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Publication : Parvalbumin-expressing inhibitory interneurons in auditory cortex are well-tuned for frequency.

First Author  Moore AK Year  2013
Journal  J Neurosci Volume  33
Issue  34 Pages  13713-23
PubMed ID  23966693 Mgi Jnum  J:201325
Mgi Id  MGI:5513025 Doi  10.1523/JNEUROSCI.0663-13.2013
Citation  Moore AK, et al. (2013) Parvalbumin-expressing inhibitory interneurons in auditory cortex are well-tuned for frequency. J Neurosci 33(34):13713-23
abstractText  In the auditory cortex, synaptic inhibition is known to be involved in shaping receptive fields, enhancing temporal precision, and regulating gain. Cortical inhibition is provided by local GABAergic interneurons, which comprise 10-20% of the cortical population and can be separated into numerous subclasses. The morphological and physiological diversity of interneurons suggests that these different subclasses have unique roles in sound processing; however, these roles are yet unknown. Understanding the receptive field properties of distinct inhibitory cell types will be critical to elucidating their computational function in cortical circuits. Here we characterized the tuning and response properties of parvalbumin-positive (PV+) interneurons, the largest inhibitory subclass. We used channelrhodopsin-2 (ChR2) as an optogenetic tag to identify PV+ and PV- neurons in vivo in transgenic mice. In contrast to PV+ neurons in mouse visual cortex, which are broadly tuned for orientation, we found that auditory cortical PV+ neurons were well tuned for frequency, although very tightly tuned PV+ cells were uncommon. This suggests that PV+ neurons play a minor role in shaping frequency tuning, and is consistent with the idea that PV+ neurons nonselectively pool input from the local network. PV+ interneurons had shallower response gain and were less intensity-tuned than PV- neurons, suggesting that PV+ neurons provide dynamic gain control and shape intensity tuning in auditory cortex. PV+ neurons also had markedly faster response latencies than PV- neurons, consistent with a computational role in enhancing the temporal precision of cortical responses.
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