrain-level envelope encoding and off-frequency neural channels for hearing in noise.SIGNIFICANCE STATEMENT Detection of target sounds in noise is often assumed to depend on energy-level encoding by neural processing channels tuned to the target frequency. In contrast, we found that tone-in-noise sensitivity in budgerigars was often greatest in midbrain neurons not tuned to the test frequency, underscoring the potential importance of off-frequency channels for perception. Furthermore, the results highlight the importance of envelope processing for hearing in noise, especially under challenging conditions with random variation in background noise level over time.

A canonical interlaminar circuit in the sensory dorsal ventricular ridge of birds: The anatomical organization of the trigeminal pallium

The dorsal ventricular ridge (DVR), which is the largest component of the avian pallium, contains discrete partitions receiving tectovisual, auditory, and trigeminal ascending projections. Recent studies have shown that the auditory and the tectovisual regions can be regarded as complexes composed of three highly interconnected layers: an internal senso-recipient one, an intermediate afferent/efferent one, and a more external re-entrant one. Cells located in homotopic positions in each of these layers are reciprocally linked by an interlaminar loop of axonal processes, forming columnar-like local circuits. Whether this type of organization also extends to the trigemino-recipient DVR is, at present, not known. This question is of interest, since afferents forming this sensory pathway, exceptional among amniotes, are not thalamic but rhombencephalic in origin. We investigated this question by placing minute injections of neural tracers into selected locations of vital slices of the chicken telencephalon. We found that neurons of the trigemino-recipient nucleus basorostralis pallii (Bas) establish reciprocal, columnar and homotopical projections with cells located in the overlying ventral mesopallium (MV). "Column-forming" axons originated in B and MV terminate also in the intermediate strip, the fronto-trigeminal nidopallium (NFT), in a restricted manner. We also found that the NFT and an internal partition of B originate substantial, coarse-topographic projections to the underlying portion of the lateral striatum. We conclude that all sensory areas of the DVR are organized according to a common neuroarchitectonic motif, which bears a striking resemblance to that of the radial/laminar intrinsic circuits of the sensory cortices of mammals.

Genetically identified neurons in avian auditory pallium mirror core principles of their mammalian counterparts

In vertebrates, advanced cognitive abilities are typically associated with the telencephalic pallium. In mammals, the pallium is a layered mixture of excitatory and inhibitory neuronal populations with distinct molecular, physiological, and network phenotypes. This cortical architecture is proposed to support efficient, high-level information processing. Comparative perspectives across vertebrates provide a lens to understand the common features of pallium that are important for advanced cognition. Studies in songbirds have established strikingly parallel features of neuronal types between mammalian and avian pallium. However, lack of genetic access to defined pallial cell types in non-mammalian vertebrates has hindered progress in resolving connections between molecular and physiological phenotypes. A definitive mapping of the physiology of pallial cells onto their molecular identities in birds is critical for understanding how synaptic and computational properties depend on underlying molecular phenotypes. Using viral tools to target excitatory versus inhibitory neurons in the zebra finch auditory association pallium (calmodulin-dependent kinase alpha [CaMKIIα] and glutamate decarboxylase 1 [GAD1] promoters, respectively), we systematically tested predictions derived from mammalian pallium. We identified two genetically distinct neuronal populations that exhibit profound physiological and computational similarities with mammalian excitatory and inhibitory pallial cells, definitively aligning putative cell types in avian caudal nidopallium with these molecular identities. Specifically, genetically identified CaMKIIα and GAD1 cell types in avian auditory association pallium exhibit distinct intrinsic physiological parameters, distinct auditory coding principles, and inhibitory-dependent pallial synchrony, gamma oscillations, and local suppression. The retention, or convergence, of these molecular and physiological features in both birds and mammals clarifies the characteristics of pallial circuits for advanced cognitive abilities.

New roles for dopamine in motor skill acquisition: lessons from primates, rodents, and songbirds

Motor learning is a core aspect of human life and appears to be ubiquitous throughout the animal kingdom. Dopamine, a neuromodulator with a multifaceted role in synaptic plasticity, may be a key signaling molecule for motor skill learning. Though typically studied in the context of reward-based associative learning, dopamine appears to be necessary for some types of motor learning. Mesencephalic dopamine structures are highly conserved among vertebrates, as are some of their primary targets within the basal ganglia, a subcortical circuit important for motor learning and motor control. With a focus on the benefits of cross-species comparisons, this review examines how "model-free" and "model-based" computational frameworks for understanding dopamine's role in associative learning may be applied to motor learning. The hypotheses that dopamine could drive motor learning either by functioning as a reward prediction error, through passive facilitating of normal basal ganglia activity, or through other mechanisms are examined in light of new studies using humans, rodents, and songbirds. Additionally, new paradigms that could enhance our understanding of dopamine's role in motor learning by bridging the gap between the theoretical literature on motor learning in humans and other species are discussed.

Adult-like neural representation of species-specific songs in the auditory forebrain of zebra finch nestlings

Encoding of conspecific signals during development can reinforce species barriers as well as set the stage for learning and production of species-typical vocalizations. In altricial songbirds, the development of the auditory system is not complete at hatching, so it is unknown the degree to which recently hatched young can process auditory signals like birdsong. We measured in vivo extracellular responses to song stimuli in a zebra finch (Taeniopygia guttata) secondary auditory forebrain region, the caudomedial nidopallium (NCM). We recorded from three age groups between 13 days post-hatch and adult to identify possible shifts in stimulus encoding that occur before the opening of the sensitive period of song motor learning. We did not find differences in putative cell type composition, firing rate, response strength, and selectivity across ages. Across ages narrow-spiking units had higher firing rates, response strength, accuracy, and trial-by-trial reliability along with lower selectivity than broad-spiking units. In addition, we showed that stimulus-specific adaptation, a characteristic of adult NCM, was also present in nestlings and fledglings. These results indicate that most features of secondary auditory processing are already adult-like shortly after hatching. Furthermore, we showed that selectivity for species-specific stimuli is similar across all ages, with the greatest fidelity in temporal coding in response to conspecific song and domesticated Bengalese finch song, and reduced fidelity in response to owl finch song, a more ecologically relevant heterospecific, and white noise. Our study provides the first evidence that the electrophysiological properties of higher-order auditory neurons are already mature in nestling songbirds.

Simple transformations capture auditory input to cortex

Sounds are processed by the ear and central auditory pathway. These processing steps are biologically complex, and many aspects of the transformation from sound waveforms to cortical response remain unclear. To understand this transformation, we combined models of the auditory periphery with various encoding models to predict auditory cortical responses to natural sounds. The cochlear models ranged from detailed biophysical simulations of the cochlea and auditory nerve to simple spectrogram-like approximations of the information processing in these structures. For three different stimulus sets, we tested the capacity of these models to predict the time course of single-unit neural responses recorded in ferret primary auditory cortex. We found that simple models based on a log-spaced spectrogram with approximately logarithmic compression perform similarly to the best-performing biophysically detailed models of the auditory periphery, and more consistently well over diverse natural and synthetic sounds. Furthermore, we demonstrated that including approximations of the three categories of auditory nerve fiber in these simple models can substantially improve prediction, particularly when combined with a network encoding model. Our findings imply that the properties of the auditory periphery and central pathway may together result in a simpler than expected functional transformation from ear to cortex. Thus, much of the detailed biological complexity seen in the auditory periphery does not appear to be important for understanding the cortical representation of sound.

An avian cortical circuit for chunking tutor song syllables into simple vocal-motor units

How are brain circuits constructed to achieve complex goals? The brains of young songbirds develop motor circuits that achieve the goal of imitating a specific tutor song to which they are exposed. Here, we set out to examine how song-generating circuits may be influenced early in song learning by a cortical region (NIf) at the interface between auditory and motor systems. Single-unit recordings reveal that, during juvenile babbling, NIf neurons burst at syllable onsets, with some neurons exhibiting selectivity for particular emerging syllable types. When juvenile birds listen to their tutor, NIf neurons are also activated at tutor syllable onsets, and are often selective for particular syllable types. We examine a simple computational model in which tutor exposure imprints the correct number of syllable patterns as ensembles in an interconnected NIf network. These ensembles are then reactivated during singing to train a set of syllable sequences in the motor network.

Young songbirds learn to imitate their parents’ songs. Here, the authors find that, in baby birds, neurons in a brain region at the interface of auditory and motor circuits signal the onsets of song syllables during both tutoring and babbling, suggesting a specific neural mechanism for vocal imitation.

A cortex-like canonical circuit in the avian forebrain

Although the avian pallium seems to lack an organization akin to that of the cerebral cortex, birds exhibit extraordinary cognitive skills that are comparable to those of mammals. We analyzed the fiber architecture of the avian pallium with three-dimensional polarized light imaging and subsequently reconstructed local and associative pallial circuits with tracing techniques. We discovered an iteratively repeated, column-like neuronal circuitry across the layer-like nuclear boundaries of the hyperpallium and the sensory dorsal ventricular ridge. These circuits are connected to neighboring columns and, via tangential layer-like connections, to higher associative and motor areas. Our findings indicate that this avian canonical circuitry is similar to its mammalian counterpart and might constitute the structural basis of neuronal computation.

Deviance detection in physiologically identified cell types in the rat auditory cortex

Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression.

Effect of Stimulus-Dependent Spike Timing on Population Coding of Sound Location in the Owl's Auditory Midbrain

In the auditory system, the spectrotemporal structure of acoustic signals determines the temporal pattern of spikes. Here, we investigated this effect in neurons of the barn owl's auditory midbrain (Tyto furcata) that are selective for auditory space and whether it can influence the coding of sound direction. We found that in the nucleus where neurons first become selective to combinations of sound localization cues, reproducibility of spike trains across repeated trials of identical sounds, a metric of across-trial temporal fidelity of spiking patterns evoked by a stimulus, was maximal at the sound direction that elicited the highest firing rate. We then tested the hypothesis that this stimulus-dependent patterning resulted in rate co-modulation of cells with similar frequency and spatial selectivity, driving stimulus-dependent synchrony of population responses. Tetrodes were used to simultaneously record multiple nearby units in the optic tectum (OT), where auditory space is topographically represented. While spiking of neurons in OT showed lower reproducibility across trials compared with upstream nuclei, spike-time synchrony between nearby OT neurons was highest for sounds at their preferred direction. A model of the midbrain circuit explained the relationship between stimulus-dependent reproducibility and synchrony, and demonstrated that this effect can improve the decoding of sound location from the OT output. Thus, stimulus-dependent spiking patterns in the auditory midbrain can have an effect on spatial coding. This study reports a functional connection between spike patterning elicited by spectrotemporal features of a sound and the coding of its location.

Inhibitory cell populations depend on age, sex, and prior experience across a neural network for Critical Period learning

In many ways, the complement of cell subtypes determines the information processing that a local brain circuit can perform. For example, the balance of excitatory and inhibitory (E/I) signaling within a brain region contributes to response magnitude and specificity in ways that influence the effectiveness of information processing. An extreme example of response changes to sensory information occur across Critical Periods (CPs). In primary mammalian visual cortex, GAD65 and parvalbumin inhibitory cell types in particular control experience-dependent responses during a CP. Here, we test how the density of GAD65- and parvalbumin-expressing cells may inform on a CP for complex behavioral learning. Juvenile male zebra finch songbirds (females cannot sing) learn to sing through coordinated sensory, sensorimotor, and motor learning processes distributed throughout a well-defined neural network. There is a CP for sensory learning, the process by which a young male forms a memory of his “tutor’s” song, which is then used to guide the young bird’s emerging song structure. We quantified the effect of sex and experience with a tutor on the cell densities of GAD65- and parvalbumin-expressing cells across major nodes of the song network, using ages that span the CP for tutor song memorization. As a resource, we also include whole-brain mapping data for both genes. Results indicate that inhibitory cell populations differ across sex, age, and experiential conditions, but not always in the ways we predicted.

Auditory Selectivity for Spectral Contrast in Cortical Neurons and Behavior

Vocal communication relies on the ability of listeners to identify, process, and respond to vocal sounds produced by others in complex environments. To accurately recognize these signals, animals' auditory systems must robustly represent acoustic features that distinguish vocal sounds from other environmental sounds. Vocalizations typically have spectral structure; power regularly fluctuates along the frequency axis, creating spectral contrast. Spectral contrast is closely related to harmonicity, which refers to spectral power peaks occurring at integer multiples of a fundamental frequency. Although both spectral contrast and harmonicity typify natural sounds, they may differ in salience for communication behavior and engage distinct neural mechanisms. Therefore, it is important to understand which of these properties of vocal sounds underlie the neural processing and perception of vocalizations.Here, we test the importance of vocalization-typical spectral features in behavioral recognition and neural processing of vocal sounds, using male zebra finches. We show that behavioral responses to natural and synthesized vocalizations rely on the presence of discrete frequency components, but not on harmonic ratios between frequencies. We identify a specific population of neurons in primary auditory cortex that are sensitive to the spectral resolution of vocal sounds. We find that behavioral and neural response selectivity is explained by sensitivity to spectral contrast rather than harmonicity. This selectivity emerges within the cortex; it is absent in the thalamorecipient region and present in the deep output region. Further, deep-region neurons that are contrast-sensitive show distinct temporal responses and selectivity for modulation density compared with unselective neurons.SIGNIFICANCE STATEMENT Auditory coding and perception are critical for vocal communication. Auditory neurons must encode acoustic features that distinguish vocalizations from other sounds in the environment and generate percepts that direct behavior. The acoustic features that drive neural and behavioral selectivity for vocal sounds are unknown, however. Here, we show that vocal response behavior scales with stimulus spectral contrast but not with harmonicity, in songbirds. We identify a distinct population of auditory cortex neurons in which response selectivity parallels behavioral selectivity. This neural response selectivity is explained by sensitivity to spectral contrast rather than to harmonicity. Our findings inform the understanding of how the auditory system encodes socially-relevant signals via detection of an acoustic feature that is ubiquitous in vocalizations.

Bayesian Filtering with Multiple Internal Models: Toward a Theory of Social Intelligence

To exhibit social intelligence, animals have to recognize whom they are communicating with. One way to make this inference is to select among internal generative models of each conspecific who may be encountered. However, these models also have to be learned via some form of Bayesian belief updating. This induces an interesting problem: When receiving sensory input generated by a particular conspecific, how does an animal know which internal model to update? We consider a theoretical and neurobiologically plausible solution that enables inference and learning of the processes that generate sensory inputs (e.g., listening and understanding) and reproduction of those inputs (e.g., talking or singing), under multiple generative models. This is based on recent advances in theoretical neurobiology-namely, active inference and post hoc (online) Bayesian model selection. In brief, this scheme fits sensory inputs under each generative model. Model parameters are then updated in proportion to the probability that each model could have generated the input (i.e., model evidence). The proposed scheme is demonstrated using a series of (real zebra finch) birdsongs, where each song is generated by several different birds. The scheme is implemented using physiologically plausible models of birdsong production. We show that generalized Bayesian filtering, combined with model selection, leads to successful learning across generative models, each possessing different parameters. These results highlight the utility of having multiple internal models when making inferences in social environments with multiple sources of sensory information.

Birds of a different feather sing together

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.

Emergent tuning for learned vocalizations in auditory cortex

Vocal learners use early social experience to develop auditory skills specialized for communication. However, it is unknown where in the auditory pathway neural responses become selective for vocalizations or how the underlying encoding mechanisms change with experience. We used a vocal tutoring manipulation in two species of songbird to reveal that tuning for conspecific song arises within the primary auditory cortical circuit. Neurons in the deep region of primary auditory cortex responded more to conspecific songs than to other species' songs and more to species-typical spectrotemporal modulations, but neurons in the intermediate (thalamorecipient) region did not. Moreover, birds that learned song from another species exhibited parallel shifts in selectivity and tuning toward the tutor species' songs in the deep but not the intermediate region. Our results locate a region in the auditory processing hierarchy where an experience-dependent coding mechanism aligns auditory responses with the output of a learned vocal motor behavior.

Rapid and long-lasting improvements in neural discrimination of acoustic signals with passive familiarization

Sensory representations in the adult brain must undergo dynamic changes to adapt to the complexity of the external world. This study investigated how passive exposure to novel sounds modifies neural representations to facilitate recognition and discrimination, using the zebra finch model organism. The neural responses in an auditory structure in the zebra finch brain, Caudal Medial Nidopallium (NCM), undergo a long-term form of adaptation with repeated stimulus presentation, providing an excellent substrate to probe the neural underpinnings of adaptive sensory representations. In Experiment 1, electrophysiological activity in NCM was recorded under passive listening conditions as novel natural vocalizations were familiarized through playback. Neural decoding of stimuli using the temporal profiles of both single-unit and multi-unit responses improved dramatically during the first few stimulus presentations. During subsequent encounters, these signals were recognized after hearing fewer initial acoustic features. Remarkably, the accuracy of neural decoding was higher when different stimuli were heard in separate blocks compared to when they were presented randomly in a shuffled sequence. NCM neurons with narrow spike waveforms generally yielded higher neural decoding accuracy than wide spike neurons, but the rate at which these accuracies improved with passive exposure was comparable between the two neuron types. Experiment 2 supported and extended these findings by showing that the rapid gains in neural decoding of novel vocalizations with passive familiarization were long-lasting, maintained for 20 hours after the initial encounter, in multi-unit responses. Taken together, these findings provide valuable insights into the mechanisms by which the nervous system dynamically modulates sensory representations to improve discrimination of novel complex signals over short and long timescales. Similar mechanisms may also be engaged during processing of human speech signals, and thus may have potential translational relevance for elucidating the neural basis of speech comprehension difficulties.

Avian Brains: Primate-like Functions of Neurons in the Crow Brain

Despite the negative connotations of the term 'birdbrain', birds possess cognitive abilities on par with primates. A new study finds that neurons in the crow's brain display characteristics similar to those displayed by neurons in the primate's brain.

Cracking the Function of Layers in the Sensory Cortex

Understanding how cortical activity generates sensory perceptions requires a detailed dissection of the function of cortical layers. Despite our relatively extensive knowledge of their anatomy and wiring, we have a limited grasp of what each layer contributes to cortical computation. We need to develop a theory of cortical function that is rooted solidly in each layer's component cell types and fine circuit architecture and produces predictions that can be validated by specific perturbations. Here we briefly review the progress toward such a theory and suggest an experimental road map toward this goal. We discuss new methods for the all-optical interrogation of cortical layers, for correlating in vivo function with precise identification of transcriptional cell type, and for mapping local and long-range activity in vivo with synaptic resolution. The new technologies that can crack the function of cortical layers are finally on the immediate horizon.

A Physiologically Inspired Model for Solving the Cocktail Party Problem

At a cocktail party, we can broadly monitor the entire acoustic scene to detect important cues (e.g., our names being called, or the fire alarm going off), or selectively listen to a target sound source (e.g., a conversation partner). It has recently been observed that individual neurons in the avian field L (analog to the mammalian auditory cortex) can display broad spatial tuning to single targets and selective tuning to a target embedded in spatially distributed sound mixtures. Here, we describe a model inspired by these experimental observations and apply it to process mixtures of human speech sentences. This processing is realized in the neural spiking domain. It converts binaural acoustic inputs into cortical spike trains using a multi-stage model composed of a cochlear filter-bank, a midbrain spatial-localization network, and a cortical network. The output spike trains of the cortical network are then converted back into an acoustic waveform, using a stimulus reconstruction technique. The intelligibility of the reconstructed output is quantified using an objective measure of speech intelligibility. We apply the algorithm to single and multi-talker speech to demonstrate that the physiologically inspired algorithm is able to achieve intelligible reconstruction of an “attended” target sentence embedded in two other non-attended masker sentences. The algorithm is also robust to masker level and displays performance trends comparable to humans. The ideas from this work may help improve the performance of hearing assistive devices (e.g., hearing aids and cochlear implants), speech-recognition technology, and computational algorithms for processing natural scenes cluttered with spatially distributed acoustic objects.

Neural mechanisms of auditory species recognition in birds

Auditory communication in humans and other animals frequently takes place in noisy environments with many co-occurring signallers. Receivers are thus challenged to rapidly recognize salient auditory signals and filter out irrelevant sounds. Most bird species produce a variety of complex vocalizations that function to communicate with other members of their own species and behavioural evidence broadly supports preferences for conspecific over heterospecific sounds (auditory species recognition). However, it remains unclear whether such auditory signals are categorically recognized by the sensory and central nervous system. Here, we review 53 published studies that compare avian neural responses between conspecific versus heterospecific vocalizations. Irrespective of the techniques used to characterize neural activity, distinct nuclei of the auditory forebrain are consistently shown to be repeatedly conspecific selective across taxa, even in response to unfamiliar individuals with distinct acoustic properties. Yet, species-specific neural discrimination is not a stereotyped auditory response, but is modulated according to its salience depending, for example, on ontogenetic exposure to conspecific versus heterospecific stimuli. Neuromodulators, in particular norepinephrine, may mediate species recognition by regulating the accuracy of neuronal coding for salient conspecific stimuli. Our review lends strong support for neural structures that categorically recognize conspecific signals despite the highly variable physical properties of the stimulus. The available data are in support of a 'perceptual filter'-based mechanism to determine the saliency of the signal, in that species identity and social experience combine to influence the neural processing of species-specific auditory stimuli. Finally, we present hypotheses and their testable predictions, to propose next steps in species-recognition research into the emerging model of the neural conceptual construct in avian auditory recognition.

Comparative Principles for Next-Generation Neuroscience

Neuroscience is enjoying a renaissance of discovery due in large part to the implementation of next-generation molecular technologies. The advent of genetically encoded tools has complemented existing methods and provided researchers the opportunity to examine the nervous system with unprecedented precision and to reveal facets of neural function at multiple scales. The weight of these discoveries, however, has been technique-driven from a small number of species amenable to the most advanced gene-editing technologies. To deepen interpretation and build on these breakthroughs, an understanding of nervous system evolution and diversity are critical. Evolutionary change integrates advantageous variants of features into lineages, but is also constrained by pre-existing organization and function. Ultimately, each species’ neural architecture comprises both properties that are species-specific and those that are retained and shared. Understanding the evolutionary history of a nervous system provides interpretive power when examining relationships between brain structure and function. The exceptional diversity of nervous systems and their unique or unusual features can also be leveraged to advance research by providing opportunities to ask new questions and interpret findings that are not accessible in individual species. As new genetic and molecular technologies are added to the experimental toolkits utilized in diverse taxa, the field is at a key juncture to revisit the significance of evolutionary and comparative approaches for next-generation neuroscience as a foundational framework for understanding fundamental principles of neural function.

A low-threshold potassium current enhances sparseness and reliability in a model of avian auditory cortex

Birdsong is a complex vocal communication signal, and like humans, birds need to discriminate between similar sequences of sound with different meanings. The caudal mesopallium (CM) is a cortical-level auditory area implicated in song discrimination. CM neurons respond sparsely to conspecific song and are tolerant of production variability. Intracellular recordings in CM have identified a diversity of intrinsic membrane dynamics, which could contribute to the emergence of these higher-order functional properties. We investigated this hypothesis using a novel linear-dynamical cascade model that incorporated detailed biophysical dynamics to simulate auditory responses to birdsong. Neuron models that included a low-threshold potassium current present in a subset of CM neurons showed increased selectivity and coding efficiency relative to models without this current. These results demonstrate the impact of intrinsic dynamics on sensory coding and the importance of including the biophysical characteristics of neural populations in simulation studies.

Maintaining a stable mental representation of an object is an important task for sensory systems, requiring both recognizing the features required for identification and ignoring incidental changes in its presentation. The prevailing explanation for these processes emphasizes precise sets of connections between neurons that capture only the essential features of an object. However, the intrinsic dynamics of the neurons themselves, which determine how these inputs are transformed into spiking outputs, may also contribute to the neural computations underlying object recognition. To understand how intrinsic dynamics contribute to sensory coding, we constructed a computational model capable of simulating a neural response to an auditory stimulus using a detailed description of different intrinsic dynamics in a higher-order avian auditory area. The results of our simulation showed that intrinsic dynamics can have a profound effect on processes underlying object recognition. These findings challenge the view that patterns of connectivity alone account for the emergence of stable object representations and encourage greater consideration of the functional implications of the diversity of neurons in the brain.

Response properties of single neurons in higher level auditory cortex of adult songbirds

The caudomedial nidopallium (NCM) is a higher level region of auditory cortex in songbirds that has been implicated in encoding learned vocalizations and mediating perception of complex sounds. We made cell-attached recordings in awake adult male zebra finches ( Taeniopygia guttata) to characterize responses of single NCM neurons to playback of tones and songs. Neurons fell into two broad classes: narrow fast-spiking cells and broad sparsely firing cells. Virtually all narrow-spiking cells responded to playback of pure tones, compared with approximately half of broad-spiking cells. In addition, narrow-spiking cells tended to have lower thresholds and faster, less variable spike onset latencies than did broad-spiking cells, as well as higher firing rates. Tonal responses of narrow-spiking cells also showed broader ranges for both frequency and amplitude compared with broad-spiking neurons and were more apt to have V-shaped tuning curves compared with broad-spiking neurons, which tended to have complex (discontinuous), columnar, or O-shaped frequency response areas. In response to playback of conspecific songs, narrow-spiking neurons showed high firing rates and low levels of selectivity whereas broad-spiking neurons responded sparsely and selectively. Broad-spiking neurons in which tones failed to evoke a response showed greater song selectivity compared with those with a clear tuning curve. These results are consistent with the idea that narrow-spiking neurons represent putative fast-spiking interneurons, which may provide a source of intrinsic inhibition that contributes to the more selective tuning in broad-spiking cells. NEW & NOTEWORTHY The response properties of neurons in higher level regions of auditory cortex in songbirds are of fundamental interest because processing in such regions is essential for vocal learning and plasticity and for auditory perception of complex sounds. Within a region of secondary auditory cortex, neurons with narrow spikes exhibited high firing rates to playback of both tones and multiple conspecific songs, whereas broad-spiking neurons responded sparsely and selectively to both tones and songs.

Differential developmental changes in cortical representations of auditory-vocal stimuli in songbirds

Procedural skill learning requires iterative comparisons between feedback of self-generated motor output and a goal sensorimotor pattern. In juvenile songbirds, neural representations of both self-generated behaviors (each bird's own immature song) and the goal motor pattern (each bird's adult tutor song) are essential for vocal learning, yet little is known about how these behaviorally relevant stimuli are encoded. We made extracellular recordings during song playback in anesthetized juvenile and adult zebra finches ( Taeniopygia guttata) in adjacent cortical regions RA (robust nucleus of the arcopallium), AId (dorsal intermediate arcopallium), and RA cup, each of which is well situated to integrate auditory-vocal information: RA is a motor cortical region that drives vocal output, AId is an adjoining cortical region whose projections converge with basal ganglia loops for song learning in the dorsal thalamus, and RA cup surrounds RA and receives inputs from primary and secondary auditory cortex. We found strong developmental differences in neural selectivity within RA, but not in AId or RA cup. Juvenile RA neurons were broadly responsive to multiple songs but preferred juvenile over adult vocal sounds; in addition, spiking responses lacked consistent temporal patterning. By adulthood, RA neurons responded most strongly to each bird's own song with precisely timed spiking activity. In contrast, we observed a complete lack of song responsivity in both juvenile and adult AId, even though this region receives song-responsive inputs. A surprisingly large proportion of sites in RA cup of both juveniles and adults did not respond to song playback, and responsive sites showed little evidence of song selectivity. NEW & NOTEWORTHY Motor skill learning entails changes in selectivity for behaviorally relevant stimuli across cortical regions, yet the neural representation of these stimuli remains understudied. We investigated how information important for vocal learning in zebra finches is represented in regions analogous to infragranular layers of motor and auditory cortices during vs. after the developmentally regulated learning period. The results provide insight into how neurons in higher level stages of cortical processing represent stimuli important for motor skill learning.

Sub-populations of Spinal V3 Interneurons Form Focal Modules of Layered Pre-motor Microcircuits

Layering of neural circuits facilitates the separation of neurons with high spatial sensitivity from those that play integrative temporal roles. Although anatomical layers are readily identifiable in the brain, layering is not structurally obvious in the spinal cord. But computational studies of motor behaviors have led to the concept of layered processing in the spinal cord. It has been postulated that spinal V3 interneurons (INs) play multiple roles in locomotion, leading us to investigate whether they form layered microcircuits. Using patch-clamp recordings in combination with holographic glutamate uncaging, we demonstrate focal, layered modules, in which ventromedial V3 INs form synapses with one another and with ventrolateral V3 INs, which in turn form synapses with ipsilateral motoneurons. Motoneurons, in turn, provide recurrent excitatory, glutamatergic input to V3 INs. Thus, ventral V3 interneurons form layered microcircuits that could function to ensure well-timed, spatially specific movements.

Zebra finches are sensitive to combinations of temporally distributed features in a model of word recognition

Discrimination between spoken words composed of overlapping elements, such as "captain" and "captive," relies on sensitivity to unique combinations of prefix and suffix elements that span a "uniqueness point" where the word candidates diverge. To model such combinatorial processing, adult female zebra finches were trained to discriminate between target and distractor syllable sequences that shared overlapping "contextual" prefixes and differed only in their "informative" suffixes. The transition from contextual to informative syllables thus created a uniqueness point analogous to that present between overlapping word candidates, where targets and distractors diverged. It was found that target recognition depended not only on informative syllables, but also on contextual syllables that were shared with distractors. Moreover, the influence of each syllable depended on proximity to the uniqueness point. Birds were then trained birds with targets and distractors that shared both prefix and suffix sequences and could only be discriminated by recognizing unique combinations of those sequences. Birds learned to robustly discriminate target and distractor combinations and maintained significant discrimination when the local transitions from prefix to suffix were disrupted. These findings indicate that birds, like humans, combine information across temporally distributed features, spanning contextual and informative elements, in recognizing and discriminating word-like stimuli.