Quantitative analysis of neurons and glial cells in the rat somatosensory cortex, with special reference to GABAergic neurons and parvalbumin-containing neurons

SummaryThe number of neuronal and glial cells in the rat somatosensory cortex (barrel area) has been estimated by a stereological method, the disector, using pairs of toluidine blue-stained, plastic-embedded 0.5-μm-thick sections, 1.5 μm distant from each other. Chemical properties of those disector-counted cells were further analyzed by postembedding immunocytochemical methods on adjacent semithin sections. Thus we were able to analyze quantitatively number, distribution, and proportion of five cell types: (1) gamma-aminobutyric acid-(GABA)-negative neurons; (2) GABA-like immunoreactive (GABA-LIR) neurons; (3) a specific calcium-binding protein parvalbumin-immunoreactive (PV-IR) neurons, a subpopulation of GABA-LIR neurons; (4) S-100β-LIR glial cells (astrocytes); and (5) S-100β-negative glial cells (oligodendrocytes and microglia). The densities of total cells, glial cells, and neurons in the rat somatosensory cortex were 85.4 × 103/mm3, 30.5 × 103/mm3, and 54.9 × 103/mm3, respectively. Of all neurons 25% and 14% were GABA-LIR and PV-IR, respectively; all PV-IR neurons are GABA-LIR, and thus about 54% of GABA-LIR neurons are PV-positive. The number of total cells under a unit surface area of 1 mm2 through the thickness of the somatosensory cortex was 171.6 × 103; the number of neurons and glial cells were 110.2 × 103 and 61.4 × 103, respectively. There were 27.7 × 103 GABA-LIR neurons and 15.0 × 103 and 12.7 × 103 PV-IR neurons and PV-negative GABA-LIR neurons, respectively. The laminar distribution of each group of cells shows prominent differences, indicating that the cellular composition was different from layer to layer. The density of GABA-LIR neurons was highest in layer IV. The numerical density of PV-IR neurons was 2–4 times higher in layer IV than in layers II/III, V, and VI, whereas that of PV-negative GABA-LIR neurons was almost constant throughout the layers.

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