Mapping the functional connectivity of the mouse anteroventral cochlear nucleus Public Deposited

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  • March 20, 2019
  • Campagnola, Luke
    • Affiliation: School of Medicine, UNC Neuroscience Center, Neuroscience Curriculum
  • The cochlear nucleus is the first central processor of auditory information and provides afferent input to most of the major brainstem and midbrain auditory nuclei. Presently, the lack of detailed data describing connectivity within the circuitry of the cochlear nucleus poses a major barrier to understanding its role in auditory processing, and thus complicates attempts to understand the auditory system as a whole. We have applied a novel, quantitative approach to mapping local circuits in the anteroventral cochlear nucleus (AVCN) using laser-scanning photostimulation. This approach included the development of new software and techniques that will allow more efficient acquisition and analysis of functional connectivity. Evoked responses to glutamate uncaging were analyzed to measure the amplitude and kinetics of individual synaptic events, providing a detailed description of connectivity and synaptic properties. We found that the majority of cells, including all three AVCN principal cell types, receive input from both D-stellate and tuberculoventral cells. Additionally, a small fraction of cells receive inhibitory input from an unidentified cell population at the dorsal-medial boundary of the AVCN, or excitatory input from within the AVCN. In agreement with previous reports, AVCN cells integrate from tuberculoventral cells occupying a narrow corresponding isofrequency region of the dorsal cochlear nucleus. In contrast, D-stellate inputs to the same cells arise from a much larger area which spans a wider frequency range. Furthermore, T-stellate cells integrate these inputs from an area that spans twice the frequency range of that integrated by bushy cells. Our results suggest that inhibitory circuits, even from a single presynaptic class, have patterns of convergence for each cell type that can support different kinds of spectral and temporal processing.
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  • In Copyright
  • McCarthy, Ken D.
  • Doctor of Philosophy
Graduation year
  • 2013

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