Journal of Comparative Physiology A

, Volume 188, Issue 11–12, pp 961–980 | Cite as

A framework for integrating the songbird brain

  •  E. Jarvis
  •  V. Smith
  •  K. Wada
  •  M. Rivas
  •  M. McElroy
  •  T. Smulders
  •  P. Carninci
  •  Y. Hayashizaki
  •  F. Dietrich
  •  X. Wu
  •  P. McConnell
  •  J. Yu
  •  P. Wang
  •  A. Hartemink
  •  S. Lin
Molecular-based Studies in Songbirds

Abstract.

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.

Bayesian network cDNA microarray improvement Multielectrode array Neural network Zebra finch 

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Copyright information

© Springer-Verlag 2002

Authors and Affiliations

  •  E. Jarvis
    • 1
  •  V. Smith
    • 1
  •  K. Wada
    • 1
  •  M. Rivas
    • 2
  •  M. McElroy
    • 1
  •  T. Smulders
    • 1
  •  P. Carninci
    • 3
  •  Y. Hayashizaki
    • 4
  •  F. Dietrich
    • 5
  •  X. Wu
    • 5
  •  P. McConnell
    • 6
  •  J. Yu
    • 7
  •  P. Wang
    • 7
  •  A. Hartemink
    • 8
  •  S. Lin
    • 6
  1. 1.Department of Neurobiology, Box 3209, Duke University Medical Center, Durham, NC 27710, USA
  2. 2.Department of Cell Biology, Box 3709, Duke University Medical Center, Durham, NC 27710, USA
  3. 3.Genome Science Laboratory, Riken Wako Main Campus, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
  4. 4.Laboratory for Genome Exploration Research Group, RIKEN Genomic Science Center (GSC), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
  5. 5.Duke Center for Genome Technology, Duke University Medical Center, Box 3568, Durham, NC 27710, USA
  6. 6.Duke Bioinformatics Shared Resource, Duke University Medical Center, Box 3958, Durham, NC 27710, USA
  7. 7.Department of Electrical and Computer Engineering, Duke University, Box 90291, Durham, NC 27708, USA
  8. 8.Department of Computer Science, Duke University, Box 90129, Durham, NC 27708, USA

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