Neuroscience
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The fruit fly Drosophila melanogaster is ideally suited for investigating the neural circuit basis of behavior. Due to the simplicity and genetic tractability of the fly brain, neurons and circuits are identifiable across animals. Additionally, a large set of transgenic lines has been developed with the aim of specifically labeling small subsets of neurons and manipulating them in sophisticated ways. ⋯ Thus, the fly brain is an attractive system in which to explore both computations and mechanisms underlying behavior at levels spanning from genes through neurons to circuits. This review summarizes the advantages Drosophila offers in achieving this objective. A recent neurophysiology study on olfactory behavior is also introduced to demonstrate the effectiveness of these advantages.
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Selection of a model organism creates tension between competing constraints. The recent explosion of modern molecular techniques has revolutionized the analysis of neural systems in organisms that are amenable to genetic techniques. Yet, the non-human primate remains the gold-standard for the analysis of the neural basis of behavior, and as a bridge to the operation of the human brain. ⋯ Here, we review experiments and computational studies on a circuit function called "neural integration" that occurs in the brainstems of larval zebrafish, primates, and species "in between". We show that analysis of circuit structure using modern molecular and imaging approaches in zebrafish has remarkable explanatory power for details of the responses of integrator neurons in the monkey. The combination of research from the two species has led to a much stronger hypothesis for the implementation of the neural integrator than could have been achieved using either species alone.
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Can the human brain itself serve as a model for a systems neuroscience approach to understanding the human brain? After all, how the brain is able to create the richness and complexity of human behavior is still largely mysterious. What better choice to study that complexity than to study it in humans? However, measurements of brain activity typically need to be made non-invasively which puts severe constraints on what can be learned about the internal workings of the brain. ⋯ Resting both on quantitative measurements and considerations of what is known through animal models, we concluded that weighting of sensory signals by the magnitude of their response is a neural mechanism for efficient selection of sensory signals and consequent improvements in behavioral performance with attention. While animal models have many technical advantages over studying the brain in humans, we believe that human systems neuroscience should endeavor to validate, replicate and extend basic knowledge learned from animal model systems and thus form a bridge to understanding how the brain creates the complex and rich cognitive capacities of humans.
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What do animals hear? While it remains challenging to adequately assess sensory perception in animal models, it is important to determine perceptual abilities in model systems to understand how physiological processes and plasticity relate to perception, learning, and cognition. Here we discuss hearing in rodents, reviewing previous and recent behavioral experiments querying acoustic perception in rats and mice, and examining the relation between behavioral data and electrophysiological recordings from the central auditory system. We focus on measurements of critical bands, which are psychoacoustic phenomena that seem to have a neural basis in the functional organization of the cochlea and the inferior colliculus. We then discuss how behavioral training, brain stimulation, and neuropathology impact auditory processing and perception.
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Many motor behaviors, from walking to speaking, are acquired through experience, in particular, through trial-and-error learning. The acquisition and maintenance of such motor behaviors in a wide range of species, including humans, appear to depend on cortical-basal ganglia circuits. In this review, we discuss recent studies in songbirds that have been pivotal in informing our current understanding of motor learning and cortical-basal ganglia function. ⋯ Computational and experimental studies highlight the importance of vocal motor variability as the substrate upon which reinforcement mechanisms could operate to shape developing song and to maintain adult song. Recent studies in songbirds indicate that this vocal motor variability is actively generated and modulated by a highly specialized cortical-basal ganglia circuit evolved for a single behavior, song. We argue that these and other recent findings illustrate how the tight association between a specialized neural circuit and a natural behavior make songbirds a unique and powerful model in which to investigate the neural substrates of motor learning and plasticity.