Publications by authors named "Michale S Fee"

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.

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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.

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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.

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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.

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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.

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The songbird system has shed light on how the brain produces precisely timed behavioral sequences, and how the brain implements reinforcement learning (RL). RL is a powerful strategy for learning what action to produce in each state, but requires a unique representation of the states involved in the task. Songbird RL circuitry is thought to operate using a representation of each moment within song syllables, consistent with the sparse sequential bursting of neurons in premotor cortical nucleus HVC.

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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.

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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).

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Songbirds learn and produce complex sequences of vocal gestures. Adult birdsong requires premotor nucleus HVC, in which projection neurons (PNs) burst sparsely at stereotyped times in the song. It has been hypothesized that PN bursts, as a population, form a continuous sequence, while a different model of HVC function proposes that both HVC PN and interneuron activity is tightly organized around motor gestures.

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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.

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The zebra finch is an important model for investigating the neural mechanisms that underlie vocal production and learning. Previous anatomical and gene expression studies have identified an interconnected set of brain areas in this organism that are important for singing. To advance our understanding of how these various brain areas act together to learn and produce a highly stereotyped song, it is necessary to record the activity of individual neurons during singing.

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Many learned motor behaviors are acquired by comparing ongoing behavior with an internal representation of correct performance, rather than using an explicit external reward. For example, juvenile songbirds learn to sing by comparing their song with the memory of a tutor song. At present, the brain regions subserving song evaluation are not known.

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Songbirds have emerged as an excellent model system to understand the neural basis of vocal and motor learning. Like humans, songbirds learn to imitate the vocalizations of their parents or other conspecific "tutors." Young songbirds learn by comparing their own vocalizations to the memory of their tutor song, slowly improving until over the course of several weeks they can achieve an excellent imitation of the tutor.

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Reinforcement learning requires the convergence of signals representing context, action, and reward. While models of basal ganglia function have well-founded hypotheses about the neural origin of signals representing context and reward, the function and origin of signals representing action are less clear. Recent findings suggest that exploratory or variable behaviors are initiated by a wide array of 'action-generating' circuits in the midbrain, brainstem, and cortex.

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The basal ganglia (BG)-recipient thalamus controls motor output but it remains unclear how its activity is regulated. Several studies report that thalamic activation occurs via disinhibition during pauses in the firing of inhibitory pallidal inputs from the BG. Other studies indicate that thalamic spiking is triggered by pallidal inputs via post-inhibitory 'rebound' calcium spikes.

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The song of a male zebra finch is a stereotyped motor sequence whose tempo varies with social context--whether or not the song is directed at a female bird--as well as with the time of day. The neural mechanisms underlying these changes in tempo are unknown. Here we show that brain temperature recorded in freely behaving male finches exhibits a global increase in response to the presentation of a female bird.

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In its simplest formulation, reinforcement learning is based on the idea that if an action taken in a particular context is followed by a favorable outcome, then, in the same context, the tendency to produce that action should be strengthened, or reinforced. While reinforcement learning forms the basis of many current theories of basal ganglia (BG) function, these models do not incorporate distinct computational roles for signals that convey context, and those that convey what action an animal takes. Recent experiments in the songbird suggest that vocal-related BG circuitry receives two functionally distinct excitatory inputs.

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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.

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The pallido-recipient thalamus transmits information from the basal ganglia to the cortex and is critical for motor initiation and learning. Thalamic activity is strongly inhibited by pallidal inputs from the basal ganglia, but the role of nonpallidal inputs, such as excitatory inputs from cortex, remains unclear. We simultaneously recorded from presynaptic pallidal axon terminals and postsynaptic thalamocortical neurons in a basal ganglia-recipient thalamic nucleus that is necessary for vocal variability and learning in zebra finches.

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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.

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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.

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Learned motor behaviors require descending forebrain control to be coordinated with midbrain and brainstem motor systems. In songbirds, such as the zebra finch, regular breathing is controlled by brainstem centers, but when the adult songbird begins to sing, its breathing becomes tightly coordinated with forebrain-controlled vocalizations. The periods of silence (gaps) between song syllables are typically filled with brief breaths, allowing the bird to sing uninterrupted for many seconds.

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Where are the 'prime movers' that control behavior? Which circuits in the brain control the order in which individual motor gestures of a learned behavior are generated, and the speed at which they progress? Here we describe two techniques recently applied to localizing and characterizing the circuitry underlying the generation of vocal sequences in the songbird. The first utilizes small, localized, temperature changes in the brain to perturb the speed of neural dynamics. The second utilizes intracellular manipulation of membrane potential in the freely behaving animal to perturb the dynamics within a single neuron.

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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).

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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.

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