An optical design enabling lightweight and large field-of-view head-mounted microscopes.

Here we present a fluorescence microscope light path that enables imaging, during free behavior, of thousands of neurons in mice and hundreds of neurons in juvenile songbirds. The light path eliminates traditional illumination optics, allowing for head-mounted microscopes that have both a lower weight and a larger field of view (FOV) than previously possible. Using this light path, we designed two microscopes: one optimized for FOV (~4 mm FOV; 1.4 g), and the other optimized for weight (1.0 mm FOV; 1.0 g).

SyConn2: dense synaptic connectivity inference for volume electron microscopy.

The ability to acquire ever larger datasets of brain tissue using volume electron microscopy leads to an increasing demand for the automated extraction of connectomic information. We introduce SyConn2, an open-source connectome analysis toolkit, which works with both on-site high-performance compute environments and rentable cloud computing clusters. SyConn2 was tested on connectomic datasets with more than 10 million synapses, provides a web-based visualization interface and makes these data amenable to complex anatomical and neuronal connectivity queries.

Growth and splitting of neural sequences in songbird vocal development.

Neural sequences are a fundamental feature of brain dynamics underlying diverse behaviours, but the mechanisms by which they develop during learning remain unknown. Songbirds learn vocalizations composed of syllables; in adult birds, each syllable is produced by a different sequence of action potential bursts in the premotor cortical area HVC. Here we carried out recordings of large populations of HVC neurons in singing juvenile birds throughout learning to examine the emergence of neural sequences. Early in vocal development, HVC neurons begin producing rhythmic bursts, temporally locked to a 'prototype' syllable. Different neurons are active at different latencies relative to syllable onset to form a continuous sequence. Through development, as new syllables emerge from the prototype syllable, initially highly overlapping burst sequences become increasingly distinct. We propose a mechanistic model in which multiple neural sequences can emerge from the growth and splitting of a common precursor sequence.

Support for a synaptic chain model of neuronal sequence generation.

In songbirds, the remarkable temporal precision of song is generated by a sparse sequence of bursts in the premotor nucleus HVC. To distinguish between two possible classes of models of neural sequence generation, we carried out intracellular recordings of HVC neurons in singing zebra finches (Taeniopygia guttata). We found that the subthreshold membrane potential is characterized by a large, rapid depolarization 5-10 ms before burst onset, consistent with a synaptically connected chain of neurons in HVC. We found no evidence for the slow membrane potential modulation predicted by models in which burst timing is controlled by subthreshold dynamics. Furthermore, bursts ride on an underlying depolarization of ∼10-ms duration, probably the result of a regenerative calcium spike within HVC neurons that could facilitate the propagation of activity through a chain network with high temporal precision. Our results provide insight into the fundamental mechanisms by which neural circuits can generate complex sequential behaviours.

Using temperature to analyse temporal dynamics in the songbird motor pathway.

Many complex behaviours, like speech or music, have a hierarchical organization with structure on many timescales, but it is not known how the brain controls the timing of behavioural sequences, or whether different circuits control different timescales of the behaviour. Here we address these issues by using temperature to manipulate the biophysical dynamics in different regions of the songbird forebrain involved in song production. We find that cooling the premotor nucleus HVC (formerly known as the high vocal centre) slows song speed across all timescales by up to 45 per cent but only slightly alters the acoustic structure, whereas cooling the downstream motor nucleus RA (robust nucleus of the arcopallium) has no observable effect on song timing. Our observations suggest that dynamics within HVC are involved in the control of song timing, perhaps through a chain-like organization. Local manipulation of brain temperature should be broadly applicable to the identification of neural circuitry that controls the timing of behavioural sequences and, more generally, to the study of the origin and role of oscillatory and other forms of brain dynamics in neural systems.

Wandering neuronal migration in the postnatal vertebrate forebrain.

Most non-mammalian vertebrate species add new neurons to existing brain circuits throughout life, a process thought to be essential for tissue maintenance, repair, and learning. How these new neurons migrate through the mature brain and which cues trigger their integration within a functioning circuit is not known. To address these questions, we used two-photon microscopy to image the addition of genetically labeled newly generated neurons into the brain of juvenile zebra finches. Time-lapse in vivo imaging revealed that the majority of migratory new neurons exhibited a multipolar morphology and moved in a nonlinear manner for hundreds of micrometers. Young neurons did not use radial glia or blood vessels as a migratory scaffold; instead, cells extended several motile processes in different directions and moved by somal translocation along an existing process. Neurons were observed migrating for ∼2 weeks after labeling injection. New neurons were observed to integrate in close proximity to the soma of mature neurons, a behavior that may explain the emergence of clusters of neuronal cell bodies in the adult songbird brain. These results provide direct, in vivo evidence for a wandering form of neuronal migration involved in the addition of new neurons in the postnatal brain.

Self-organization of songbird neural sequences during social isolation.

Behaviors emerge via a combination of experience and innate predispositions. As the brain matures, it undergoes major changes in cellular, network, and functional properties that can be due to sensory experience as well as developmental processes. In normal birdsong learning, neural sequences emerge to control song syllables learned from a tutor. Here, we disambiguate the role of tutor experience and development in neural sequence formation by delaying exposure to a tutor. Using functional calcium imaging, we observe neural sequences in the absence of tutoring, demonstrating that tutor experience is not necessary for the formation of sequences. However, after exposure to a tutor, pre-existing sequences can become tightly associated with new song syllables. Since we delayed tutoring, only half our birds learned new syllables following tutor exposure. The birds that failed to learn were the birds in which pre-tutoring neural sequences were most 'crystallized,' that is, already tightly associated with their (untutored) song.

Two distinct modes of forebrain circuit dynamics underlie temporal patterning in the vocalizations of young songbirds.

Accurate timing is a critical aspect of motor control, yet the temporal structure of many mature behaviors emerges during learning from highly variable exploratory actions. How does a developing brain acquire the precise control of timing in behavioral sequences? To investigate the development of timing, we analyzed the songs of young juvenile zebra finches. These highly variable vocalizations, akin to human babbling, gradually develop into temporally stereotyped adult songs. We find that the durations of syllables and silences in juvenile singing are formed by a mixture of two distinct modes of timing: a random mode producing broadly distributed durations early in development, and a stereotyped mode underlying the gradual emergence of stereotyped durations. Using lesions, inactivations, and localized brain cooling, we investigated the roles of neural dynamics within two premotor cortical areas in the production of these temporal modes. We find that LMAN (lateral magnocellular nucleus of the nidopallium) is required specifically for the generation of the random mode of timing and that mild cooling of LMAN causes an increase in the durations produced by this mode. On the contrary, HVC (used as a proper name) is required specifically for producing the stereotyped mode of timing, and its cooling causes a slowing of all stereotyped components. These results show that two neural pathways contribute to the timing of juvenile songs and suggest an interesting organization in the forebrain, whereby different brain areas are specialized for the production of distinct forms of neural dynamics.

Integration of cortical and pallidal inputs in the basal ganglia-recipient thalamus of singing birds.

The basal ganglia-recipient thalamus receives inhibitory inputs from the pallidum and excitatory inputs from cortex, but it is unclear how these inputs interact during behavior. We recorded simultaneously from thalamic neurons and their putative synaptically connected pallidal inputs in singing zebra finches. We find, first, that each pallidal spike produces an extremely brief (∼5 ms) pulse of inhibition that completely suppresses thalamic spiking. As a result, thalamic spikes are entrained to pallidal spikes with submillisecond precision. Second, we find that the number of thalamic spikes that discharge within a single pallidal interspike interval (ISI) depends linearly on the duration of that interval but does not depend on pallidal activity prior to the interval. In a detailed biophysical model, our results were not easily explained by the postinhibitory "rebound" mechanism previously observed in anesthetized birds and in brain slices, nor could most of our data be characterized as "gating" of excitatory transmission by inhibitory pallidal input. Instead, we propose a novel "entrainment" mechanism of pallidothalamic transmission that highlights the importance of an excitatory conductance that drives spiking, interacting with brief pulses of pallidal inhibition. Building on our recent finding that cortical inputs can drive syllable-locked rate modulations in thalamic neurons during singing, we report here that excitatory inputs affect thalamic spiking in two ways: by shortening the latency of a thalamic spike after a pallidal spike and by increasing thalamic firing rates within individual pallidal ISIs. We present a unifying biophysical model that can reproduce all known modes of pallidothalamic transmission--rebound, gating, and entrainment--depending on the amount of excitation the thalamic neuron receives.

A basal ganglia-forebrain circuit in the songbird biases motor output to avoid vocal errors.

In songbirds, as in mammals, basal ganglia-forebrain circuits are necessary for the learning and production of complex motor behaviors; however, the precise role of these circuits remains unknown. It has recently been shown that a basal ganglia-forebrain circuit in the songbird, which projects directly to vocal-motor circuitry, has a premotor function driving exploration necessary for vocal learning. It has also been hypothesized that this circuit, known as the anterior forebrain pathway (AFP), may generate an instructive signal that improves performance in the motor pathway. Here, we show that the output of the AFP directly implements a motor correction that reduces vocal errors. We use disruptive auditory feedback, contingent on song pitch, to induce learned changes in song structure over the course of hours and find that reversible inactivation of the output of the AFP produces an immediate regression of these learned changes. Thus, the AFP is involved in generating an error-reducing bias, which could increase the efficiency of vocal exploration and instruct synaptic changes in the motor pathway. We also find that learned changes in the song generated by the AFP are incorporated into the motor pathway within 1 day. Our observations support a view that basal ganglia-related circuits directly implement behavioral adaptations that minimize errors and subsequently stabilize these adaptations by training premotor cortical areas.

Singing-related neural activity distinguishes two putative pallidal cell types in the songbird basal ganglia: comparison to the primate internal and external pallidal segments.

The songbird area X is a basal ganglia homolog that contains two pallidal cell types-local neurons that project within the basal ganglia and output neurons that project to the thalamus. Based on these projections, it has been proposed that these classes are structurally homologous to the primate external (GPe) and internal (GPi) pallidal segments. To test the hypothesis that the two area X pallidal types are functionally homologous to GPe and GPi neurons, we recorded from neurons in area X of singing juvenile male zebra finches, and directly compared their firing patterns to neurons recorded in the primate pallidus. In area X, we found two cell classes that exhibited high firing (HF) rates (>60 Hz) characteristic of pallidal neurons. HF-1 neurons, like most GPe neurons we examined, exhibited large firing rate modulations, including bursts and long pauses. In contrast, HF-2 neurons, like GPi neurons, discharged continuously without bursts or long pauses. To test whether HF-2 neurons were the output neurons that project to the thalamus, we next recorded directly from pallidal axon terminals in thalamic nucleus DLM, and found that all terminals exhibited singing-related firing patterns indistinguishable from HF-2 neurons. Our data show that singing-related neural activity distinguishes two putative pallidal cell types in area X: thalamus-projecting neurons that exhibit activity similar to the primate GPi, and non-thalamus-projecting neurons that exhibit activity similar to the primate GPe. These results suggest that song learning in birds and motor learning in mammals use conserved basal ganglia signaling strategies.

Learning to breathe and sing: development of respiratory-vocal coordination in young songbirds.

How do animals with learned vocalizations coordinate vocal production with respiration? Songbirds such as the zebra finch learn their songs, beginning with highly variable babbling vocalizations known as subsong. After several weeks of practice, zebra finches are able to produce a precisely timed pattern of syllables and silences, precisely coordinated with expiratory and inspiratory pulses (Franz M, Goller F. J Neurobiol 51: 129-141, 2002). While respiration in adult song is well described, relatively little is known about respiratory patterns in subsong or about the processes by which respiratory and vocal patterns become coordinated. To address these questions, we recorded thoracic air sac pressure in juvenile zebra finches prior to the appearance of any consistent temporal or acoustic structure in their songs. We found that subsong contains brief inspiratory pulses (50 ms) alternating with longer pulses of sustained expiratory pressure (50-500 ms). In striking contrast to adult song, expiratory pulses often contained multiple (0-8) variably timed syllables separated by expiratory gaps and were only partially vocalized. During development, expiratory pulses became shorter and more stereotyped in duration with shorter and fewer nonvocalized parts. These developmental changes eventually resulted in the production of a single syllable per expiratory pulse and a single inspiratory pulse filling each gap, forming a coordinated sequence similar to that of adult song. To examine the role of forebrain song-control nuclei in the development of respiratory patterns, we performed pressure recordings before and after lesions of nucleus HVC (proper name) and found that this manipulation reverses the developmental trends in measures of the respiratory pattern.

Vocal babbling in songbirds requires the basal ganglia-recipient motor thalamus but not the basal ganglia.

Young songbirds produce vocal "babbling," and the variability of their songs is thought to underlie a process of trial-and-error vocal learning. It is known that this exploratory variability requires the "cortical" component of a basal ganglia (BG) thalamocortical loop, but less understood is the role of the BG and thalamic components in this behavior. We found that large bilateral lesions to the songbird BG homolog Area X had little or no effect on song variability during vocal babbling. In contrast, lesions to the BG-recipient thalamic nucleus DLM (medial portion of the dorsolateral thalamus) largely abolished normal vocal babbling in young birds and caused a dramatic increase in song stereotypy. These findings support the idea that the motor thalamus plays a key role in the expression of exploratory juvenile behaviors during learning.

Changes in the neural control of a complex motor sequence during learning.

The acquisition of complex motor sequences often proceeds through trial-and-error learning, requiring the deliberate exploration of motor actions and the concomitant evaluation of the resulting performance. Songbirds learn their song in this manner, producing highly variable vocalizations as juveniles. As the song improves, vocal variability is gradually reduced until it is all but eliminated in adult birds. In the present study we examine how the motor program underlying such a complex motor behavior evolves during learning by recording from the robust nucleus of the arcopallium (RA), a motor cortex analog brain region. In young birds, neurons in RA exhibited highly variable firing patterns that throughout development became more precise, sparse, and bursty. We further explored how the developing motor program in RA is shaped by its two main inputs: LMAN, the output nucleus of a basal ganglia-forebrain circuit, and HVC, a premotor nucleus. Pharmacological inactivation of LMAN during singing made the song-aligned firing patterns of RA neurons adultlike in their stereotypy without dramatically affecting the spike statistics or the overall firing patterns. Removing the input from HVC, on the other hand, resulted in a complete loss of stereotypy of both the song and the underlying motor program. Thus our results show that a basal ganglia-forebrain circuit drives motor exploration required for trial-and-error learning by adding variability to the developing motor program. As learning proceeds and the motor circuits mature, the relative contribution of LMAN is reduced, allowing the premotor input from HVC to drive an increasingly stereotyped song.

Singing-related neural activity distinguishes four classes of putative striatal neurons in the songbird basal ganglia.

The striatum-the primary input nucleus of the basal ganglia-plays a major role in motor control and learning. Four main classes of striatal neuron are thought to be essential for normal striatal function: medium spiny neurons, fast-spiking interneurons, cholinergic tonically active neurons, and low-threshold spiking interneurons. However, the nature of the interaction of these neurons during behavior is poorly understood. The songbird area X is a specialized striato-pallidal basal ganglia nucleus that contains two pallidal cell types as well as the same four cell types found in the mammalian striatum. We recorded 185 single units in Area X of singing juvenile birds and, based on singing-related firing patterns and spike waveforms, find six distinct cell classes--two classes of putative pallidal neuron that exhibited a high spontaneous firing rate (> 60 Hz), and four cell classes that exhibited low spontaneous firing rates characteristic of striatal neurons. In this study, we examine in detail the four putative striatal cell classes. Type-1 neurons were the most frequently encountered and exhibited sparse temporally precise singing-related activity. Type-2 neurons were distinguished by their narrow spike waveforms and exhibited brief, high-frequency bursts during singing. Type-3 neurons were tonically active and did not burst, whereas type-4 neurons were inactive outside of singing and during singing generated long high-frequency bursts that could reach firing rates over 1 kHz. Based on comparison to the mammalian literature, we suggest that these four putative striatal cell classes correspond, respectively, to the medium spiny neurons, fast-spiking interneurons, tonically active neurons, and low-threshold spiking interneurons that are known to reside in area X.

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.

Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience.

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here, we describe a software toolbox-called seqNMF-with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral datas. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.

Vocal experimentation in the juvenile songbird requires a basal ganglia circuit.

Songbirds learn their songs by trial-and-error experimentation, producing highly variable vocal output as juveniles. By comparing their own sounds to the song of a tutor, young songbirds gradually converge to a stable song that can be a remarkably good copy of the tutor song. Here we show that vocal variability in the learning songbird is induced by a basal-ganglia-related circuit, the output of which projects to the motor pathway via the lateral magnocellular nucleus of the nidopallium (LMAN). We found that pharmacological inactivation of LMAN dramatically reduced acoustic and sequence variability in the songs of juvenile zebra finches, doing so in a rapid and reversible manner. In addition, recordings from LMAN neurons projecting to the motor pathway revealed highly variable spiking activity across song renditions, showing that LMAN may act as a source of variability. Lastly, pharmacological blockade of synaptic inputs from LMAN to its target premotor area also reduced song variability. Our results establish that, in the juvenile songbird, the exploratory motor behavior required to learn a complex motor sequence is dependent on a dedicated neural circuit homologous to cortico-basal ganglia circuits in mammals.

Computational training for the next generation of neuroscientists.

Neuroscience research has become increasingly reliant upon quantitative and computational data analysis and modeling techniques. However, the vast majority of neuroscientists are still trained within the traditional biology curriculum, in which computational and quantitative approaches beyond elementary statistics may be given little emphasis. Here we provide the results of an informal poll of computational and other neuroscientists that sought to identify critical needs, areas for improvement, and educational resources for computational neuroscience training. Motivated by this survey, we suggest steps to facilitate quantitative and computational training for future neuroscientists.

Rhythmic syllable-related activity in a songbird motor thalamic nucleus necessary for learned vocalizations.

Birdsong is a complex behavior that exhibits hierarchical organization. While the representation of singing behavior and its hierarchical organization has been studied in some detail in avian cortical premotor circuits, our understanding of the role of the thalamus in adult birdsong is incomplete. Using a combination of behavioral and electrophysiological studies, we seek to expand on earlier work showing that the thalamic nucleus Uvaeformis (Uva) is necessary for the production of stereotyped, adult song in zebra finch (Taeniopygia guttata). We confirm that complete bilateral lesions of Uva abolish singing in the 'directed' social context, but find that in the 'undirected' social context, such lesions result in highly variable vocalizations similar to early babbling song in juvenile birds. Recordings of neural activity in Uva reveal strong syllable-related modulation, maximally active prior to syllable onsets and minimally active prior to syllable offsets. Furthermore, both song and Uva activity exhibit a pronounced coherent modulation at 10Hz-a pattern observed in downstream premotor areas in adult and, even more prominently, in juvenile birds. These findings are broadly consistent with the idea that Uva is critical in the sequential activation of behavioral modules in HVC.