Total Number and Ratio of Excitatory and Inhibitory Synapses Converging onto Single Interneurons of Different Types in the CA1 Area of the Rat Hippocampus
Open Access
- 15 November 1999
- journal article
- Published by Society for Neuroscience in Journal of Neuroscience
- Vol. 19 (22) , 10082-10097
- https://doi.org/10.1523/jneurosci.19-22-10082.1999
Abstract
The least known aspect of the functional architecture of hippocampal microcircuits is the quantitative distribution of synaptic inputs of identified cell classes. The complete dendritic trees of functionally distinct interneuron types containing parvalbumin (PV), calbindin D28k (CB), or calretinin (CR) were reconstructed at the light microscopic level to describe their geometry, total length, and laminar distribution. Serial electron microscopic reconstruction and postembedding GABA immunostaining was then used to determine the density of GABA-negative asymmetrical (excitatory) and GABA-positive symmetrical (inhibitory) synaptic inputs on their dendrites, somata, and axon initial segments. The total convergence and the distribution of excitatory and inhibitory inputs were then calculated using the light and electron microscopic data sets. The three populations showed characteristic differences in dendritic morphology and in the density and distribution of afferent synapses. PV cells possessed the most extensive dendritic tree (4300 μm) and the thickest dendrites. CR cells had the smallest dendritic tree (2500 μm) and the thinnest shafts. The density of inputs as well as the total number of excitatory plus inhibitory synapses was several times higher on PV cells (on average, 16,294) than on CB (3839) or CR (2186) cells. The ratio of GABAergic inputs was significantly higher on CB (29.4%) and CR (20.71%) cells than on PV cells (6.4%). The density of inhibitory terminals was higher in the perisomatic region than on the distal dendrites. These anatomical data are essential to understand the distinct behavior and role of these interneuron types during hippocampal activity patterns and represent fundamental information for modeling studies.Keywords
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