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  EM connectomics reveals axonal target variation in a sequence-generating network

Kornfeld, J., Benezra, S. E., Narayanan, R. T., Svara, F., Egger, R., Oberlaender, M., et al. (2017). EM connectomics reveals axonal target variation in a sequence-generating network. eLife, 6: e24364. doi:10.7554/eLife.24364.

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 Creators:
Kornfeld, Jörgen1, Author           
Benezra, Sam E.2, Author
Narayanan, Rajeevan T.2, Author
Svara, Fabian1, Author           
Egger, Robert2, Author
Oberlaender, Marcel2, Author
Denk, Winfried1, Author           
Long, Michael A.2, Author
Affiliations:
1Department: Electrons-Photons-Neurons / Denk, MPI of Neurobiology, Max Planck Society, ou_1128546              
2external, ou_persistent22              

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Free keywords: IDENTIFIED HVC NEURONS; ZEBRA FINCH; VISUAL-CORTEX; NUCLEUS HVC; RESOLUTION CONNECTOMICS; CORTICAL-NEURONS; IN-VIVO; SONG; MOTOR; MODELLife Sciences & Biomedicine - Other Topics;
 Abstract: The sequential activation of neurons has been observed in various areas of the brain, but in no case is the underlying network structure well understood. Here we examined the circuit anatomy of zebra finch HVC, a cortical region that generates sequences underlying the temporal progression of the song. We combined serial block-face electron microscopy with light microscopy to determine the cell types targeted by HVC(RA) neurons, which control song timing. Close to their soma, axons almost exclusively targeted inhibitory interneurons, consistent with what had been found with electrical recordings from pairs of cells. Conversely, far from the soma the targets were mostly other excitatory neurons, about half of these being other HVC(RA) cells. Both observations are consistent with the notion that the neural sequences that pace the song are generated by global synaptic chains in HVC embedded within local inhibitory networks.

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Language(s): eng - English
 Dates: 2017-04-21
 Publication Status: Published online
 Pages: 20
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: 000399792700001
DOI: 10.7554/eLife.24364
 Degree: -

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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 6 Sequence Number: e24364 Start / End Page: - Identifier: Other: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X