A framework for integrating the songbird brain.
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2002-12
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Biological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird vocal communication system is ideal for such integration due to many years of ethological investigation and a discreet dedicated brain network. Here we announce the beginnings of a songbird brain integrative project that involves high-throughput, molecular, anatomical, electrophysiological and behavioral levels of analysis. We first formed a rationale for inclusion of specific biological levels of analysis, then developed high-throughput molecular technologies on songbird brains, developed technologies for combined analysis of electrophysiological activity and gene regulation in awake behaving animals, and developed bioinformatic tools that predict causal interactions within and between biological levels of organization. This integrative brain project is fitting for the interdisciplinary approaches taken in the current songbird issue of the Journal of Comparative Physiology A and is expected to be conducive to deciphering how brains generate and perceive complex behaviors.
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Jarvis, ED, VA Smith, K Wada, MV Rivas, M McElroy, TV Smulders, P Carninci, Y Hayashizaki, et al. (2002). A framework for integrating the songbird brain. J Comp Physiol A Neuroethol Sens Neural Behav Physiol, 188(11-12). pp. 961–980. 10.1007/s00359-002-0358-y Retrieved from https://hdl.handle.net/10161/11222.
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Erich David Jarvis
Dr. Jarvis' laboratory studies the neurobiology of vocal communication. Emphasis is placed on the molecular pathways involved in the perception and production of learned vocalizations. They use an integrative approach that combines behavioral, anatomical, electrophysiological and molecular biological techniques. The main animal model used is songbirds, one of the few vertebrate groups that evolved the ability to learn vocalizations. The generality of the discoveries is tested in other vocal learning orders, such as parrots and hummingbirds, as well as non-vocal learners, such as pigeons and non-human primates. Some of the questions require performing behavior/molecular biology experiments in freely ranging animals, such as hummingbirds in tropical forest of Brazil. Recent results show that in songbirds, parrots and hummingbirds, perception and production of song are accompanied by anatomically distinct patterns of gene expression. All three groups were found to exhibit vocally-activated gene expression in exactly 7 forebrain nuclei that are very similar to each other. These structures for vocal learning and production are thought to have evolved independently within the past 70 million years, since they are absent from interrelated non-vocal learning orders. One structure, Area X of the basal ganglia's striatum in songbirds, shows large differential gene activation depending on the social context in which the bird sings. These differences may reflect a semantic content of song, perhaps similar to human language.
The overall goal of the research is to advance knowledge of the neural mechanisms for vocal learning and basic mechanisms of brain function. These goals are further achieved by combined collaborative efforts with the laboratories of Drs. Mooney and Nowicki at Duke University, who study respectively behavior and electrophysiological aspects of songbird vocal communication.
Alexander J. Hartemink
Computational biology, machine learning, Bayesian statistics, transcriptional regulation, genomics and epigenomics, graphical models, Bayesian networks, hidden Markov models, systems biology, computational neurobiology, classification, feature selection
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