Using temperature to analyse temporal dynamics in the songbird motor pathway

Encoding time in neural dynamic regimes with distinct computational tradeoffs

Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to exhibit temporal scaling, generalize to novel contexts, or robustness to noise. It is not known how neural circuits can encode time and satisfy distinct computational requirements, nor is it known whether similar patterns of neural activity at the population level can exhibit dramatically different computational or generalization properties. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamic patterns at the level of single intervals, could exhibit fundamentally different properties, including, generalization, the connectivity structure of the trained networks, and the contribution of excitatory and inhibitory neurons. Critically, depending on the task structure RNNs were better suited for generalization or robustness to noise. Further analysis revealed different connection patterns underlying the different regimes. Our results predict that apparently similar neural dynamic patterns at the population level (e.g., neural sequences) can exhibit fundamentally different computational properties in regards to their ability to generalize to novel stimuli and their robustness to noise—and that these differences are associated with differences in network connectivity and distinct contributions of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time.

The ability to tell time and anticipate when external events will occur are among the most fundamental computations the brain performs. Converging evidence suggests the brain encodes time through changing patterns of neural activity. Different temporal tasks, however, have distinct computational requirements, such as the need to flexibly scale temporal patterns or generalize to novel inputs. To understand how networks can encode time and satisfy different computational requirements we trained recurrent neural networks (RNNs) on two timing tasks that have previously been used in behavioral studies. Both tasks required producing identically timed output patterns. Using a novel framework to quantify how networks encode different intervals, we found that similar patterns of neural activity—neural sequences—were associated with fundamentally different underlying mechanisms, including the connectivity patterns of the RNNs. Critically, depending on the task the RNNs were trained on, they were better suited for generalization or robustness to noise. Our results predict that similar patterns of neural activity can be produced by distinct RNN configurations, which in turn have fundamentally different computational tradeoffs. Our results also predict that differences in task structure account for some of the experimentally observed variability in how networks encode time.

A speech planning network for interactive language use

During conversation, people take turns speaking by rapidly responding to their partners while simultaneously avoiding interruption1,2. Such interactions display a remarkable degree of coordination, as gaps between turns are typically about 200 milliseconds3-approximately the duration of an eyeblink4. These latencies are considerably shorter than those observed in simple word-production tasks, which indicates that speakers often plan their responses while listening to their partners2. Although a distributed network of brain regions has been implicated in speech planning5-9, the neural dynamics underlying the specific preparatory processes that enable rapid turn-taking are poorly understood. Here we use intracranial electrocorticography to precisely measure neural activity as participants perform interactive tasks, and we observe a functionally and anatomically distinct class of planning-related cortical dynamics. We localize these responses to a frontotemporal circuit centred on the language-critical caudal inferior frontal cortex10 (Broca's region) and the caudal middle frontal gyrus-a region not normally implicated in speech planning11-13. Using a series of motor tasks, we then show that this planning network is more active when preparing speech as opposed to non-linguistic actions. Finally, we delineate planning-related circuitry during natural conversation that is nearly identical to the network mapped with our interactive tasks, and we find this circuit to be most active before participant speech during unconstrained turn-taking. Therefore, we have identified a speech planning network that is central to natural language generation during social interaction.

Chronic recording of cortical activity underlying vocalization in awake minipigs

BACKGROUND

Investigating brain dynamics underlying vocal production in animals is a powerful way to inform on the neural bases of human speech. In particular, brain networks underlying vocal production in non-human primates show striking similarities with the human speech production network. However, despite increasing findings also in birds and more recently in rodents, the extent to which the primate vocal cortical network model generalizes to other non-primate mammals remains unclear. Especially, no domestic species has yet been proposed to investigate vocal brain activity using electrophysiological approaches.

NEW METHOD

In the present study, we introduce a novel experimental paradigm to identify the cortical dynamics underlying vocal production in behaving minipigs. A key problem to chronically implant cortical probes in pigs is the presence and growth of frontal sinuses extending caudally to the parietal bone and preventing safe access to neural structures with conventional craniotomy in adult animals.

RESULTS

Here we first show that implantations of soft ECoG grids can be done safely using conventional craniotomy in minipigs younger than 5 months, a period when sinuses are not yet well developed. Using wireless recordings in behaving animals, we further show activation of the motor and premotor cortex around the onset of vocal production of grunts, the most common vocalization of pigs.

CONCLUSION

These results suggest that minipigs, which are very loquacious and social animals, can be a good experimental large animal model to study the cortical bases of vocal production.

A Platform for Spatiotemporal "Matrix" Stimulation in Brain Networks Reveals Novel Forms of Circuit Plasticity

Here we demonstrate a facile method by which to deliver complex spatiotemporal stimulation to neural networks in fast patterns, to trigger interesting forms of circuit-level plasticity in cortical areas. We present a complete platform by which patterns of electricity can be arbitrarily defined and distributed across a brain circuit, either simultaneously, asynchronously, or in complex patterns that can be easily designed and orchestrated with precise timing. Interfacing with acute slices of mouse cortex, we show that our system can be used to activate neurons at many locations and drive synaptic transmission in distributed patterns, and that this elicits new forms of plasticity that may not be observable via traditional methods, including interesting measurements of associational and sequence plasticity. Finally, we introduce an automated "network assay" for imaging activation and plasticity across a circuit. Spatiotemporal stimulation opens the door for high-throughput explorations of plasticity at the circuit level, and may provide a basis for new types of adaptive neural prosthetics.

Behavioral evidence for nested central pattern generator control of Drosophila grooming

Central pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, organizing control over different time scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On a short time scale (5-7 Hz, ~ 200 ms/movement), flies clean with periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head sweeping and leg rubbing are also periodic on a longer time scale (0.3-0.6 Hz, ~2 s/bout). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase-a hallmark of CPG control-and also that rhythms at the two time scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship holds when sensory drive is held constant using optogenetic activation, but oscillations can decouple in spontaneously grooming flies, showing that alternative control modes are possible. Loss of sensory feedback does not disrupt periodicity but slow down the longer time scale alternation. Nested CPGs simplify the generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.

Sleep replay reveals premotor circuit structure for a skilled behavior

Neural circuits often exhibit sequences of activity, but the contribution of local networks to their generation remains unclear. In the zebra finch, song-related premotor sequences within HVC may result from some combination of local connectivity and long-range thalamic inputs from nucleus uvaeformis (Uva). Because lesions to either structure abolish song, we examine "sleep replay" using high-density recording methods to reconstruct precise song-related events. Replay activity persists after the upstream nucleus interfacialis of the nidopallium is lesioned and slows when HVC is cooled, demonstrating that HVC provides temporal structure for these events. To further gauge the importance of intra-HVC connectivity for shaping network dynamics, we lesion Uva during sleep and find that residual replay sequences could span syllable boundaries, supporting a model in which HVC can propagate sequences throughout the duration of the song. Our results highlight the power of studying offline activity to investigate behaviorally relevant circuit organization.

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.

Fast and accurate annotation of acoustic signals with deep neural networks

Acoustic signals serve communication within and across species throughout the animal kingdom. Studying the genetics, evolution, and neurobiology of acoustic communication requires annotating acoustic signals: segmenting and identifying individual acoustic elements like syllables or sound pulses. To be useful, annotations need to be accurate, robust to noise, and fast.

We here introduce DeepAudioSegmenter (DAS), a method that annotates acoustic signals across species based on a deep-learning derived hierarchical presentation of sound. We demonstrate the accuracy, robustness, and speed of DAS using acoustic signals with diverse characteristics from insects, birds, and mammals. DAS comes with a graphical user interface for annotating song, training the network, and for generating and proofreading annotations. The method can be trained to annotate signals from new species with little manual annotation and can be combined with unsupervised methods to discover novel signal types. DAS annotates song with high throughput and low latency for experimental interventions in realtime. Overall, DAS is a universal, versatile, and accessible tool for annotating acoustic communication signals.

A synaptic temperature sensor for body cooling

Deep brain temperature detection by hypothalamic warm-sensitive neurons (WSNs) has been proposed to provide feedback information relevant for thermoregulation. WSNs increase their action potential firing rates upon warming, a property that has been presumed to rely on the composition of thermosensitive ion channels within WSNs. Here, we describe a synaptic mechanism that regulates temperature sensitivity of preoptic WSNs and body temperature. Experimentally induced warming of the mouse hypothalamic preoptic area in vivo triggers body cooling. TRPM2 ion channels facilitate this homeostatic response and, at the cellular level, enhance temperature responses of WSNs, thereby linking WSN function with thermoregulation for the first time. Rather than acting within WSNs, we-unexpectedly-find TRPM2 to temperature-dependently increase synaptic drive onto WSNs by disinhibition. Our data emphasize a network-based interoceptive paradigm that likely plays a key role in encoding body temperature and that may facilitate integration of diverse inputs into thermoregulatory pathways.

DARPP-32 distinguishes a subset of adult-born neurons in zebra finch HVC

Adult male zebra finches (Taeniopygia guttata) continually incorporate adult-born neurons into HVC, a telencephalic brain region necessary for the production of learned song. These neurons express activity-dependent immediate early genes (e.g., zenk and c-fos) following song production, suggesting that these neurons are active during song production. Half of these adult-born HVC neurons (HVC NNs) can be backfilled from the robust nucleus of the arcopallium (RA) and are a part of the vocal motor pathway underlying learned song production, but the other half do not backfill from RA, and they remain to be characterized. Here, we used cell birth-dating, retrograde tract tracing, and immunofluorescence to demonstrate that half of all HVC NNs express the phosphoprotein DARPP-32, a protein associated with dopamine receptor expression. We also demonstrate that DARPP-32+ HVC NNs are contacted by tyrosine hydroxylase immunoreactive fibers, suggesting that they receive catecholaminergic input, have transiently larger nuclei than DARPP-32-neg HVC NNs, and do not backfill from RA. Taken together, these findings help characterize a group of HVC NNs that have no apparent projections to RA and so far have eluded positive identification other than HVC NN status.

Using focal cooling to link neural dynamics and behavior

Establishing a causal link between neural function and behavioral output has remained a challenging problem. Commonly used perturbation techniques enable unprecedented control over intrinsic activity patterns and can effectively identify crucial circuit elements important for specific behaviors. However, these approaches may severely disrupt activity, precluding an investigation into the behavioral relevance of moment-to-moment neural dynamics within a specified brain region. Here we discuss the application of mild focal cooling to slow down intrinsic neural circuit activity while preserving its overall structure. Using network modeling and examples from multiple species, we highlight the power and versatility of focal cooling for understanding how neural dynamics control behavior and argue for its wider adoption within the systems neuroscience community.

Vocal learning and flexible rhythm pattern perception are linked: Evidence from songbirds

We can recognize the cadence of a friend’s voice or the rhythm of a familiar song across a wide range of tempi. This shows that our perception of temporal patterns relies strongly on the relative timing of events rather than on specific absolute durations. This tendency is foundational to speech and music perception, but to what extent is it shared by other species? We hypothesize that animals that learn their vocalizations are more likely to share this tendency. Here, we show that a vocal learning songbird robustly recognizes a basic rhythmic pattern independent of rate. Our findings pave the way for neurobiological studies to identify how the brain represents and perceives the temporal structure of auditory sequences.

Rhythm perception is fundamental to speech and music. Humans readily recognize a rhythmic pattern, such as that of a familiar song, independently of the tempo at which it occurs. This shows that our perception of auditory rhythms is flexible, relying on global relational patterns more than on the absolute durations of specific time intervals. Given that auditory rhythm perception in humans engages a complex auditory–motor cortical network even in the absence of movement and that the evolution of vocal learning is accompanied by strengthening of forebrain auditory–motor pathways, we hypothesize that vocal learning species share our perceptual facility for relational rhythm processing. We test this by asking whether the best-studied animal model for vocal learning, the zebra finch, can recognize a fundamental rhythmic pattern—equal timing between event onsets (isochrony)—based on temporal relations between intervals rather than on absolute durations. Prior work suggests that vocal nonlearners (pigeons and rats) are quite limited in this regard and are biased to attend to absolute durations when listening to rhythmic sequences. In contrast, using naturalistic sounds at multiple stimulus rates, we show that male zebra finches robustly recognize isochrony independent of absolute time intervals, even at rates distant from those used in training. Our findings highlight the importance of comparative studies of rhythmic processing and suggest that vocal learning species are promising animal models for key aspects of human rhythm perception. Such models are needed to understand the neural mechanisms behind the positive effect of rhythm on certain speech and movement disorders.

Plasticity of stereotyped birdsong driven by chronic manipulation of cortical-basal ganglia activity

Cortical-basal ganglia (CBG) circuits are critical for motor learning and performance, and are a major site of pathology. In songbirds, a CBG circuit regulates moment-by-moment variability in song and also enables song plasticity. Studies have shown that variable burst firing in LMAN, the output nucleus of this CBG circuit, actively drives acute song variability, but whether and how LMAN drives long-lasting changes in song remains unclear. Here, we ask whether chronic pharmacological augmentation of LMAN bursting is sufficient to drive plasticity in birds singing stereotyped songs. We show that altered LMAN activity drives cumulative changes in acoustic structure, timing, and sequencing over multiple days, and induces repetitions and silent pauses reminiscent of human stuttering. Changes persisted when LMAN was subsequently inactivated, indicating plasticity in song motor regions. Following cessation of pharmacological treatment, acoustic features and song sequence gradually recovered to their baseline values over a period of days to weeks. Together, our findings show that augmented bursting in CBG circuitry drives plasticity in well-learned motor skills, and may inform treatments for basal ganglia movement disorders.

Neurogenomic insights into the behavioral and vocal development of the zebra finch

The zebra finch (Taeniopygia guttata) is a socially monogamous and colonial opportunistic breeder with pronounced sexual differences in singing and plumage coloration. Its natural history has led to it becoming a model species for research into sex differences in vocal communication, as well as behavioral, neural and genomic studies of imitative auditory learning. As scientists tap into the genetic and behavioral diversity of both wild and captive lineages, the zebra finch will continue to inform research into culture, learning, and social bonding, as well as adaptability to a changing climate.

Neurophysiological coordination of duet singing

Coordination of behavior for cooperative performances often relies on linkages mediated by sensory cues exchanged between participants. How neurophysiological responses to sensory information affect motor programs to coordinate behavior between individuals is not known. We investigated how plain-tailed wrens (Pheugopedius euophrys) use acoustic feedback to coordinate extraordinary duet performances in which females and males rapidly take turns singing. We made simultaneous neurophysiological recordings in a song control area "HVC" in pairs of singing wrens at a field site in Ecuador. HVC is a premotor area that integrates auditory feedback and is necessary for song production. We found that spiking activity of HVC neurons in each sex increased for production of its own syllables. In contrast, hearing sensory feedback produced by the bird's partner decreased HVC activity during duet singing, potentially coordinating HVC premotor activity in each bird through inhibition. When birds sang alone, HVC neurons in females but not males were inhibited by hearing the partner bird. When birds were anesthetized with urethane, which antagonizes GABAergic (γ-aminobutyric acid) transmission, HVC neurons were excited rather than inhibited, suggesting a role for GABA in the coordination of duet singing. These data suggest that HVC integrates information across partners during duets and that rapid turn taking may be mediated, in part, by inhibition.

Local Axonal Conduction Shapes the Spatiotemporal Properties of Neural Sequences

Sequential activation of neurons has been observed during various behavioral and cognitive processes, but the underlying circuit mechanisms remain poorly understood. Here, we investigate premotor sequences in HVC (proper name) of the adult zebra finch forebrain that are central to the performance of the temporally precise courtship song. We use high-density silicon probes to measure song-related population activity, and we compare these observations with predictions from a range of network models. Our results support a circuit architecture in which heterogeneous delays between sequentially active neurons shape the spatiotemporal patterns of HVC premotor neuron activity. We gauge the impact of several delay sources, and we find the primary contributor to be slow conduction through axonal collaterals within HVC, which typically adds between 1 and 7.5 ms for each link within the sequence. Thus, local axonal "delay lines" can play an important role in determining the dynamical repertoire of neural circuits.

Feasibility of cerium-doped LSO particles as a scintillator for x-ray induced optogenetics

Objective.Non-invasive light delivery into the brain is needed forin vivooptogenetics to avoid physical damage. An innovative strategy could employ x-ray activation of radioluminescent particles (RLPs) to emit localized light. However, modulation of neuronal or synaptic function by x-ray induced radioluminescence from RLPs has not yet been demonstrated.Approach.Molecular and electrophysiological approaches were used to determine if x-ray dependent radioluminescence emitted from RLPs can activate light sensitive proteins. RLPs composed of cerium doped lutetium oxyorthosilicate (LSO:Ce), an inorganic scintillator that emits blue light, were used as they are biocompatible with neuronal function and synaptic transmission.Main results.We show that 30 min of x-ray exposure at a rate of 0.042 Gy s-1caused no change in the strength of basal glutamatergic transmission during extracellular field recordings in mouse hippocampal slices. Additionally, long-term potentiation, a robust measure of synaptic integrity, was induced after x-ray exposure and expressed at a magnitude not different from control conditions (absence of x-rays). We found that x-ray stimulation of RLPs elevated cAMP levels in HEK293T cells expressing OptoXR, a chimeric opsin receptor that combines the extracellular light-sensitive domain of rhodopsin with an intracellular second messenger signaling cascade. This demonstrates that x-ray radioluminescence from LSO:Ce particles can activate OptoXR. Next, we tested whether x-ray activation of the RLPs can enhance synaptic activity in whole-cell recordings from hippocampal neurons expressing channelrhodopsin-2, both in cell culture and acute hippocampal slices. Importantly, x-ray radioluminescence caused an increase in the frequency of spontaneous excitatory postsynaptic currents in both systems, indicating activation of channelrhodopsin-2 and excitation of neurons.Significance.Together, our results show that x-ray activation of LSO:Ce particles can heighten cellular and synaptic function. The combination of LSO:Ce inorganic scintillators and x-rays is therefore a viable method for optogenetics as an alternative to more invasive light delivery methods.

Kilohertz-frequency stimulation of the nervous system: A review of underlying mechanisms

BACKGROUND

Electrical stimulation in the kilohertz-frequency range has gained interest in the field of neuroscience. The mechanisms underlying stimulation in this frequency range, however, are poorly characterized to date.

OBJECTIVE/HYPOTHESIS

To summarize the manifold biological effects elicited by kilohertz-frequency stimulation in the context of the currently existing literature and provide a mechanistic framework for the neural responses observed in this frequency range.

METHODS

A comprehensive search of the peer-reviewed literature was conducted across electronic databases. Relevant computational, clinical, and mechanistic studies were selected for review.

RESULTS

The effects of kilohertz-frequency stimulation on neural tissue are diverse and yield effects that are distinct from conventional stimulation. Broadly, these can be divided into 1) subthreshold, 2) suprathreshold, 3) synaptic and 4) thermal effects. While facilitation is the dominating mechanism at the subthreshold level, desynchronization, spike-rate adaptation, conduction block, and non-monotonic activation can be observed during suprathreshold kilohertz-frequency stimulation. At the synaptic level, kilohertz-frequency stimulation has been associated with the transient depletion of the available neurotransmitter pool - also known as synaptic fatigue. Finally, thermal effects associated with extrinsic (environmental) and intrinsic (associated with kilohertz-frequency stimulation) temperature changes have been suggested to alter the neural response to stimulation paradigms.

CONCLUSION

The diverse spectrum of neural responses to stimulation in the kilohertz-frequency range is distinct from that associated with conventional stimulation. This offers the potential for new therapeutic avenues across stimulation modalities. However, stimulation in the kilohertz-frequency range is associated with distinct challenges and caveats that need to be considered in experimental paradigms.

Addition of new neurons and the emergence of a local neural circuit for precise timing

During development, neurons arrive at local brain areas in an extended period of time, but how they form local neural circuits is unknown. Here we computationally model the emergence of a network for precise timing in the premotor nucleus HVC in songbird. We show that new projection neurons, added to HVC post hatch at early stages of song development, are recruited to the end of a growing feedforward network. High spontaneous activity of the new neurons makes them the prime targets for recruitment in a self-organized process via synaptic plasticity. Once recruited, the new neurons fire readily at precise times, and they become mature. Neurons that are not recruited become silent and replaced by new immature neurons. Our model incorporates realistic HVC features such as interneurons, spatial distributions of neurons, and distributed axonal delays. The model predicts that the birth order of the projection neurons correlates with their burst timing during the song.

Functions of local neural circuits depend on their specific network structures, but how the networks are wired is unknown. We show that such structures can emerge during development through a self-organized process, during which the network is wired by neuron-by-neuron recruitment. This growth is facilitated by steady supply of immature neurons, which are highly excitable and plastic. We suggest that neuron maturation dynamics is an integral part of constructing local neural circuits.

Synchronous activity patterns in the dentate gyrus during immobility

The hippocampal dentate gyrus is an important relay conveying sensory information from the entorhinal cortex to the hippocampus proper. During exploration, the dentate gyrus has been proposed to act as a pattern separator. However, the dentate gyrus also shows structured activity during immobility and sleep. The properties of these activity patterns at cellular resolution, and their role in hippocampal-dependent memory processes have remained unclear. Using dual-color in vivo two-photon Ca²⁺ imaging, we show that in immobile mice dentate granule cells generate sparse, synchronized activity patterns associated with entorhinal cortex activation. These population events are structured and modified by changes in the environment; and they incorporate place- and speed cells. Importantly, they are more similar than expected by chance to population patterns evoked during self-motion. Using optogenetic inhibition, we show that granule cell activity is not only required during exploration, but also during immobility in order to form dentate gyrus-dependent spatial memories.

Compliant peripheral nerve interfaces

Peripheral nerve interfaces (PNIs) record and/or modulate neural activity of nerves, which are responsible for conducting sensory-motor information to and from the central nervous system, and for regulating the activity of inner organs. PNIs are used both in neuroscience research and in therapeutical applications such as precise closed-loop control of neuroprosthetic limbs, treatment of neuropathic pain and restoration of vital functions (e.g. breathing and bladder management). Implantable interfaces represent an attractive solution to directly access peripheral nerves and provide enhanced selectivity both in recording and in stimulation, compared to their non-invasive counterparts. Nevertheless, the long-term functionality of implantable PNIs is limited by tissue damage, which occurs at the implant-tissue interface, and is thus highly dependent on material properties, biocompatibility and implant design. Current research focuses on the development of mechanically compliant PNIs, which adapt to the anatomy and dynamic movements of nerves in the body thereby limiting foreign body response. In this paper, we review recent progress in the development of flexible and implantable PNIs, highlighting promising solutions related to materials selection and their associated fabrication methods, and integrated functions. We report on the variety of available interface designs (intraneural, extraneural and regenerative) and different modulation techniques (electrical, optical, chemical) emphasizing the main challenges associated with integrating such systems on compliant substrates.

Intrinsic plasticity and birdsong learning

Although information processing and storage in the brain is thought to be primarily orchestrated by synaptic plasticity, other neural mechanisms such as intrinsic plasticity are available. While a number of recent studies have described the plasticity of intrinsic excitability in several types of neurons, the significance of non-synaptic mechanisms in memory and learning remains elusive. After reviewing plasticity of intrinsic excitation in relation to learning and homeostatic mechanisms, we focus on the intrinsic properties of a class of basal-ganglia projecting song system neurons in zebra finch, how these related to each bird's unique learned song, how these properties change over development, and how they are maintained dynamically to rapidly change in response to auditory feedback perturbations. We place these results in the broader theme of learning and changes in intrinsic properties, emphasizing the computational implications of this form of plasticity, which are distinct from synaptic plasticity. The results suggest that exploring reciprocal interactions between intrinsic and network properties will be a fruitful avenue for understanding mechanisms of birdsong learning.

Coupling between fast and slow oscillator circuits in Cancer borealis is temperature-compensated

Coupled oscillatory circuits are ubiquitous in nervous systems. Given that most biological processes are temperature-sensitive, it is remarkable that the neuronal circuits of poikilothermic animals can maintain coupling across a wide range of temperatures. Within the stomatogastric ganglion (STG) of the crab, Cancer borealis, the fast pyloric rhythm (~1 Hz) and the slow gastric mill rhythm (~0.1 Hz) are precisely coordinated at ~11°C such that there is an integer number of pyloric cycles per gastric mill cycle (integer coupling). Upon increasing temperature from 7°C to 23°C, both oscillators showed similar temperature-dependent increases in cycle frequency, and integer coupling between the circuits was conserved. Thus, although both rhythms show temperature-dependent changes in rhythm frequency, the processes that couple these circuits maintain their coordination over a wide range of temperatures. Such robustness to temperature changes could be part of a toolbox of processes that enables neural circuits to maintain function despite global perturbations.

Autism-linked gene FoxP1 selectively regulates the cultural transmission of learned vocalizations

Autism spectrum disorders (ASDs) are characterized by impaired learning of social skills and language. Memories of how parents and other social models behave are used to guide behavioral learning. How ASD-linked genes affect the intertwined aspects of observational learning and behavioral imitation is not known. Here, we examine how disrupted expression of the ASD gene FOXP1, which causes severe impairments in speech and language learning, affects the cultural transmission of birdsong between adult and juvenile zebra finches. FoxP1 is widely expressed in striatal-projecting forebrain mirror neurons. Knockdown of FoxP1 in this circuit prevents juvenile birds from forming memories of an adult song model but does not interrupt learning how to vocally imitate a previously memorized song. This selective learning deficit is associated with potent disruptions to experience-dependent structural and synaptic plasticity in mirror neurons. Thus, FoxP1 regulates the ability to form memories essential to the cultural transmission of behavior.

Dynamic transcriptome landscape in the song nucleus HVC between juvenile and adult zebra finches

Male juvenile zebra finches learn to sing by imitating songs of adult males early in life. The development of the song control circuit and song learning and maturation are highly intertwined processes, involving gene expression, neurogenesis, circuit formation, synaptic modification, and sensory-motor learning. To better understand the genetic and genomic mechanisms underlying these events, we used RNA-Seq to examine genome-wide transcriptomes in the song control nucleus HVC of male juvenile (45 d) and adult (100 d) zebra finches. We report that gene groups related to axon guidance, RNA processing, lipid metabolism, and mitochondrial functions show enriched expression in juvenile HVC compared to the rest of the brain. As juveniles mature into adulthood, massive gene expression changes occur. Expression of genes related to amino acid metabolism, cell cycle, and mitochondrial function is reduced, accompanied by increased and enriched expression of genes with synaptic functions, including genes related to G-protein signaling, neurotransmitter receptors, transport of small molecules, and potassium channels. Unexpectedly, a group of genes with immune system functions is also developmentally regulated, suggesting potential roles in the development and functions of HVC. These data will serve as a rich resource for investigations into the development and function of a neural circuit that controls vocal behavior.

Brain Temperature Alters Contributions of Excitatory and Inhibitory Inputs to Evoked Field Potentials in the Rat Frontal Cortex

Changes in brain temperature have been reported to affect various brain functions. However, little is known about the effects of temperature on the neural activity at the network level, where multiple inputs are integrated. In this study, we recorded cortical evoked potentials while altering the local brain temperature in anesthetized rats. We delivered electrical stimulations to the midbrain dopamine area and measured the evoked potentials in the frontal cortex, the temperature of which was locally altered using a thermal control device. We focused on the maximum negative peaks, which was presumed to result mainly from polysynaptic responses, to examine the effect of local temperature on network activity. We showed that focal cortical cooling increased the amplitude of evoked potentials (negative correlation, >17°C); further cooling decreased their amplitude. This relationship would be graphically represented as an inverted-U-shaped curve. The pharmacological blockade of GABAergic inhibitory inputs eliminated the negative correlation (>17°C) and even showed a positive correlation when the concentration of GABA_A receptor antagonist was sufficiently high. Blocking the glutamatergic excitatory inputs decreased the amplitude but did not cause such inversion. Our results suggest that the negative correlation between the amplitude of evoked potentials and the near-physiological local temperature is caused by the alteration of the balance of contribution between excitatory and inhibitory inputs to the evoked potentials, possibly due to higher temperature sensitivity of inhibitory inputs.

A Functionally and Anatomically Bipartite Vocal Pattern Generator in the Rat Brain Stem

The mammalian vocal pattern generator is situated in the brainstem but its exact structure is debated. We mapped these circuits in rats by cooling and microstimulation. Local cooling disrupted call production above an anterior and a posterior brainstem position. Anterior cooling affected predominantly high-frequency calls, whereas posterior cooling affected low-frequency calls. Electrical microstimulation of the anterior part led to modulated high-frequency calls, whereas microstimulation of the posterior part led to flat, low-frequency calls. At intermediate positions cooling did not affect calls and stimulation did not elicit calls. The anterior region corresponds to a subsection of the parvicellular reticular formation that we term the vocalization parvicellular reticular formation (VoPaRt). The posterior vocalization sites coincide with the nucleus retroambiguus (NRA). VoPaRt and NRA neurons were very small and the VoPaRt was highly myelinated, suggestive of high-speed processing. Our data suggest an anatomically and functionally bipartite vocal pattern generator.

Variable but not random: temporal pattern coding in a songbird brain area necessary for song modification

Practice of a complex motor gesture involves motor exploration to attain a better match to target, but little is known about the neural code for such exploration. We examine spiking in a premotor area of the songbird brain critical for song modification and quantify correlations between spiking and time in the motor sequence. While isolated spikes code for time in song during performance of song to a female bird, extended strings of spiking and silence, particularly bursts, code for time in song during undirected (solo) singing, or "practice." Bursts code for particular times in song with more information than individual spikes, and this spike-spike synergy is significantly higher during undirected singing. The observed pattern information cannot be accounted for by a Poisson model with a matched time-varying rate, indicating that the precise timing of spikes in both bursts in undirected singing and isolated spikes in directed singing code for song with a temporal code. Temporal coding during practice supports the hypothesis that lateral magnocellular nucleus of the anterior nidopallium neurons actively guide song modification at local instances in time.NEW & NOTEWORTHY This paper shows that bursts of spikes in the songbird brain during practice carry information about the output motor pattern. The brain's code for song changes with social context, in performance versus practice. Synergistic combinations of spiking and silence code for time in the bird's song. This is one of the first uses of information theory to quantify neural information about a motor output. This activity may guide changes to the song.

Focal Cortical Surface Cooling is a Novel and Safe Method for Intraoperative Functional Brain Mapping

OBJECTIVE

Electric cortical stimulation (ECS) has been the gold standard for intraoperative functional mapping in neurosurgery, yet it carries the risk of induced seizures. We assess the safety of focal cortical cooling (CC) as a potential alternative to ECS.

METHODS

We reviewed 40 patients (13 with tumor and 27 with mesial temporal lobe epilepsy) who underwent intraoperative CC at the University of Iowa Hospital and Clinics (CC group), of whom 38 underwent ECS preceding CC. Intraoperative and postoperative seizure incidence, postoperative neurologic deficits, and new postoperative radiographic findings were collected to assess CC safety. Fifty-five patients who underwent ECS mapping without CC (ECS-alone group) were reviewed as a control cohort. Another 25 patients who underwent anterior temporal lobectomy (ATL) without CC or ECS (no ECS/no CC-ATL group) were also reviewed to evaluate long-term effects of CC.

RESULTS

Seventy-nine brain sites in the CC group were cooled, comprising inferior frontal gyrus (44%), precentral gyrus (39%), postcentral gyrus (6%), subcentral gyrus (4%), and superior temporal gyrus (6%). The incidence of intraoperative seizure(s) was 0% (CC group) and 3.6% (ECS-alone group). The incidence of seizure(s) within the first postoperative week did not significantly differ among CC (7.9%), ECS-alone (9.0%), and no ECS/no CC-ATL groups (12%). There was no significant difference in the incidence of postoperative radiographic change between CC (7.5%) and ECS-alone groups (5.5%). Long-term seizure outcome (Engel I+II) for mesial temporal epilepsy did not differ among CC (80%), ECS-alone (83.3%), and no ECS/no CC-ATL groups (83.3%).

CONCLUSIONS

CC when used as an intraoperative mapping technique is safe and may complement ECS.

Statistical structure of the trial-to-trial timing variability in synfire chains

Timing and its variability are crucial for behavior. Consequently, neural circuits that take part in the control of timing and in the measurement of temporal intervals have been the subject of much research. Here we provide an analytical and computational account of the temporal variability in what is perhaps the most basic model of a timing circuit-the synfire chain. First we study the statistical structure of trial-to-trial timing variability in a reduced but analytically tractable model: a chain of single integrate-and-fire neurons. We show that this circuit's variability is well described by a generative model consisting of local, global, and jitter components. We relate each of these components to distinct neural mechanisms in the model. Next we establish in simulations that these results carry over to a noisy homogeneous synfire chain. Finally, motivated by the fact that a synfire chain is thought to underlie the circuit that takes part in the control and timing of the zebra finch song, we present simulations of a biologically realistic synfire chain model of the zebra finch timekeeping circuit. We find the structure of trial-to-trial timing variability to be consistent with our previous findings and to agree with experimental observations of the song's temporal variability. Our study therefore provides a possible neuronal account of behavioral variability in zebra finches.

Persistence of tri-trophic interactions in seasonal environments

The interplay between species interactions and environmental variation is well-understood for pairwise interactions but not for multi-trophic interactions. Understanding how such interactions persist in a thermally variable environment is particularly important given that most biodiversity on the planet consists of ectotherms whose body temperature depends on the environmental temperature. Here we present a trait-based mathematical framework for investigating how tri-trophic food chains persist in seasonal environments. We report two key findings. First, the persistence of the tri-trophic interaction is enhanced if species at upper trophic levels (e.g. top predators) are more cold-adapted than those at lower levels (e.g. basal resources) by virtue of lower thermal optima, wider response breadths and lower mortality within the favourable temperature range. The important implication is that the assembly and persistence of multi-trophic interactions requires that species at lower trophic levels be somewhat maladapted to their ambient thermal environment, as in the case of recent invasions. Second, differential sensitivity to thermally varying environments provides a mechanistic explanation for the conflict of interest between the intermediate consumer and top predator. The same cold-adaptations that increase the consumer's ability to increase when rare deter the predator's ability to do so. Thus, being well-adapted to its thermal environment makes the intermediate consumer better able to acquire resources and avoid predators. We predict that the hierarchy in cold-adaptation should constrain the number of trophic levels that can be supported in a given thermal environment, and that ectotherm food chain lengths should increase with increasing latitude because larger-amplitude seasonal fluctuations generate more opportunities for species to diverge in their thermal optima.

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.

Neural Sequences as an Optimal Dynamical Regime for the Readout of Time

Converging evidence suggests that the brain encodes time through dynamically changing patterns of neural activity, including neural sequences, ramping activity, and complex spatiotemporal dynamics. However, the potential computational significance and advantage of these different regimes have remained unaddressed. We combined large-scale recordings and modeling to compare population dynamics between premotor cortex and striatum in mice performing a two-interval timing task. Conventional decoders revealed that the dynamics within each area encoded time equally well; however, the dynamics in striatum exhibited a higher degree of sequentiality. Analysis of premotor and striatal dynamics, together with a large set of simulated prototypical dynamical regimes, revealed that regimes with higher sequentiality allowed a biologically constrained artificial downstream network to better read out time. These results suggest that, although different strategies exist for encoding time in the brain, neural sequences represent an ideal and flexible dynamical regime for enabling downstream areas to read out this information.

Brain Lateralization: A Comparative Perspective

Comparative studies on brain asymmetry date back to the 19th century but then largely disappeared due to the assumption that lateralization is uniquely human. Since the reemergence of this field in the 1970s, we learned that left-right differences of brain and behavior exist throughout the animal kingdom and pay off in terms of sensory, cognitive, and motor efficiency. Ontogenetically, lateralization starts in many species with asymmetrical expression patterns of genes within the Nodal cascade that set up the scene for later complex interactions of genetic, environmental, and epigenetic factors. These take effect during different time points of ontogeny and create asymmetries of neural networks in diverse species. As a result, depending on task demands, left- or right-hemispheric loops of feedforward or feedback projections are then activated and can temporarily dominate a neural process. In addition, asymmetries of commissural transfer can shape lateralized processes in each hemisphere. It is still unclear if interhemispheric interactions depend on an inhibition/excitation dichotomy or instead adjust the contralateral temporal neural structure to delay the other hemisphere or synchronize with it during joint action. As outlined in our review, novel animal models and approaches could be established in the last decades, and they already produced a substantial increase of knowledge. Since there is practically no realm of human perception, cognition, emotion, or action that is not affected by our lateralized neural organization, insights from these comparative studies are crucial to understand the functions and pathologies of our asymmetric brain.

Neurotelemetry Reveals Putative Predictive Activity in HVC during Call-Based Vocal Communications in Zebra Finches

Premotor predictions facilitate vocal interactions. Here, we study such mechanisms in the forebrain nucleus HVC (proper name), a cortex-like sensorimotor area of songbirds, otherwise known for being essential for singing in zebra finches. To study the role of the HVC in calling interactions between male and female mates, we used wireless telemetric systems for simultaneous measurement of neuronal activity of male zebra finches and vocalizations of males and females that freely interact with each other. In a non-social context, male HVC neurons displayed stereotypic premotor activity in relation to active calling and showed auditory-evoked activity to hearing of played-back female calls. In a social context, HVC neurons displayed auditory-evoked activity to hearing of female calls only if that neuron showed activity preceding the upcoming female calls. We hypothesize that this activity preceding the auditory-evoked activity in the male HVC represents a neural correlate of behavioral anticipation, predictive activity that helps to coordinate vocal communication between social partners.SIGNIFICANCE STATEMENT Most social-living vertebrates produce large numbers of calls per day, and the calls have prominent roles in social interactions. Here, we show neuronal mechanisms that are active during call-based vocal communication of zebra finches, a highly social songbird species. HVC, a forebrain nucleus known for its importance in control of learned vocalizations of songbirds, displays predictive activity that may enable the male to adjust his own calling pattern to produce very fast sequences of male female call exchanges.

Effects of Cortical Cooling on Activity Across Layers of the Rat Barrel Cortex

Moderate cortical cooling is known to suppress slow oscillations and to evoke persistent cortical activity. However, the cooling-induced changes in electrical activity across cortical layers remain largely unknown. Here, we performed multi-channel local field potential (LFP) and multi-unit activity (MUA) recordings with linear silicone probes through the layers of single cortical barrel columns in urethane-anesthetized rats under normothermia (38°C) and during local cortical surface cooling (30°C). During cortically generated slow oscillations, moderate cortical cooling decreased delta wave amplitude, delta-wave occurrence, the duration of silent states, and delta wave-locked MUA synchronization. Moderate cortical cooling increased total time spent in the active state and decreased total time spent in the silent state. Cooling-evoked changes in the MUA firing rate in cortical layer 5 (L5) varied from increase to decrease across animals, and the polarity of changes in L5 MUA correlated with changes in total time spent in the active state. The decrease in temperature reduced MUA firing rates in all other cortical layers. Sensory-evoked MUA responses also decreased during cooling through all cortical layers. The cooling-dependent slowdown was detected at the fast time-scale with a decreased frequency of sensory-evoked high-frequency oscillations (HFO). Thus, moderate cortical cooling suppresses slow oscillations and desynchronizes neuronal activity through all cortical layers, and is associated with reduced firing across all cortical layers except L5, where cooling induces variable and non-consistent changes in neuronal firing, which are common features of the transition from slow-wave synchronization to desynchronized activity in the barrel cortex.

Regulation of vocal precision by noradrenergic modulation of a motor nucleus

Norepinephrine (NE) function is often implicated in regulating arousal levels. Recent theory suggests that the noradrenergic system also regulates the optimization of behavior with respect to reward maximization by controlling a switch between exploration and exploitation of the specific actions that yield greatest utility. We show in the songbird that NE can act directly on a cortical motor area and cause a switch between exploratory and exploitative behavior.

Mapping Functional Connectivity from the Dorsal Cortex to the Thalamus

Neural activity in the corticothalamic network is crucial for sensation, memory, decision, and action. Nevertheless, a systematic characterization of corticothalamic functional connectivity has not been achieved. Here, we developed a high throughput method to systematically map functional connections from the dorsal cortex to the thalamus in awake mice by combing optogenetic inactivation with multi-channel recording. Cortical inactivation resulted in a rapid reduction of thalamic activity, revealing topographically organized corticothalamic excitatory inputs. Cluster analysis showed that groups of neurons within individual thalamic nuclei exhibited distinct dynamics. The effects of inactivation evolved with time and were modulated by behavioral states. Furthermore, we found that a subset of thalamic neurons received convergent inputs from widespread cortical regions. Our results present a framework for collecting, analyzing, and presenting large electrophysiological datasets with region-specific optogenetic perturbations and serve as a foundation for further investigation of information processing in the corticothalamic pathway.

Hidden neural states underlie canary song syntax

Coordinated skills such as speech or dance involve sequences of actions that follow syntactic rules in which transitions between elements depend on the identity and order of past actions. Canary songs are comprised of repeated syllables, called phrases, and the ordering of these phrases follows long-range rules¹, where the choice of what to sing depends on song structure many seconds prior. The neural substrates that support these long-range correlations are unknown. Using miniature head-mounted microscopes and cell-type-specific genetic tools, we observed neural activity in the premotor nucleus HVC^2–4 as canaries explore various phrase sequences in their repertoire. We find neurons that encode past transitions, extending over 4 phrases and spanning up to 4 seconds and 40 syllables. These neurons preferentially encode past actions rather than future actions, can reflect more than a single song history, and occur mostly during the rare phrases that involve history-dependent transitions in song. These findings demonstrate that HVC dynamics includes “hidden states” not reflected in ongoing behavior – states that carry information about prior actions. These states provide a possible substrate to control syntax transitions governed by long-range rules.

Parting self from others: Individual and self-recognition in birds

Individual recognition is the ability to differentiate between conspecifics based on their individual features. It forms the basis of many complex communicative and social behaviours. Here, we review studies investigating individual recognition in the auditory and visual domain in birds. It is well established that auditory signals are used by many birds to discriminate conspecifics. In songbirds, the neuronal structures underpinning auditory recognition are associated with the song system. Individual recognition in the visual domain has mainly been explored in chickens and pigeons, and is less well understood. Currently it is unknown which visual cues birds use to identify conspecifics, and whether they have cortical areas dedicated to processing individual features. Moreover, whether birds can recognise themselves visually, as evidenced by mirror self-recognition, remains controversial. In the auditory domain, the responses of neurons in the song system suggest identification of the bird's own song. The surveyed behavioural and neural findings can provide a framework for more controlled investigations of individual recognition in birds and other species.

Cooling of Medial Septum Reveals Theta Phase Lag Coordination of Hippocampal Cell Assemblies

Hippocampal theta oscillations coordinate neuronal firing to support memory and spatial navigation. The medial septum (MS) is critical in theta generation by two possible mechanisms: either a unitary "pacemaker" timing signal is imposed on the hippocampal system, or it may assist in organizing target subcircuits within the phase space of theta oscillations. We used temperature manipulation of the MS to test these models. Cooling of the MS reduced both theta frequency and power and was associated with an enhanced incidence of errors in a spatial navigation task, but it did not affect spatial correlates of neurons. MS cooling decreased theta frequency oscillations of place cells and reduced distance-time compression but preserved distance-phase compression of place field sequences within the theta cycle. Thus, the septum is critical for sustaining precise theta phase coordination of cell assemblies in the hippocampal system, a mechanism needed for spatial memory.

Acetylcholine acts on songbird premotor circuitry to invigorate vocal output

Acetylcholine is well-understood to enhance cortical sensory responses and perceptual sensitivity in aroused or attentive states. Yet little is known about cholinergic influences on motor cortical regions. Here we use the quantifiable nature of birdsong to investigate how acetylcholine modulates the cortical (pallial) premotor nucleus HVC and shapes vocal output. We found that dialyzing the cholinergic agonist carbachol into HVC increased the pitch, amplitude, tempo and stereotypy of song, similar to the natural invigoration of song that occurs when males direct their songs to females. These carbachol-induced effects were associated with increased neural activity in HVC and occurred independently of basal ganglia circuitry. Moreover, we discovered that the normal invigoration of female-directed song was also accompanied by increased HVC activity and was attenuated by blocking muscarinic acetylcholine receptors. These results indicate that, analogous to its influence on sensory systems, acetylcholine can act directly on cortical premotor circuitry to adaptively shape behavior.

Inception of memories that guide vocal learning in the songbird

Animals learn many complex behaviors by emulating the behavior of more experienced individuals. This essential, yet still poorly understood, form of learning relies on the ability to encode lasting memories of observed behaviors. We identified a vocal-motor pathway in the zebra finch where memories that guide learning of song-element durations can be implanted. Activation of synapses in this pathway seeds memories that guide learning of song-element duration and can override learning from social interactions with other individuals. Genetic lesions of this circuit after memory formation, however, do not disrupt subsequent song imitation, which suggests that these memories are stored at downstream synapses. Thus, activity at these sensorimotor synapses can bypass learning from auditory and social experience and embed memories that guide learning of song timing.

Hemispheric asymmetry of calbindin-positive neurons is associated with successful song imitation

The plasticity that facilitates learning during critical (sensitive) periods in development is tightly regulated by inhibitory neurons. Song acquisition in birds is one example of a learning process that occurs during a sensitive period early in development. Sensory experience with a song 'tutor' during this sensitive period prunes excitatory and inhibitory synapses in the song production nucleus HVC (proper noun). Neurons in the caudomedial nidopallium (NCM), a secondary auditory region, lose their tutor song selectivity when gamma-aminobutyric acid (GABA) signaling is blocked. Given the importance of inhibition in the song learning process, we investigated whether individual differences in learning outcomes can be explained by the distribution of specific populations of (mostly) inhibitory neurons in HVC and NCM. We measured the densities of distinct neuronal populations (defined by their expression of the calcium-binding proteins calbindin, calretinin, and parvalbumin) in these two regions. We found that lateralization of calbindin-positive neurons was related to successful song learning: good learners were characterized by hemispheric asymmetry of calbindin-positive neurons in the medial NCM (fewer CB+ neurons in the left hemisphere), whereas poor learners did not show any asymmetry. In contrast, the density of all three neuronal populations in HVC did not differ between good and poor learners. These findings not only identify a specific (presumably) inhibitory cell type (calbindin-expressing neurons) that is related to song learning, but also emphasize the role of hemispheric asymmetry in auditory memory formation.

High-fidelity continuum modeling predicts avian voiced sound production

Voiced sound production is the primary form of acoustic communication in terrestrial vertebrates, particularly birds and mammals, including humans. Developing a causal physics-based model that ultimately links descending vocal motor control to tissue vibration and sound requires embodied approaches that include realistic representations of voice physiology. Here, we first implement and then experimentally test a high-fidelity three-dimensional (3D) continuum model for voiced sound production in birds. Driven by individual-based physiologically quantifiable inputs, combined with noninvasive inverse methods for tissue material parameterization, our model accurately predicts observed key vibratory and acoustic performance traits. These results demonstrate that realistic models lead to accurate predictions and support the continuum model approach as a critical tool toward a causal model of voiced sound production.

The neurobiology of innate and learned vocalizations in rodents and songbirds

Vocalizations are an important medium for sexual and social signaling in mammals and birds. In most mammals other than humans, vocalizations are specified by innate mechanisms and develop normally in the absence of auditory experience. By contrast, juvenile songbirds memorize and copy the songs of adult tutors, a process with many parallels to human speech learning. Despite the centrality of vocal learning to human speech, vocal production in humans as well as in songbirds exploits ancestral circuitry for innate vocalizations, and effective vocal communication depends on the fluent blending of innate and learned elements. This review covers recent advances in our understanding of central mechanisms for learned and innate vocalizations in birds and mice, including brainstem mechanisms that help to 'gate' vocalizations on or off, cortical involvement in learned and innate vocalizations, and the delineation of circuits that evaluate and reinforce song performance to facilitate vocal learning.

Latitudinal directionality in ectotherm invasion success

A striking pattern, seen in both fossil and extant taxa, is that tropical ectotherms are better at invading temperate habitats than vice versa. This is puzzling because tropical ectotherms, being thermal specialists, face a harsher abiotic environment and competition from temperate residents that are thermal generalists. We develop a mathematical framework to address this puzzle. We find that (i) tropical ectotherms can invade temperate habitats if they have higher consumption rates and lower mortality during warmer summers, (ii) stronger seasonal fluctuations at higher latitudes create more temporal niches, allowing coexistence of tropical invaders and temperate residents, and (iii) temperate ectotherms' failure to invade tropical habitats is due to greater mortality rather than lower competitive ability. Our framework yields predictions about population-level outcomes of invasion success based solely on species' trait responses to temperature. It provides a potential ecological explanation for why the tropics constitute both a cradle and a museum of biodiversity.

Manipulations of inhibition in cortical circuitry differentially affect spectral and temporal features of Bengalese finch song

The interplay between inhibition and excitation can regulate behavioral expression and control, including the expression of communicative behaviors like birdsong. Computational models postulate varying degrees to which inhibition within vocal motor circuitry influences birdsong, but few studies have tested these models by manipulating inhibition. Here we enhanced and attenuated inhibition in the cortical nucleus HVC (used as proper name) of Bengalese finches (Lonchura striata var. domestica). Enhancement of inhibition (with muscimol) in HVC dose-dependently reduced the amount of song produced. Infusions of higher concentrations of muscimol caused some birds to produce spectrally degraded songs, whereas infusions of lower doses of muscimol led to the production of relatively normal (nondegraded) songs. However, the spectral and temporal structures of these nondegraded songs were significantly different from songs produced under control conditions. In particular, muscimol infusions decreased the frequency and amplitude of syllables, increased various measures of acoustic entropy, and increased the variability of syllable structure. Muscimol also increased sequence durations and the variability of syllable timing and syllable sequencing. Attenuation of inhibition (with bicuculline) in HVC led to changes to song distinct from and often opposite to enhancing inhibition. For example, in contrast to muscimol, bicuculline infusions increased syllable amplitude, frequency, and duration and decreased the variability of acoustic features. However, like muscimol, bicuculline increased the variability of syllable sequencing. These data highlight the importance of inhibition to the production of stereotyped vocalizations and demonstrate that changes to neural dynamics within cortical circuitry can differentially affect spectral and temporal features of song.NEW & NOTEWORTHY We reveal that manipulations of inhibition in the cortical nucleus HVC affect the structure, timing, and sequencing of syllables in Bengalese finch song. Enhancing and blocking inhibition led to opposite changes to the acoustic structure and timing of vocalizations, but both caused similar changes to vocal sequencing. These data provide support for computational models of song control but also motivate refinement of existing models to account for differential effects on syllable structure, timing, and sequencing.