Journal
JOURNAL OF NEUROSCIENCE
Volume 31, Issue 41, Pages 14639-14653Publisher
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.0086-11.2011
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Funding
- Japan Society for the Promotion of Science (JPS) [23300149, 23700492]
- Grants-in-Aid for Scientific Research [23300149, 23700492] Funding Source: KAKEN
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Recent evidence indicates the existence of pyramidal cells (PCs) and interneurons with nontrivial tuning characteristics for sound attributes in the primary auditory cortex (A1) of mammals. These neurons are functionally distributed into layers and sparsely organized at a small scale. However, their topological locations at a large scale in A1 have not yet been investigated. Furthermore, these neurons are usually classified from fine maps of attribute-dependent spiking activity, and not much attention is paid to population postsynaptic potentials related to their activity. We used extracellular recordings obtained from multiple sites in A1 of adult rats to determine neuronal codifiers for sound attributes defined by coarse representations of the population dose-response curves. We demonstrated that these codifiers, majorly involving PCs, are heterogeneously distributed along A1. Spiking activity in these neurons during stimulation was correlated to beta(12-25 Hz) and low gamma(25-70 Hz) postsynaptic oscillations in the infragranular layer, whereas in the supragranular layer, better correlations were found with high gamma(70-170 Hz) oscillations. The time-frequency analysis of the postsynaptic potentials showed a transient broadband power increase in all layers after the stimulus onset that was followed by a sustained high gamma oscillation in the supragranular layer, fluctuations in the laminar content of the low-frequency oscillations, and a global attenuation in the low-frequency powers after the stimulus offset that happened together with a long-lasting strengthening of the beta oscillations. We concluded that, for rats, sounds are codified in A1 by segregated networks of specialized PCs whose postsynaptic activity impinges on the emergence of sparse/dense spiking patterns.
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