Transgenic Mouse Lines Subdivide Medial Vestibular Nucleus Neurons into Discrete, Neurochemically Distinct Populations
Open Access
- 28 February 2007
- journal article
- Published by Society for Neuroscience in Journal of Neuroscience
- Vol. 27 (9) , 2318-2330
- https://doi.org/10.1523/jneurosci.4322-06.2007
Abstract
The identification of neuron types within circuits is fundamental to understanding their relevance to behavior. In the vestibular nuclei, several classes of neurons have been definedin vivoon the basis of their activity during behavior, but it is unclear how those types correspond to neurons identified in slice preparations. By targeting recordings to neurons labeled in transgenic mouse lines, this study reveals that the continuous distribution of intrinsic parameters observed in medial vestibular nucleus (MVN) neurons can be neatly subdivided into two populations of neurons, one of which is GABAergic and the other of which is exclusively glycinergic or glutamatergic. In slice recordings, GABAergic neurons labeled in the EGFP (enhanced green fluorescent protein)-expressing inhibitory neuron (GIN) line displayed lower maximum firing rates (<250 Hz) than glycinergic and glutamatergic neurons labeled in the yellow fluorescent protein-16 (YFP-16) line (up to 500 Hz). In contrast to cortical and hippocampal interneurons, GABAergic MVN neurons exhibited wider action potentials than glutamatergic (and glycinergic) neurons. Responses to current injection differed between the neurons labeled in the two lines, with GIN neurons modulating their firing rates over a smaller input range, adapting less during steady depolarization, and exhibiting less rebound firing than YFP-16 neurons. These results provide a scheme for robust classification of unidentified MVN neurons by their physiological properties. Finally, dye labeling in slices shows that both GABAergic and glycinergic neurons project to the contralateral vestibular nuclei, indicating that commissural inhibition is accomplished through at least two processing streams with differential input and output properties.Keywords
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